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    Volume 38,2022 Issue 23
    2022,38(23):1-12, DOI: 10.11975/j.issn.1002-6819.2022.23.001
    Abstract:
    Flat seeds have the characteristics of irregular structure and large difference in size, When using air-suction metering device, the flat seeds are difficult to fit with the suction hole, and the low adsorption stability leads to poor seeding performance. The traditional air-suction seed metering device was used to carry out the seeding test, results showed that the main adsorption posture of the seeds and the suction surface were horizontal adsorption and vertical adsorption, In the pre-test, the traditional air suction seed metering device was used to seed flat corn seeds, results showed that the main adsorption posture of the seeds and the suction surface were horizontal adsorption and vertical adsorption,the higher horizontal adsorption ratio, the better filling and seeding performance. It shows that the adsorption posture of the seeds has an important influence on filling and seeding performance. Therefore, this paper designs an air-suction metering device with inclined convex seed picking structure to adjust the adsorption posture of flat corn seeds. This can make the seeds reach a stable adsorption posture when they are separated from the population, and improve the seeding accuracy. The corn seeds are graded according to their triaxial dimensions, and the selected flat seeds are divided into circle flat and length flat forms.Theoretical analysis and design calculation of the operation process of the inclined convex seed metering device were carried out, force analysis of flat seeds and convex collision process,and the mechanism of the inclined convex to control the posture of the flat seeds during the filling process was clarified. Discrete element simulation analysis was carried out for the operation process of three types discs: plane disc, groove disc and convex disc. Simulation results showed that the disturbance ability, dispersion degree and torque of the convex disc were higher than other discs. The tilted convex plate could change the attitude of the seed during the seed picking process and realize the parallel adsorption between flat surface of the seed and the suction surface. The bench test was carried out under different operating parameters, and the results showed that the single adsorption rate of the convex disc was significantly better than that of the groove disc and the plane disc. With the increase of forward speed, the single adsorption rate first increased and then decreased, reaching the highest value of 91.70% at 8km/h. With the increase of negative pressure, the single particle adsorption rate showed the same trend, reaching the highest value of 90.84% at 3kPa. The stable adsorption rate and parallel adsorption rate of the convex disc decreased slightly with the increase of speed, increased gradually with the increase of negative pressure and tended to be stable at 3kPa. The adsorption performance of onvex disc was better than the other two discs. At the same time, the parallel adsorption rate of the three seed discs was proportional to the stable adsorption rate. When forward speed was 4-8 km/h, the qualified rate of the convex disc was stable at 97%, and then gradually decreases to 93.18% at 12 km/h. Results of field tests showed that the lowest qualified rate of convex disc was 90.34% and the highest missing rate was 6.52% at the speed of 12 km/h. The convex type seed metering device meets the requirements of precision sowing.The inclined convex seed-picking structure can effectively adjust the adsorption posture of flat seeds, improve the adsorption stability and the working performance of the seed-metering device. This research can provide technical reference for high-speed and accurate seed-picking of flat seeds.
    2022,38(23):13-20, DOI: 10.11975/j.issn.1002-6819.2022.23.002
    Abstract:
    In order to improve the precision and intelligent degree of excavator construction in farmland reconstruction, real-time acquisition of bucket position and attitude is the basis for realizing intelligent and accurate operation of excavator. This paper proposes a method for measuring bucket position and attitude of excavator based on BDS (BeiDou Navigation Satellite System) and IMU (Inertial Measurement Unit). The real-time solution model of the three-dimensional coordinates of the excavator bucket end is established: Measure the body parameters of excavator to establish the body coordinate system, and install IMU attitude sensors at the appropriate positions of the boom, stick and bucket of the excavator to measure the attitude angle information of each actuator of the excavator, by accounting data to get the three-dimensional coordinates of the bucket end under the excavator body coordinate system; Install BDS dual antenna on the roof to obtain the vehicle body yawing angle and spatial position information, and install IMU attitude sensor on the vehicle body to obtain the rolling angle and pitching angle of the vehicle body, then the dual antenna BDS and IMU output high-frequency and high-precision position and attitude information is fused based on the Kalman filtering algorithm to build the attitude rotation matrix. with this solution, the three-dimensional coordinates of the excavator bucket end under the vehicle body coordinate system are rotated to the local construction coordinate system. Static and dynamic tests were carried out to simulate the actual construction scene of the excavator: in the static test, the three-dimensional coordinates of the prism at the excavator bucket under each group of test actions were continuously collected by the total station under different heading angles and attitudes of the simulated operating excavator body and mechanical arm, then calculate the deviation between the measured value of total station and solution value of bucket pose measurement algorithm. The results show that the method can accurately measure the three-dimensional coordinates at the end of the excavator bucket. The maximum absolute deviations of X, Y and Z axial coordinates of bucket measuring points are 17.69 mm, 14.99 mm and 11.68 mm respectively, which are less than 20 mm; The minimum deviation, maximum deviation and average deviation of the calculated distance between two coordinate points and the true value (verification value) are 7.40mm, 0.65mm and 13.57mm respectively. In the dynamic test, the excavator was operated in test group 1: the body course did not move, and each mechanism arm acted; Test group 2: the vehicle body rotates in heading, and each mechanism arm does not move; Test group 3: The body heading and each mechanism arm act at the same time, which were used to simulate the actual construction operation scene such as deep excavation, leveling, slope brushing, etc. in the excavator construction operation. The total station was used to automatically follow the prism placed on the bucket to collect the three-dimensional coordinates of the bucket in real time to verify the three-dimensional coordinate calculation value of the bucket end. The results show that under different test actions, the average absolute deviation and root mean square deviation between the calculated values of the X, Y, Z three axial coordinates and the true value (verification value) are less than 20mm, and the proportion of the data with absolute deviation ≤ 30mm is not less than 95.35%. At the same time, the calculated value of the three-dimensional coordinates at the end of the excavator bucket is consistent with the movement track change of the measured value of the total station, and the root mean square deviation of the distance between the calculated value and the real value (the verified value) are 27.49mm, 26.30mm and 23.50mm respectively, which are less than 30mm. The accurate measurement of the position and posture of the excavator bucket provides a basis for the intelligent guidance of the precise construction of the excavator.
    2022,38(23):21-29, DOI: 10.11975/j.issn.1002-6819.2022.23.003
    Abstract:
    In China, all pineapples are harvested manually. But the agricultural labour force is aging more and more seriously. Automatic navigation is one important direction for the development of pineapple harvest machines. In order to improve the mechanization and automation level of pineapple harvesting, this study proposed a path planning algorithm as navigation scheme for a pineapple harvester. An improved RRT* algorithm was used as the planning algorithm for global path planning. Firstly, the self-heuristic idea was used to constrain the generation range of sampling points. Then, the bias probability pbias was introduced in generating random sampling points. Sampling points were randomly generated with probability p in the space, when p>pbias. Otherwise, the target point was used as the sampling point so as to decrease the blindness of sampling point generation. Thirdly, the gravitational field idea of the artificial potential field algorithm, and the concept of direction weight were introduced in new node expansion. The weights wg and wk were assigned to the directions of the sampling point and the target point respectively, and the direction of expansion of the new node was constrained by those two weights. Fourthly, bidirectional expansion was used to speed up the iteration speed by referring the idea of double-tree expansion. Finally, the greedy algorithm was applied to prune the redundant nodes of the path, and the Cantmull-Rom interpolation function was used to smooth the path corners. Three environments, including multiple obstacles, mazes and narrow passages, were created to simulate the path planning process and to compare the performance among the improved navigation path planning algorithm, RRT* algorithm and bidirectional RRT* algorithm. Planning time, node number and path length were selected as the comparison indicators. Each algorithm was experimented 30 times in every single environment. The average, maximum, minimum and standard deviation of the simulation data of the three indicators were calculated respectively. The simulation results showed that the average planning time of the proposed algorithm in the three environments was 17.97% that of the RRT* algorithm, 46.12% that of the bidirectional RRT* algorithm, which mean that its average programming speed was 4.7 times as quick as that of the RRT* algorithm, about 2.2 times as quick as that of the bidirectional RRT* algorithm. The average of node number of the proposed algorithm was 87.22% less than that of the RRT* algorithm and was 52.52% less than the bidirectional RRT* algorithm. The average path length of the proposed algorithm was 3.81% less than the RRT* algorithm and was 6.08% less than the bidirectional RRT* algorithm. The field test results showed that the planning time of the proposed algorithm was only 14.12% that of the RRT* algorithm and was 20.34% that of the bidirectional RRT*. The iteration number of the proposed algorithm was 80.89% less than that of the RRT* algorithm, and was 69.70% less than that of the bidirectional RRT*. In addition, the rotation angles of bigger than 60° on the path planned by RRT* and bidirectional RRT* algorithms were 1.56 times and 2.06 times as much as that of the proposed algorithm, respectively, and the rotation angles of bigger than 100°on the path were 1.55 times and 2.18 times as much as that of the proposed algorithm, respectively. The improved RRT* algorithm planed the path in the field which can meet the path navigation requirements of agricultural machinery. As moving with speed of 0.2, 0.4, and 0.6m/s, the pineapple harvester can run along the planned path to the target point, but the position deviation and heading deviation increased with moving speed. This study can provide a reference for the navigation study of pineapple harvesters and other agricultural machines.
    2022,38(23):30-41, DOI: 10.11975/j.issn.1002-6819.2022.23.004
    Abstract:
    In the paddy upland rotation area in the middle and lower of the Yangtze River, rice-rape or rice-wheat rotation in paddy field is the dominant rotation system. The alternate drying and wetting process in the rotation tends to make the soil sticky and compact. In actual preparation of arable lands, the soil easily adheres to soil-engaging components of tillage machine and affects the plowing efficiency and quality, thus leading to low traction efficiency and high power consumption. Aiming at the problems of poor quality and low efficiency of rotary blade roller caused by soil adhesion during paddy field operation in the paddy upland rotation area in the middle and lower reaches of the Yangtze River, a barrier type rotary anti-adhesion blade roller with vibration crosspiece was designed in this study. It can be used to realize the anti-adhesion of inherent components and the detachment performance of the crosspiece in the operation process. The rotation radius of crosspiece is greater than the cutter shaft. During the working process, a closed cylindrical area could be formed to isolate the cutter shaft, so as to prevent the soil thrown by the rotary tillage blade from adhering to the cutter shaft. The shear movement direction of the upper and lower crosspiece symmetrically installed on the blade roller driven by the vibration excitation device is opposite. It could shear the soil adhered on the cutter shaft to break it and then fall off. At the same time, the acceleration generated by the reciprocating motion of the crosspiece driven by the vibration excitation device makes it difficult for the soil to adhere to the crosspiece bar surface. Finally, by the comprehensive effect of barrier, shear and vibration of the crosspiece, the soil that enters to the rotary blade roller could realizes the function of adhesion reduction and detachment. The force state of soil particles under the action of vibration crosspiece and the structure of vibration excitation device were analyzed to determine the range of structural parameters of vibration excitation device. Through the analysis of the structure of anti-adhesion blade roller and the throwing kinematics and dynamic process of rotary tillage blade, the structural parameters of anti-adhesion blade roller were designed, and the kinematic requirements for the separation of soil and rotary tillage blade were obtained. The key factors affecting the detachment performance of anti-adhesion blade roller were determined as cutting pitch of rotary tillage, blade roller rotary speed and rotation radius of crosspiece. Combined with the discrete element simulation, the Box-Behnken experiment was carried out with the number of contact between soil particles and crosspiece per unit time as the evaluation index of the detachment performance of rotary blade roller. The optimal combination of parameters was determined as the cutting pitch of rotary tillage of 6.3cm, the blade roller rotary speed of 260r/min and the rotation radius of crosspiece of 140mm. The simulation experiment was carried out again according to the optimization results, and the contact numbers between crosspiece and soil particles per unit time were 127.89, and the relative errors was 6.44% respectively, which was basically consistent with the prediction results of the regression equation. Under the condition of optimal parameter combination, the structural parameters of vibration excitation device were optimized. The motion characteristics of the crosspiece driven by vibration excitation device were analyzed by MATLAB software, and the structural parameters were obtained. In order to verify the applicability and detachment performance of a barrier type rotary anti-adhesion blade roller with vibration crosspiece, three paddy fields were selected as experimental sites. The field experiments were carried out under the optimal parameters combination. The results of multi field performance experiment and rotary tillage comparison experiment showed that it was suitable for mechanized seed bed preparation in most paddy fields. The soil adhesion of the designed rotary tillage anti-adhesion blade roller was much less than that of the traditional rotary blade roller. The average values of tillage depth stability coefficient, soil layer levelness, soil broken rate, adhesion mass, soil distribution uniformity and straw buried rate were 92.02%, 15.21 mm, 81.81%, 2.63 kg, 10.99% and 92.27% respectively. All indexes could meet the design index and agronomic requirements. The research results can provide theoretical basis and technical support for the design of adhesion reduction and detachment of rotary tiller in paddy field in the middle and lower reaches of the Yangtze River.
    2022,38(23):42-50, DOI: 10.11975/j.issn.1002-6819.2022.23.005
    Abstract:
    The farmland clustering tendency and energy shortage situation in China have extremely promoted the development of hybrid electric tractors (HETs) and the prosperity of hybrid power system. However, the dynamic and variable load condition of working tractor in the unstructured road have increased the design difficulty for the powertrain flow that could realized the coupling and decoupling between output power of driven axle and power take off (PTO). The powertrain of tractor was flexible and worthy of study, which can further improve the operation effect of agriculture. Thus, a novel coupled-split powertrain system has been proposed with the principle of graph theory towards the single engine, dual motors and clutch, which could satisfied all power ranges demand with variable combination mode between clutch and power units. In addition, to optimize the energy allocation between the engine and motors in the background of non-linear loads, a Markov decision process (MDP) based energy management strategy (EMS) has been proposed in this paper to allocated the power between engine and motors along with the dynamic and variable load. Firstly, the working load spectrum was consulted in period and used to distinguish the working scenarios, which the sample of working environment includes the plains, the hills and the basins; then, the demand power in plowing was abstracted as the state transition process of the MDP in the premise of tractor parameters collected under the plow condition, with which the comprehensive dynamics of tractor loads were mathematically formulated. Furthermore, the energy consumption was defined as the cost function in the optimal control process, which was solved by the value iteration function. And the working range of motor-2 has been determined under the guidance of optimal control law. In the actual plowing condition, the torque of motor-2 was optimized and determined along with the demand power and state of charge (SOC), which was converted to look-up table and download in vehicle control unit (VCU). Finally, the effectiveness and feasibility of the proposed EMS were validated with the hardware-in-loop test that the program was conducted in the VCU in actual test bench, meanwhile the model of tractor was built in computer, and there were co-simulation. The result has indicated that the proposed EMS could reduce the fuel consumption by 7.2% compared with the traditional rule-based strategy. The proposed demand power forecast strategy could improve the energy efficiency characteristics of drive motor further, in plain plowing environment. In addition, the novel powertrain configurations of tractor were contained the direct and indirect coupled-split power system which expands the path of power flow between power units and wheels. Besides, the direct coupled-split configuration has the potential application to replace the technical difficulties of traditional power shift and continuously variable transmission (CVT). The proposed strategy has significant advantages in terms of energy efficiency characteristics. The powertrain of coupled-split configuration provided a reference for breaking through the difficultly situation of power shift and CVT for high-power tractors. The study was expected to make progress in hybrid power system of tractor in agricultural.
    2022,38(23):51-62, DOI: 10.11975/j.issn.1002-6819.2022.23.006
    Abstract:
    With the continuous improvement of agricultural mechanization, precision seeders have been widely used in large-scale sowing operations. The precision seeder in Xinjiang was mainly pneumatic dibbler, which could realize the function of one hole and one seed. It could not only save the cotton seeds during sowing, but also increase the yield of cotton. However, in the traditional sowing operation, the seeding process of the pneumatic dibbler was accomplished in a closed state. The operator could not directly judge its working state. And it was impossible to completely avoid such sowing failures as the missed-seeding and multiple-seeding, which seriously affect the sowing quality. To solve the problem of missed-seeding, the main solution were to reseed at the position of missed sowing after the emergence of seedlings. However, it may caused the cotton could not opened and be harvested in time. It could resulted in a decline in quality and yield of cotton. In addition, to solve the problem of multiple-seeding, the main solution was the thinning seedlings in late stage. The cost of these methods were huge. Therefore, it was necessary to judge the sowing state through the detection methods of seeding. However, the traditional detection device was not suitable for the pneumatic dibbler. It was often influenced by the temperature and humidity. In response for these problems, a real-time monitoring system for the seeding of pneumatic dibbler was designed and developed based on interdigital capacitive sensor in this research. First of all, the sensor was designed based on the structure and working characteristics of the pneumatic dibbler. The output capacitance value of the sensor was collected and analyzed by the micro capacitance acquisition system which was developed by the Pcap02 chip. System performance verification test, simulation verification test and bench test were then conducted, which were mainly composed by the interdigital capacitive sensor , the micro capacitance acquisition system and experimental prototype dibbler. The performance verification test showed that the measurement error of the system capacitance was within 1%. The measurement error of prediction model of cotton seed quality was less than 3%. It inferred that the micro capacitance acquisition system fully met the requirements of measurement. Simulation verification test showed that the system was accurate in the missed-seeding test. In the normal sowing test, the misjudgment rate was less than 3%. Due to the difference of the quality of cotton seed, the normal sowing was misjudged as miss-seeding and multiple-seeding in this test. In the multi-seeding test, the misjudgment rate was less than 4%.The multiple-seeding was misjudged as uni-grain sowing. Because the quality of cotton seed combination was approximated to the multiple-seeding judgment threshold. The bench test showed that the overall monitoring accuracy of the system decreased due to the certain vibration caused by the motor, but the overall monitoring accuracy of the system remains at 93%. Among them, the overall monitoring accuracy of normal sowing, missed-seeding and multi-seeding was 96.4, 94.04 and 93.9% respectively under the working speed of 30-45 r/min, which was lower than the overall monitoring accuracy of the simulation verification test. In order to judge the difference between the system and the machine vision, the variance of the test data was analyzed through the F test. The F values of the number of normal seeding, missed-seeding and multiple-seeding, which were measured by the system and machine vision, were lesser than F0.05 (6.39). The P0.05 value of the number of normal seeding, missed-seeding and multiple-seeding were greater than 0.05. Therefore there was no significant difference between the system monitoring values and the machine vision measured values, and the system had good detection accuracy and stability. It has a great significance for the precision sowing of cotton.
    2022,38(23):63-71, DOI: 10.11975/j.issn.1002-6819.2022.23.007
    Abstract:
    Reference crop evapotranspiration (ET0) is one of the most important hydroclimatic variables for scheduling irrigation, driving hydrologic and crop models, and estimating actual evapotranspiration for a region. Predicting ET0 a few months in advance will be beneficial for the water management and irrigation communities for making long-term planning decisions. This research explored the potential of using the model data of Beijing Climate Center second-generation climate prediction system (BCC_CPSv2) and the surface meteorological observations at 172 stations during 1991 to 2020, for monthly predictions of ET0 over the Huaihe River basin. Mean air temperature, net radiation, relative humidity and wind speed of BCC_CPSv2 were downscaled by bilinear interpolation and corrected by the quantile mapping method. ET0 predictions were calculated using the Penman-Monteith equation and those four downscaled variables. Four statistical quantitative indicators including correlation coefficient (r), mean bias error (MBE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were employed to evaluate the prediction performances of the model for ET0 and four climatic variables before and after correction. Results showed that mean air temperature, net radiation and relative humidity from the model were significantly smaller than observations before correction in each month with RMSE of 1.84℃, 1.70 (MJ/m2d) and 15.8% respectively. Wind speed was smaller during March to June and larger in other months with RMSE of 1.39 m/s. Errors in climatic variables led to lower ET0 during February to June and larger ET0 in January as well as July to December compared with the calculations. RMSE of ET0 before correction ranged from 0.11 to 1.70 mm/d for each month, and was highest in summer. In January and October, larger RMSE exceeding 0.5mm/d occurred in eastern coastal areas, while in April and July, the southwestern mountainous areas had higher RMSE exceeding 0.7 mm/d. The model skills on predicting climatic variables and ET0 were improved effectively by the quantile mapping method. RMSE of air temperature, net radiation, relative humidity and wind speed decreased to 1.32℃, 0.74 (MJ/m2d), 7.4% and 0.5m/s. Especially, MAPE of wind speed and net radiation decreased by more than 19%. RMSE of ET0 after correction ranged between 0.05 and 1.22 mm/d for each month, and decreased in 80% of the months. The performances of the model were improved significantly for the eastern coastal areas in January and the southwest mountainous areas in April, July and October, and RMSE decreased by more than 0.3mm/d. Before and after the correction, the net radiation and relative humidity were the primary factors causing ET0 prediction errors in summer half year and winter half year respectively, due to the larger errors of the model and the higher sensitivity of ET0 to them. Monthly ET0 prediction with the model correction performed satisfactorily with the error about 10%. It can provide valuable information for water resources management, irrigation schedule planning and agricultural water demand decision-making.
    2022,38(23):72-83, DOI: 10.11975/j.issn.1002-6819.2022.23.008
    Abstract:
    Agricultural carbon emissions are one of the major sources of carbon emissions, in the era of peak carbon and carbon neutrality. Therefore, it is of great significance to clarify the status quo of agricultural carbon emissions and analyze spatial-temporal changes and influencing factors. As we know, Jiangxi Province is a big agricultural Province, which has attracted tremendous research interest. In recent years, the rapid development of agriculture in Jiangxi province is accompanied by the continuous increase in agricultural carbon emissions. Herein, based on the four major carbon sources in Jiangxi Province, including paddy field planting, agricultural investment inputs, soil plowing and livestock and poultry farming, the agricultural carbon emission measurement system of Jiangxi Province was established to calculate the agricultural carbon emission in 81 counties of Jiangxi Province from 2000 to 2020. The spatial pattern of agricultural carbon emissions was analyzed by spatial autocorrelation and center of gravity transfer at county level and the relevant influence factors in Jiangxi Province was analyzed by logarithmic mean Divisia index (LMDI) method. The results could be summarized as follows: 1) The agricultural carbon emission in Jiangxi Province ranges from 10.98 million tons to 14.72 million tons. On the whole, the agricultural carbon emission in Jiangxi Province has an obvious increasing trend, and its carbon emission intensity has an overall decreasing trend. The carbon emission intensity of planting industry showed a decreasing trend, ranging from 2.50 tons per ten thousand yuan to 3.87 tons per ten thousand yuan, and the carbon emission intensity of animal husbandry showed a decreasing trend, ranging from 0.76 tons per ten thousand yuan to 2.03 tons per ten thousand yuan. Particularly, the total carbon emissions of each carbon source and its proportion in total agricultural carbon emissions presented the following tendency: paddy field planting (8.10 million tons, 61.15%) > livestock and poultry (2.43 million tons, 18.57%) > agricultural investment inputs (2.38 million tons, 18.02%) > soil plowing (0.27 million tons, 2.26%); 2) The spatial characteristic of agricultural carbon emissions in Jiangxi Province was apparent. For example, the high carbon emission areas were concentrated in the Poyang Plain and the Jitai Basin, whilst spatial distribution of agricultural carbon emission intensity from relative dispersion to concentration in The Northern Jiangxi Province, the carbon emission intensity in The Southern Jiangxi Province is relatively low. The center of gravity of total carbon emissions in Jiangxi Province moves northward, the carbon emission in The Northern Jiangxi Province is higher than that in The Southern Jiangxi Province. 3) Agricultural production efficiency improvement was the most important factor to restrain the sustained growth of the agricultural carbon emissions. Each factor on agricultural carbon emission reduction and its proportion in the total agricultural carbon emission reduction displayed the following tendency: agricultural production efficiency (18.28 million tons, 56.57%)> regional industrial structure (12.65 million tons, 39.15%) > rural population size (0.86 million tons, 2.66%) > agricultural industrial structure (0.52 million tons, 1.62%).Overall, the order of absolute value of agricultural carbon emission reduction by each factor is: The North Jiangxi Province > The Middle Jiangxi Province >The South Jiangxi Province. The present work could light on a scientific strategy for the estimation of agricultural carbon emissions in Jiangxi Province and even other major grain producing areas in China.
    2022,38(23):84-93, DOI: 10.11975/j.issn.1002-6819.2022.23.009
    Abstract:
    The spoil dumps are the main sediment source in the open-pit mining area. Its erosion control is of great significance to the high-quality development of the energy zone. On the base of plot construction of platform-steep slope system and field scouring experiments, this article aims to analysis the gully development and sediment process of spoil dumps. The flow rate ranged from 60 L/min to 80 L/min and the time of each run was 45 mins. The results showed that: 1) The gully developed by the combination of different erosion progresses including headcut migration, bed incision, and lateral erosion on the platform-steep slope system. Notably, the gully showed stage differences in topography due to the variation of dominant erosion progress. Gully on platform experienced a three staged development process of headcut formation stage, migration-expansion stage, and stable stage. The gully on steep slope exhibited the four developmental processes of incision of sandy loam layer, expansion of sandy loam layer, incision of clay loam layer, and decelerated stage. No significant differences were found between various flow rates of gully development speed on platform. Whereas, the transformed time increased with flow rate between adjacent gully development stages on steep slope. 2) In terms of sediment process, migration - expansion stage was the main erosion period on the platform. The incision of sandy loam layer and clay loam layer were the main erosion stages on the steep slope with accumulated sediment yields accounting for 29.72%-53.36% and 19.06%-48.88% respectively. Spatially, the runoff shear force and stream power increased by 7.11-120.86 times and 7.59-239.59 times separately, and the erosion rate increased by -0.84-66.20 times after the runoff flowed from the platform into the steep slope. The steep slope was the main sediment source of the platform and steep slope system. Its cumulative sediment yield accounted for 88.15%-90.16% of the total amount of platform and steep slope system. Hence, the separation and control of runoff on platform is a vital way to control gully erosion in the platform-steep slope system of spoil dumps. 3) In terms of flow hydraulics, the platform velocity decreased first and increased then with the gully development. Conversely, the slope velocity decreased gradually. Meanwhile, the runoff shear stress and the runoff stream power increased gradually with the gully development on the platform, and increased first and decreased finally on the steep slope. 4) Comparatively, the erosion rate had a more sensitive response to the stream power than the runoff shear force, and the response regularity differed with gully development stages. The erosion rate linearly responded to the stream power in the migration-expansion stage and stable stage of platform. As for the steep slope, the responses were still linear in the expansion of sandy loam layer and decelerated stage, but were exponential in the incision of sandy loam layer and clay loam layer. Therefore, it is necessary to consider the difference of responses in various gully development stages to improve the applicability of sediment transport model for gully erosion. The results revealed the staged development of gully and sediment process on the platform-steep slope system of spoil dumps. It offers basis for the layout of soil and water conservation measures in spoil dump, and provides reference for scientific understanding of the gully process.
    2022,38(23):94-103, DOI: 10.11975/j.issn.1002-6819.2022.23.010
    Abstract:
    The frost heave damage is an important aspect of trapezoidal concrete lined canal with an open system in cold regions. The Winkler elastic foundation plate theory, which could describe the relationship between canal lining and frozen soil foundation, was used to establish the frost heave failure model of l canal lining considering the frost heave force and adfreeze force. The top of the slope of the canal and the soil of the channel foundation are frozen together, and the foot of the slope and the bottom plate are mutually hinge constraints, so the two ends of the plate at the depth direction are assumed to be simply supported boundaries. The adjacent canal lining joints are mostly filled with soft elastic waterproof material, which allows relatively large deformation, so the adjacent canal lining board joints are assumed to be free boundaries. The analytical solution of the model was obtained, and the influence of groundwater depth and geometric parameters of canal lining was analyzed. Compared with the existing field observation and calculation results, the correctness of the calculation results in this paper is verified. The results show that the bottom plate is subjected to uniform frost heaving force, that generate the unevenly distributing of the internal force and stress along the height direction of the plate, also the stress at the free boundary is slightly larger than that at other positions. Bending moment and shear force of the slope plate is unevenly distributed. And the maximum deflection is 2/3 from the top of the slope to the foot of the slope, and the maximum bending moment is close to the bottom plate. The stress distribution and the internal force distribution are similarly, which is also consistent with the existing research results. The maximum stress position occurs at the maximum deflection position. Torque distributed symmetrically along the center of the canal lining, and the maximum value distributed at four corners, which are easy to produce a stress concentration at the corners. Compared with the beam theory, the results of plate theory show that the deflection and internal force of the lining plate are not uniformly distributed along the plate width direction, and the deflection and bending moment is greater at the free boundary (longitudinal expansion joint), and the torque distributed at the corner of the canal lining. The tangential force has little influence on frost heaving of the canal. The maximum deflection of the canal after adding the tangential force increased 0.7 mm, but the adfreeze force will produce an eccentric bending moment on the canal lining, which will increase the overall bending moment of the canal lining. Therefore, the influence of adfreeze force should be considered in the antifreeze design of the canal lining. The relationship between groundwater and frost heave plays an important role in preventing the frost damage of the canal. Different thicknesses of lining plate should be selected for the working conditions of different groundwater depth. With the increase of groundwater depth, the frost heave displacement of slope plate gradually decreases, and the position of the maximum frost heave displacement section has not changed. Increasing the thickness of the canal lining can also effectively prevent the frost heave damage of the canal. When the water table is high, thickening canal lining or enhancing concrete strength should be chosen to prevent freezing damage. According to the canals with different groundwater levels, the safe range of canal lining thickness is obtained, which can provide a referent and theoretical basis for the frost heave resistant design of cast-in-place concrete trapezoidal canals.
    2022,38(23):104-114, DOI: 10.11975/j.issn.1002-6819.2022.23.011
    Abstract:
    As the temporary salt reservoir of study area, the salt of salinized wasteland was much higher than the average level. Therefore, exploring the difference of spectral response of soil salinity in different land use types and its influence on the remote sensing model of salinity is an important way to realize the inversion value of soil salinity in different land types closer to the real value. Yongji of Hetao irrigation district in China, a typical salinization region, was chosen as the study region in this paper. The distribution of salinized wasteland in study area was relatively scattered, mostly concentrated around agricultural land, and the salt content was much higher than that in agricultural land. Firstly, in-situ hyperspectral measurement (FieldSpec 4 Hi-Res, ASD) was carried out for agricultural land and salinized wasteland in April from 2018 to 2020. Secondly, the spectral data was subjected to various spectral transformations, include fundamental transformation (original, reciprocal, logarithm and radical transformation), derivative transformation (first derivative and second derivative) and spectral index (Normalized Differential Soil Index, Difference Soil Index and Simple Ratio Soil Indices), respectively. Thirdly, the multiple stepwise regressions were used to get the characteristic bands and spectral indices. Lastly, the single land type salt inversion model (Agricultural Land (AL), Salinized Wasteland (SW)) and the overall salt inversion model (Agricultural Land + Salinized Wasteland (AL+SW)) were constructed based on the characteristic wavelength and characteristic spectral index, respectively. The model accuracy under different modeling methods was evaluted based on the coefficient of determination (R2) and root mean square error (Root Mean Square Error, RMSE), and the best modeling method of regional soil salinization was proposed. The results showed that the average soil salinity content of samples in AL, SW and AL+SW was 5.09 g/kg, 13.42 g/kg and 7.09 g/kg, respectively, and the spectral reflectance of SW was greater than that of AL in each wavelength range of different grades of salt zone, where the average differences for slightly saline soil, moderately saline soil and strongly saline soil was 0.040, 0.020, and 0.034, respectively. Spectral transformation and spectral index can effectively improve the correlation between soil salt and spectrum in different land types. Compared with the fundamental transformations (reciprocal, logarithm, root, etc.), the derivative transformations can increase the range of sensitive wavelengths and improve the correlation coefficient at specific wavelengths significantly. Accuracy of models based on characteristic spectral index was higher than that based on characteristic wavelength in different land types. After the first derivative transformation, the average R2 of AL, SW and AL + SW regression models increased 0.30, 0.38 and 0.00 compared with the wavelength regression model, and after the second derivative transformation, the average R2 of AL, SW and AL+SW regression models increased 0.28, 0.28 and 0.02, respectively. The single land type salinization inversion model significantly improved the inversion accuracy of regional soil salt. The average R2 of the spectral index model under each transformation in the single land type salinization inversion model (AL, SW) increased from 0.50 to 0.61 compared with the overall model ( AL + SW model ). The average R2 of the fundamental transformation, first derivative and second derivative models was 0.06, 0.11 and 0.17 higher than that of the overall model, respectively. At the same time, the average R2 of the single land type salinization inversion model based on the optimal spectral index increased from 0.74 to 0.92 compared with the overall model. Therefore, the construction of soil salt inversion models for different land use types can ensure that the inversion results are closer to the actual situation when the region has various land use types with large differences in salinity.
    2022,38(23):115-124, DOI: 10.11975/j.issn.1002-6819.2022.23.012
    Abstract:
    Branch and leaf pruning has been an important link in the process of tomato planting to reduce disease rate and improve tomato economic benefits. However, pruning tomato branch and leaf in manual has also been a time-consuming and labor-intensive task in large-scale production. Identification of tomato lateral branch pruning point is helpful for the automatic operation of tomato branch and leaf pruning. In this study, an identification method of tomato lateral branch pruning point based on improved Mask R-CNN was proposed. First, the backbone network ResNet50 in the original Mask R-CNN was replaced with MobileNetv3-Large to reduce model complexity, and Efficient Channel Attention was added to feature map C3 and C4 to focus more on features of lateral branch and main branch rather than other useless features, then, tomato lateral branch and main branch were predicted through the improved Mask R-CNN. In order to solve the problem that some single branches were divided into multiple masks, the lateral branch and main branch masks were distinguished by the aspect ratio of the bounding boxes, and overlap and pole constraints of adjacent masks that belonged to the same branch were analyzed, then masks that met the constraints were merged and joined. The lateral branch pruning point could only be at one of the two ends of the lateral branch. In order to determine the coordinate of the lateral pruning point, a lateral pruning point identification method based on the main branch assistance was proposed. Firstly, the range near main branch was determined, then, branch pruning end was determined by estimatingwhich of the lateral branch left and right endpoints was in the range, and finally the center point close to the endpoint of the pruning end was determined as the pruning point of the lateral branch. The original and improved Mask R-CNN were compared to verify the improved Mask R-CNNfor detection of the lateral branch and main branch. The recall rate and precision of original Mask R-CNN are 87.9% and 93.3%, and the recall rate and precision of improved Mask R-CNN are 91.2% and 88.6%. The backbone network parameters of improved Mask R-CNN was only 21.1% of that in the original Mask R-CNN, and the average segmentation time of the improved Mask R-CNN decreased 0.038s. The results showed that backbone network MobileNetv3-Large in the improved Mask R-CNN could reduce model parameters and improve speed, and adding Efficient Channel Attention mechanism to feature map C3 and C4 could make the model recognize more branches. Lateral branches and main branches divided into multiple masks were selected randomly to verify the performance of merging masks. The merging success rate of lateral branch masks was lower than the main branch masks, because curved shape of lateral branch was more obvious. The average success rate of merging masks was 86.2%, indicating that the method of merging masks could effectively avoid the existence of multiple pruning points caused by a single branch divided into multiple masks. Then someimagesin test set were selected randomly to verify recognition accuracy for lateral branch pruning point. The result showed that the recognition success rate on sunny days was higher than that on cloudy days, and the average recognition success rate was 82.9%,which met the requirements of lateral branch pruning point recognition accuracy. This research can provide technical supports for tomato branch and leaf pruning automatically.
    2022,38(23):125-133, DOI: 10.11975/j.issn.1002-6819.2022.23.013
    Abstract:
    Estimation of apple tree depth from a single RGB image can be applied to precise fruit positioning and robot autonomous harvesting. In order to satisfy the actual requirements of obtaining depth information for apple mechanized picking, the improved High-Resolution Network (HRNet) was used to carry out research on the monocular depth estimation method of apple tree in the natural scene. Firstly, a multi-branch parallel encoder network was constructed based on HRNet to extract multi-scale features, and the continuity in the feature transfer process was enhanced by introducing a dense connection mechanism. In order to reduce the noise interference caused by redundant features, the Convolutional Block Attention Module (CBAM) was used to recalibrate the fused feature maps at the channel and pixel levels, effectively learn the different weight distributions of the feature maps, and enhance the structure information. In the decoder network, the Stripe Refinement Module (SRM) was used to gather the boundary pixels in the horizontal and vertical orthogonal directions, adaptively optimize the boundary details of the feature map, highlight the edge features, and reduce the blurry edge in the predicted results. Finally, the prediction depth images of the same size as the RGB images were generated by up-sampling. An image acquisition platform was set up to collect RGB and depth images of apple orchards at different times, and then enhanced the data using horizontal mirroring, color jitter, and random rotation. Through data enhancement, totally 3374 orchard RGB images and depth images were obtained to make our depth datasets. Experiments were conducted on the NYU Depth V2 dataset and the orchard depth dataset. Firstly, ablation experiments were performed on HRNet networks with different degrees of improvement. Compared with the traditional HRNet network, the predictive performance of different improved networks had been improved to some extent, which indicated the introduction of dense connection mechanism, adding CBAM, SRM could improve model performance. Secondly, we compared the algorithm in this paper with the current mainstream networks, the average relative error (REL), root mean square error (RMS), logarithmic mean error (log10), depth edge accuracy error () and edge integrity error () of the proposed improved HRNet network on the orchard depth dataset were 0.123, 0.547, 0.051, 3.90 and 10.76; the accuracy at different thresholds reached 0.850, 0.975, 0.993; in terms of subjective vision, the depth map generated by the improved HRNet network had more accurate spatial resolution, which could better present the depth information distribution of the image, with clear edges and more texture details, the depth information of some small-sized objects were also displayed, and the overall effect was the best, which was closer to the real depth map. The ablation analysis of the above network and the comparison of subjective and objective effects with other depth estimation algorithms fully demonstrate the effectiveness of the proposed algorithm. Based on the experiment results, the proposed network outperformed for both visual quality and objective measurement on NYU Depth V2 dataset and the orchard depth dataset, which can provide the apple automatic picking machine with a new idea to obtain depth information.
    2022,38(23):134-144, DOI: 10.11975/j.issn.1002-6819.2022.23.014
    Abstract:
    In modern dairy farming, it is necessary to monitor the oestrus behavior of dairy cows timely and accurately. In this research, aiming at the problems of untimely and low efficiency of artificial monitoring of cows' oestrus, a lightweight method for detecting cows' oestrus behavior was proposed, which combined YOLO v5n and channel pruning algorithm. On the premise of ensuring the precision of the network. First, the model was sparsely trained according to different sparsity rates, and it was concluded that the sparsity effect of the model was best when the sparsity rate was 0.005. Then, based on the channel pruning algorithm, the modules, including the CSPDarknet53 backbone feature extraction network, were pruned to compress the model structure, params and improve the detection speed. In order to verify the effectiveness of the algorithm, 2239 images of cows' mounting behavior were collected, including 1473 images in the daytime, 88 images in the daytime (backlight), and 160 images in the nighttime. Four occlusion situations were considered, including 1045 images without occlusion, 397 images with slight occlusion, 184 images with moderate occlusion, and 95 images with heavy occlusion. Three target sizes were considered, including 46 images with large targets, 1191 images with medium targets, and 484 images with small targets. The pruned model was tested on the test set and compared with Faster R-CNN, SSD, YOLOX-Nano and YOLOv5-Nano. The test results showed that the mean average precision (mAP) of the model after pruning was 97.70%, the Params were 0.72 M, the Floating Point operations (FLOPs) were 0.68 G, and the detection speed was 50.26 fps. Compared with the original model YOLOv5-Nano, the Params and FLOPs reduced by 59.32 and 49.63 percentage point, respectively under the condition of constant mAP, and the detection speed increased by 33.71 percentage point, which showed that the pruning operation used in this research could effectively improve the model's performance. The mAP of this research model was close to Faster R-CNN, SSD, YOLOX-Nano, but the Params reduced by 135.97, 22.89 and 0.18 M respectively, the FLOPs reduced by 153.69, 86.73 and 0.14 G respectively, and the detection speed increased by 36.04, 13.22 and 23.02 fps respectively. In addition, the detection effects of the model in complex environments such as different lighting, different occlusion, multi-scale targets, and new environments were tested. The results showed that the mAP in the nighttime environment was 99.50%, the average mAP under the three occlusion conditions was 93.53%, the average mAP of medium and small targets was 98.77%, the detection rate of cows' mounting behavior in the generalization test was 84.62%, and the false detection rate was 7.69%. To sum up, the model in this research has the advantages of being lightweight, high precision, being real-time, being robust, and having high generalization, which could meet the requirements for accurate and real-time monitoring of cows' oestrus behavior under complex breeding environments and all-weather conditions.
    2022,38(23):145-155, DOI: 10.11975/j.issn.1002-6819.2022.23.015
    Abstract:
    High-resolution precipitation data are essential for the accurate simulation of hydrological, meteorological, and biological systems and can be used to characterize the spatial-temporal differentiation features of precipitation. Therefore, it is crucial to implement spatial downscaling for precipitation products with poor spatial resolution. However, the precision and detail features in downscaling precipitation data are frequently insufficient due to a lack of consideration for how scale variations affect the spatial distribution of precipitation. In order to improve the TRMM precipitation data in the Wei River basin (WRB), the paper proposed a spatial downscaling approach that integrated a multi-scale geographically weighted regression (MGWR) model, in view of the fact that the MGWR enables conditional relationships between the response variable and predictor variables that change at spatial scales. Therein, the goodness of fit (R2), relative deviation (BIAS) and root mean square error (RMSE) were employed to determine the suitability of the TRMM satellite precipitation product through a comparison with actual precipitation data from meteorological stations. Normalized difference vegetation index (NDVI), digital elevation model (DEM), slope, aspect, latitude and longitude were induced as geographic environmental factors (GEFs) and in the construction of MGWR models of monthly TRMM precipitation data to further investigate the scale effects of factors on precipitation distribution. The spatial downscaling of TRMM production data was then implemented using a scale conversion process. Finally, it was confirmed that the spatial downscaling results for TRMM precipitation products were reliable. The results illustrated that: 1) The TRMM precipitation data are well suited for use at different scales in the WRB. The statistics of R2 (0.807), BIAS (2.909%), and RMSE (83.477 mm) at the annual scale demonstrate acceptable fitness. The maximum R2 was 0.847 at the seasonal scale, the largest RMSE was 62.393 mm in the summer, and the values of BIAS were lower in all four seasons. On the monthly scale, the R2 varied between 0.456 and 0.815, with the smallest value in June and the largest value in September. The BIAS is positive in most months, indicating that TRMM product data generally overestimate precipitation, and the range of RMSE index values is 3.019-37.841 mm, which is lower than the value of the annual and seasonal scales. 2) Different scale characteristics can be seen in the influence of various GEFs on the spatial pattern of precipitation divergence in wet and dry years. Slope has a global scale, whereas DEM, NDVI, aspect, latitude, and longitude have local effects on precipitation in wet years, and all GEFs use local impacts in dry years. 3) The downscaled TRMM data on the watershed and station scales are more precise as compared to the product data, showing an increase in the R2 of the entire watershed of 3%, a decrease in the RMSE of 1 mm. The accuracy of station downscaling precipitation data at the annual scale, however, is worse than that at the monthly scale due to the accumulation of errors on the time scale, as shown by the R2 range decreasing from 0.8-0.91 (monthly) to 0.4-0.95 (yearly) and the RMSE range increasing from 11-17 (monthly) to 32-150 (yearly). 4) The downscaled TRMM data has better detailed characteristics, greater precision at annual and monthly scales, and a more delicate geographical distribution than the product data. They can provide strong data support for hydrological design in areas with a lack of precipitation data.
    2022,38(23):156-165, DOI: 10.11975/j.issn.1002-6819.2022.23.016
    Abstract:
    As a mature discrete element analysis software, PFC software has been widely used because of its excellent performance in dealing with continuous and discontinuous media. However, the mesoscopic parameters required by PFC software can only be obtained by repeated debugging of laboratory test data through trial-and-error method, which has low efficiency and high blindness. Even experienced scholars need dozens of trial and error to obtain a set of usable parameters. For novice scholars, more trial and error are needed to obtain usable parameters. This matter requires scholars' own parameter calibration experience, which seriously affects the promotion of PFC software and the follow-up test process. Therefore, there is an urgent need for a mesoscopic parameter calibration method that does not require the experience of scholars in parameter calibration, and can be correctly and quickly calibrated. Based on the uniaxial creep test of corn stalk particles and combined with the built-in Burgers model of the discrete element software PFC 2D, the uniaxial creep test model of corn stalk is established. The relationship between the macroscopic and mesoscopic parameters of the Burgers model is analyzed by the multivariate analysis of variance method of the orthogonal experiment, which proves that there is a complex relationship between the macroscopic and mesoscopic parameters. That is, the significance of the influence of each mesoscopic parameter on the macroscopic parameter is quite different, and the relationship between the macroscopic and mesoscopic parameters is highly nonlinear. Therefore, it is not appropriate to calibrate the mesoscopic parameters by obtaining the relationship between the macroscopic and mesoscopic parameters through regression analysis. However, these complex relationships are just suitable for parameter calibration using BP neural network. According to the number and characteristics of macroscopic and mesoscopic parameters, a BP neural network with 4 nodes in the input layer, 9 nodes in the hidden layer, and 5 nodes in the output layer is created through continuous attempts. Then, the created BP neural network is trained and calibrated using 150 sets of macroscopic and mesoscopic parameters. According to the results of the calibration of mesoscopic parameters using the created BP neural network, it is concluded that the calibration accuracy of all mesoscopic parameters in the Burgers model is above 92%, with relatively stable errors. Moreover, the correlation coefficient R of the trained BP neural network is greater than 0.96, which proves that the inversion performance of BP neural network is more reliable and it can be popularized and used as a new parameter calibration method for mesoscopic parameter calibration of Burgers model. Bringing the macroscopic parameters of the uniaxial creep test of corn stalk into the trained BP neural network for calibration of the mesoscopic parameters, and comparing the simulated creep test results with the physical creep test results, it is found that the creep curves of the two tests are basically the same, and the maximum error of the dependent variable is 2%, which proves that BP neural network has good parameter calibration ability and can provide certain reference value for PFC parameter calibration.
    2022,38(23):166-173, DOI: 10.11975/j.issn.1002-6819.2022.23.017
    Abstract:
    The semantic segmentation of fish bodies is the basis for realizing the three-dimensional modeling of fish bodies and semantic point clouds, and calculating the growth information of fish. The accuracy of point cloud computing depends on the precision of fish body segmentation. However, the feature fusion path in the traditional Mask R-CNN network is too long, resulting in the low-level information containing the accurate location of the target cannot be fully used. In addition, noise such as light and water quality will affect the images collected in the real breeding environment, which makes the collected images have quality degradation problems. This problem affects the extraction of fish features by the network, and leads to poor edge segmentation. In order to improve the precision of fish semantic segmentation in complex environments, a Mask R-CNN that hybrids the SimAM attention mechanism is studied, and twice-transfer learning is conducted during the training process. An attention mechanism is added at each layer of the residual network of the backbone network. After feature extraction, the features are dynamically assigned weights so that the network can focus on information related to the fish body. While maintaining the lightweight feature of the model. The first transfer learning is conducted by training the COCO dataset pre-trained model on the Open Images DatasetV6 fish images, followed by the second transfer learning on the self-built dataset. The self-built dataset is the frame splitting of the captured video using a ZED binocular camera in the real culturing environment. The images in the self-built dataset have the features of a lot of noise and complex backgrounds. The self-built dataset and the Open Images Dataset V6 fish images both have similar feature spaces. Since the fish images in the Open Images Dataset V6 data have the features of high clarity and less noise, it is conducive to the network learning the texture and detail information of the fish body. The influence caused by images with noise is alleviated through twice-transfer learning on two datasets with similar feature spaces. Experiments on the test set of the self-built dataset show that the IoU of the proposed method is 93.82%, F1 is 96.04%, precision is 96.98%, recall is 95.12% and F1 is 96.04%. To verify the effectiveness of the improved model in this paper, other models are used for comparative experiments. The experimental results show that the segmentation effect of SA-Mask R-CNN is better than that of SegNet and U-Net++, IoU is improved by 9.22 percentage points and 9.03 percentage points, the precision is improved by 9.92 percentage points and 9.33 percentage points, the recall is increased by 10.33 percentage points and 9.83 percentage points, and F1 is improved by 10.13 percentage points and 9.58 percentage points, respectively. Compared with SE-Mask R-CNN and CBAM-Mask R-CNN, IoU increased by 1.79 percentage points and 0.33 percentage points the precision increased by 1.44 percentage points and 0.25 percentage points, the recall increased by 2.59 percentage points and 0.51 percentage points, F1 increased by 2.03 percentage points and 0.38 percentage points. Meanwhile, the number of model parameters decreased by 4.7MB and 5MB, respectively. In order to verify the effectiveness of the twice-transfer learning method, the two different training methods are compared. The result shows that SA2-Mask R-CNN improves IoU by 0.67 percentage points, precision by 0.82 percentage points, recall by 0.27 percentage points, and F1 by 0.54 percentage points compared with SA1-Mask R-CNN. In summary, experimental comparison verifies that the proposed method improves the precision of fish semantic segmentation without increasing the number of model parameters. Therefore, the method in this paper is more conducive to model deployment and porting. At the same time, experiments also verify the precision of twice-transfer learning to improve the semantic segmentation of fish bodies. The research results can provide a reference for cloud computing of fish body points.
    2022,38(23):174-184, DOI: 10.11975/j.issn.1002-6819.2022.23.018
    Abstract:
    Late frost is one of the most destructive meteorological disasters that threaten the sustainable production of apple and could cause great economic losses for the apple industry in the Loess Plateau of China. Thus, exploring and analyzing the occurrence of late frost events is of great significance for the prevention of apple late frost disaster and for the planning and management of thelocal apple industry. In this study, the late frost return periods were investigated based on the duration and severity of late frost events based on the Coupla functions to verify the reliability of this method to analyze the characteristics of apple late frost. The study area was the apple producing areas of Shaanxi Province. Based on the meteorological datasets of seven different weather stations in 1971-2018, daily minimum temperature (Tmin) of 0 ℃ was taken as the critical temperature for the occurrence of apple late frost event to extract the two characteristic variables of duration and severity of late frost events. These two characteristic variables of late frost events were fitted by seven common distribution functions, respectively. Then, they wereevaluated through the Kolmogorov Smirnov (K-S) test method. The joint distributions of late frost characteristic variables were constructed based on six different Copula functionsand the corresponding values of goodness-of-fit were evaluated. The occurrence probability and return period of late frost events were analyzed with the optimized Copula functions. The results showed that from 1971 to 2018, the severityof late frostrisks generally increased from southeast to northwest for the stations in the apple producing areas in Shaanxi Province.The optimal marginal distribution of late frost duration at the stationswas log-normaldistribution, while the optimal marginal distributions of late frost severity were different. There was a significant positive correlation between the variables of duration and severity of late frost at each station. According to the goodness-of-fit test, most of the stations had the optimal distribution of Normal Copula function for late frost events. When the severity and duration of late frost increased, the joint cumulative probability increased accordingly, but the increasing trend became slower. When the univariate value had the same increase, the increase of co-occurrence return period was significantly higher than that of joint return period. The univariate return period was always between the joint return period and the co-occurrence return period. When the value of univariate return period was small enough, the range of actual univariate return period could be estimated according to the joint return period and the co-occurrence return period. In general, the probability of late frost events with long duration and high severity islow at the weather stations in apple producing areas in Shaanxi Province. However, the stations in the Yan'an area aremore susceptibleto late frost events with high severity or long duration, as well as late frost events with both high severity and long duration. Thus, the stations in the Yan'an area need more attention in future studies on late frost risks. This study could provide atheoreticalbase for Shaanxi province to deal with late frost disaster in apple production.
    2022,38(23):185-191, DOI: 10.11975/j.issn.1002-6819.2022.23.019
    Abstract:
    High-temperature aerobic composting technology is developing rapidly, but many studies point to the production of greenhouse gases during the composting process, mainly including CH4 and N2O. In order to reduce greenhouse gases emission in the composting process of kitchen waste, a 35-day aerobic co-composting of kitchen waste and yard trimming (chipped stems) was carried out in 60 L forced aerated static composting reactors. Three commercial microbial agents of VT1000 compound consortia (VT), Bacillus subtilis (BS) and Bacillus licheniformis (BL) were added to compost materials respectively, the amount of fungi added was 1.5% of the dry weight of all raw materials composted, and the treatment without bacterial agents was used as the control (CK). CH4 and N2O emissions during composting process were monitored to investigate the effect of microbial agents on greenhouse gas (GHG) emission. The results showed that the addition of microbial agents not only accelerated temperature rising and maturity of compost, but also significantly reduced GHG emission in varying degrees. In terms of reactor heating, the high temperature duration of all treatments could meet the harmless requirements, but the treatment with added microbial agents had better secondary heating effect, VT had the fastest temperature recovery and the highest temperature, followed by BS, and BL was slower than CK. From the perspective of maturity, the electric conductivity and pH value of all treatments meet the compost quality requirements, the treatment of uninoculated microbial agents (CK) cannot meet the rot standard, and the treatment of Bacillus subtilis (BS) had a slight advantage over the treatment added with VT1000 (VT) and the treatment added with Bacillus licheniformis (BL) in terms of compost maturity. About greenhouse gas emission reduction, N2O emissions amounted to 76.83%-88.57% of the total GHG emission expressed as CO2-C equivalent, which was much higher than CH4. The emission peaks occurred at the initial stage and mature phase, respectively. The emission peak of CH4 occurred at the cooling stage, and the cumulative emissions reached 1.65%-2.40% of the total greenhouse gas emissions equivalent. The cumulative CH4 emissions of the four treatments were CK>BL>BS>VT in descending order, and the CH4 emission reduction effect of VT teratment was the best, which was 18.89%, while the addition of Bacillus subtilis had the best emission reduction effect on N2O in this study, with a reduction rate of 61.86%, followed by VT, with a emission reduction rate of 49.22%, and Bacillus licheniformus was the lowest, with a emission reduction rate of 35.32%. Total GHG emissions equivalent of each treatment were 95.84 kg·t-1 (CK), 52.31 kg·t-1 (VT), 42.03 kg·t-1 (BS), and 62.49 kg·t-1 (BL), respectively. Compared with CK treatment, BS treatment showed the best total greenhouse gases mitigation, with the reduction rate of 56.15%, BL treatment was the lowest of 34.80%, while VT treatment was 45.42%. N2O abatement was better achieved than methane by the addition of the inoculants, ranging from 35.32% to 61.87%. Taken together, addition of the microbial agents in the experiment can effectively mitigate greenhouse gases on the premise of ensuring the quality of composting products, and overall, the treatment with 1.5% Bacillus subtilis (BS) had the best effect.
    2022,38(23):192-198, DOI: 10.11975/j.issn.1002-6819.2022.23.020
    Abstract:
    To improve the energy efficiency of waste biogas residue and the resource utilization rate of low-rank coal, the co-pyrolysis method of long-flame coal and biogas residue was employed to deeply study the effect of temperature on the properties of co-pyrolysis products of long-flame coal and biogas residue mixed in equal proportions was investigated in depth. After the experiment was completed, the data obtained from the experiment was analyzed by GC-MS and gas chromatography, and the understanding of the pyrolysis products was further improved through product analysis. The experimental findings showed that the actual thermogravimetric curves of long-flame coal and biogas residue are different from the calculated curves, and the co-pyrolysis of the two had an obvious synergistic effect. The optimal pyrolysis temperature range of biogas residue and long-flame coal is different, and there is a synergistic effect in the overlapping range of pyrolysis temperature of the two, which affects the results of pyrolysis experiments and the thermogravimetric curve. The results of co-pyrolysis showed that the presence of lignin in biogas residue can promote the formation of tar, inhibit the formation of gaseous products and thus affect the proportion of oil and gas in the co pyrolysis products. The yield of pyrolysis oil increased first and then decreased with the increase of temperature. When the pyrolysis temperature increased from 400 °C to 500 ℃, the oil yield rose from 9.23 wt.% to 12.12 wt.% and then decreased to 9.30 wt.% at 700 ℃. The water yield increased first and then decreased from the increase in temperature,which increased from 3.71 wt.% at 400 °C to 5.28 wt.% at 600 °C and then decreased to 4.81 wt.% at 700 °C. The char yield gradually decreased with the increase of temperature, while the gas yield increased moderately with the increase of temperature. The GC-MS results showed that the content of ketones decreased first and then increased from the increase in temperature, which was produced by coal pyrolysis at high temperature, and the synergistic effect could inhibit their production. The relative content of mono- and bi-cyclic aromatic hydrocarbons in the pyrolysis oil at 600 °C reached the highest and the oxygen content was less, indicating that the compounds in the co-pyrolysis oil were significantly improved due to the existence presence of synergistic effect. The gas analysis results of co-pyrolysis showed that the yields of H2 and CO first decreased and then increased with the increase of temperature, while the yield of CH4 increased first and then decreased with the increase of temperature. As the temperature increased from 400 °C to 700 °C, the yield of H2 decreased from 10.82% to 8.23% at 500 °C and then increased to 37.68% at 700 °C, while the yield of CH4 increased from 400 °C 9.69% of C increased to 18.28% of 500 °C, and finally decreased to 16.58% of 700 °C. The high heating value of pyrolysis gas first increased and then decreased with the increase of temperature, and reached a maximum value of 15.33 MJ/m3 at 600 °C. The experimental results and data analysis show that the pyrolysis of biogas residue and long-flame coal has a certain synergistic effect, which can increase the yield of pyrolysis products and improve the quality of pyrolysis products.
    2022,38(23):199-206, DOI: 10.11975/j.issn.1002-6819.2022.23.021
    Abstract:
    Nowadays, edible mushroom is the most common dish on the dining-table of global people. The growing demand for edible mushroom produced unimaginable amount of culture medium waste (mushroom residue) waiting for processing. At present, the mainstream treatment method of the mushroom residue is discarding or burning, which causes environmental pollution and waste of resources. Therefore, the recycling of mushroom residue has important economic value and environmental protection significance. Thus, to develop a high-value processing method for the mushroom residue is extremely urgent now. As far as we known, biomass derived carbon materials have great application potential in electrochemical energy storage devices such as lithium ion batteries, sodium ion batteries, and lithium-sulfur (Li-S) batteries. Among them, the Li-S battery is considered to be a potential next-generation power battery system due to the ultrahigh theoretical capacity and energy density. The unique microstructure of biomass derived carbon materialshas great influence on electrochemical performance of Li-S battery.Thus, this study used waste culture residue of oyster mushroomas raw material to fabricate porous carbon materials, which further applied as conductive skeleton in cathode materials in Li-S battery. The effects of cultural batch and KOH activation process on the microstructure of the mushroom residue derived carbon materials were investigated in detail. This study not only provided a new kind of resource to prepare cathode materials for Li-S battery, but also provided a new method for the high-value recycling of edible mushrooms culture medium waste. Firstly, the influence of culture batchof edible oyster mushroom on the structural evolution of cultural residue was investigated. Then, a series of porous carbon materials with different porous structureswere successfully prepared from different cultural residues after various culture batches by a sample high-temperature carbonization method.Furthermore, KOH assistedhigh-temperature carbonization method was also used to optimize the porous structure. Finally, the elemental S was integrated with porous carbon products by melting method and used as cathode material for Li-S battery. The experimental results demonstrated that the porous carbon product (MRC-I) derived from the cultural residue of batch one had a high specific surface area and a honeycomb microstructure due to the interpenetration and decomposition of mycelia,which would be an ideal matrix for high storage amount of S and efficient transport of electrolyte. As expected, after S-loading, the MRC-I/S cathode exhibited excellent electrochemical performance. In addition, after activated by KOH under high-temperature carbonization process, a sponge-like carbon material (AMRC-I) with developed three-dimensional channels was obtained, which also exhibited a high specific surface area and hierarchical porous structure. The spongy structure and unique three-dimensional channels could encapsulate more Sactive materials and capture polysulfide ions physically, improving the utilization rate of active S substance and cycling stability. What's more, compared with other carbon materials, AMRC-I showedenhanced electrochemical performances, such as a high initial discharge capacity (1 111.31 mAh/g at 0.1 C) and a stable cycle life (355.99 mAh/g of reversible capacity after 100 cycles). This research provides a low-cost, available, and effective method to prepare carbon material for cathode in Li-S battery. This work also provides a high-value strategy for recycling of mushroom cultural residue resource.
    2022,38(23):207-217, DOI: 10.11975/j.issn.1002-6819.2022.23.022
    Abstract:
    The optimal reuse of abandoned mining land is of great practical significance to the construction and expansion space required by the transformation of resource-based towns. Taking Mentougou District of Beijing as an example, this paper integrated 3S technology and field research to analyze the type, area, distribution, reuse status and temporal and spatial changes of abandoned mining land in the study area. The geographical process dynamic environment model (Dinamica EGO) was used to simulate the reuse pattern of abandoned mining land under the trend development scenario. Based on the functional positioning of "Capital ecological conservation development area" of Mentougou District, coupled with principal component analysis and BP neural network method, the appropriateness of abandoned mining land reused for ecological agriculture, ecological tourism and high-tech industry was evaluated. According to the suitability evaluation results and the land needs of industrial transformation, the land conversion rules were set up, and the quantitative structure was optimized by combining the linear niche programming model and constraint conditions. Dinamica EGO model was used to optimize the spatial pattern of the reuse of abandoned mining land serving the industrial transformation. Regulation was conducted by comparing the optimization pattern with the trend development pattern. The results showed are as follows: 1) From 2006 to 2018, a total of 323.30 hm2 of abandoned mining land was reused in Mentougou District. The abandoned mining land in western towns was mainly reused as woodland, cultivated land and orchards, while the abandoned mining land in eastern towns was mainly reused as woodland, park, residential land and high-tech industrial land. 2) In the trend development scenario pattern, the abandoned mining land reused as ecological agricultural land was mainly distributed in Miaofengshan Town and Tanzhesi Town, the abandoned mining land reused as ecological tourism industry was mainly distributed in Datai Street and Wangping Town, and the abandoned mining land reused as high-tech industrial land was mainly distributed in Datai Street and Junzhuang Town. In the optimized pattern of abandoned mining land reuse serving industrial transformation, the area of abandoned mining land reused as ecological agriculture was 251.75 hm2, mainly concentrated in Junzhuang Town, Wangping Town, etc., the area reused as ecotourism was 67.25 hm2, mainly distributed in Miaofengshan Town, Qingshui Town, etc., and the area reused as high-tech industry was 84.25 hm2, mainly distributed in Wangping Town and Miaofengshan Town. 3) In the two scenarios, about 108.5 hm2 of abandoned mining land was reused for the same purpose, and no adjustment was needed. About 63.75 hm2 of abandoned mining land was reused as ecological tourism land under the trend development scenario, which should be adjusted to ecological agriculture land. About 61 hm2 of abandoned mining land was reused as ecological agriculture land under the trend development scenario, which should be adjusted to ecological tourism land. The 12.5 hm2 abandoned mining land in Miaofeng Mountain Town, Wangping Town and Yongding Town should adjusted and developed into high-tech industrial land in combination with local infrastructure. This study realized the direct and substantial combination of the reuse of abandoned mine land and the demand for industrial transformation of mineral resource-based towns. The research results have greater practical significance and practical application value, and provide theoretical support for the reuse and regulation of local abandoned mine land.
    2022,38(23):218-227, DOI: 10.11975/j.issn.1002-6819.2022.23.023
    Abstract:
    Accurate land cover information contributes to provide basic dataset for regional ecological protection and environmental management. Remote sensing (RS) images are commonly used as the main data source for land cover information extraction at present. However, there are complex landscape, broken distribution of ground objects, frequent cloud cover as well as serious radiometric distortion in hilly and mountainous areas, and thus it's difficult to accurately gain the distribution information of ground object only by satellite images. Fortunately, the collaborative application of multi-source heterogeneous data can make up for the deficiency of a single data source, accumulate more valuable information and increase the separability of ground objects, bringing great prospects for the extraction of land cover information in areas with complex surface landscape. In addition, the stacking algorithm combining the strength of different machine learning methods, presents superior and robust predictive performance in recently classification tasks. Therefore, the aim of current study is to explore the effectiveness of the multi-source heterogeneous data and stacking algorithm in land cover classification of hilly and mountainous areas. Specifically, taking the Qian Jiang District in Chongqing Province of China as the study area, various feature variables were extracted from multi-source heterogeneous data including Sentinel-1/2 images, digital elevation model (DEM), soil and climate data. Boruta method and Variance Inflation Factor (VIF) were applied to eliminate redundant feature and simplify statistic issue. Then, five schemes with different inputs (purely RS variables, RS variables plus climate factors, RS variables plus terrain parameters, RS variables plus soil parameters, and all variables) were created based on the optimized variables subset. Stacking algorithm was used to construct the classification model for exploring the impacts of different types of variables on land cover classification accuracy. Meanwhile, the best classification results using stacking algorithm were compared with support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost). Additionally, a novel Shapley Addictive Explanation (SHAP) method was introduced to quantify the importance of variables in the model. The results showed that the land cover classification accuracy was the lowest purely using remote sensing variables. After adding climate, soil, and terrain variables separately, the overall accuracy, Kappa coefficient and F1-score were significantly improved. Among them, the addition of soil variables brought the most improvement, followed by terrain parameters and climate variables. And the improvement in classification accuracy of agricultural land types (dry farmland, paddy field and orchard) is greater than that of other land cover types. Based on the stacking algorithm, the experimental scheme that combines all feature variables achieved the best classification accuracy with overall accuracy of 96.61%, Kappa of 0.96 and F1-score of 94.81%. Its classification accuracy is higher than that of the SVM, RF and XGBoost under the same variables. The SHAP method explicitly quantified and evaluated the global importance of each variable, indicating that the traditional vegetation and water spectral indictors are the most important feature variables. Besides, this technique also showed the local contribution of each variable for each land cover type, providing more valuable information on the selection and optimization of variables for the extraction of objects information for hilly and mountainous areas. This study offered technical support and theoretical reference for land cover mapping research in areas with complex landscape.
    2022,38(23):228-241, DOI: 10.11975/j.issn.1002-6819.2022.23.024
    Abstract:
    Scientific measurement of multi-functional trade-off and synergy of cultivated land is of great significance for quantifying and characterizing the hidden form of cultivated land, which can provide a scientific basis for constructing the regulation path of green transformation of land use and revealing the evolution process of human-land relationship. Based on the multi-functional theory of cultivated land, this study constructed the multi-functional analytical framework and functional classification evaluation system of cultivated land in the Yellow River Basin ( Henan section ) by using the time series social and economic development data from 1990 to 2020. The function of cultivated land was divided into production function, social function, ecological function and cultural function, and the multi-functional index of cultivated land in the Yellow River Basin ( Henan section ) was calculated. The evolution law of multi-functionality of cultivated land was revealed, and the dominant function of cultivated land in the Yellow River Basin ( Henan section ) at different stages of transformation was clarified. On this basis, the land system function trade-off degree ( LFTD ) model was used for trade-off and collaborative analysis. To explore the complex changes and mutual influence mechanism of cultivated land multi-function in the process of cultivated land transformation, so as to reveal the evolution law of hidden form of cultivated land use.The results show that : 1) From 1990 to 2020, the multi-function of cultivated land in the Yellow River Basin ( Henan section ) showed a fluctuating upward trend. Due to the improvement of the yield level of grain crops and the total power of agricultural machinery, the production function of cultivated land in the Yellow River Basin ( Henan section ) continues to increase ; with the increase of per capita net income of farmers, the social function index of cultivated land in the Yellow River Basin ( Henan section ) also increased slightly. At the same time, the continuous increase in the use of chemical fertilizers has led to a downward trend in the ecological function index of cultivated land in the Yellow River Basin ( Henan section ) after 2010. With the increase of cultural investment and agricultural sightseeing garden area, the cultural function of cultivated land in the Yellow River Basin ( Henan section ) continues to increase. 2) According to the functional hierarchy, the change of cultivated land multifunctionality from 1990 to 2020 was divided into six stages. In the first four stages of 1990-2010, production and ecological functions are the main functions, and in the last two stages of 2010-2020, production and cultural functions are the main functions, and the relationship between functions is more complicated. 3) From 1990 to 2020, the interaction among the production, social, ecological and cultural functions of cultivated land showed the evolution characteristics of " trade-off is dominant-trade-off and synergistic is balanced-trade-off is dominant ", and the cultivated land function in the Yellow River Basin ( Henan Section ) showed significant transformation characteristics after 2010. 4) The correlation of influencing factors of cultivated land transformation varies with time. The correlation changes of influencing factors from 1990 to 2020 show that urbanization rate, total power of agricultural machinery, total grain output and proportion of tertiary industry are significant influencing factors.The hidden morphological changes of cultivated land can deeply manifest the transformation of cultivated land use and provide reference for the sustainable use of cultivated land.
    2022,38(23):242-251, DOI: 10.11975/j.issn.1002-6819.2022.23.025
    Abstract:
    Hainan Island is one of the areas with frequent typhoons in China. The research on risk assessment agricultural typhoon disaster risk in Hainan Island can provide technical support for optimizing the layout of agricultural planting and strengthening agricultural disaster prevention and reduction. Supported by the theory and method of natural disaster system, this research has combined the rainfall, wind speed, typhoon occurrence time, digital elevation model data, rivers and watersheds, ratio vegetation index, agricultural population, agricultural output value, cultivated land area, land area and other factors during the occurrence of typhoons in Hainan Island for many years. Considering the risk of disaster-causing factors, the exposure of hazard-formative environments and the vulnerability of hazard-affected bodies, this research has constructed the assessment index system of agricultural typhoon disaster in Hainan Island involving 8 indicators, including maximum wind speed accumulation, rainfall accumulation, influence index of terrain factor, river network density, vegetation exposure, agricultural population density, output value per unit area of agricultural land and the proportion of cultivated land in land area, and has illustrated the risk comprehensive assessment model of agricultural typhoon disaster. Based on the analytic hierarchy process method, retained 15 experienced experts engaged in meteorology, agriculture, hydrology and geography to give the score according relative importance of each index. Then the weight is calculated by matrix judgment and consistency, and the contribution degree of 8 indexes for each Criteria layer and index layer is obtained. Combined with the typhoon occurrence data of Hainan Island over the years from 2001 to 2020, this paper has evaluated and analyzed the agricultural typhoon disaster risk of Hainan Island, and divided the agricultural typhoon disaster risk of cities and counties into five levels: level I, level II, level III, level IV and level V. The results showed that: the risk of agricultural typhoon disaster in Hainan Island is high, and the risk index is between 0.40 and 0.80, with an average of 0.61. The area of agricultural typhoon disaster risk level III and above accounts for 74.8%. The overall difference is obvious, showing that the risk of typhoon disaster in the northern and coastal areas of Hainan Island is much higher than that in the central mountainous area. Among them, Qionghai and Haikou have the highest risk, with the disaster risk integrated index of 0.712 and 0.689 respectively. Baoting, Baisha, Wuzhishan and Qiongzhong have the lowest disaster risk, and the integrated index of disaster risk are all lower than 0.540. The risk of disaster-causing factors and the exposure of hazard-formative environment for agricultural typhoon in Hainan Island are at a high level in northern areas such as Haikou, Wenchang, Ding'an, Chengmai, coastal areas such as Qionghai and Danzhou, and at a low level in central areas such as Baisha, Qiongzhong and Wuzhishan. The vulnerability of hazard-affected bodies is at a high level in Qionghai, Lingshui and Sanya, and at a low level in Baisha and Qiongzhong. This paper has proposed three countermeasures for agricultural typhoon disaster prevention and reduction and sustainable development, including adjusting the layout of agricultural planting, improving risk monitoring and early warning capability, and strengthening investment in agricultural policy insurance, according to the typhoon characteristics of Hainan Island and the risk distribution of agricultural typhoon disasters. The specific measures include giving priority to planting typhoon-resistant crops and winter melon and vegetable in Qiongdong region, establishing an intelligent monitoring and perception network using space-sky-terrestrial integration technology for agricultural typhoon disaster risk in remote mountainous areas, introducing new remote sensing technology in areas with developed agricultural activities to innovate the agricultural insurance underwriting and claim settlement mode, etc. The risk level distribution of agricultural typhoon disasters in cities and counties of Hainan Island and the corresponding countermeasures can support relevant departments to establish disaster prevention methods and emergency plans for regions with different disaster risk levels.
    2022,38(23):252-263, DOI: 10.11975/j.issn.1002-6819.2022.23.026
    Abstract:
    As an important reserve cultivated land resource, the rational development and efficient utilization of saline-alkali land is of great significance to food security in China and even the world. It is of great significance for the investigation, management and utilization of saline-alkali land resources to construct a systematic analysis framework and clearly define the concept and classification of saline-alkali land. Based on the theory and logic of the key belt of the earth, this study constructs a systematic analysis framework of saline-alkali land resources covering three layers of utilization layer, soil layer and DEM, defines the concepts and types of saline-alkali land and saline-alkali soil, in order to answer the key question of what is saline-alkali land and saline-alkali soil. Combined with the land use status map, soil map and DEM map, the characteristics of saline-alkali land resources in Songnen Plain were analyzed by GIS overlay analysis method, and the feasibility and scientificity of the system analysis method of saline-alkali land constructed in this paper were verified. The results showed that: 1) based on the theory and logic of the Earth 's critical zone, with the three-dimensional space as the link of organizing and connecting all levels, with the digital elevation as the base, according to the vertical and horizontal latitudes, the 'three-layer fusion' system analysis framework of saline-alkali land resources was constructed, which clearly defined the concept and classification of saline-alkali soil and saline-alkali land, and accurately expressed the characteristics of saline-alkali land resources; 2) Saline-alkali land is the land whose soil type is saline-alkali soil, which includes 6 categories: saline-alkali cultivated land, saline-alkali forest land, saline-alkali grassland, saline-alkali wetland, saline-alkali wasteland and other saline-alkali land; saline-alkali soil is a simple soil concept, which belongs to three types : saline soil, alkaline soil and saline-alkaline soil; 3) According to the data superposition, the total area of saline-alkali land in Songnen Plain is 2.55 million hm2, which is concentrated in the west of Songnen Plain. Wherein the largest area of saline-alkali farmland, 0.96 million hm2, mainly in the southern Tongyu County and other places. Saline-alkali wasteland, saline-alkali grassland, saline-alkali wetland and other saline-alkali land, with an area of 0.64 million hm2, 0.47 million hm2, 0.12 million hm2, 0.08 million hm2; the area of saline-alkali soil in Songnen Plain is the largest, which is 2.00 million hm2, the area of alkaline soil is 0.47 million hm2, and the area of saline soil is 0.11 million hm2; 4) The elevation of saline-alkali cultivated land in Songnen Plain is concentrated at 100-200 m, and the elevation gradually increases from the middle to the surrounding area. The slope is relatively gentle, concentrated below 6°, and the slope gradually increases from west to east. Saline-alkali unused land is mostly distributed in the southern region, and the altitude is concentrated at 100-150 m. Most of the slopes are below 2 °.Saline-alkali unused land has low terrain, slow slope and good development conditions. From this point of view, through the analysis method of saline-alkali land system constructed in this paper, the characteristics of saline-alkali land resources are analyzed accurately and scientifically, the concept of saline-alkali land is clearly defined, and the relationship between saline-alkali land and saline-alkali soil is clarified. This study can provide theoretical and methodological support for the investigation of saline-alkali land resources, provide scientific basis for the management and development of saline-alkali land in songnen plain, and also provide some theoretical and methodological references for the third soil census and saline-alkali land investigation in this area.
    2022,38(23):264-271, DOI: 10.11975/j.issn.1002-6819.2022.23.027
    Abstract:
    In order to explore the effect of Carrot antifreeze proteins (CaAFPs) on the properties of the dough under different freeze-thaw cycles and determine if -12℃ is suitable for frozen dough storage and its state, CaAFPs were added to the dough at a proportion of 0.5%, and the dough without CaAFPs was used as a control. By comparing 4 ℃ refrigerated, and subfrozen,-12℃ and -18 ℃ under three kinds of frozen storage temperature, freeze-thaw as the auxiliary means, measured under the different conditions of moisture content and water loss rate, freezable water content, texture and pH, in order to research on the freeze-thaw CaAFPs under the influence of the frozen dough properties and its mechanism. Through the comparison and significance analysis of the above data, certain rules can be found. The results showed that after five freeze-thaw cycles, the water loss rate of the dough in the control group showed an increasing trend in different degrees (P<0.05), and the addition of CaAFPs was helpful to delay the water loss of the dough, and the water loss rate in all groups decreased. The water content of the control group showed a decreasing trend in different degrees (P<0.05), and the water content was higher than that of the control group after adding CaAFPs (P<0.05) under freeze-thaw. The freezable water content of the dough in the control group showed an increasing trend in different degrees (P<0.05) under freeze-thaw. The addition of CaAFPs had a certain protective effect on the network structure of the dough, and the freezable water content decreased. In the control group, the hardness and gumminess showed an upward trend (P<0.05), while the springing, cohesiveness and chewiness showed a downward trend (P<0.05) under freeze-thaw. After adding CaAFPs, the texture characteristics of dough could be improved to a certain extent, making the texture change more slowly. In the control group, the pH of dough showed a decreasing trend in different degrees (P<0.05). After adding CaAFPs, the acidification of dough could be delayed, and the pH change trend of dough became smaller. In general, with the increase of freeze-thaw times, the moisture content of dough decreased, the water loss rate increased, the content of freezable water increased, the pH value decreased, and the texture became hard. But as the temperature drops, the opposite trend occurs. Among them, -12℃ and -18 ℃ are significantly better than 4℃, and there is no significant difference between them in the first two times of freeze-thaw, but after three times of freeze-thaw, -18℃ is obviously better than -12℃.The research results provide a certain reference for the application of CaAFPs in frozen dough and the optimization of freezing storage temperature. Dough can maintain good properties at -12℃ in sub-freezing storage, so it can be considered to store dough at -12℃ to save energy consumption and maintain its better state. At the same time, it also provides the research idea to study the properties of antifreeze proteins in the subfreezing state.
    2022,38(23):272-281, DOI: 10.11975/j.issn.1002-6819.2022.23.028
    Abstract:
    China is a major consumer of fruits, but its post production testing equipment for fruits is relatively backward. In order to solve the problem that the current online device cannot collect the full surface image information of apple and cannot accurately calculate the defect area, the research takes the rapid detection of the surface defect area of apple as the main goal, proposes the full surface image synthesis algorithm and defect area correction algorithm based on the ideal ball model, and designs a set of online detection and grading device for the external quality of apple. This device is different from the traditional full surface detection device. Four cameras are used to collect images at the same time to obtain the full surface images of apple, and then the two algorithms are used to synthesize and correct the collected images in order to obtain more accurate surface defect area values. This research takes apples as an example. By exploring the best excitation light source required for apple image acquisition and the refraction effect and influence on the fruit cup material, an online detection device is designed. Then, based on the ball model, an algorithm for apple full surface image synthesis and a defect area correction algorithm are proposed to accurately calculate the surface defect area of apples. Through experimental verification, after segmentation and synthesis of the apple surface image, the overall image miss rate is 0. A defect area correction algorithm is proposed, which can calculate the real area of apple defects at any position in the image. 120 samples are selected for verification, including 30 scratch samples, 30 bruise samples, 30 spot samples, and 30 surface corruption samples. The determination coefficient R2 between the predicted value and the true value of the scratch sample defect area is 0.978 7, the standard error RMSE (Root Mean Squared Error) is 3.577 4 mm2, R2 in the deflection angle experiment is 0.975 8, and the RMSE is 3.466 3 mm2. The R2 between the predicted value and the true value of the defect area of the impact sample is 0.973 0, the RMSE is 3.981 9 mm2, the R2 in the deflection angle experiment is 0.974 2, and the RMSE is 4.062 4 mm2. The R2 between the predicted value and the true value of the defect area of the speckled spot sample is 0.9708, the RMSE is 3.836 6 mm2, and the R2 in the deflection angle experiment is 0.977 9, the RMSE is 3.895 3 mm2; The R2 between the predicted value and the true value of the surface corruption sample defect area is 0.9812, the RMSE is 3.178 1 mm2, the R2 in the deflection angle experiment is 0.974 8, and the RMSE is 6.304 4 mm2. The detection speed of the device is 2 apples/s, the rating accuracy is 95%, the detection and apple rating accuracy is high, the work is relatively stable, and the detection and grading evaluation of external defects of apples are realized, providing technical support for the external quality detection of apple.
    2022,38(23):282-289, DOI: 10.11975/j.issn.1002-6819.2022.23.029
    Abstract:
    Green mold caused by Penicillium digitatum is one the most destructive postharvest diseases in citrus fruit. Chemical fungicides such as prochloraz can effectively control this disease, but their widespread use can easily lead to the drug resistance of this pathogen, environmental pollution and food safety problems. Previous studies have shown that plant essential oils and their bioactive components might be a type of potential biofungicide because they could effectively reduce the postharvest disease in citrus fruit without impairing the fruit quality, but its application was largely limited by their volatility and easily oxidized property. The inclusion of plant essential oils with cyclodextrins could overcome these drawbacks and thus improve the effectiveness of plant essential oils. In this study, the saturated aqueous solution method will be used to prepare the inclusion complexes of trans-2-hexenal, an active component in plant essential oils, with four kinds of cyclodextrins including α-cyclodextrin (α-CD), β-cyclodextrin (β-CD), γ-cyclodextrin (γ-CD) and hydroxypropyl-β-cyclodextrin (HP-β-CD), in an effort to improve the antifungal efficiency of trans-2-hexenal. At the same time, the antifungal activity of these inclusion complexes against P. digitatum will be analyzed by in vitro assay, and the structure and the corresponding inclusion mode of the inclusion complexe with highest efficiency will be determined. As a result, four inclusion compounds designated as α-CDTH, β-CDTH, γ-CDTH and HP-β-CDTH, respectively, were prepared by the saturated aqueous solution method. The morphological results showed that α-CDTH, β-CDTH and γ-CDTH powders were fine and dense, while HP-β-CDTH powder was rough and the particles were distinct. The in vitro antifungal results demonstrated that these inclusion compounds could effectively inhibit the growth of P. digitatum mycelium in a concentration-dependent manner. The minimum antifungal concentration (MFC) of β-CDTH and γ-CDTH to the mycelial growth of P. digitatum was estimated to be both 1.00 mg/mL, while the MFCs of α-CDTH and HP-β-CDTH were 2.00 mg/mL and 4.00 mg/mL, respectively. Results of the entrapment efficiency indicated that γ-CDTH has the highest entrapment efficiency (75.36 %) whereas HP-β-CDTH has the lowest entrapment efficiency (38.63 %). The phase solubility curves of the four cyclodextrin inclusion compounds were of AL type, and the solubility was in the order of HP-β-CD>γ-CD>β-CD>α-CD. Taken the in vitro antifungal efficiency, entrapment efficiency and solubility into consideration, γ-CDTH had the best overall performance and was selected for the follow-up experiments. In vivo assay showed that γ-CDTH at different concentrations could reduce the incidence of green mold in citrus fruit at varying degrees (P<0.05), with 8.00 g/L γ-CDTH being the most effective concentration. When the control fruit were totally rotten after 6 d of storage, the disease incidence in samples of 8.00 g/L γ-CDTH treatment was only 58.3 %, which was comparable to that of prochloraz (56.7 %). In addition, γ-CDTH treatment effectively maintained citrus fruit firmness and had no adverse effects on the weight loss rate, color, vitamin C and total soluble solids contents of citrus fruit. The scanning electron microscopy (SEM) observation revealed that the shapes and sizes of γ-CDTH were quite different from those of γ-CD and physical mixtures. For γ-CD, the varying sizes and irregular crystals were found. In contrast, the physical mixtures had a rough surface whereas the γ-CDTH had a smooth surface with a flake-like morphology. The nuclear magnetic resonance (NMR) analysis demonstrated that the hydrogen bonding interactions between H-3? and H-5? of γ-CD and H-6? of trans-2-hexenal were attributed to the formation of γ-CDTH. In summary, four inclusion compounds of trans-2-hexenal with cyclodextrins were prepared and the antifungal efficiency and structural characteristics of γ-CDTH were further verified. Our present results can provide a direct basis for the use of γ-CDTH in controlling citrus postharvest diseases and a theoretical basis for the development of plant-derived natural preservatives.
    2022,38(23):290-298, DOI: 10.11975/j.issn.1002-6819.2022.23.030
    Abstract:
    Akind of cheap cold storage material is prepared according to the requirements of temperature cold chain logistics field of fresh refrigerated transport. Firstly, the mixed solutions of the main energy storage agent's glycine, sorbitol, mannitol and potassium chloride are respectively configured into aqueous solutions of different concentrations. Then, differential scanning calorimetry (DSC) was used to determine the latent heat of phase transition and Onset temperature at different concentrations. Through comparison and discussion, the combination of glycine and sorbitol, potassium chloride and mannitol were finally selected, and two kinds of combination schemes were obtained.The first one was based on 0.1 mol/L sorbitol aqueous solution as the compound of Onset temperature adjustment. According to the volume ratio of 1:1, 0.8 mol/L, 0.6, 0.4, 0.2 and 0.1 mol/L glycine aqueous solution (named as composite solution A1-A5) were added respectively. In the other compound scheme, 0.6 mol/L mannitol aqueous solution was used as the compound agent to adjust the temperature of Onset. According to the volume ratio of 1:1, 0.8, 0.6, 0.2, 0.1 and 0.05 mol/L potassium chloride aqueous solution (named as composite solution B1-B5) were added respectively. Through the undercooling test of composite solution A1-A5, it is concluded that composite solution A2 has better performance. The thermal properties of compound solutions A2 and B1-B5 were determined by differential scanning calorimetry (DSC). The composite solution B1-B5 is prone to undercooling, so the composite liquid A2 is chosen as the main energy storage agent of the final composite phase change cold storage material. Finally, the mixed solution A2:0.6 mol/L glycine +0.1 mol/L sorbitol was determined as the main coolant, which was named TA2. Then, nano-sized titanium dioxide and nano-sized alumina were added to system TA2 as the base liquid, and super absorbent resin (SAP) was added to optimize the leakage prevention phenomenon, to explore the latent heat and thermal cycle stability of composite phase change cold storage materials after the addition of nanoparticles. It is concluded that adding 0.5% nano-TiO2 has the best effect on improving the supercooling degree and thermal conductivity of cold storage materials. In view of the leakage problem of cold storage bag, adding 0.25% super absorbent resin (SAP) can effectively prevent leakage. The final optimized nanophase change cold storage material is TA2+0.5%TiO2+0.25%SAP, its latent heat is 294.57J/g, the initial temperature is -5.8℃. It can meet the temperature zone performance requirements of fresh refrigerated transport. The results of 200 cycle tests show that the material has good stability and can be used in practical cold chain logistics. This nano-composite phase change cold storage material was applied to a homemade incubator, and the cooling properties of the incubator were tested with crystal pear as the test object. Considering the influence of side arrangement and top arrangement plus side arrangement on the cooling performance of the cold storage incubator, the temperature changes of each point in the cold storage incubator under loaded and empty conditions were compared. The results show that the average temperature in most of the boxes is 1.9℃ under the arrangement of side cloth and top cloth, which can be kept at 0~ 5℃ for 480min. The temperature field is more uniform, which is conducive to maintaining the freshness of fresh products.
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      2022,38(22):1-11, DOI: 10.11975/j.issn.1002-6819.2022.22.001
      Abstract:
      Abstract: Soybean is one of the most important grains and oil crops in China, due to a major source of oil and high-quality vegetable protein. It is very necessary to realize the low-loss harvest of soybean fields in the southern and Huanghuaihai regions. In this study, a 4LZ-1.5 type combine harvester was designed to consider the harvest of soybean breeding plots. The operation process was also theoretically analyzed for the soybean reel harvesting, according to the soybean pods easy to be fried at maturity. A numerical model was established for the reel structure and motion parameters. Some parameters were then optimized, such as the reel radius, reel speed ratio, and reel rotational speed. After that, the soil removal mechanism was optimized for the soybeans with the low pods and easy-to-shovel soil, according to the statistical parameters of soybean grain size. Furthermore, a soybean threshing and separation device was designed for the easy threshing and breakage of soybeans at maturity. The arrangement and distribution of the arch teeth were also determined via the increasing characteristics of the second-order arithmetic sequence. The angle of the deflector was adjusted for the various input amount. The blade fan-combined screen cleaning device was designed to optimize the structural parameters of the fan and cleaning screen. The pneumatic grain unloading device was designed to optimize the vortex fan. The plot harvesting required the high soybean mixed seeding, particularly for the breeding plot with a small planting scale and many varieties, compared with the field production. Frequent seed cleaning was required after harvesting to reduce the missed and mixed seeding, according to the harvest requirements of the breeding area. An optimization mathematical model was established to develop the seed cleaning device, together with the objective function and constraint conditions. A numerical simulation was then carried out using MATLAB, in order to determine the structural parameters of the seed-cleaning device. A series of comparative experiments in field harvesting were conducted in the Xinjiang Uygur Autonomous Region, Shandong province, and Hebei province of China. The better operating performance was achieved in the 4LZ-1.5 soybean combine harvester: the loss rate < 3.5%, broken rate < 1.5%, and impurity rate < 1%, fully meeting the soybean harvest requirements in most hilly areas. After harvest testing of 14 soybean varieties in a 3m×6m breeding plot, the test results were all achieved: the loss rate < 3%, broken rate < 1.5%, impurity rate < 1%, mixed seed rate < 0.2%, and the clearing time of 200-270 s, fully meeting the requirements of the harvesting operation indicators in the breeding plots. Compared with the existing soybean harvesting machinery, the harvest loss rate of 4LZ-1.5 soybean combine harvester was reduced by 1.5%-5.0%, the broken rate was reduced by 3.5%-6.5%, and the impurity rate was reduced by 2.0%-7.0%. The findings can provide a strong reference for the structural optimization of operating parameters in soybean harvesters.
      2022,38(22):12-22, DOI: 10.11975/j.issn.1002-6819.2022.22.002
      Abstract:
      Abstract: An energy recovery device, the double-suction centrifugal pump as the turbine has a wide application prospect in the field of large flow and high-pressure head. The impeller is one of the most important rotating flow components. Its working efficiency can pose a great influence on the energy conversion of the double-suction pump as the turbine. Meanwhile, the internal friction and unstable flow in the impeller can cause the hydraulic loss of the double-suction pump as the turbine, leading to the low efficiency and safety of the pump as the turbine operates. However, the local and wall entropy production rate can be classified as the dissipation caused by irreversible factors, according to the entropy production theory. The local entropy production rate includes the direct entropy production rate caused by non-uniform time average velocity distribution and the turbulent entropy production rate caused by non-uniform fluctuation velocity distribution. Furthermore, the location and size of the irreversible loss in the flow process can be diagnosed by the entropy production theory. In this study, a Shear Stress Transport(SST) κ-ω turbulence model was adopted to clarify the energy loss mechanism in the pump as the turbine impeller. A numerical simulation was then carried out using reasonable mesh division and an accurate boundary layer under Computational Fluid Dynamics(CFD). An external characteristic test was conducted to verify the numerical simulation strategy. Finally, a systematic analysis was made on the energy loss of each flow-through component in the pump under different flow rates, in order to determine the area of high entropy production rate in the pump as the turbine impeller. The energy loss mechanism of the impeller area was clarified to combine with the entropy production theory. The results show that the main reasons for the hydraulic loss in the whole machine were the entropy production rate of turbulent caused by the unstable flow in the impeller channel, and the wall entropy production rate caused by the internal friction in the near-wall area. The average proportions were 41% and 55%, respectively, indicating the extremely low proportion of direct entropy production rate. The total entropy production rate of each flow-through component was ranked in the descending order of the impeller, draft chamber, and volute, where the average proportions were 55%, 30%, and 15%, respectively. In the local entropy production rate of the impeller area, the main reasons were determined for the increase of turbulent entropy production rate and energy loss. Specifically, the uneven distribution of velocity was found in the flow field, due to the unstable flow, such as vortex, reflux, and flow separation. Among them, the reverse transmission was normally attributed to the internal flow state of the impeller, including the flow separation and vortex generated at the suction and pressure side of the blade, dynamic and static interference between the volute tongue and impeller, the curved flow with the strong curvature between some impeller channels, and the backwater area of the draft chamber. In addition, the entropy production rate continuously increased on the wall with the increase of flow, due to the dynamic and static interference between the volute tongue and the blade, the interaction between blade, shroud, and fluid, the sharp increase of velocity gradient near the wall, and the increase of shear force and viscous force. At the same time, the flow in the channel posed a great influence on the entropy production of the front cover wall. But, there was no influence on the rear cover wall, which was closely related to the special back-to-back impeller structure of the double suction pump. This finding can provide a strong reference for the hydraulic optimization design of the double-suction pump as the turbine.
      2022,38(22):23-31, DOI: 10.11975/j.issn.1002-6819.2022.22.003
      Abstract:
      Abstract: Sugarcane is mainly planted in hilly areas, such as the province of Guangxi and Yunnan, China. Time-varying and nonlinear working parameters can often be found in the sugarcane horizontal planters, due to the relatively complex and changeable operating conditions. A high failure rate of blockage can often occur in the fertilization mechanism in this case. Moreover, it is difficult to maintain the damage to the chain and drive shaft after the blockage. The performance of fertilization can also be reduced to destroy the transmission mechanism, because the wet and agglomerated fertilizer can be concurrently blocked in the fertilization mechanism of the sugarcane horizontal planter. Moreover, it is still lacking in the automatic control of clearing and blocking in the fertilization mechanism of mechanical transmission type. In this study, a fertilization monitoring system was proposed to carry out the electro-hydraulic transmission and control transformation of the fertilization mechanism. A set of fertilization and anti-blocking control system was constructed using Particle Swarm Optimization (PSO) - Back Propagation (BP) neural network prediction. The input parameters were taken as the pressure and speed of the fertilizing motor, as well as the amount of fertilizer in the fertilizer tank, whereas, the output was the working state (no load, normal, heavy load, and blocked) of the fertilizing mechanism. The BP neural network was used to establish the mapping relationship between the input and the output. The PSO was used to optimize the weights and thresholds of the BP. After that, the prediction accuracy increased from 97% to 99%, and the determination coefficient R2 increased from 0.977 5 to 0.982 9. The results showed that the PSO-optimized BP neural network presented a better prediction effect. The BP neural network optimized by the PSO was used to identify the fertilization state with higher accuracy. The PSO-optimized BP neural network was selected as the network model to predict the working state of fertilization. The control program of the single-chip microcomputer was written into the trained prediction model. The control system of the fertilizer application mechanism was designed, where the pressure transmitter was to collect the pressure value of the hydraulic motor, the Hall proximity switch was to collect the speed value of the screw shaft, and the photoelectric sensor was to monitor the fertilizer status in the fertilizer box in real time. The workshop test was carried out, where the test indicators were the accuracy rate to identify the response of the fertilization mechanism working state, and the probability of preventing blockage under heavy load. The results showed that: the accuracy rate of working state response recognition was 89% under the heavy load state. The control system was used to control the forward and reverse rotation of the fertilization motor. The probability was 87.5% for the removal of blockages. Therefore, the monitoring system with a neural network can be used to accurately identify the various working states of the fertilization mechanism during the field experiment. The heavy-load state of the fertilization mechanism can be accurately predicted by the monitoring system. The anti-blocking control command was executed without blockage failure. Anyway, the fertilization anti-clogging monitoring system can fully meet the working condition prediction and anti-clogging control requirements of the fertilization mechanism under complex and changeable working conditions. Consequently, the working condition monitoring and anti-blocking control system of the fertilization mechanism in the sugarcane planters can be expected to promote the high quality and efficiency of fertilization operations, in order to effectively reduce the blockage failure rate and the time of downtime for troubleshooting. This finding can also provide a new reference for the automation transformation of fertilization.
      2022,38(22):32-40, DOI: 10.11975/j.issn.1002-6819.2022.22.004
      Abstract:
      Abstract: High-driving comfort seat has been one of the core components in various vehicles for market competitiveness. Among them, the driving comfort of tractors has also received much more attention in agricultural production. The seat is the main contact part between the tractor and the driver. However, the current ergonomics design of the tractor seat can easily trigger driver back fatigue, even waist occupational disease. It is a high demand to optimize the parameter of the seat for better human-machine matching of the tractor. In this study, a three-dimensional model of the driving environment was established under the layout of the tractor, according to the relevant standards of cab design. A "Hill muscle model" was adopted to propose a musculoskeletal model suitable for the human body size of Chinese adults, according to the Chinese human body size standard GB 10000-1988 "Human Size of Chinese Adults". An operator-operation environment coupled biomechanical model was also established using the biomechanical software AnyBody, where the contact constraints were set to balance the degree of freedom. The 5th, 50th, and 95th percentile drivers were selected as the research objects. The target parameters were taken as the tractor seat backrest inclination, the horizontal distance between the SWC point and the SIP point, as well as the vertical height between the SIP point and the floor. The indicators were the activity of the lumbar muscle group erector spinae, multifidus, rectus abdominis, and external oblique. The contribution rate of each muscle group was determined by the coefficient of variation, in order to measure the overall comfort of the waist. A systematic analysis was then made to clarify the effect of the seat parameters on the biomechanical characteristics of the driver's lumbar muscle. As such, the optimal seat parameters were determined using inverse dynamics. A multi-degree-of-freedom driving platform was developed to test the different seat positions under the condition of various parameters. The muscle activity of the four main muscle groups in the lumbar region was also calculated for the different percentages of drivers. The results show that a better consistence between the test and simulation was achieved to effectively adjust the seat parameters for the better comfort of the driver's lumbar. In the 5th and 50th percentile drivers, the seat backrest inclination was a dominant effect on lumbar comfort. By contrast, the seat horizontal distance and vertical height were dominated by the lumbar comfort of the 95th percentile driver. An optimal combination of parameters was also obtained for the lowest total activity of the four muscle groups and the highest comfort of the driver's lumbar. In the 5th percentile driver, the optimal combination was: the seat backrest inclination was 9.7°, the horizontal distance was 472.1 mm, and the vertical height was 465.3 mm. In the 50th percentile driver, the optimal seat backrest inclination was 13.9°, the horizontal distance was 495.6 mm, and the vertical height was 485.3 mm. In the 95th percentile driver, the optimal seat backrest inclination was 14.8°, the horizontal distance was 526.4 mm, and the vertical height was 520.7 mm. The dynamic and static driving comfort of the seat can be expected to further quantify in the combination with the actual driving operations when turning the steering wheel or stepping on the pedal. The finding can provide a new idea to optimize the seat position parameters of agricultural equipment.
      2022,38(22):41-51, DOI: 10.11975/j.issn.1002-6819.2022.22.005
      Abstract:
      Abstract: Unmanned Aerial Vehicle (UAV) has been widely used to collect data from the wireless sensor node in fields. Some problems can be solved in this case, such as no network infrastructure in farmland, fast power consumption of multi-hop data forwarding, premature death of nodes near the gateway, and shortened network life cycle. However, the multiple nodes overlapping can often occur during UAVs collection at the same time, due to the possible redundancy of adjacent sensor data. In this study, a UAV data collection method was proposed to plan the node selection, hovering position, and collecting order using improved deep reinforcement learning. The UAV data collection from the sensor nodes was then divided into two scenarios: data collection from the partial nodes under perceptual redundancy coverage, and data collection from all nodes. The optimization was made to save the UAV energy consumption in less mission completion time. The data collection of partial nodes under perceived redundancy coverage was suitable for the relatively high proportion of redundant coverage area among nodes. The UAV energy also failed to complete the data collection tasks of all nodes, indicating the low requirements of data integrity. By contrast, the all-node data collection fully met the high requirement of data integrity. In the scenario of partial node data collection with perceived redundant coverage, the Dueling Double Deep Q Network (DDDQN) was used to select the collection nodes and then plan the collecting order, indicating the high energy efficiency of the UAV with the less redundant data. Simulation results show that the DDDQN presented greater data coverage and lower effective coverage average energy consumption than the Deep Q Network (DQN) under the same configuration. The training process of DDDQN was more stable than that of DQN, particularly for the higher returns at the end of learning. More importantly, the flight distance and energy consumption of the DDDQN were reduced by 1.21 km, and 27.9%, respectively, compared with the DQN. In the scenario of all-node data collection, a Double Deep Reinforcement Learning (DDRL) was proposed to optimize the hovering position and UAV collection sequence, in order to minimize the total energy consumption of the UAV during data collection. A comparison was made on the DDRL with the classical PSO-TSP and MEFC. A systematic evaluation was made to clarify the impact of the UAV flight speed on the total energy consumption and total working time, the impact of different node data loads on the UAV energy consumption, the impact of different flight speeds on the UAV hover collection time, and the impact of the number of sensor nodes on the total energy consumption. The simulation results show that the total energy consumption of the improved model was at least 6.3% less than that of the classical PSO-based Travel Salesman Problem (PSO-TSP), and the Minimized Energy Flight Control (MEFC) under different node numbers and UAV flight speeds, especially at the data load of a single node less than 160 kB. Finally, the flight and hover powers of the quadrotor UAV were tested to determine the packet loss rate and received signal strength of the UAV in the field experiments. The actual field flight experiments were carried out on the DDRL and the data collection of the classical PSO-TSP. Field experiment results show that the DDRL-based data collection was reduced by 11.5% for the total energy consumption of UAV, compared with the PSO-TSP. The DDDQN and DDRL approaches can be expected to provide the optimal energy consumption for the UAVs' data collection of wireless sensor nodes in the field.
      2022,38(22):52-62, DOI: 10.11975/j.issn.1002-6819.2022.22.006
      Abstract:
      Abstract: Black soil can be one of the most fertile soil groups with relatively high carbon stocks and production capacity. The black soil region can also play an important role in national food security and sustainable development in China. However, overexploitation and utilization have caused serious soil erosion in the black soil region of northeast China in recent years. There is a direct impact of the difference in tillage pattern on the soil erosion characteristics of sloping farmland. Fortunately, ridge farming can be commonly used in the tillage pattern. Furthermore, the ridge-furrow intervals with less amount of soil movement can also be used without occupying the farmland in this region. Therefore, it is of great significance to accurately evaluate the suitable measures of soil and water conservation. In this study, a systematic review was proposed to clarify the effects of ridge direction, ridge size, and ridge-furrow intervals on the soil erosion characteristics of sloping farmland in the Chinese black soil region. Furthermore, the relationship among the ridge patterns, the ridge-furrow intervals, and soil erosion was then established to determine the key fields to be strengthened in future studies for the major challenges. The results indicated that the pattern of longitudinal ridge-tillage was still the most common-used tillage pattern. The soil erosion gradually deteriorated to shift the soil erosion types from sheet to rill erosion, leading to less soil quality and crop yield. A better way was found to control soil erosion in the general patterns of contour ridge-tillage and sloping ridge-tillage, which was closely related to ridge failure. Among them, the pattern of sloping ridge-tillage was more likely to occur the ridge failure. Once the ridge failure occurred, the soil erosion increased significantly, even much more than that of the pattern of contour ridge-tillage. Thus, the pattern of contour ridge-tillage can be expected to effectively decrease the soil erosion at the sloping farmland in the black soil region. Furthermore, the pattern of the narrow ridge is also commonly used in the black soil region of northeast China in the long term. Therefore, it is very necessary to determine the effects of narrow ridges and their operation patterns on soil erosion. The pattern of the wide ridge is widely used in large-scale intensive farms and rural cooperatives, rather than individual farms, due to the outstanding control effect on the soil erosion for the high crop yield. Thus, it is a high demand for wide ridges among the individual farms in the future, in order to protect the precious black soil resources. The control effect of the ridge-furrow intervals pattern on the soil erosion depended mainly on the rainfall amount, rainfall intensity, slope gradient, ridge size, and the spacing of the ridge-furrow intervals. Therefore, it is suggested that the pattern of ridge-furrow intervals is gradually applied to the sloping farmland in the black soil region, in order to separate the layout, and then cooperate with the wide ridge, slope terrace, plant hedge, subsoiling, and straw return. The optimal allocation mode can be further improved the better measures of the composite soil and water conservation for less soil erosion. Much effort was also made into the effects of tillage patterns on the soil erosion of sloping farmland in the black soil region. Nevertheless, the technical conditions can still be limited to systematic research in this field. As such, the future directions can be proposed to analyze the influencing mechanism of ridge patterns, the coupling relationship between ridge direction and ridge size, the ridge design for the pattern of ridge-furrow intervals, and the comprehensive factors analysis of the effect of ridge pattern on the soil erosion in the sloping farmland. In conclusion, the systematic research is very necessary to focus on the effects of ridge patterns and ridge-furrow intervals on soil erosion at the sloping farmland in the black soil region.
      2022,38(22):63-72, DOI: 10.11975/j.issn.1002-6819.2022.22.007
      Abstract:
      Abstract: Driving mechanisms of Fractional Vegetation Cover (FVC) can be a prerequisite for decision-making on vegetation restoration and management. As the intersection of farming and animal husbandry activities in China, the Liaohe River basin is of great significance for the regional ecological construction and environmental protection, in order to clarify the internal vegetation change characteristics and driving mechanisms. Much effort has been made into the characteristics and influencing factors of vegetation change in the region. However, it is still lacking in the spatial heterogeneity of vegetation in the region as an Agro-pastoral intersection zone. Since vegetation change is a complex process, it is very necessary to fully consider the complex influence of the interaction between environmental factors on vegetation change, rather than only the individual factors. In this study, the spatial heterogeneity of FVC was analyzed in the Liaohe River Basin from 2010 to 2019 using the Normalized Difference Vegetation Index derived from the MOD13Q1 product. Furthermore, the factor regression and interaction were combined to jointly explore the effects of natural and socioeconomic factors on the vegetation changes from a regional and overall perspective. The results showed that: 1) There was an overall rising trend of FVC, with a 10-year average FVC of 68% and an overall high level of vegetation cover. The most significant was ranked in the order of the pastoral areas > agricultural areas > semi-pastoral areas, and the vegetation improvement trend in the pastoral areas, in terms of the rising trend of vegetation cover. 2) The explanatory power of natural factors on the vegetation changes in the whole basin was greater than that of human factors, among which the explanatory power of precipitation was the most significant. At the same time, there was an outstanding synchronization between the vegetation and precipitation change, where this trend was the most significant in the pastoral areas. 3) The interaction indicated that most factors showed a mutually reinforcing and non-linear enhancement of vegetation change. It infers that the vegetation change was a complex process with multi-factor effects from a system perspective. There were no completely independent factors. The three largest groups of interacting factors across the basin were the precipitation and temperature, precipitation and elevation, and precipitation and wind speed. The natural factors dominated the interaction of vegetation in the pastoral and semi-pastoral areas. By contrast, a combination of natural and human activities significantly affected the vegetation change in the agricultural areas. 4) The precipitation gradient greatly contributed to the explanation degree of FVC spatial heterogeneity. The environmental factors better fitted the FVC with the increase in precipitation. The precipitation was an important catalyst for the vegetation change. 5) human activities also posed an important influence on the vegetation change. The positive effects of human activities were generally dominant in the study area over the past 10 years. Such reasonable human activities can be maintained to increase the FVC in the Liaohe River basin.
      2022,38(22):73-80, DOI: 10.11975/j.issn.1002-6819.2022.22.008
      Abstract:
      Abstract: To further understand the response mechanism of stomatal traits and leaf gas exchange of maize (Zea mays L.) to elevated CO2 concentration and high temperature stress, we examined the combined effects of double atmospheric CO2 concentration and high temperature on plant growth, stomatal traits, and leaf gas exchange parameters of maize grown at six environmental growth chambers with three temperature regimes ((day/night) 25/19 ℃, 31/25 ℃, and 37/31 ℃) and two CO2 concentrations (400 μmol/mol (C400) and 800 μmol/mol (C800)), respectively. These environmental growth chambers were controlled with the same environmental factors, where the Photosynthetic Photon Flux Density (PPFD) was 1 000 μmol/(m2·s) and the relative humidity was 50%to 60%. In each chamber, we measured the net photosynthetic rate (Pn), transpiration rate (Tr) and stomatal conductance (gs) using a portable photosynthesis system (LI-6400XT, LI-COR Inc., Lincoln, NE, USA). The maximum photochemical efficiency of PSII (Fv/Fm) was estimated by measuring chlorophyll fluorescence with a photosynthesis efficiency analyzer (Handy PEA, Hansatech Instrument Ltd., Norfolk, UK). In addition, we also measured the leaf area, leaf length, and leaf width as well as the final leaf number of maize plants. The results showed that: 1) The stomatal density of maize was significantly increased by temperature (P < 0.001), but barely affected by CO2 concentration (P > 0.05). Meanwhile, the increase of stomatal density on the adaxial leaf surface was significantly higher than that on the abaxial surface of maize leaves, which indicated that the response of stomatal density on the adaxial leaf surface to elevated temperature might be more sensitive than that on the abaxial leaf surface of maize. Furthermore, the results also showed that the increase of stomatal density was accelerated with the elevated temperature on both the adaxial and abaxial leaf surfaces of maize. 2) The leaf transpiration rate were significantly enhanced by 57% and 84% with increasing growth temperature(day/night) from 25/19 ℃ to 37/31 ℃ at both the ambient (C400) and double atmospheric CO2 concentrations (C800). And there were linear positive correlation between the stomatal density on the adaxial and abaxial leaf surfaces and the transpiration rate of maize plants (adaxial surface, R2=0.69; abaxial surface, R2=0.71), which indicated that the leaf transpiration rate could be improved by adjusting stomatal density to optimize leaf gas exchange efficiency under high temperature environment. 3) The net photosynthetic rate (Pn) of maize was also significantly enhanced by 23% and 21% with increasing temperature(day/night) from 25/19 ℃ to 31/25 ℃, however, the Pn drastically declined by 24% and 13% when the temperature increased from 31/25 ℃ to 37/31 ℃ at both CO2 concentrations, which indicated that the high temperature (37/31 ℃) might result in physiological damages to the sites of photosynthetic reaction center, but this thermal stress from high temperature could be alleviated by elevated CO2 concentration. Also, the maximum photochemical efficiency (Fv/Fm) of maize drastically decreased at both CO2 concentrations when the temperature was elevated from 31/25 ℃ to 37/31 ℃. Overall, The results in this study maybe of significance for further understanding the potential mechanisms and processes of elevated atmospheric CO2 concentration mitigating the physiological damage of high temperature to maize plants under future climate change.
      2022,38(22):81-88, DOI: 10.11975/j.issn.1002-6819.2022.22.009
      Abstract:
      Abstract: Nitrogen is one of the most essential elements for crop growth. Nitrogen fertilizer has been widely applied to increase crop yields. At the same time, a large number of negative impacts have posed a great threat to the ecological environment in recent years. Among them, nitrogen leaching can be attributed to the excessive application of chemical fertilizers in farmland. Fortunately, the combined application of organic and chemical fertilizers can be expected to effectively reduce soil nitrogen leaching in normal fertilization during agricultural production at present. Therefore, this study aims to explore the combination application mode of organic and chemical fertilizers with a low risk of nitrogen leaching in farmland. The search terms were selected as chemical fertilizer, organic fertilizer, and nitrogen leaching using the two databases of China National Knowledge Infrastructure (CNKI) and Web of Science. The peer-reviewed and published papers were then obtained up to January 2022. Finally, a total of 35 papers (22 papers from Web of Science, 13 papers from CNKI) and 331 effective data pairs were collected after screening for the combination application of organic and chemical fertilizers in farmland. The target variables were taken as the total nitrogen (TN), nitrate nitrogen (NO3--N), and dissolved organic nitrogen (DON), while the chemical fertilizer was the control. After that, Metawin 2.1 software was used to determine the overall effects of the total amount of fertilization, fertilization structure (organic fertilizer substitution ratio), fertilization time (basic topdressing), and the types of organic fertilizers on the nitrogen leaching, where the chemical fertilizer was as the control. The results showed that there was a significant influence of the above fertilization behavior on nitrogen leaching. Once the total amount of nitrogen was less than 200kg/hm2, the leaching of TN and NO3--N in farmland decreased by 36.77% and 65.05%, respectively. When the substitution ratio of organic fertilizers was higher than 70%, the TN leaching was reduced by 39.64%, whereas the risk of dissolved DON leaching increased by 15.78%. Especially, there was a 26.31% increase in DON leaching in the application of animal-based organic fertilizers combined with chemical fertilizers. Correspondingly, the application of nitrogen fertilizer significantly reduced the leaching of TN and NO3--N by 43.58% and 70.51%(P<0.05), respectively. A certain impact was also found in the soil pH and land use patterns on nitrogen leaching. For example, the combined application of organic and chemical fertilizers on the alkaline dryland soil effectively inhibited the leaching of TN and NO3--N, whereas, there was an increase in the leaching of DON by 26.63%-42.95%. Nitrogen leaching in dryland was dominated by the NO3--N leaching. By contrast, the emission factor (EF) was higher than that in the paddy field. The increasing replacement ratio of organic fertilizers can be expected to greatly reduce the soil nitrogen leaching in dryland, but to enhance the DON leaching. In addition, the Matlab software was used to analyze the importance of factors using the random forest model. Specifically, the replacement ratio of organic fertilizer demonstrated a dominant effect on TN leaching. There was also the more important effect of the nitrogen application level on the NO3--N and DON leaching. Therefore, the low level of nitrogen application and the high substitution ratio of animal-based organic fertilizers can be used to effectively reduce the soil nitrogen leaching loss in the alkaline dryland, compared with the chemical fertilizers only. The finding can provide the practical basis for the combined application of organic and chemical fertilizers in farmland.
      2022,38(22):89-101, DOI: 10.11975/j.issn.1002-6819.2022.22.010
      Abstract:
      Abstract: Field surface temperature is one of the most important parameters for the water/heat exchange between soil, crop and atmosphere, particularly for the remote sensing inversion model of irrigation areas. Among them, the crop canopy temperature and soil surface temperatureare often mixed in the field surface temperature data at the early growth stage, due to the crop growth and development in the row and plant spacing. Continuous observation can normally be implemented using the thermal infrared sensor of the automatic monitoring system. The mean value of monitored temperature data is usually used to replace the temperature at the actual position at present. The mixed temperature data can pose a great challenge to the calculation accuracy of the fine field irrigation model during data processing. In this study, an improved screening was combined with the Logistic crop growth model to accurately partition the massive monitoring data of field surface temperature, considering the Leaf Area Index (LAI), crop canopy height, and the key points of crop growth status. The measured temperature data of maize and sunflower was collected in the Yongji experimental station in Inner Mongolia of China in 2021. The scanning temperature data was obtained using the field monitoring system (CTMS-On line). The screening algorithm was then designed and verified. The field observation data of maize and sunflower was collected in the Jiefangzha irrigation field in 2015, while the maize data was in the Changchun experimental station of Jilin Province from 2018 to 2019. Results showed that: 1) An efficient determination was achieved in the data screening for the surface temperature of sparse vegetation in the fields. A logistic model was used to simulate the key points in the screening algorithm, considering the crop growth indicators of LAI and crop canopy height. 2) Taking the relative error as an example, the optimization ranges of canopy temperature and soil surface temperature were about 10%, and more than 5%, compared with the temperature measured by the hand-held thermometer. A higher accuracy of data screening was achieved in the canopy temperature and soil surface temperature acquisition. 3) The correction factor after the screening was then determined, according to the crop planting density and LAI. Among them, the correction factors of crop canopy temperature (0.9) and soil surface temperature (1.1) were selected for the maize. The correction factors for the sunflower were specified as the correction factors of crop canopy temperature of 0.7 and the correction factors of soil surface temperature of 1.2, due to the baseline of LAImax=4. Therefore, one recommendation was proposed to apply the screening in different field situations. Specifically, each increasing value can increase the correction factors of crop canopy temperature by 0.35 and reduce the correction factors of soil surface temperature by 0.18 in the 1 of sunflower LAImax. Therefore, important technical support can be obtained for precision irrigation management for the better performance of field monitoring data. The finding can also provide a strong reference to deal with the field temperature data of sparse vegetation crops. A great contribution can then be made to the precision screening of remote sensing data from unmanned aerial vehicles and satellites.
      2022,38(22):102-112, DOI: 10.11975/j.issn.1002-6819.2022.22.011
      Abstract:
      Abstract: Lycium barbarum fruit is widely used as a medicinal food in China. This study aims to clarify the effects of brackish water irrigation amount and salt ion composition on the yield, appearance quality, and nutritional quality of the Lycium barbarum. An optimal amount of brackish water was also determined under different water qualities, according to the comprehensive score after irrigation simulation. A L8 (41×24) orthogonal test was carried out with the "Ningqi No.1" Lycium barbarum as the test material. Eight orthogonal treatments included the four irrigation levels (60, 70, 80, and 100 mm) and two concentrations (according to 1 or 2 times of ion concentration in groundwater in the study area) of NaCl, NaHCO3, Na2SO4, and CaCl2. The optimal levels of each factor were obtained and scored for each index, including the yield, 100 grains dry mass, and nutritional quality. The greatest correlation with the comprehensive score was selected as the salt ions. A gaussian regression model was established for the sensitive ion concentration and comprehensive score Ci, in order to obtain the optimal irrigation quantity range under different water quality using the screening program. The water quality and irrigation quantity scheme achieved higher scores than before. The results showed that there were significant effects of the brackish water irrigation amount and the concentrations of NaCl, NaHCO3, Na2SO4, and CaCl2 on the yield, dry mass of 100 grains, and nutritional quality. In the yield and appearance quality, the irrigation amount presented the most significant effects on the dry fruit yield, dry mass of 100 grains, fruit shape index, and dry fruit ratio. The maximum yield and dry mass of 100 grains were achieved at the irrigation amount of 70mm, and 100 mm, respectively. The NaCl effect on the dry fruit yield was higher than that of the rest salts. The maximum yield was reached at the N1 level. In the nutritional quality, the concentration of CaCl2 was dominated by the total amount of carotenoids, betaine, and amino acids, the highest of which was C2 (0.24%, 15.2 g/kg, and 11.67 g/100g, respectively). NaCl was determined as the total sugar, the highest which was the N1. The highest amount of flavonoids was obtained at the irrigation amount of 100mm. The comprehensive score showed that the T8 (W4, C2, HC1, N1, and S2) treatment with the high water. The CaCl2 presented the highest nutritional quality (Cpi=0.895), and planting benefit (Ci=0.719). The T5 treatment with the high water and NaCl was the lowest (Cpi=0.172, Ci=0.200). Ci was very negatively correlated with the concentration of Na+ (P<0.01), and Cl- (P<0.05), whereas, there was a very significant positive correlation with the concentration of Ca2+ (P<0.01). Ci was significantly positively and negatively correlated with Ca2+ and Na+ concentrations, respectively, and negatively correlated with Cl-. Gaussian regression showed that the brackish water with the concentrations of Na+, Ca2+, and Cl- of 34.8-38.8, 15.3-15.6, and 50.9-55.9 mmol/L were better suitable for irrigation, compared with the planting benefit fit Ci>0.7 with 96.9-97.9 mm in the single irrigation. The optimal irrigation amount was achieved under different water quality: In the Cl- content of 63.02-81.50 mmol/L, the Na+ contents were 18.55-30, 30-35, 35-40, 40-53, and 53-55 mmol/L, where the optimal irrigation amount was 91-98, 82-98, 77-83, 77-99, and 96-98 mm. In the Cl- content of 81.50-99.11 with the Na+ contents of 18.55-30 and 35-55 mmol/L, the optimal irrigation amount was 97-99 and 69-77 mm. In the Na+ content of 30-35 mmol/L with the Ca2+ concentrations of 8.77-13.00 and 13.00-17.54 mmol/L, the optimal irrigation amount was 74-98 and 78-82 mm. The findings can provide a scientific basis to utilize the brackish water for the better planting benefits of Lycium barbarum in the Hetao Irrigation area.
      2022,38(22):113-122, DOI: 10.11975/j.issn.1002-6819.2022.22.012
      Abstract:
      Abstract: Land cover types have changed dramatically in the tropics as human activity is ever increasing in recent years. These changes can cause great impacts on regional water security. Therefore, it is a high demand to accurately quantify the effect of land cover change on evapotranspiration (ET) for a better understanding of the mechanism of the water cycle under global warming. This study aims to investigate the effects of land cover change on the ET in the tropical Lancang-Mekong River Basin (LMRB) from 2001 to 2020. Firstly, the land cover data was reclassified and we corrected the unreasonable change types. The land cover product (MCD12Q1) was then evaluated using high spatial resolution images with Google Earth Pro. Secondly, the ET product (MOD16) was assessed using a total of 10 eddy covariance observation sites. Pearson's correlation coefficient (r), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Percentage Error (MRPE) were also used to analyze the land cover changes and ET trends in this region. Finally, a dynamic analysis was developed to accurately quantify the effect of land cover changes on ET water consumption, where the impacts of climate change were excluded. The results show that: 1) The MCD12Q1 performed better with an overall accuracy beyond 82%, the forests and cropland of which were 90.5% and 89.4%, respectively. The RMSE values of MOD16 on the 8-day and monthly scales were only slightly larger than 1 mm/day. Therefore, the two products (land cover and ET) can be expected to analyze the ET changes in the study area. 2) The changing area accounted for 24.7% of the total. There was a degradation trend of the overall vegetation, where the conversion areas of the forest to shrubs and shrubs to cropland accounted for 61.2% of the changing area. 3) The trend analysis showed that there was an increasing average ET of 5 mm/year in the entire region. 4) A significant difference was observed in the annual average ET of each land cover type. Generally, the annual average ET of the forest was higher than that of shrubs, and the annual average ET of shrubs was higher than that of cropland. 5) The major types of land cover change caused a total decrease of 27.89 billion cubic meters of water consumption, whereas, climate change led to an increase of 19.10 billion cubic meters of ET water consumption. 6) Although there was a decrease of ET in the land cover change area, there was no significant influence of the land cover change area on the increasing ET. This is because the land cover change area just accounted for only about 25% of the total basin. In general, the vegetation degradation resulted in a decrease in ET and water consumption, indicating the conversion of forests to shrubs and shrubs to cropland from 2001 to 2020. A better understanding of the water cycle response to global change can provide useful knowledge to effectively monitor the water resources security and the allocation of land and water resources in the tropical LMRB.
      2022,38(22):123-132, DOI: 10.11975/j.issn.1002-6819.2022.22.013
      Abstract:
      Abstract: Plant nematode disease is one of the major diseases to threaten agricultural safety in China. The green, high-efficiency, and low-toxic nematicide pesticides can be one of the better means to control plant nematode disease, further to prevent the large-scale spread of nematode disease. However, the manual visual inspection cannot fully meet the large-scale screening and test of the nematicidal pesticide activity, such as time-consuming, low accuracy, and heavy workload. Particularly, it is very necessary to accurately and rapidly count the number of nematodes in the solution, and then to identify the dead and living insects. In this study, a fast identification was proposed for the nematodes using a coordinate attention mechanism and efficient bounding box regression loss YOLOFN (YOLO for nematodes). Firstly, the sawdust samples of tree trunks with the pine wood nematode were collected in the epidemic area of pine wood nematode disease. The solution slides of pine wood nematode were prepared with the different concentrations, after the pine wood nematode was separated in the laboratory. Secondly, the optical microscope and single lens reflex camera were used to collect the pine wood nematode images. The offline data enhancement was combined with the mosaic online data enhancement to expand the training samples of pine wood nematode images, according to the similar characteristics of pine wood nematode images. Thirdly, the feature extraction module of the coordinate attention mechanism was embedded in the backbone network, according to the theoretical framework of YOLOv5s target detection. The position information of the nematode feature map was then integrated into the channel attention, As such, this improvement enabled the model to focus on the target category and target location at the same time. Finally, a tradeoff was made on the overlapping ratio of the nematode target, the center point distance of the nematode target, the width and height of the prediction frame in the nematode target, as well as the proportion of positive and negative samples of the nematode target. The Efficient Intersection over Union (EIoU) and Focal loss functions was utilized to optimize the localization and classification loss function. There was a minimum difference between the width and height of the real frame and the predicted frame. The weight of the easily distinguishable samples was dynamically reduced to quickly focus the beneficial training samples. The analytical ability and regression accuracy of the model were improved to overlap the nematode targets. The experimental results showed that the performance indicators of YOLOFN were improved by 0.2, 4.4, and 3.8 percentage points, in terms of accuracy, recall, and mean Average Precision (mAP). The mAP of the improved model increased by 1.1, 31.7, and 15.1 percentage points, respectively, compared with the classical detection YOLOv3, SSD, and Faster R-CNN3. There was no difference in the inference time, where the mAP was higher than 11, 16.3, and 15 percentage points, respectively, compared with the lightweight backbone depth-separable convolution-YOLOv5, Mobilenetv2-YOLOv5, GhostNet-YOLOv5. Therefore, the YOLOFN model can be expected to quickly, accurately and efficiently realize the nematode microscopic examination and statistics, fully meeting the actual needs of research and development of plant nematode pesticides. The finding can provide strong technical support to accelerate the development of new drugs for plant nematode disease control. In the future research, the systematic deployment of the model can greatly contribute to the development of green nematicide, and the protection of plant nematode diseases. The high requirements of rapid end-to-side nematode counting and mortality measurement can be fully met using the expansion of the nematode species image data set.
      2022,38(22):133-140, DOI: 10.11975/j.issn.1002-6819.2022.22.014
      Abstract:
      Abstract: Dissolved organic material (DOM) has posed adverse impacts on the detection of water quality between different water pollutants. Once the total amount of DOM reaches a critical level, the explosive growth of algae can be induced by eutrophication in the water, leading to a more complicated composition. There is a more serious interference in the detection, as the DOM aggravated during this time. The previous research also shows that the effect of DOM is closely related to the total amount, and the components. It is a high demand to accurately measure the DOM components for effective water quality monitoring. Particularly, the DOM component measurement is highly required to effectively implement, due to the complex organic structure. For this reason, it is difficult for a single sensor to complete the complicated test of the total amount and components of DOM in water. In this study, the fiber sensing array was proposed to detect the DOM components using the non-specific selectivity of the fiber SPR sensor. The cross-sensitivity analysis was carried out to obtain the different SPR sensing arrays using the fiber SPR sensor. A field test was been realized by the SPR sensing array in large-scale water bodies. Particle Swarm Optimization (PSO) was selected to optimize the artificial neural network (ANN). As such, effective predictions were obtained for the five DOM components and their concentrations in four kinds of measured water. The SPR sensors were then prepared with different optimal refractive indices using multimode fiber and gold film with seven thicknesses of 55-85 nm. The optimal refractive index of each sensor was effectively distributed in the range of 1.33 to 1.43, according to the design requirements. Correspondingly, each sensor presented excellent sensitivity and linearity in the best measurement interval. The sensitive crossing-response was achieved in the measurement interval corresponding to other sensors through the wavelength, spectrum width, and light intensity. In terms of the classifier and intelligent algorithm, the global search PSO was used to train the BP-ANN, in order to avoid the local search easy to fall into the local extremum. After that, the DOM water sample was prepared to determine the DOM components in the water body. The SPR effect was realized to measure the refractive index using a sensing array. The artificial intelligence network BP-ANN was trained by the PSO. Three classifiers were then constructed, including the PSO-BP (wavelength), PSO-BP (spectral width), and PSO-BP (light intensity). The comprehensive training was verified by the resonance wavelength, spectral width and light intensity of the SPR effect in the tested water. Therefore, five DOM components were tested, including the P1.n, P2.n, P3.n, P4.n, P5.n (tyrosine proteins, tryptophan proteins, fulvic acid, soluble microbial metabolites, and humic acids) of Outer Canal (A), Hongze Lak (B), Park Landscape Lake (C) and Campus Landscape Lake (D). The highest recognition rate was up to 85% from the samples of P2.n in Hongze Lak (B), indicating the excellent prediction of DOM components. Anyway, the PSO-BP multi-classifiers can be expected to mine the cross-sensitivity information by the SPR sensor. The finding can provide a new idea for the application of fiber SPR sensors and multi-classifiers using cross-sensitivity analysis.
      2022,38(22):141-148, DOI: 10.11975/j.issn.1002-6819.2022.22.015
      Abstract:
      Abstract: A safety risk has often posed a great threat to large-span greenhouse structures with the cables in extreme weather, such as snow and wind. It is very necessary to detect the broken wires in the cables of large-span greenhouse structures. However, the environmental magnetic field can dominate the magnetic memory detection for cable damage. In this study, an effective detection was presented for the broken wires using magnetic gradient tensor and magnetic charge surface integral theory, in order to remove the influence of the environmental magnetic field. The magnetic gradient tensor was then combined with the magnetic charge surface integral to derive the calculation formula for the magnetic gradient of cable wires. The characteristic information of cable wires was given before and after the wires broke. The judgment was also proposed for the wire breakage position and number of broken wires. The magnetic test was carried out to verify the evaluation. Theoretical calculation results show that there was a sudden change in the magnetic gradient curve at the wire breakage position when a broken wire occurred in a cable. As such, the baseline was established for the position of wire breakage using the bottom of the trough and the inflection point between the peak and trough of the magnetic gradient curve. Once there were two broken wires in a cable, the areas enclosed by the abrupt changes of magnetic gradient curves were 2.07, 2.89, and 2.13 times those in one broken wire, with an average value of 2.37 with integer of 2, according to theoretical calculation. There was no effect of the cable length on the amplitude of mutation in the magnetic gradient curve. The average values of the environmental magnetic gradient's absolute values account for 0.17%, 0.92% and 0.21% of the total magnetic gradient respectively. The influence of the environmental magnetic gradient can be ignored and it can be considered that the measured total magnetic gradient is equal to the cable's own magnetic gradient. The experimental results show that the theoretical and actual wire breakage positions were 496, and 500 mm, respectively, with an error of 0.8%, in terms of the average value of abrupt changes in the magnetic gradient curves. There was a great increase in the areas and peaks/troughs depths that were surrounded by the abrupt changes of magnetic gradient curves, as the number of broken wires increased, according to the superposition effect. In order to verify the repeatability of the experiment, measurement was conducted twice for each wire-breaking condition. As for the first test results, the areas surrounded by the abrupt changes of magnetic gradient curves in the two broken wires were 1.47, 1.78, and 1.34 times those in the one broken, with an average value of 1.53 with integer of 2. As for the second test results, the area ratios were 1.48, 1.84, and 1.31, with an average value of 1.54 with integer of 2. The very small deviation between the results of the two measurements verified the repeatability and reliability of the monitoring. Anyway, the number of broken wires should be judged by three magnetic gradients in the practical engineering application. This finding can provide a theoretical basis for cable wire breakage monitoring, and effectively eliminate the interference of the environmental magnetic field.
      2022,38(22):149-157, DOI: 10.11975/j.issn.1002-6819.2022.22.016
      Abstract:
      Abstract: A water-circulating solar energy system has been widely used in the field of greenhouse heating. But, real-time heat harvesting is still lacking in the arrangement of time points or indoor air temperature. It is a high demand to consider the thermal condition of the collector surface in the current operation control system. This study aims to explore the high-efficiency and energy-saving operating system. An intelligent control device was first developed for solar heat collection and release. A simulation was then performed on the appearance and condition of the water-circulating solar collector (also as the heating radiator) without the impact of water flow. A new control strategy was finally proposed using the simulating device. Specifically, the difference between the surface sol-air temperature and the tank water temperature was utilized to control the daytime heat collection, whereas, the surface sol-air temperature was to control the nighttime heat release. A theoretical analysis was also implemented to verify the control strategy. The surface sol-air temperature of the device surface in the daytime was used to reveal the collectible excess solar heat on the collector surface. As a result, the balance was achieved between the solar radiant heat absorbed by the surface and the heat exchanged between the surface and the internal environment, and between the surface and the greenhouse environment. Thereby, the control strategy accurately enables heat collection at the right time. The sol-air surface temperature at night was closely related to the indoor air temperature. Correspondingly, heat-releasing control was essential using indoor air temperature. The field tests were carried out to investigate the solar heat collection and release effect of the control strategy applied to the water-circulating solar energy system with an indoor collector (as a heating radiator during nighttime) constructed of hollow polycarbonate sheets. And a comparison was also made with the existing control strategy capability. During daytime, weather conditions had significant influence on the surface sol-air temperature. The maximum temperature reached 59.9°C on a sunny day, much higher than those on cloudy and overcast days (47.2 and 35.0°C, respectively). The heat collection on a sunny day (404.1 MJ) was also much higher than those on cloudy and overcast days (225.9 and 62.7 MJ, respectively). Obviously, the setting time points led to some issues for the heat collection control, such as less heat collection (1.4 h) or ineffective operation (1.7 h) on a sunny day, and long-term ineffective operation on cloudy and overcast days. The control system of indoor air temperature also missed some heat collection opportunities, due to the low air temperature. Particularly, the heat (31.8 MJ) needed to be collected for a significant energy saving (coefficient of performance: 20.2) in the early stage of heat collection with the strong solar radiation. Besides, the short-term ineffective operation often occurred (0.7 and 2.4 h on cloudy and overcast days, respectively). By contrast, the new control strategy of heat collection was achieved in the higher heat collection with the lower energy consumption. The heat release control also performed better to reduce the ineffective operation time, due to the rapid response of surface sol-air temperature to exchange in solar thermal energy. The control strategy was also applied in the water circulation systems, in order to tap the harnessing potential of solar energy and saving energy. Besides, the heat collection control strategy can be expected to apply in forced-circulation solar water heating systems. The control strategy can be further optimized for the more ideal heat collection and release. The finding can provide the technical reference to improve the structure and installation of the simulating device in the temperature change management of heat release.
      2022,38(22):158-165, DOI: 10.11975/j.issn.1002-6819.2022.22.017
      Abstract:
      Abstract: A huge area of saline-alkali land cannot be cultivated in China, due to the salt stress and low nutrient. Pyrolysis fluid with high acidity has been used to improve the saline soils. Among them, phenolic substances are adverse to the growth of plants. Therefore, the aim of the study was to explore the improvement effect of pyrolysis fluid on the saline soils, in order to efficiently reduce the phenols during pyrolysis. Firstly, the pyrolysis fluid was prepared at different temperatures (300, 400, 500, 600, and 700℃), and then refined under the three-stage condensation mode. Secondly, an analysis was made to clarify the effect of graded condensation on the product composition. Taking the Chinese cabbage as an indicator, a pot experiment was performed on the saline soils using the tertiary product under different dilution folds (50, 200, 400 and 600). Finally, a systematic investigation was implemented to determine the effects of the tertiary product on the growth of Chinese cabbage, soil pH, total salt, sucrase, urease, alkaline phosphatase, catalase, organic matter, alkaline digested nitrogen, fast-acting phosphorus and potassium. The results showed that: 1) No new substance was found in the tertiary product from the pyrolysis fluid phase during three-stage condensation, compared with the single-stage. The graded condensation was used to realize the rapid and efficient separation of phenols and acids from the fluid phase products of cotton stalk pyrolysis. The concentrations of phenols and acids in the secondary product were 2.18-2.24 and 0.07-0.11 times higher than those by the single-stage, respectively. In the tertiary product, the concentrations of phenols and acids were 0.50-0.55 and 1.21-1.35 times higher than those by the single-stage, respectively. 2) The tertiary product significantly promoted the germination and growth of the Chinese cabbage (P<0.05). This promotion also depended mainly on both pyrolysis temperature and dilution ratio. The medium pyrolysis temperature and the larger dilution folds were more favorable for the Chinese cabbage seed germination. The best growth of Chinese cabbage was observed in the T500-D600 treatment (pyrolysis temperature of 500 ℃, dilution fold of 600), with 32.12%, 95.11%, and 120.03% increase in the germination rate, plant height, and fresh weight per plant, respectively, while 48.39% decrease in the malondialdehyde content. 3) The soil enzyme activity was dominated by the irrigation of the tertiary product with different dilution ratios (P<0.05). Interestingly, the activities of urease and alkaline phosphatase were reduced, only when the tertiary product was diluted by 50 times into the saline soil. Additionally, the activities of urease, alkaline phosphatase, sucrase and catalase in the saline soil increased by 218.13%, 123.65%, 64.78%, and 36.87% respectively, compared with the control. 4) The tertiary products significantly reduced the pH and total salt amounts in the saline soil, whereas, there was a significant increase in the nutrient contents (P<0.05). The contents of organic matter, alkaline soluble nitrogen, fast-acting phosphorus, and fast-acting potassium in the saline soil increased by 64.86%, 33.07%, 64.65% and 17.29%, respectively. Anyway, the tertiary-stage condensation products of cotton stalk pyrolysis greatly contributed to the high fertility and enzyme activity of saline soil, as well as the better growth of Chinese cabbage. This finding can provide a sound theoretical basis for the biomass pyrolysis fluid to improve the saline-alkali land.
      2022,38(22):166-171, DOI: 10.11975/j.issn.1002-6819.2022.22.018
      Abstract:
      Abstract: Solar and wind resources are usually abundant in saline-alkali lands of China. These renewable energies can be expected to partially replace fossil fuel energy for the carbon peaking and carbon neutrality goals in recent years. Specifically, energy utilization and resource regeneration can also be realized for the waste of solar and wind energy nearby to electrolyze wastewater from the saline-alkali land treatment. It is of practical significance to utilize renewable energy for the treatment of wastewater and the production of H2/Cl2. Correspondingly, the first step is to concentrate the wastewater, due to a very low salt concentration (about 0.2 mol/L) after sprinkler irrigation in the saline-alkali land. It is necessary to explore the appropriate concentration of saline water for the better stable production of Cl2. In addition, the existing purification cannot fully meet the high requirement so far, particularly in the complicated process with the high cost. This study aims to explore a low-carbon and economic process for the removal of impurities from saline wastewater. A feasible treatment technology was also proposed to reduce the impurity ions for the cost-saving purification of high-salt wastewater. A series of electrolysis experiments were carried out on the wastewater from saline-alkali land treatment. A systematic investigation was then implemented to clarify the effects of salt concentration and the impurity removal processes before/during electrolysis. The CO2 regulation cell was added in this case. The influence of Ca(OH)2 was explored in the process of impurity removal before electrolysis. The electrolytic experiment was set without or with the CO2 input flow of 44.3 mL/min. Results showed that there was a linear correlation of the current density with the production of H2/Cl2 in the wastewater electrolysis under different salt concentrations. More importantly, the rate of H2 production was slightly higher than that of Cl2 production. The side reaction of oxygen evolution took a small proportion in the anodic reaction. The suitable concentration of salt for the wastewater electrolysis was 3.5 mol/L, which contributed to the largest current density and cathode pH. In the optimal process, Ca(OH)2 was added to the wastewater followed by concentration. The concentrations of Ca2+, Mg2+ and SO42- were also achieved lower than 0.02, 0.1, and 0.2 mol/L, respectively. The reason was that the Mg2+ and Ca(OH)2 reacted first, when a certain amount of Ca(OH)2 was added to the wastewater. Subsequently, the Mg2+ was removed in the form of Mg(OH)2. The concentrations of Ca2+ and SO42- were then similar in the wastewater after the removal of Mg2+. Therefore, the Ca2+ and SO42- were both removed as CaSO4 by the concentration. Moreover, the continuous injection of CO2 during electrolysis can be expected to convert the hydroxide precipitation of Ca2+ and Mg2+ ions into bicarbonate with high solubility. As such, only a few adverse effects were caused by precipitation generation and accumulation in the process of electrolysis. In the end, the adverse effect of impurity ions was further reduced, with which the H2/Cl2 yield increased by about 10%.
      2022,38(22):172-182, DOI: 10.11975/j.issn.1002-6819.2022.22.019
      Abstract:
      Abstract: An ever-increasing number of pollutants have posed serious hazards to human health and ecological environment, especially industrial wastewater, dye wastewater, and heavy-metal carcinogenic substances with the development of industrialization and urbanization in recent years. Fortunately, the iron-carbon composites can be expected to prepare using agricultural and forestry wastes. Among them, ferromagnetic additives have been widely used in the treatment of environmental pollution, due to the high specific surface area, better porosity, and abundant surface functional groups. The current preparation of iron-carbon composites includes hydrothermal synthesis, solvent heat, chemical co-precipitation, arc discharge, impregnation pyrolysis, and microwave. In this review, the latest research progress was summarized for the pros and cons of various syntheses. Among them, the hydrothermal environment accelerated the physicochemical interaction between the biomass and the aqueous solution in the hydrothermal synthesis. In turn, the formation of oxygen-containing functional groups was promoted on the surface of the carbonized materials. The solvent heat method was utilized to effectively inhibit the oxidation of products for the preparation of high-purity substances. The impregnation pyrolysis greatly contributed to a large number of pore structures in the carbonized products. The chemical co-precipitation was able to attach the metal ions and metal oxides to the surface of carbon materials or inside the pore channels. The arc discharge was used to precisely control the synthesis of nanoparticles via the varying electrode potential and current density. The microwave method was applied to realize the internal heating for less reaction time. The prepared iron-carbon composites exhibited excellent adsorption performance, easy separation, and high recycling rate. Extensive application prospects can be expected in the potential treatment of pollutants. A systematic investigation was then focused on the application progress of iron-carbon composites prepared from agricultural and forestry wastes in environmental pollution management, especially, the removal of heavy metals (Zn, Pb, Cd, Cr, Co, Ca, Mg, and Ni) from the wastewater, the treatment of dye wastewater, and the soil heavy metal pollution. More importantly, the removal of heavy metals and dyeing wastewater contained a combination of multiple adsorptions. Among them, the physical adsorption was caused by the Van der Waals forces between the molecules on the surface of iron-carbon composites and heavy metal or dye pollutant ions. The chemisorption was the process in the presence of elements via the redox reactions, especially the change of valence state. The optimal adsorption was achieved under the various chemical behavior, biological effectiveness, and migration ability of heavy metals. As such, the heavy metals were remediated in the soil pollutants, due to the significant effect of the iron-carbon composites on the immobilization of metal ions in the soil. Specifically, the iron-carbon composites with positive surfaces shared a great ability to immobilize anionic pollutants, whereas, the iron-carbon composites with negative surfaces mainly immobilized the cationic pollutants. The modified biochar can be expected to serve as a very promising immobilizer for soil heavy metal pollution. Therefore, the iron-carbon composites were prepared from the agricultural and forestry wastes in the environmental pollution remediation applications. Therefore, the low-cost, high-performance, high-efficiency adsorbent and remediation agent can provide great potential to leading technology and material for future environmental pollution treatment.
      2022,38(22):183-189, DOI: 10.11975/j.issn.1002-6819.2022.22.020
      Abstract:
      Abstract: Biodegradable packaging materials have received widespread attention in recent years. The reason is that non-biodegradable packaging materials have caused serious environmental and human health issues during disposal after mass production. Fortunately, the mycelium material can be expected to serve as one of the promising biodegradable materials. In this study, the mycelium biomass material was cultivated to determine the effect of preparation process parameters on mechanical properties. Pleurotus ostreatus was selected to inoculate in a culture substrate, including the wood chips, cotton seed hulls, corn cobs, wheat bran, lime, and gypsum. The process parameters were then optimized for the properties of mycelium biomass material. After that, a three-factor and the three-level orthogonal test was carried out to investigate the three process parameters (inoculum amounts, particle size of substrate, and water addition) using the minimum cushioning coefficient and bending strength as the evaluation indexes. The maximum and minimum average diameters of mycelium were 1641 and 520 nm, indicating the significant influence of different process parameters on the growth state of mycelium. The influencing factors were ranked in descending order of the particle size of the substrate, followed by the water addition, and inoculum amount. The bending resistance and buffering effect of mycelium material decreased as the particle size of the substrate decreased, due to the reduced internal space of substrate material. The low growth of mycelium and adherence between the substrates was attributed to the limited deformation space of material for less air circulation. The best bending resistance and buffering efficiency were achieved in the amount of water addition of 60%. As such, the bonding between the substrate inside the material depended mainly on the amount of water addition. The better mechanical properties were obtained in the relatively strong bonding, where the metabolism and growth of mycelium with suitable water was a benefit to wrapping the substrate. By contrast, the air circulation was reduced, where too much water filled the internal void in the material. The needed oxygen and metabolic carbon dioxide were not exchanged during the mycelium growth in time, leading to the low bending strength and buffering performance of the mycelium material without growth. The best bending resistance and buffering efficiency were achieved in the optimal inoculum of 10%. Once the inoculum was too low, the strains have limited contact with the substrate area, resulting in a limited area for colonization and growth. The insufficient mycelium growth reduced the bonding between substrates, leading to a decrease in the bending strength of mycelium material. A high inoculum greatly contributed to the strains competing with each other for the nutrient source, leading to the limited growth of mycelium in all strains. The optimum process parameters were optimized for the inoculum amounts of 10%, the particle size of substrate 10 mm, and water addition of 60%, corresponding to the minimum cushioning coefficient of 4.17 and the highest bending strength of 417.43 kPa of the mycelium material. Therefore, the bending strength of mycelium material was comparable to that of expanded polystyrene foam. But, the cushioning performance was less than that of expanded polystyrene foam. Three process parameters can be expected to further optimize the growth of mycelium, particularly for the better mechanical properties of the mycelium material. This finding can provide a strong reference to optimize the preparation process parameters and mechanical properties of mycelium biomass material.
      2022,38(22):190-198, DOI: 10.11975/j.issn.1002-6819.2022.22.021
      Abstract:
      Abstract: An accurate and rapid extraction can be highly required for the crop sown area and spatial distribution from the remote sensing images, particularly for the sustainable development of cultivated land and food security. However, winter wheat mapping using remote sensing depends mainly on optical images and complex classification at present. Besides, it is still unclear on the classification performance and time-transferring capability of existing classification with the small sample sets in the highly land-fragmentation areas. The fragmentation of cultivated land has always been the core of rural land regulation, where the land resources are wasted to reduce the cultivated land productivity in the soil fertility with the high production costs. The difficulty of crop mapping in finely fragmented areas is generally higher than that in large-scale farming areas. The applicability and stability are very important for the study of such areas. It is necessary to realize long-term large-scale crop mapping with a low dependence on the number of samples and high efficiency. Therefore, it is of practical significance to develop a new extraction with a low complexity suitable for small samples. Previous studies have shown that the accuracy of crop mapping using single-phase satellite imagery cannot fully meet the high requirement in recent years, especially in land fragmentation areas. In this study, the high-level fragmentation of cultivated land was selected as the study area in the Wancheng District, Nanyang City, China. Using the Google Earth Engine cloud computing and Sentinel-1 SAR and Sentinel-2 optical images, three advanced classifications were evaluated, including the time-weighted dynamic time warming (TWDTW), random forest (RF), and OTSU with distance measure (DSF), for the winter wheat mapping accuracy and time-transferring capability with the small sample sets in the study area. The results show that effective extraction was achieved in the sown area and spatial distribution of winter wheat in 2020, but there were some differences in the classification accuracies. The TWDTW presented the highest classification accuracy, with the Overall Accuracy (OA) and Kappa coefficients 0.923 and 0.843, respectively, followed by the RF (OA=0.906, Kappa=0.809) and DSF (OA=0.887, Kappa=0.767). The OTSU with the Euclidean Distance showed the lowest classification accuracy. When transferring to extract the winter wheat classification maps of 2021, the classification accuracy of each model decreased: The TWDTW and DSF showed better stability and classification accuracy than the RF. The TWDTW shared the highest accuracy with the OA and Kappa of 0.889 and 0.755, respectively. The classification accuracy of RF decreased significantly, and the OA and Kappa decreased by 7% and 19%, respectively, indicating the lower stability of the model. In general, the TWDTW presented low sensitivity to the training samples and spatial heterogeneity. As such, the high-precision continuous mapping was realized for the winter wheat in the agricultural areas with high spatial heterogeneity under the condition of limited samples. However, the RF was sensitive to the training samples and spatial heterogeneity. The condition of limited samples can cause low stability in the continuous winter wheat mapping in high spatial heterogeneity agricultural areas. This finding can provide important selection ideas and scientific support for continuous crop mapping with the small sample sets in the highly land-fragmentation areas.
      2022,38(22):199-209, DOI: 10.11975/j.issn.1002-6819.2022.22.022
      Abstract:
      Abstract: Accurate land use classification is highly required using Unmanned Aerial Vehicle (UAV) images, especially the data selection. In this study, the UAV orthographic remote sensing images were acquired at different aerial heights in Tongji Village, Baishui County, Weibei dry land, China. The land use was then classified using a variety of deep learning and machine learning. The DJI Mavic 2Pro was used to obtain 80 and 160m aerial images in the study area. There were 96 routes, the total length of routes was 42.43 km, the heading overlap degree was 75%, the side overlap degree was 60%, and a total of 2248 original aerial photos were taken at a flight height of 80 m. At 160m flight height, there were 20 routes with a total length of 17.90 km, the heading overlap degree was 70%, the side overlap degree was 55%, and a total of 502 original aerial images were taken in this case. The geo-positioning of the photo control points was performed on the Zhuolin A8 handheld Beidou GPS locator. Agisoft PhotoScan 1.4.5 software was used to splice and process the original single-image data. A comparison was made on the visual interpretation of different aerial photography heights and the prediction of various deep learning and machine learning models. Labelme4.5.6 software was used for the visual interpretation. As such, the best performance was achieved during this time. The results show that the performance of deep learning was far better than that of traditional machine learning. The best-performing of deep learning (DeepLabv3+) presented a pixel accuracy of 90.06%, which was 24.65 percentage points, and 21.32 percentage points higher than that of random forest (RF) and support vector machine (SVM), respectively. The improved DeepLabv3+_BA model performed the best overall classification. The improvement of deep learning was attributed to two aspects. Firstly, the BN layer was removed after the first two separate convolution layers in the Entry flow in the encoder Xception part of the original DeepLabv3+ model. The BN layer was removed in ASPP after the last three separate convolutional layers in the Exit flow. The BN layer was removed after each dilated convolutional layer. Secondly, the ASPP atrous rate combination design was re-optimized, according to the characteristics of the data set. The pixel accuracy of the improved model was 91.37%, which was 7.43 percentage points, 10.12 percentage points, 2.27 percentage points, and 1.31 percentage points higher than those of FCN, SegNet, UNet, and DeepLabv3+, respectively. The number of iterations required for the best accuracy was reduced by about 50%, compared with the other four deep-learning models. Taking the extraction of apple orchard as an example, the F1 value of DeepLabv3+_BA was 89.10%, which was 19.94 percentage points, 23.68 percentage points, 2.04 percentage points, 2.97 percentage points, 2.4 percentage points, and 0.78 percentage points higher than those of SVM, RF, FCN, SegNet, UNet, and DeepLabv3+, respectively. The accuracy of various algorithms was higher than 80m on 160m datasets. The performance of various deep learning on the test set demonstrated that the accuracy of DeepLabv3+_BA reached more than 90% for the apple orchard, bare field, stubble field, and road ground object classification. The improved model DeepLabv3+_BA presented higher accuracy and robustness of ground object classification. This finding can also provide a strong reference for the land use information census using UAV images and deep learning.
      2022,38(22):210-219, DOI: 10.11975/j.issn.1002-6819.2022.22.023
      Abstract:
      Abstract: Human activity has been one of the most important factors inducing regional ecological risks in recent years. But, there are different visualization and response degree of ecological risks and human activities in different land scales. It is a high demand to scientifically analyze the correlation characteristics of regional Landscape Ecological Risk (LER) and Human Activity Intensity (HAI), in order to coordinate the territorial system of human-environment interaction for better regional high-quality development. The ever-increasing conflict can be found between ecological protection and economic and social development, due mainly to rapid urbanization. The Yangtze River Delta (YRD) is one of the typical regions with intensive human activities, remarkable economic development, and outstanding ecological status. Taking the YRD as the subject, a three-level scale of city, county, and grid was established to construct the LER and HAI assessment models, in order to characterize the spatial and temporal response at different scales. The data was also collected from the land use, nighttime lighting, and population spatial distribution in the four periods from 1990 to 2020. The Copula function, bivariate spatial autocorrelation, and coupled coordination degree models were used to reveal the spatial and temporal correlation between the LER and HAI. The results show that (1) the spatial distribution pattern of LER was high in the north of the study area, and low in the south under different scales. The high risk areas continued to decrease during 1990-2020, whereas, the low risk areas showed an increasing trend. There was the most outstanding reduction in the high risk areas at the city scale, with a decrease of 19.51 percentage points over 30 years. By contrast, there was the most significant increase in the low-medium risk and low risk areas at the county scale, indicating an increase of 16.29 percentage points over 30 years. (2) The spatial distribution pattern of HAI was high in the northeast of the study area during 1990-2020, while low in the southwest under different scales. All the regions with high HAI showed a significant increasing trend. There was a significant decreasing trend in the regions with low HAI. The high intensity region presented the largest increase at 13.42 percentage points on the grid scale, whereas, the low intensity region was the most significant decrease at 9.76 percentage points on the city scale. (3) The correlation between HAI and LER shared a positive correlation between 1990 and 2020, but the correlation between them was weakening, indicating the weak influence of regional HAI on LER. By contrast, the coupling and coordination between them showed an increasing trend from 0.3031 in 1990 to 0.3112 in 2020. It infers that the relationship between them was gradually shifting from conflict to coordination. Spatially, there was a continuous decreasing trend in the H-H clustering area. Furthermore, the L-L clustering area showed an increasing and then decreasing trend with an overall decrease. Both L-H and H-L increased significantly after 2010. The spatial correlation characteristics of regional LER and HAI were combined to manage and control the regional ecological environment. The finding can provide a theoretical basis for land management and landscape planning, together with the spatial guidelines for the regional ecological risk prevention and ecological restoration.
      2022,38(22):220-228, DOI: 10.11975/j.issn.1002-6819.2022.22.024
      Abstract:
      Abstract: Seafood is one of the most valuable nutrients in nature, due to the high protein content rich in amino acids and vitamins. Among them, the Asian swamp eel (Monopterus albus) is one of the most widely distributed freshwater fish in China. However, a great challenge is still remained in the aquatic products processing, due mainly to the manual sectioning with high labor intensity, low work efficiency and low safety, particularly for the Monopterus albus and pond loach (Misgurnus anguillicaudatus) freshwater fish. Taking the fresh Monopterus albus as the test object, this study aims to design and develop a new sectioning device, according to the fish habits and body characteristics. A series of experiments were carried out to determine the fish body clamping and force characteristics, in order to analyze the fish feeding, body positioning and clamping behavior. The sectioning device was composed of the tilting hopper, fish inlet channel, counter roller, and blade disc. Specifically, the structural parameters of the sectioning device were set, where the fish inlet channel was 180 mm long and the diameter at the fish inlet was 28 mm; the edge of the roller was serrated with a wide top and narrow bottom; and the diameter of the blade disc was 114 mm. The influencing factors of the sectioning were selected as the diameter of the roller, the initial gap of the roller, the rotation of the roller, and the exposed height of the blade disc. An optimization test was carried out with the impact factors of roller diameter, roller initial gap, roller rotation rate, and the exposed height of the blade disc as the influencing factors, and the acceptability score of the sectioning as the evaluation index. The results showed that the better clamping performance of the fish body was achieved in the roller diameter of 180 mm. The highest sensory score of the abdominal section was obtained in the roller initial gap of 8 mm. Furthermore, the clamping performance was significantly better at the high roller rotation rate than that at the low one in the constant roller diameter. The sensory score of the abdominal section increased gradually with the increase of the exposed height of the fish body support plate by the blade disc. The orthogonal test showed that the highest sensory score of abdominal dissection was obtained, when the roller rotation rate was 180 r/min, the exposed height of the blade disc to the support surface was 22 mm, and the roller's initial gap was 8 mm. The generality test showed that the new section device can be expected to better apply to freshwater fish with different body sizes, fully meeting the actual processing requirements. The optimal production capacity reached 24.3 pieces/min. The finding can also provide a strong reference to developing sectioning devices for freshwater fish.
      2022,38(22):229-245, DOI: 10.11975/j.issn.1002-6819.2022.22.025
      Abstract:
      Abstract: Electrolysis Water (EW) has been widely used as a non-thermal technology in agriculture, medical treatment, and food processing in recent years. Particularly, EW technology is ever-increasing in the postharvest preservation and commercial treatment of fruits and vegetables, due to its environmental friendliness, cost saving, as well as high safety and efficiency. The purpose of this review is to further understand the relevant research progress of EW technology in the postharvest and preservation field, with emphasis on the pros and cons. A technical and mechanism summary of EW was performed mainly on the inhibition of microorganisms, the removal of pesticide residues, and preservation quality improvement. The process mode and the Patent application Status of EW technology were also summarized for the postharvest fruits and vegetables in recent years. The results showed that as follows. (1) The different functions were derived from the EW physical and chemical characteristics, such as Acid Electrolytic Water (AEW), Alkaline Electrolytic Water (AlEW), New Water (NEW), Slightly Acidic Electrolytic Water (SAEW), Electrolytic Oxidized Water (EOW), Electrolytic Reducing Water (ERW), and Low Concentration Electrolytic Water (LcEW), especially with the development of EW preparation. Furthermore, there was no systematic application for the different types of EW in the postharvest preservation field. (2) Sufficient technical and theoretical research was found about the AEW and SAEW to remove and inhibit the food-borne microorganisms in fruits and vegetables, especially in fresh-cut vegetables. The low pH value, the active chlorine component, and the high redox potential of acid EW cooperated to effectively inactivate bacteria. However, it was still lacking in the inhibition of fruit and vegetable disease and decay fungi. There was no specific anti-fungal technology and anti-bacterial mechanism so far. (3) A large number of studies reported that the acidic, alkaline and oxidizing EW dominated the removal of pesticide residues on the surface of fruits and vegetables. However, the specific mechanism was a high demand for the AEW and SAEW degradation of organophosphorus pesticides. Much effort can be focused on the alkaline electrolytic water degradation of pesticide residues, as well as the EW degradation of organochlorine and permethrin pesticides. (4) The EW treatment can be expected to effectively improve the resistance for the less chilling injury, or the Browning of fruits and vegetables. But the specific efficacy and mechanism of EW needed to be clarified for the better quality and preservation of fruits and vegetables. In addition, the scarce patent application of special EW technology and equipment cannot fully match the ever-increasing market demand for the postharvest preservation of fruits and vegetables in China. Therefore, this review can provide the theoretical basis and guidance for the application of EW technology in the field of postharvest fruits and vegetable preservation.
      2022,38(22):246-252, DOI: 10.11975/j.issn.1002-6819.2022.22.026
      Abstract:
      Abstract: Northeast Rice is mainly grown in the plain areas of Heilongjiang, Jilin, and Liaoning provinces of China. The unique quality of Northeast rice can be attributed to the environmental advantages, including the fertile soil, sufficient sunshine, excellent water quality, long accumulated temperature, and large temperature difference between day and night. However, it is difficult to identify the Northeast rice in the market for the protection of regional special products. An accurate and rapid identification technology is of great significance to the Northeast rice origin. In this study, a total of 10 sampling areas were prepared in Heilongjiang, Jilin, and Liaoning provinces. 90 soil surface and rice samples were then collected. Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the content of 23 trace elements (such as Li, B, and Be) in 90 soil-crop seeds from the main rice-producing areas. The SPSS and SIMCA statistical analysis software was also used to analyze the distribution of trace elements in rice and soil from different producing areas. Correlation analysis showed that the contents of Mo and Zn in rice were positively correlated with the contents of Mo and Zn in soil. The analysis of variance showed that there was a consistent distribution of Ga, Pb, Sr, Zr, and Ba in rice from the three provinces, whereas, the rest 18 elements showed significant differences. Principal component analysis (PCA), partial least squares regression analysis (PLS-DA), orthogonal partial least squares regression analysis (OPLS-DA), fisher discriminant analysis (FDA), and multi-layer perceptron neural network (MLP-NN) were performed on the 18 elements with significant differences in rice. Furthermore, the cumulative variance of the first principal component and the second principal component was 46.39%, indicating only a little original variable information. There was no aggregate for the rice from the different provinces in two-dimensional space in the projection of the principal component score. By contrast, there was a small difference in rice element characteristics in the PLS-DA score chart, due to the geographical proximity. Meanwhile, confusion and cross phenomenon were found among rice samples from different producing areas. OPLS-DA, FDA, and MLP-NN were utilized to distinguish the rice from different producing areas. The OPLS-DA scores performed better to distinguish the rice from the Heilongjiang and Jilin provinces. There were a few overlaps in the samples between Jilin and Liaoning provinces, or between Heilongjiang and Liaoning provinces. The result of permutation test shows that the model established by orthogonal partial least squares regression analysis is reliable. In the FDA, the elements that were introduced into the Fisher discriminant model were B, Cr, Ni, Cu, Ge, Mo, and W in the order of stepwise discriminant analysis. The accuracy of the discriminant function was 93.8% for the original grouped cases, and 92.6% for the cross-validation of the rest. The multi-layer perceptron neural network was used to analyze 63 actual training samples, and 27 verification samples, with the group as the dependent variable, and 18 elements content as the covariable. The correct discrimination rate of training samples was 100%, and the comprehensive correct discrimination rate of the overall test group was 96.3%. Consequently, the different discrimination models, the content of trace elements in rice, and the characteristic elements can be expected to effectively distinguish the rice-producing areas of the three provinces in Northeast China.
      2022,38(22):253-261, DOI: 10.11975/j.issn.1002-6819.2022.22.027
      Abstract:
      Abstract: Broken-winged chicken carcasses can be one of the most common defects in broiler slaughter plants. Manual detection cannot fully meet the large-scale production, due to the high labor intensity with the low efficiency and accuracy. Therefore, it is a high demand to rapidly and accurately detect broken wings on chicken carcasses. This study aims to realize the rapid inspection of broken-winged chicken carcasses in the progress of broiler slaughter, in order to improve the production efficiency for the cost-saving slaughter line. 1053 broiler carcass images were collected from a broiler slaughter line using a computer vision system. Rapid identification was then constructed for the broken wing defects. Specifically, the front view of the chicken carcass was obtained in the machine vision system. The preprocessing was then deployed to obtain the chicken carcass images without the background, including the weighted average (graying), two-dimensional median filtering (denoising), and iterative (threshold segmentation). The code was also written in the MATLAB platform. After that, a total of 11 characteristic values were calculated, covering the exact distance starting from the left and right ends of the chicken carcass image to the centroid and the difference (d1, d2, and dc), the heights of the lowest point in the two wings and their difference (h1, h2, and hc), the areas of the two wings and ratio of them (S1, S2, and Sr), squareness (R), and width-length ratio (rate). As such, the eight principal components were achieved in the principal component analysis after the reduction of several dimensions. Separately, the principal components and characteristic values were imported into the specific model of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), random forest (RF), support vector machine (SVM), and BP neural network. Among them, the input parameter of the VGG16 model was from the RGB maps of the chicken carcass with the removed background. Finally, a comparison was made for the F1-scores and total accuracy of each model. Thus, the highest recall rate of 91.13% was achieved in the RF model with the characteristic values as the input parameters among the shallow learning models. The second higher recognition accuracy and F1-score were 96.28% and 92.58%, respectively in the SVM model with the characteristic values as input parameters. The highest total accuracy of model recognition was achieved in the quadratic discriminant and SVM models with the characteristic values as the input parameters, both up to a proportion of 91.78%. Moreover, the F-score and total accuracy of the VGG16 model were the highest among the total model combinations, with respective rates of 94.35% and 93.28%, respectively. In terms of the prediction time of models, the shortest prediction time was obtained in the SVM model with the principal components as the input parameters. Specifically, the capacity was found to determine 353 sample images in 0.000 9 s, with an average speed of 3.92×105 images per second. By contrast, the longest prediction time was observed in the VGG16 model, where 24.46 s to determine 253 sample images, with an average speed of 10.34 images per second. In conclusion, the VGG16 model can be expected to serve as the best classification of broken wings in chicken carcasses.
      2022,38(22):262-269, DOI: 10.11975/j.issn.1002-6819.2022.22.028
      Abstract:
      Abstract: Blueberry is one of the most economically important nutritional fruits, particularly in popularity with the remarkable blue color and high health benefits of antioxidant potential. The purpose of this study was to establish a comprehensive quality evaluation of highbush blueberry using principal component analysis. A total of 11 quality indicators were selected (including single fruit weight, diameter of fruit, Longitudinal diameter of fruit, fruit shape index, fruit hardness, soluble solids mass fraction, soluble sugar mass fraction, titration acidity mass fraction, sugar acid ratio, vitamin C mass fraction, and anthocyanin mass fraction) for 26 highbush blueberry cultivars. There was a significant difference in the variation coefficient of the 11 fruit quality index of blueberry cultivars. In terms of fruit quality indexes, the coefficients of variation were 33.67%, 32.25%, 30.84%, and 28.48% for the sugar-acid ratio, titratable acidity, single fruit weight, and anthocyanin mass fraction, respectively. There was only 10.00% or less in the coefficient of variation of the fruit shape index. The medium variation coefficient (10.00% to 20.00%) was recorded in the six remaining fruit quality indices. Besides, principal component analysis was used to extract four principal components with eigenvalues greater than 1, where the cumulative variance contribution rate was 78.19%. Specifically, the contribution rate of the first principal component (28.05%) was determined as the reflected fruit size, i.e., fruit diameter, single fruit weight, and fruit longitudinal diameter. The contribution rate of the second principal component (25.89%) was determined as the parameters related to the sweet taste and nutritional quality of fruit, such as the soluble solid mass fraction, soluble sugar mass fraction, sugar-acid ratio, anthocyanin mass fraction, and vitamin C mass fraction. The third principal component accounted for 14.73% of the fruit acidity and fruit firmness, in terms of the titratable acidity and fruit firmness. The contribution rate of the fourth principal component was 9.52%, which was determined by the fruit shape index. Furthermore, six of 11 evaluated indexes (single fruit weight, fruit shape index, soluble sugar mass fraction, titratable acidity mass fraction, vitamin C mass fraction, and fruit firmness) were screened as the evaluation indexes of blueberry quality, which were characterized by the fruit size, fruit shape, sweet, sour, nutritional, and texture index. An excellent level order of 26 blueberry cultivars was achieved in the quality evaluation model: Big bluegold, Legacy, Duke, Sunrise, Weymouth, Bluechip, Earliblue, Bluecrop, Patriot, and Bonus. The findings can provide a theoretical reference to evaluate the blueberry quality, and then screen the blueberry varieties with excellent quality, particularly for the rational development and application of blueberry cultivars.
      2022,38(22):270-279, DOI: 10.11975/j.issn.1002-6819.2022.22.029
      Abstract:
      Abstract: Freshness is one of the most important attributes to assess meat quality, sale ability, and consumption. However, traditional freshness detection cannot fully meet the rapid and non-destructive monitoring of meat at present, due to the labor intensity and destructive measurement. Therefore, a rapid and non-destructive fluorescence imaging technique can be expected to evaluate lamb meat freshness in the meat industry. The fluorescence substances in meat can be identified as a potential indicator of freshness. Accordingly, this study aims to clarify the relationship between fluorescent substances and freshness index in meat. The fluorescent characteristic markers were also screened to characterize the change in lamb meat freshness. The longissimus dorsi muscle of sheep at 24 h postmortem was prepared in the air-sealed packaging, and then stored at 0℃ for 0, 1, 3, 5, 7, 9, 11, 13, 15, 17, and 21 days. The specific contents were measured in the lamb meat, including the tyrosine (Tyr), adenosine triphosphate (ATP), nicotinamide adenine dicylate (NADH), tryptophan (Trp), riboflavin (VB2), protoporphyrin (PPIX), and several freshness indexes (TVB-N, TBARS, TVC, pH value, and meat color). The results showed that the TBARS, TVB-N, and TVC of the lamb meat increased significantly during storage, whereas, the pH value decreased first and then increased, and the L*, a*, and b* values increased first and then decreased in the meat. The potential fluorescent markers (Tyr, Trp and PPIX) of freshness showed a significant increasing trend, while the NADH and ATP were the opposite change pattern, and the VB2 was a trend of increase firstly and then decrease in the meat. The correlation and cluster analysis demonstrated that the ATP, NADH, Tyr, Trp, and PPIX shared a significant positive correlation with the TVB-N and TVC, where the correlation coefficients ranged from 0.60 to 0.88. The fluorescence features molecule was verified at 4℃. It was found that the fluorescence features molecule was consistent with that at 0℃. Stepwise regression analysis was conducted with the ATP, NADH, Tyr, Trp, and PPIX indexes. Among them, the TVB-N (mg/100g) =87.926X2-47.222X3-26.773 (R2=0.926) and TBARS (mg/kg) =1.850X2-2.227X3-1.072 (R2=0.878) were obtained for the optimal regression models to predict the TVB-N and TBARS in the lamb meat by Tyr and Trp, respectively. The optimal regression model of the TVC was the TVC (lg CFU/g)=-0.018X1+15.131X2-2.273 (R2=0.952) by the NADH and Tyr. Thus, the NADH, Tyr, and Trp can be expected to serve as fluorescent characteristic markers for the detection of lamb meat freshness during storage. The findings can provide a theoretical basis for the subsequent development of lamb freshness detection using hyperspectral fluorescence imaging.
      2022,38(22):280-286, DOI: 10.11975/j.issn.1002-6819.2022.22.030
      Abstract:
      Abstract: Teejet atomizing nozzle is one of the most important components in the mobile micro-sprinkler system for the greenhouse. Three kinds of fan-shaped nozzle structures with different diameters can fully meet the irrigation requirements to adjust the farmland microclimate for better crop growth stress in the various scenes. Therefore, this sprinkler can be expected for greenhouse irrigation, due to its wide application range, high safety, and long service life. However, there is no accurate reference to the parameters of sprinklers, such as hydraulic performance and operating conditions. The purpose of this study is to obtain a better configuration condition of atomizing nozzle. The hydraulic performances of the single and combined nozzle were optimized on the installation height, equivalent diameter, working pressure, and combined spacing of the Teejet atomizing nozzle. A water distribution test was carried out to verify the hydraulic performance parameters of atomizing nozzle under different working conditions. The experimental analysis, theoretical calculation, and comprehensive evaluation were then combined to clarify the influence of the equivalent diameter, installation height, and working pressure on the hydraulic performance of atomizing nozzle. The quantitative relationship was obtained between the installation height, working pressure, equivalent diameter, combination spacing and uniformity coefficient. A comprehensive evaluation index system was constructed using technical and economic indicators. Finally, the principal component analysis was implemented to determine the optimal configuration scheme for atomizing nozzles. The results show that: 1) The velocity of water flow increased significantly in the pipeline with the increase of working pressure, while the peak value of sprinkler irrigation intensity gradually increased to widen the spraying range. The slow water diffusion of a single nozzle was observed for the uniform water distribution, as the installation height increased. As such, the wider spraying range of the nozzle was obtained than before. In the same installation height and working pressure, the larger the equivalent diameter of the nozzle was, the larger the outlet flow was, and the greater the peak sprinkler irrigation intensity of the nozzle was. 2) There was the basically same variation trend of the combination uniformity coefficient in the three equivalent diameter sprinklers. The combination spacing presented the most outstanding influence on the combination uniformity coefficient. Furthermore, the combination uniformity coefficient tended to decrease first, then increase and finally decrease, with the increase of the combination spacing in the sprinklers. A relatively significant influence was also observed in the working pressure and installation height on the combination uniformity coefficient. 3) A comprehensive index evaluation model was established using principal component analysis. The optimal configuration conditions of atomizing nozzles were obtained by SPSS analysis, including, the nozzle equivalent diameter of 1.81 mm, the installation height of 0.6 m, combined spacing of 0.2 m, and working pressure of 400 kPa. This finding can provide theoretical support to the parameter configuration of mobile micro-sprinkler for greenhouse irrigation.
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    February 03, 2023 , DOI:
    Abstract:
    Sub surface waterlogging is one of the primary agro-meteorological disasters affecting wheat yield in the middle and lower reaches of the Yangtze River, Aim at the problems about the current waterlogging assessment methods ,such as the incomprehensive consideration of the hazard factors and the failure to consider the waterlogging tolerance variances in the growth period of crop, In this paper, a characteristic model using WI index (Waterlogging Index in the whole growth period) was proposed to represent the degree of wheat sub surface waterlogging. WI index takes into account the influence of soil hypoxia on root system and the variant of wheat waterlogging tolerance in different growth stages. The SMAP (Soil Moisture Active Passive) soil surface moisture product data from 2016 to 2022 were substituted into the model to calculate the WI index values of each grid point (10km*10km) in the middle and lower reaches of the Yangtze River. The spatial distribution of the damage rate in the middle and lower reaches of the Yangtze River was obtained by taking the WI index greater than 0.005 as the damage area, and the area was divided according to the damage rate. The results showed that wheat waterlogging areas in Hubei province, Anhui Province and Jiangsu province were mainly concentrated along the Yangtze River, that is, in the south of each province, the middle risk area was the main risk area.The areas with high risk of wheat waterlogging in Hunan province and Jiangxi Province are mainly concentrated in the middle part of each province, and almost all the areas in hunan province and Jiangxi Province are in the middle risk area.The total area of no-waterlogging area accounted for 28.1%, low risk area accounted for 8.9%, medium risk area accounted for 34.4%, high risk area accounted for 28.6%.
    February 01, 2023 , DOI:
    Abstract:
    The direct or indirect discharge of industrial wastewater leads to the high degree of pollution of heavy metals in Chinese natural water resources. The removal of heavy metals sewage is a problem that is exigent to be solved. However, existing heavy metal removal methods are generally found to be too complicated or expensive. Because the waste concrete particles contain cement hydration products and unhydrated cement particles, which have a certain activity and a high specific surface area. This paper tries to use the waste concrete particles as the adsorption material of water polluted by heavy metals. Through the heavy metals leaching test, it is found that the heavy metal leaching capacity is related to the particle size of the waste concrete. The larger the particle size is, the smaller the heavy metal leaching capacity is. Based on the test data and the discharge threshold requirements of the National Comprehensive Sewage Discharge Standard, the optimal selected particle size of the waste concrete particle material is finally determined. Then, by the static adsorption test, the effect of the adsorption time, the adsorbent dosage and the initial mass concentration of heavy metal on the adsorption of heavy metals copper and lead in waste concrete are mainly investigated. The result shows that the adsorption time, waste concrete dosage and initial concentration of heavy metal copper and lead will affect the adsorption properties of waste concrete. With the increase of adsorption time, the adsorption of two heavy metals copper and lead shows a trend of increasing first and then stabilizing. In the first 100 min, the adsorption of copper and lead quickly reaches more than 95% of the saturated adsorption amount, and the adsorption capacity reaches the extreme value of 65.34 and 35.17 mg/g. With the increase of the initial mass concentration of copper and lead, the removal rate of the two heavy metal gradually decreases, and the adsorption capacity gradually increases and then stabilizes. When the initial mass concentration is less than 150 mg/L, the adsorption capacity for heavy metal copper is positively correlated ,while heavy metal lead is positively correlated at the initial mass concentration of 200 mg/L. However, with the increase of waste concrete dosage, the removal rate of the two heavy metals copper and lead increases first and then stabilized. The adsorption of heavy metals copper and lead on waste concrete conforms to the Langmiur isothermal adsorption model, and the maximum adsorption capacity obtains 40.75 mg/g and 86.73 mg/g respectively; the pseudo-second-order kinetic model is more suitable for describing the adsorption process of heavy metals copper and lead on waste concrete, which indicating that the adsorption rate is controlled by chemisorption. Compared with other common adsorbent materials, the maximum adsorption capacity of heavy metals lead and copper on the waste concrete is much higher than natural zeolite and palygorskite, while the maximum adsorption capacity of heavy metal copper is lower than activated carbon. However, based on the price, the recycling price of waste concrete is still far lower than the market price of activated carbon even if the processing cost caused by crushing. This also reflects that the waste concrete has good adsorption capacity for the heavy metals copper and lead, which can be used as an adsorption material to treat the wastewater containing heavy metals copper and lead.
    February 01, 2023 , DOI:
    Abstract:
    Above-ground biomass (AGB) is one of the most important indicators to reflect the status of grassland use. Accurate and rapid monitoring is of great significance to scientific management and rational use. Alternatively, remote sensing technology has been widely used to estimate the AGB in recent years. However, the estimation errors can often be caused by the common phenomenon of “same spectrum, different species” in remote sensing. One of the potential solutions can be to use the spectral and meteorological data to invert the AGB grassland. In this study, a machine learning model was developed to characterize the spectral indices and meteorological data using Landsat 8 remote sensing and ground survey as data sources. A systematic investigation was implemented to explore the performance of regression models constructed by five machine learning algorithms. Specifically, the AGB of grassland was estimated to obtain the high accuracy inversion of remote sensing for the grassland biomass. Nine vegetation indices were selected to calculate in Hulunbuir of Inner Mongolia and Dornod of Mongolia in China. An optimal random forest (RF) regression model was then reconstructed by feature selection. The regression validation revealed that a similar overall performance was achieved in the six machine learning models. But the lower performance was found in the spectral data as the input only (root mean square error (RMSE): 63.852~87.944 g/m2, relative root mean square error (rRMSE%): 33.712~46.432, coefficient of determination (R2): 0.388~0.647). Furthermore, the error of all regression decreased gradually, as the number of features increased in the data combination. The model fitting ability increased gradually as well, indicating that the increasing number of features in the different regression models was effectively handled through the fusion of multiple data inputs. The best evaluation was obtained from each regression model in the data combination of spectra + precipitation + temperature. The RF also obtained the best performance (RMSE = 51.702 g/m2, rRMSE% = 27.297, and R2 = 0.749). The weights of the multiple source data in the model were determined to assess the relative importance of the input data. The results showed that the precipitation was the most important input feature of the model, with a maximum weight of more than 0.1, much higher than the other spectral data. Three vegetation indices of VARI, MSAVI, and GEMI in the spectral data were weighted more than 0.09 as the features, which was higher than the rest. The more stable performance was achieved in the optimized RF regression model, with a correlation coefficient (R2) of 0.801 between predicted and measured values, an RMSE of 43.709 g/m2, and an rRMSE% of 23.077. The AGB spatial distribution in the study area was lower in the central area, but higher on the east and west sides, with a maximum of 357.2 g/m2 and a minimum of 33.0 g/m2. It was closely related to the spatial heterogeneity of climate and grassland use patterns.
    February 01, 2023 , DOI:
    Abstract:
    Crops biomass has been one of the most important indicators to predict the plant growth status and crop yield. This study aims to estimate the dry biomass of the winter wheat aboveground using optical satellite remote sensing. The winter wheat biomass was acquired at four growth stages (jointing, heading, flowering, and filling stage), and three nitrogen treatments (N1, N2, and N3) in 2011, 2012, and 2014 at the agricultural meteorological experiment station, Nanjing University of Information Science and Technology, Nanjing, China. Simultaneously, the narrow-band spectral reflectance of canopy was also collected from the winter wheat using Analytical Spectral Device (ASD). Afterwards, the hyperspectral remote sensing data was resampled into the broad band reflectance of RapidEye, Sentinel-2, and WorldView-2 satellites with the red edge bands using the satellite spectral response functions. All possible band combinations of normalized difference vegetation index like (NDVI-like) were validated in the different growth stages and nitrogen treatments. Meanwhile, the satellite broad-band reflectance was used as the inputs for the six machine and deep learning for the biomass estimation, including the Random Forest (RF), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), Deep Neural Network (DNN), Long- and Short-Term Memory recursive neural network (LSTM), and one-dimensional Convolutional Neural Network (1D-CNN). Finally, the models were developed using Leave-One-Out cross validation under different growth stages and nitrogen treatments. The results showed that the optimal NDVI-like vegetation indices that derived from the two arbitrary bands presented the highest sensitivity to the winter wheat biomass at the flowering stage (coefficient of determination, R2=0.50-0.56). It was also difficult to accurately estimate the biomass of winter wheat using only one vegetation index in the whole growth period. The nitrogen treatments were dominated the correlation between the vegetation indices and winter wheat biomass. Specifically, the high nitrogen treatment was enhanced the sensitivity of vegetation index to the winter wheat biomass. The vegetation index with the Sentinel-2 bands performed better than that with the rest. The R2 was over 0.50 between the vegetation index and biomass at the jointing and flowering stages. The best performance was achieved in the estimation model of winter wheat biomass using DNN among the six machine and deep learning. The performance of DNN-based model was also depended on the growth stages and nitrogen treatments. In the single growth stage, the highest estimation accuracy was observed at the jointing stage (R2=0.69-0.78 and the normalized root mean square error (NRMSE)=26%-31%), and at the flowering stage (R2=0.69-0.70 and NRMSE =24%-35%). The highest estimation accuracy was obtained in the DNN-based model with the Sentinel-2 bands as the inputs, indicating the R2 of 0.70 in the whole growth period. The high nitrogen treatment was also enhanced the estimation accuracy of DNN model, where the R2 was over 0.71 and RMSE was within 219 g/m2 at the N3 condition for all the three satellite bands. Therefore, the optical satellite remote sensing data can be expected to estimate the winter wheat biomass under the different growth stages and nitrogen treatment conditions
    February 01, 2023 , DOI:
    Abstract:
    The Bohai Sea and the Yellow Sea have been the essential marine granary and eco-environmental governance areas in China. Wherein the carbon dioxide emission from fishing vessels can be normally neglected to assess the global greenhouse gas (GHG). It is very necessary to identify the specific contribution of the productive fishing vessels to the GHG emission, in order to reduce the carbon emission for the carbon neutral. Taking the Bohai Sea and the Yellow Sea as the research areas, this study aims to explore the spatiotemporal characteristics of carbon dioxide emission from the fishing vessels. A dynamic calculation model of carbon dioxide emission from fishing vessels was established using vessel management and position data, in order to reveal the impact of fishery production activities on climate warming. Nine types of fishing vessels were also selected to analyze the carbon dioxide emissions intensity and spatiotemporal characteristics from 2020 to 2021. Results showed that: 1) The total carbon dioxide emissions of fishing vessels in Bohai Sea and the Yellow Sea were 4.5 and 9.45 million tons, respectively, indicating the distribution characteristics of low nearshore and high offshore. Hot spots were distributed mainly in the fishing ground of Bohai Bay, Luanhekou, Haidong, Yanwei, Shidao, Shidong, Haizhou Bay, and Daisha. Every ton of fishing catches emitted approximately 1.57 and 3.27 tons of carbon dioxide, respectively, when considering the yield data. 2) Trawler and gillnet fishing vessels were the main contributors to the total carbon dioxide emissions, accounting for more than 70% of the total emissions from all fishing vessels. Among them, the auxiliary vessels were the highest, followed by the purse seiner vessels, in terms of emissions per vessel per unit sailing time. Carbon dioxide emissions per unit sailing time from the single vessel were similar to the trawler, gillnet, stow net, purse seine, auxiliary, and unknown types, whereas, there was the significant difference for the line, and aquaculture types. 3) There was the similar spatial distribution of carbon dioxide emissions from the fishing vessels in the same month in the different years. But the hot spots exhibited a strong spatial difference. Firstly, the hot spots occurred in the central and southern part of the Yellow Sea from January to April, where a high-value belt was extended the southeast from the Haizhou Bay to the East China Sea. Then, there was no carbon dioxide emission in the offshore area from May to August. Eventually, the hot spots were shifted to the central Bohai Sea, the eastern Shandong Peninsula, and the central Yellow Sea from September to December. In general, the center of gravity of carbon dioxide emission from the fishing vessels was transferred from the coastal to the central open waters. The finding can provide a theoretical basis for the transformation of fisheries into the low carbon. Two suggestions were also proposed to reduce the carbon emissions of fishing vessels. One is to accelerate the transformation of fishery production and product formats, and another is to strengthen the carbon emission management of key fishing vessels and key areas. In the end, it can be expected to assess the carbon emission system for the fishing vessels.
    February 01, 2023 , DOI:
    Abstract:
    An accurate extraction of the crop spatial distribution is of great significance for the decision-making on management measures in modern agriculture. Fortunately, the remote sensing images can be widely used as the important data sources for the spatial distribution of crops at present. It is a high demand to extract the high-quality features from the spatial distribution of crops using the remote sensing images. In this study, the Sentinel-2A images were selected to extract the high-precision spatial distribution of winter wheat, in order to avoid the data scale reduction and feature fusion. Firstly, the red edge resource was utilized to classify the important features of winter wheat. The visible light and red edge bands were also combined to effectively reduce the misclassification of pixels for the high accuracy. A downscale model Red Edge Down Scale (REDS) was then established to balance the spatial scale of the data in the Sentinel-2A images, due to the different band resolution between the red edge (20m) and the visible light (10m). The generative countermeasure network was constructed using the three red edge bands of B5, B6 and B7. More importantly, the spatial resolution of B11 shortwave infrared band was reduced from 20 to 10 m, in order to obtain the better consistence in the spatial resolution of visible light and red edge band. The edge blur of image was also prevented from the interpolation (nearest neighbor interpolation). Secondly, the inputs of REDS consisted of the low- and high-resolution channel, correspondingly to the spectral and texture information, respectively. The spatial structure information was then input from the high- into the low-resolution channel. As such, the improved model was achieved in the image data from the high-resolution red edge and short-wave infrared (SWIR) channel. Secondly, the original data was extracted, and then combined into the basic input data, including the three red edge bands after scaling down, the visible light band with a resolution of 10m, and three remote-sensing index products, namely Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Red-Edge1 (NDRE1). Thirdly, the semantic feature extraction model was constructed as the Red Edge and Vegetation Index Feature Network (REVINet) using convolutional neural network. The coding and decoding units were constructed in the REVINet model using residual network. The linear model was used to fuse the multi-scale features for the output by the decoding units. SoftMax function was used as a classifier for the pixel-by-pixel classification. Finally, the segmentation, and the spatial distribution of winter wheat were generated to verify the REVINet model, compared with the ERFNet, U-Net, and RefineNet models. The experimental results show that the smoother contour edge was extracted from the planting area of winter wheat, particularly with the less misclassification. Meanwhile, the recall (92.15%), precision (93.74%), accuracy (93.09%), and F1 score (92.94%) were better than the rest models, indicating the ideal performance. The spatial distribution of the whole research area demonstrated that the winter wheat in China was mainly distributed in the south of the Great Wall in 2022. The relatively high accuracy of extracted areas was achieved with the better coincidence degree, compared with the standard released by the National Statistical Department in 2021. Therefore, the data organization and feature extraction can be expected to serve as the spatial distribution of winter wheat using the Sentinel-2A. The finding can also provide the technical reference for the Sentinel-2A data in the agricultural field.
    February 01, 2023 , DOI:
    Abstract:
    Rice-turtle integrated system is a green and high-efficiency ecological agricultural system. However, there are few studies on the effects of rice-turtle co-cropping on soil microbial community structure and functional characteristics and its driving factors. Illumina high-throughput sequencing technology was used to analyze the changes of soil bacterial and fungal community structure in paddy soils treated with rice monoculture system(RM) and rice-turtle integrated system(RT). The correlation between soil physical and chemical properties and microbial community structure was further analyzed. The results showed that: (1) Rice-turtle integrated system was beneficial to increase soil nutrient contents and improve soil fertility. The contents of SOM, TK, AN, AP and AK were significantly increased by 37.72%, 15.15%, 13.80%, 37.37% and 21.57% (P < 0.05). (2) Rice-turtle integrated system could increase soil microbial richness and diversity, and changed the microbial community structure. The relative abundance of soil Proteobacteria, Acidobacteriota, Ascomycota and Rozellomycota increased by 6.42%, 1.16%, 0.44% and 2.96%, respectively. And the relative abundance of Basidiomycota decreased by 0.22%. (3) Rice-turtle integrated system changed the interaction pattern of microbial communities, enhanced the relationship between soil bacterial and fungal communities, which was conducive to the stability of microbial community structure. (4) The contents of SOM, TK and AK were the main environmental factors affecting the change of soil bacterial community structure, while the contents of TK, AK and AP were the main factors affecting the fungal community structure. In conclusion, the application of rice-turtle integrated could reduce the input of chemical fertilizers and pesticides, improve soil fertility of paddy fields. At the same time, co-cropping was conducive to improving the structure and diversity of soil microbial communities, increasing soil beneficial flora, and maintaining the stability of rice field ecosystems. This study provides an important scientific basis for exploring scientific and reasonable paddy field cultivation mode.
    January 31, 2023 , DOI:
    Abstract:
    The comprehensive management of cultivated land in agricultural space is of significance to agricultural-rural development, and territorial space governance. However, it’s urgent to scientifically evaluate the ecological sustainability of cultivated land for ecological restoration of territorial space in the new era. From the mine damage, landscape pattern, ecological stability and ecological space occupation, this study mainly used the Revised Universal Soil Loss Equation (RUSLE), spatial analysis, landscape pattern index to identify ecological problems of cultivated land in Jiangxi Province during 2000-2018. Based on the analytic hierarchy process and entropy method, we constructed a framework for evaluating the ecological sustainability of cultivated land in Jiangxi Province at the county scale. The results showed that the soil and water erosion of cultivated land in Jiangxi province was mainly caused by mild erosion, and the total area decreased by 50.98%. The phenomenon of soil and water erosion in the upper reaches of Ganjiang River and the surrounding area of Poyang Lake intensified. The patch density and fragmentation degree of cultivated land patch showed an increasing trend, and the aggregation degree showed a decreasing trend. Cultivated land occupied 739.15km2 of ecological land such as forest land, water and wetlands. The total area of cultivated land destroyed by abandoned mines such as building materials, brick clay and rare earth metals was 13.18km2. Overall, the ecological sustainability level of cultivated land was generally in good condition. Yihuang County and Nanfeng County in the middle and lower reaches of Ganjiang River and Fuhe River Basin were high, while the Poyang Lake, Xinjiang River Basin and the upper reaches of Ganjiang River was relatively low. We provide methodological support for the high-quality development of agricultural space in territorial space planning, and our findings provide scientific basis for the ecological restoration of agricultural space in Jiangxi Province.
    January 30, 2023 , DOI:
    Abstract:
    Adopting saline water or slight saline water for agricultural irrigation is an important way to alleviate the current contradiction between the water supply and the demand in Xinjiang agriculture, and to boost the sustainable development of local cotton industry. To explicitly demonstrate the effects of different combinations of the amount (I) and electrical conductivity (ECI) of irrigation water on the yields and profits of cotton, the data regarding soil (e.g. soil texture and bulk density), crop (e.g. cotton yield), irrigation management (e.g. I and ECI) in 9 different experimental sites in Xinjiang were collected through one two-year field experiments for cotton under film mulched drip irrigation as well as literature retrievals, and used to evaluate the applicability and reliability of a biological-physical model—ANSWER (ANalytical Salt WatER) in estimating cotton yield. Combined with Break-even method, ANSWER is applied to investigate and evaluate the effects of different combinations of I and ECI on the yield and profit of cotton based on scenario analysis. Three statistical indices such as the determination coefficient (R2), root mean squared error (RMSE) and relative root mean squared error (RRMSE) were employed to evaluate the performance of the model. The results show that ANSWER adequately estimated relative yields of cotton for different experimental sites and irrigation treatments with various levels of I and/or ECI. The R2 between the simulated and measured relative yields were consistently greater than 0.54, while RMSE and RRMSE were not more than 0.14 and 0.16, respectively. The differences of the optimized values of each biological parameter in ANSWER (representing the physiological response of crop root water uptake to water-salinity stresses) among all experimental sites were found to be relatively small, with the absolute CV (Coefficients of Variation) value ranging from 0.08 to 0.37 and a mean of 0.19. An individual parameter presented a large degree of variation (i.e. CV = 0.37) but little sensitivity for the estimation of relative yield. When the combination of the mean (MN) of originally optimized biological parameters for different experimental sites was used to estimate the relative yields of cotton for each specific experimental site, the estimated results were comparable to the measurements, with a R2 of 0.59, a RMSE of 0.06, and a RRMSE of 0.07. Based on scenario analysis, it was found that cotton profit first increased and then decreased with increasing I under a given ECI, and that the I required for reaching or being close to maximum profit at least increased rapidly with increasing ECI. When the ECI was limited to 10 dS/m, the resulting profit by saline water irrigation still has the potential to approach or even exceed the level of profit resulted from fresh water irrigation only by means of sufficient saline water replenishment; however when the ECI was above15 dS/m, there will be no profit due to excessive salt stress induced low yield. Moreover, if a relative yield of 0.80 is desired or expected, the ECI should be set to less than 17 dS/m, and meanwhile the relative irrigation amount (I Tp-1) should be set to larger than 0.8. Overall, to balance the relationships of high profit, water-saving, and sustainable use of saline water, the I Tp-1 linked to the peak value of profit can be used as an appropriate value of irrigation amount to guide the irrigation management under a specific ECI, while it is necessary to provide some measures (e.g. physical, chemical or biological) for soil salt removal or reduction to avoid or relieve its excessive accumulation in the root zone. The research provides theoretical basis for the evaluation of cotton yield and profit, and the rational development and utilization of saline water resources in Xinjiang.
    January 30, 2023 , DOI:
    Abstract:
    Previous studies on soil organic matter prediction often extracted only one spectral input and ignored the complementarity between different spectral inputs. In order to explore the optimal combination of spectral input in predicting soil organic matter and the variation trend of different spectral input under different decomposition scales of discrete wavelet transform, this study took soil organic matter in Baoqing County as the research object and carried out discrete wavelet transform on spectral reflectance. The characteristic spectral parameters, spectral indices and principal components were extracted from the characteristic spectra at each decomposition scale and combined respectively. The random forest model was established based on eight spectral inputs to predict soil organic matter. The results show that: 1) The accuracy of soil organic matter prediction by extracting different spectral inputs is higher than that of direct spectral reflectance modeling. The verification accuracy of principal component in single spectral index is the highest, and that of the combination of spectral characteristic parameters and principal component is the highest, which is higher than that of the principal component modeling alone, indicating that combining different spectral inputs can improve the prediction accuracy. However, simply stacking spectral inputs as inputs does not help improve the prediction accuracy.2) With the increase of decomposition scale, the variation trend of prediction accuracy of different spectral inputs is also different, and the variation trend of prediction accuracy of different spectral input combinations will change with the different spectral inputs in the combination, and will reflect the variation characteristics of spectral inputs in the combination.3) The combination with the highest verification accuracy was the combination of spectral characteristic parameters and principal components with decomposition scale of 6, R2 reaching 0.78 and RMSE reaching 1.32%, indicating that the spectral input combined with discrete wavelet transform modeling is feasible to predict organic matter and has good prediction ability, providing a reliable idea for soil organic matter prediction. It provides theoretical support for the dynamic monitoring of soil organic matter and its temporal and spatial changes.
    January 29, 2023 , DOI:
    Abstract:
    It is of great significance to reveal the characteristics and influencing mechanism of cultivated land abandonment in rapidly urbanizing areas for farmland protection and food security in the process of urbanization and industrialization in China. This paper constructs a theoretical framework of the impact mechanism of farmland abandonment in rapidly urbanizing areas from the aspects of land resource conditions, economic level, social development and policy regulation. Taking Liyang county as a case area, it analyzes the degree of cultivated land abandonment, spatial pattern characteristics and influencing factors, and proposes Policy suggestions for preventing and controlling the abandonment of cultivated land in rapidly urbanizing areas are presented. The results show that: ①The abandoned area of cultivated land in Liyang county was 1344.48 hm2, and the abandonment rate was 3.03%, and the abandonment rate of each village ranged from 0.01%~54.26%. The abandonment of cultivated land in rapidly urbanizing areas is widespread, and should be paid attention to. ②Cultivated land abandonment in rapidly urbanizing areas has a certain agglomeration and driving effect in space. The high-density abandoned cultivated land area in Liyang is mainly concentrated in areas with high development level industry of commerce and tourism, and high proportion of non-irrigated land. ③The scale of industrial, storage and commercial land, the proportion of three or more residential sites, the area of cultivated land per labor and the proportion of high school and above education are positively correlated with the rate of cultivated land abandonment in Liyang, respectively. The proportion of irrigated, the density of rural roads, the proportion of operator households on the transfer scale are negatively related to the rate of cultivated land abandonment. The loss of labor and the level of rural non-agricultural economy both drive the abandonment of cultivated land; which good cultivated land resource and conditions, land transfer policy, prime farmland policy can effectively restrain cultivated land abandonment in rapid urbanization areas. In the future, we can continue to promote the land renovation project, encourage farmers' land transfer, guide agricultural capital and enterprises to go to the village, innovate the "tourism + agriculture" development model and strengthen the policy of permanent prime farmland in the rapidly urbanized areas, so as to provide theoretical support and practical operation decision-making reference for the protection of cultivated land and food security in rapidly urbanizing areas.
    January 28, 2023 , DOI:
    Abstract:
    The stability of agricultural product prices is of great significance to social economy and agricultural development, but the fluctuation of agricultural product prices is characterized by non-stationary, non-linear, and high volatility, and it is difficult to predict accurately. Based on signal decomposition and deep learning, this paper proposes a decomposition-reconstruction-extraction-associated-output agricultural product price prediction model (CT-BiSeq2seq) and adds multi-dimensional data such as the average temperature, fertilizer cost (price of pig formula feed and urea), and public attention to improve the model prediction accuracy. Firstly, the complex original price series are divided into simple series by using the complementary ensemble empirical mode decomposition method (CEEMD). Secondly, the original price series is reconstructed into high-frequency items, low-frequency items, and residual items by analyzing the Pearson correlation coefficient and the decomposed subsequence. Next, the data features of the reconstructed sequence are extracted through a temporal convolutional network (TCN). At this time, the input dimension is 7-dimensional data, which can extract the factors that affect the price of agricultural products, and the output steps are equal to the input steps. Subsequently, a Biseq2seq model is constructed which is composed of an encoder and a decoder, and its encoder introduces a bi-directional Long Short-Term Memory network (Bi-LSTM) to strengthen the global correlation between sequence data. Finally, the decoder introduces the LSTM network to output prediction value which can output the predictive value of the number of any steps. Taking the pork price of the Fengtai District wholesale market in Beijing for empirical analysis, the prediction performance of the CT-BiSeq2seq model proposed in this paper is remarkably better than other benchmark models, and the number of lags reached the optimal effect in 11 days. The mean square error, the mean absolute error, and the mean absolute error are 0.6611(rmb/kg), 0.5014(rmb/kg), and 2.1138% respectively. This shows that in agricultural product price forecasting, too few days lag is easy to fall into local optimum and cannot fully reflect the overall characteristics. If the lag days are too long, overfitting is easy to occur, and the prediction accuracy will also be reduced. On the other hand, this model also has an accurate and stable prediction effect in other data sets. The mean square error of spinach, apple, and egg is 0.6277(rmb/kg), 0.4632(rmb/kg), and 0.5526(rmb/kg) respectively, the mean absolute error is 0.5431(rmb/kg), 0.4425(rmb/kg), and 0.5339(rmb/kg) respectively, and the mean absolute percentage error is 3.2047%, 2.2361% and 2.2314% respectively. At the same time, according to the results of different data sets, it is found that agricultural products with large price fluctuations are suitable for large lag steps, while agricultural products with small price fluctuations are suitable for small lag steps. For agricultural products with large price changes, the large number of lag days can completely learn the trend of price change. For agricultural products with smaller price changes, due to the relatively stable trend of price change, the short lag days can fit the time sequence relationship. Specifically, the prices of spinach and eggs fluctuate greatly in the data range, and the loss error reaches the minimum when the lag days are 11 days. Apple's price fluctuates less in the data range, and the loss error reaches the minimum when the lag days are 7 days. This model can provide a reference for forecasting the price fluctuation of agricultural products.
    January 28, 2023 , DOI:
    Abstract:
    Sunset yellow was a common synthetic colorant in food processing to maintain or improve the color of food. Due to containing azo group and benzene ring, excessive consumption of sunset yellow would be harmful to human health and might cause some symptoms such as allergies, asthma, diarrhea and cancer. In order to prevent and avoid the risks of food safety caused by abuse of sunset yellow, it was necessary to establish a fast, sensitive and accurate analysis method for this kind of colorant. In this paper, a novel electrochemical sensor for sunset yellow detection was developed based on copper oxide-carboxylated graphene (CuO-CG) nanocomposites modified glassy carbon electrode. The CuO-CG nanocomposites modified glassy carbon electrode was fabricated by electrochemical deposition of CG and Cu on the surface of a bare glassy carbon electrode in sequence, followed by in situ oxidization of the Cu film to form the CuO layer. The electrochemical oxidation behaviors of sunset yellow on the surface of CuO-CG nanocomposites modified glassy carbon electrode were studied by cyclic voltammetry and chronoamperometry. According to the results of cyclic voltammetry, an obvious peak at 0.52 V for sunset yellow oxidation was observed by CuO-CG nanocomposites modified glassy carbon electrode, and the obtained peak current value was 74.6-fold higher than that of the bare glassy carbon electrode, which implied that the CuO-CG nanocomposites modified glassy carbon electrode-based electrochemical sensor was possibly realized for detection of sunset yellow with good performances. To obtain a sensitive response, the experimental conditions that affected on the electrochemical detection of sunset yellow were optimized using chronoamperometry, including the deposition order of the electrode materials of CuO and CG, the deposition time and deposition voltage of CG, the deposition time and deposition voltage of Cu, the concentration of sodium hydroxide, and the applied voltage for sunset yellow detection. Under the optimal experimental conditions, the analytical performances of the CuO-CG nanocomposites modified glassy carbon electrode-based electrochemical sensor for sunset yellow detection such as response time, linear range, detection limit, reproducibility, stability, selectivity and accuracy were investigated in details using chronoamperometry. The main results obtained by this electrochemical sensor were showed as follows. Firstly, the results displayed that the optimal deposition order of the proposed electrode materials was first deposition of CG using chronoamperometry, and then deposition of CuO using chronoamperometry and cyclic voltammetry. When the other experimental conditions were fixed, the optimal deposition time and deposition voltage of CG was 900 s and –1.4 V, and the optimal deposition time and deposition voltage of Cu was 120 s and –1.1 V. When the other experimental conditions were fixed, the optimal concentration of sodium hydroxide was 0.10 mol/L, and the optimal applied voltage for sunset yellow detection using chronoamperometry was 0.55 V. Secondly, the results revealed that the response time of the electrochemical sensor to sunset yellow was within 5 s, implying fast response of the developed sensor towards sunset yellow detection. And the oxidation current of sunset yellow increased linearly with the increase of its concentration in the range of 0.20 μg/mL~4.07 mg/mL. The detection limit of the electrochemical sensor for sunset yellow was 79.36 ng/mL. Thirdly, this electrochemical sensor was further used for detecting the concentration of sunset yellow in drink samples. There were no need of complicated sample processing steps, and the recoveries obtained using chronoamperometry and standard addition method were in the range of 99.35%~105.88%, which indicated that this electrochemical sensor could be successfully employed for trace detection of sunset yellow in real samples. The developed CuO-CG nanocomposites modified electrode-based electrochemical sensor had the advantages of short response time, wide linear range, low detection limit, good reproducibility, good stability, high selectivity and accuracy, which expanded the applications of CuO-CG nanocomposites.
    January 28, 2023 , DOI:
    Abstract:
    Abstract: In recently, pH-colorimetric films have received wide attentions because they can exhibit straightforward information by visible color changes without opening packages and the increasing consciousness of people’s food safety. Purple cabbage anthocyanins (PCA), a natural anthocyanin pigment with high pH sensitivity, can show different color changes with the change in pH due to their unique structure easily. The PCA color changed from dark to light red in acid solutions (pH=2~4) as the dominant of flavylium cation. At pH level of 5~6, flavylium cation reacted with hydrogen and transformed to carbinol pseudobase (colorless) or chalcone (colorless) and appeared pink. With increasing of pH (7~8), quinoidal base was established. Subsequently, anion quinoidal (blue) was dominant in alkalinity pH (9~10). At pH 11, the color turns greenish-blue for the anionic quinoidal base (blue) is synthesized. Soy Protein Isolate (SPI), a byproduct of the soybean oil industry, is characterized by low cost, good biodegradability, biocompatible, and excellent film-forming properties. Also, as a natural material, SPI is easy to fuse with purple cabbage anthocyanins. Hence, SPI was selected as a film-forming material. However, the SPI films presented relatively low mechanical properties and thermal stability due to the hydrophilic bonds (-OH, -NH2, -COOH, -SH) in film matrix. There is typical C6-C3-C6 carbon skeleton structure in anthocyanins contains two benzoyl rings and oxygenated hexameric heterocycles with cations (a typical 2-phenyl-benzopyran cation structure). The two typical and highly reactive structural in PCA molecules can cross-linking with SPI molecules through hydrogen bonds and electrostatic interactions to form homogeneity and low surface roughness of films due to excellent fusibility and compatibility of PCA and SPI, which improved the mechanical properties and pH sensitivity of SPI/PCA indicator films. Therefore, this study aims to synthesize the SPI/PCA-based pH-indicator films with uniform structure, excellent mechanical properties, and strong pH sensitivity and apply it into freshness monitoring of pasteurized milk. FTIR and SEM demonstrated that PCA was successfully dispersed in the SPI film matrix, interacting with the SPI molecules under electrostatic interactions and hydrogen bonds. In SEM micro graphs, it could be observed that a certain amount of small particles floated on surface and small holes in the section of indicator films with overdose PCA. The above situation showed that the highest limitation of fusion degree of PCA with SPI maybe 4%. PCA significantly enhanced the mechanical properties of indicator films. The tensile strength of indicator films increased by 53.25% (from 2.46 to 3.77 MPa) and elongation at break increased by 25.25% (from 105% to 131%) compared to SPI film. The thermal stability of indicator films with PCA was similar as SPI films (167℃ to 170℃). The color difference (ΔE) of indicator films containing PCA from standard white increased from 21.23 to 52.88. L value decreased and indicator film was yellowish-green. The indicator films presented strong chromatic stability without visible color difference within 5 days at room temperature and highly pH sensitive with visible color difference under different pH value, which two properties are helpful for monitoring the freshness of indicator film. When the indicator films were applied in freshness monitoring of pasteurized milk, the color changed from green to red accompanying with deterioration of milk. Also, the color difference with initial film was visibility (ΔE≥5) at any time. Hence, the innovation of this study is that purple cabbage anthocyanins endowed the indicator function of pure SPI films, and the indicator films monitor the freshness of pasteurized milk through the color change. Therefore, the indicator films can widely be expected to apply in intelligent packaging, mainly due to excellent pH-sensitive properties and color stability. The research can provide insightful ideas to design and produce SPI/PCA based pH-indicator films.
    January 28, 2023 , DOI:
    Abstract:
    Rice is a significant food cash crop in China. The annual production of rice exceeded 200 million tons. Rice should be dried in time after harvest, which may prevent the rice from mold, sprouting, and some other defects caused by environment and other factors, thus ensuring grain yield and quality. Hot-air drying was the primary method for drying rice. In the drying stage, one-way ventilation was applied in most vertical box-type hot air dryers, which might cause the rice not to be dried uniformly. The structure and arrangement of the angle tubes were the keys that determined the uniformity of airflow distribution in the drying section. The study was intended to improve the uniformity of airflow distribution in the grain layer and maintain rice quality. In this study, the four-way ventilation mixed-flow drying process was used as the basis. The double-side inlet variable diameter air ducts were designed for the four-way ventilation mixed flow drying section. A mathematical model of coupled heat and moisture transfer within the rice layer was established by CFD and porous media heat and mass transfer theory. The static flow field, temperature, and humidity distribution in the drying section were numerically simulated by FLUENT software. The research showed that the best reducer angle of the double-side inlet air duct was 0.85° which meets the requirement of uniform air distribution in the drying section. The wind velocity non-uniformity coefficient of the section below the inlet air duct was reduced by 6.11% compared with that before optimization. After using double-side inlet variable diameter air ducts in the drying section, the problems of uneven flow field distribution, uneven temperature distribution, and moisture along the longitudinal direction of the inlet air duct were effectively solved. Four-way ventilation mixed flow drying experimental bench was utilized. In the quadratic orthogonal rotation combination experiments with three factors and five levels, parameters optimization experiments were carried out with the temperature of hot air, the air velocity, and the initial moisture content as the experimental factors, while the drying rate, the crackle-added ratio and taste value as the experimental index. Design Expert 8.0.6 was utilized to analyze the experiment data and obtain regression equations and response surface plots. The optimal combination of operating parameters obtained was listed as follows: optimal hot air temperature, the inlet air velocity of the air duct, and the initial moisture content were calculated as 43 ℃, 4.1 m/s, and 18.2%, respectively, where the results of the drying rate, crackle-added ratio and taste value were 1.116 %/h, 1.7% and 80.33 points, respectively. The experimental results of the optimal parameters combination were consistent with the mathematical model optimization results. The drying experiments showed that the moisture non-uniformity of the rice was 0.7%. The four-way ventilation mixed flow drying section for rice had good drying effects. The drying section with double inlet variable diameter air ducts and drying optimization parameters had practical application value. This study might provide an effective reference for optimizing the drying technology of rice.
    January 19, 2023 , DOI:
    Abstract:
    The Mu Us Sandy Land is a typical ecologically fragile area, and its remediation and utilization in Yulin has achieved remarkable results in recent years, which also has a profound impact on the soil environment. As an important indicator of soil fertility and productivity, it is important to monitor the dynamic changes of soil organic matter from large scale space and long time series to find out the trend of soil organic matter under different natural conditions and anthropogenic influence, and help decision makers to understand the stability and security of soil ecosystem in time. The purpose of this study is to determine the characteristics of land use changes in the conspicuous sandy land in Yulin City in the past three decades, to investigate the changes in soil organic matter content under different land types transformed from sandy land, and to clarify the magnitude of the effects of different remediation and utilization methods on soil organic matter in sandy land. In this study, the dominant sandy land in Yulin city was selected, and the land use transformation characteristics of the dominant sandy land in Yulin city were analyzed by calculating its land use dynamic attitude; using the information of each waveband of multispectral remote sensing images and related spectral indices, combining the factors related to natural conditions and land use change characteristics of sandy land, by comparing the fitting accuracy of three machine learning methods, namely decision tree classification, random forest classification and XGBoost, finally The XGBoost method was selected to invert the soil organic matter content from 1990 to 2020; analyze the change of soil organic matter content and spatial distribution characteristics under different land types, reveal its spatial variability by semi-variance function, calculate the average content change of soil organic matter under different land use types transformed from sandy land in the study area, and clarify the influence of anthropogenic factors and natural environment on desert soil organic matter. The results show that more than half of the sandy land in Yulin City was remediated and utilized in the first three decades, the sandy land transformation was the fastest in the first decade, sandy-grassland was the most important land transformation method, and the construction land area grew the fastest, with the growth rate exceeding 70% at one time; the multispectral remote sensing using XGBoost machine learning method The inversion can better estimate the soil organic matter content, and the inversion error is within 13% by comparing with the relevant studies on soil organic matter content measurement in Yulin City in the past. The average value of soil organic matter of land use types represented by arable land and water area reached nearly 0.8%, and after 2010, the soil organic matter of all land use types decreased significantly, and the average value of soil organic matter decreased to 0.51% in 2020. Soil organic matter in the Yulin sand region has a strong spatial autoregulation and is mainly influenced by natural environmental factors such as temperature, precipitation and topography. Initially, anthropogenic use had a positive impact on it, but as the intensity of sand use increased, it had a negative impact on soil organic matter, which in turn led to a decline in its content and a crisis of land degradation.This study recommends strengthening the restoration and improvement of degraded forest and grass, slowing down the development efforts, and reducing human activities, in order to provide theoretical and practical implications for sandy land remediation, protect the soil environmental safety of Yulin sandy land, and realize the harmonious coexistence between human and nature.
    January 16, 2023 , DOI:
    Abstract:
    Multi-beam fishing sonar (also known as fish finder),as an active sonar,transmits underwater acoustic signals to the water by the underwater transducer.The signal received by the transducer is received by the transducer, among which the multi-beam fishing sonar host is the core hardware of the fishing sonar system,which has the characteristics of high technical performance,high integration and high reliability.As the key technology of sonar host design,thermal design directly affects whether the whole system can complete the detection of marine organisms,and plays a vital role in improving the stability and reliability of sonar host.This study starts from the heat dissipation analysis of the sonar host for fishing, and uses the relevant theories of heat transfer and structural design to carry out the thermal design of the sonar host for fishing.First,through the research on the structure of the sonar host and various heat dissipation methods,combined with the requirements of the airtight performance of the sonar host,it is determined that the shell of the host and the external environment are naturally cooled,and the interior of the host adopts forced air cooling.Heat dissipation method;then use the system analysis method to analyze the structure of the sonar host for fishing,and then analyze the heat dissipation through the entire heat dissipation process from the heat source to the board to the chassis and finally to the external environment. Suggestions in the whole process of design and manufacture;secondly,the thermal simulation software is used to simulate the heat dissipation process of the sonar host.By comparing the simulation results of the four design schemes,the design of the air duct is optimized and the design scheme of the four air ducts is determined.By comparing the simulation results of various cooling fans,a cooling fan with a simple structure and meeting the cooling requirements was selected,and the impact on the thermal stability of the host at ambient temperatures of 20°C, 30°C, 40°C,and 50°C was analyzed.The higher the temperature,the worse the thermal stability of the host.The temperature distribution before and after the thermal design of the sonar host is compared,which proves the effectiveness of the sonar host thermal design.Finally, through the heat dissipation test,the temperature changes of the eight FPGA boards were detected,which proved that the thermal design scheme effectively controlled the temperature rise inside the host,and further verified the overall heat dissipation performance of the host.The results show that through the thermal design of the fishing sonar host,the heat dissipation capacity is greatly improved,and the heat accumulation phenomenon is greatly improved.Through this research,suggestions on the thermal stability of the equipment are provided for the design and manufacturing process of the multi-beam fishing sonar host,and it is proved through heat dissipation simulation and heat dissipation test that a low thermal resistance channel is formed between the heat source and the external environment of the host,The thermal design method of the fishing sonar host proposed in this paper takes into account the installation requirements of the internal structure of the sonar host,fully considers the space utilization and heat dissipation effect,and has a certain pertinence.It guides the multi-beam fishing sonar host to carry out the corresponding structural design.
    January 16, 2023 , DOI:
    Abstract:
    Accurately detecting the content and composition of soil salt during the freeze-thaw period is of great importance for controlling and improving soil salinization, as well as the emergence and growth of crops in the next growing period. Most of the previous studies used spectral data to monitor soil salinity during the crop growing period, when soil is in an unfrozen state. In fact, freezing can change soil reflectance, which may make the monitoring models established at unfrozen state not applicable any more. To explore the feasibility of using hyperspectral technology to establish the inversion model of soil water-soluble salt ions in frozen state, and to compare the accuracy of the model in frozen and unfrozen state, soil samples with different salinity gradients were collected from the Jiefangzha Irrigation Area of Hetao Irrigation District in the Inner Mongolia. The spectra and the contents of major water-soluble salt ions (i.e., HCO3-, Cl-, CO32-, SO42-, K+, Na+, Ca2+, and Mg2+) in frozen soil were measured. The soil samples were then frozen at -15 °C for 12 hours, and the above-mentioned spectra and ion contents were measured again. After selecting the sensitive bands using Standard Normal Variable (SNV) and Variable Importance in Projection (VIP), the hyperspectral inversion model of soil ion content based on characteristic spectrum was formulated by Partial Least Squares Regression (PLSR), Support Vector Regression (SVR) and Extreme Learning Machine (ELM). The results showed that the hyperspectral monitoring model based on the VIP method managed to invert the content of most water-soluble salt ions in frozen soil, but the inversion accuracy of different ions varied a lot. Among them, the prediction accuracy of Cl-and K+ was extremely high, and the Residual Predictive Deviation (RPD) was above 2.5, the prediction accuracy of SO42-, Ca2+ and Na+ was reasonably good (2.0≤RPD≤2.5), but the Mg2+ was poorly predicted, and the HCO3- was even not predictable. Freezing or not did not change the optimal models applicable to different ions, where K+ and Cl- were always best predicted using SVM models, and the other ions were better predicted by ELM models. Among the three regression methods, the ELM model has the highest accuracy, and the PLSR model was the worst. However, freezing resultantly affected the inversion accuracy of salt ions. For the same model, the inversion accuracy of Cl-, SO42-, K+ and Na+ was improved after freezing, but that of Ca2+ and Mg2+ decreased. Among them, Mg2+ was the most affected and the RPD change of each ion optimal model was ranged from -34.45% to 24.43%. The model of water-soluble salt ions in frozen state constructed in this study provides a new way to rapidly diagnosis the salt ions in seasonally frozen saline soil, enabling the monitoring of salt ions throughout the year. In the future, the underlying mechanism of how freezing affects the spectral responses and the inversion of different ions should be systematically explored in the field.
    January 16, 2023 , DOI:
    Abstract:
    It is of great significance to clarify the spatial distribution characteristics of soil salt leaching quota in the leisure period in northwest arid region for the effective utilization of water resources and the prevention of soil salinization. However, due to the spatial variability of soil salinity and texture, the salinity leaching quota obtained at the point scale is difficult to reflect the regional situation. Taking Alar irrigation district of southern Xinjiang as an example, the spatial distribution characteristics of soil salinity and texture in irrigation area were determined by combining statistics and spatial interpolation. By dividing into hydraulic response unit with identical simulation condition, a distributed model based on SHAW model was established to clarify the spatial distribution characteristics of appropriate salt leaching quota under different irrigation modes. The soil salt distribution showed that the soil salt content in Alar irrigation area was larger in the west than in the east, and larger in the south than in the north. The soil texture was mainly silt loam and sandy loam, accounting for about 36.81% and 19.44% of the soil in this area. Soil salinity and sand content are the main factors affecting salt leaching quota. Among the three irrigation modes (only winter irrigation, only spring irrigation, and winter irrigation + a small amount of spring irrigation), the treatment of winter irrigation + a small amount of spring irrigation (20 m3/ mu) combines the advantages of only winter irrigation and spring irrigation. The suitable winter irrigation quota of winter irrigation + a small amount of spring irrigation in the irrigated area is mainly between 100 and 150 m3/ mu, and is the most beneficial option for saving water and crop emergence. This study can provide reference for the optimal allocation of local water resources and for the soil salinization control.
    January 12, 2023 , DOI:
    Abstract:
    In order to study the effects of planting density and regulated deficit irrigation on transpiration, soil evaporation and yield of maize, two planting densities (conventional low density D1 and high density D2) and different irrigation treatments were used in field experiments for three consecutive years from 2017 to 2019 (2017 and 2018 is the maize for seed). The experiment was conducted at the national field scientific observation and research station on efficient water use of oasis agriculture in Wuwei of Gansu Province (102°51′E, 37°52′N). In 2017, four water treatments were set: local irrigation (W1), full irrigation (W2), mild deficit (2/3 of full irrigation per irrigation) in the whole growth period (W3), and full irrigation at silking stage, mild deficit in the rest growth period (W4). Based on the experiment in 2017, the experimental design was adjusted in 2018 with three water treatments: full irrigation (W2), mild deficit (W5) in vegetative growth stage (end of seedling stage, jointing stage), and medium deficit (1/2 of full irrigation amount per irrigation) in vegetative growth stage (W6). In 2019, there were three water treatments: full irrigation (W2), mild deficit at the vegetative growth stage and end of filling (W7), and medium deficit at the vegetative growth stage and end of filling (W8). In 2017, it was border irrigation under film, drip irrigation under film in 2018 and 2019, local irrigation (W1) was irrigated with fixed irrigation amount, and the rest water treatment was irrigated according to soil moisture content. The effects of different planting densities and irrigation treatments on stem flow, soil evaporation between plants, canopy coverage (CC), yield and yield response factors of maize were studied in the experiment. The results showed that the stem flow rate of maize per plant was significantly affected by planting density and water deficit, increasing planting density and water deficit would reduce the stem flow rate of maize, and rewatering could alleviate the decrease of stem flow rate caused by water deficit. Compared with water deficit, planting density has a more obvious effect on CC, and high density treatment has a larger CC. There was no significant difference in soil evaporation during the whole growth period of each treatment. Increasing planting density in all three years of experiments increased yield while decreasing 100-grain quality. Water deficit in the whole growth period obviously resulted in the decrease of yield, while the water regulation deficit in the partial growth period had no significant effect on the yield. At high planting densities, maize plants are more sensitive to water stress, and the same degree of water deficit can cause more severe yield reduction. Compared with local irrigation methods, full irrigation based on soil water content can save 15.09% to 15.99% of water without significant yield change. Increasing planting density under adequate irrigation (W2) increased maize yield by 15.82%, 34.89% and 22.64% in 2017, 2018 and 2019, respectively, compared to low planting density (local density). Compared to local empirical irrigation practices, a mild water deficit treatment (W7) at the late vegetative growth stage and late filling stage of the crop under high density (D2) could save about 23.14% of water with no significant yield reduction. Therefore, increasing planting density and conducting mild water deficit at late vegetative growth stage and late filling stage of the crop can significantly increase yield and reduce water consumption, and the results provide scientific basis for further water saving and yield increase of maize in Northwest China.
    January 12, 2023 , DOI:
    Abstract:
    Seasonal frozen soil regions occupy more than half of China’s land surface, and the freeze-thaw process significantly change soil properties and water and heat transfer process in the vadose zone. Since most of the seasonal frozen regions belong to arid and semi-arid areas, soil is usually in dry condition, and temperature and water vapor have a significant impact on soil moisture in this region. During the past several decades, the significant effect of vapor flow on soil water movement for both freezing and non-freezing periods have been gradually recognized. Conducting the research of coupled water, vapor, and heat transport is not only suitable for actual conditions of seasonal frozen soil regions, but also crucial for revealing the mechanism of soil hydrological cycle. The coupled water, vapor, and heat transport theory was firstly proposed by Philip and de Vries, and they divided the total soil water flux into four components, including the liquid water flux and water vapor flux driven by water potential and temperature gradients, respectively. Since then, extensive researches about the coupled transport have been carried out and related theory are continuously improved. When soil is frozen, liquid water, vapor, and ice coexist in the unsaturated zone. The influence of phase changes between liquid water and ice on the coupled water, vapor, and heat transport is mainly in two aspects. On the one hand, the calculation methods of several hydraulic parameters are significantly affected, such as the soil freezing curve and hydraulic conductivity for liquid water, which are critical for understanding the hydrological cycle process. On the other hand, the spatial and temporal distribution of soil moisture in the vadose zone is dominated by seasonal freeze-thaw process as well. With the variations of soil temperature, the unfrozen water content and ice content change accordingly. Due to the increasing computational capacity and improving simulation accuracy, numerical simulation has gradually become the main approach for related studies. Influenced by the ice-water phase change, the establishment of coupled numerical model faces great challenges. Through reasonable simplification, establishing appropriate coupling model is crucial to numerical simulation. Based on the simulation results by different models, the underlying mechanism of coupled water and vapor flow is gradually revealed. Effected by the relatively low soil moisture and large temperature gradient in the shallow layer, vapor flux become a significant part in soil water movement, usually accounting for 10%~30% of the total water flux. Since the liquid water flow is impeded due to the presence of ice, the importance of vapor flow become more significant during the freezing period. In order to provide scientific basis for deepening the theoretical research and solving the practical problems related to seasonal frozen soil areas, some research interests that needs to be strengthened in this field are put forward. First, since soil water is critical for vegetation growth in fragile ecological areas, the condensation and accumulation of water vapor can help vegetation overcome soil drought and freezing stress and is of great significance for maintaining desert vegetation ecosystem. By coupling the vegetation module with the proposed coupled water, vapor, and heat model, further studies will allow us to explore the specific impact of liquid water and vapor to surface vegetation in seasonal frozen region. Second, the coupled transport of liquid water and vapor affect many engineering construction activities as well, such as frost heave in railway embankments caused by continuous liquid water and vapor transport from deep soil layer. By strengthening in-situ monitoring and simulating research, the detailed process of liquid and vapor transport below the surface impermeable layer can be revealed, thus providing scientific basis for disaster prevention and control during the freeze-thaw process.
    January 12, 2023 , DOI:
    Abstract:
    Global climate change directly affects crop production. As one of the most widely cultivated crops in China, it is important to systematically explore the impacts of future climate change on maize potential yield to ensure high and stable yield of it and food security. We analyzed the changes of agricultural climate resources during the whole growth period of maize in China under climate change, based on the daily meteorological data of SSP126 and SSP585 climate scenarios from 1981 to 2100, the maize phenology data, and the soil data of the agrometeorological observation station of the China Meteorological Administration. We further simulated the potential yield and rain-fed potential yield of maize based on the validated Agricultural Production Systems sIMulator (APSIM-Maize), and analyzed the impacts of future climate change on maize potential yield. The results show that: (1) Under both SSP126 and SSP585 scenarios, the temperature during the whole growth period of maize tended to rise, and the temperature in the north increased higher than that in the South; The ≥10oC effective accumulated temperature (EAT) generally showed an upward trend, and the rise amplitude of EAT under SSP585 was higher than that under SSP126; The interannual fluctuation of precipitation was large, and the overall change trend was not significant. It increased slightly under SSP126 but decreased slightly under SSP585; The total solar radiation increased first and then decreased. (2) Without adaptation measures, the whole growth period, vegetative period and reproductive period of maize were shortened under climate change, and the shortening trend under SSP585 scenario was greater than that under SSP126 scenario. As time goes on, the shortening trend increased significantly. (3) Without adaptation measures, the future climate change reduced the potential yield and rain-fed potential yield of maize. The yield reduction rates under SSP585 scenario were greater than that under SSP126 scenario. The average yield reduction rates of potential yield under SSP585 and SSP126 scenarios were 13.8% and 11.9%, respectively, and the average yield reduction rates of rain-fed potential yield were 17.5% and 14.0%, respectively. Future climate change improved the stability of the potential yield and the rain-fed potential yield of maize slightly, but there were differences between subregions.
    January 12, 2023 , DOI:
    Abstract:
    Reliable streamflow prediction in monthly timescale is of great significance for water resources allocation, flood defense, drought mitigation, and ecological environment protection, especially for streamflow prediction in the long lead time. The changes in streamflow are closely related to precipitation, temperature, evapotranspiration, and antecedent streamflow. Given the flexibility of vine copulas in handling multidimensional variables by decomposing them into pair copula constructions and the superiority of Bayesian model averaging (BMA) in managing multi-model ensemble prediction, we proposed a novel streamflow prediction model by integrating multiple vine copula models with BMA (i.e., Bayesian model averaging ensemble Vine Copula (BVC) model). The streamflow predictions of Tangnaihai, Minhe, Hongqi, and Zheqiao hydrological stations in the upstream of Yellow River basin are selected as the study case. To obtain the corresponding precipitation, temperature, and potential evapotranspiration data at each hydrological station, the spatial average of precipitation, temperature, and evaporation of the watershed controlled by each hydrological station was calculated. For each month, the related hydroclimatic variables (that is, precipitation, temperature, potential evapotranspiration, and streamflow) were first fitted with the best marginal distribution functions from the pool of Normal, Gamma, Weibull, and Log-Normal functions. Vine copulas model was leveraged to couple these variables (incorporated four explainable variables and a predictand variable) under five-dimensional situation. As the streamflow predictions based on the vine copulas model may differentiate for distinct variable ordering, the BMA technology was employed to combine these streamflow predictions based on these candidate vine copula model to reduce the prediction uncertainty introduced by the individual vine copulas model. The Random Forest (RF) model and the Long Short-Term Memory neural network (LSTM) model were adopted as two reference models. At the four hydrological stations, based on the chi-square test, the best-fitted marginal distributions for the precipitation, temperature, potential evapotranspiration, and streamflow were the Gamma, Normal, Weibull, and Log-Normal. The minimum values of coefficient of the determination (R2) (Nash-Sutcliffe efficiency coefficient (NSE)), for the 1–3-month lead streamflow predictions based on the BVC model during the validation period (1963–2006), were all above 0.83 (0.78) and root mean squared error (RMSE) values were sustained at a lower level. In comparison with the RF model, the BVC model can greatly capture the variations of monthly streamflow for these hydrological stations, especially for extreme streamflow (i.e., the streamflow during the driest and wettest seasons, which correspond to the average lowest and highest streamflow of three consecutive months during 1963–2006, respectively). To further evaluate the prediction skills of BVC and RF models for the four hydrological stations in the upstream of Yellow River basin, the precipitation, temperature, potential evapotranspiration, and streamflow time series over the driest and wettest seasons are leveraged. The driest season focused on the January-March period at all four hydrological stations; the wettest season was in the July-September period at the TNH and HQ hydrological stations, while that appeared in the August-October period at the MH and ZQ hydrological stations. Similarly, the streamflow predictions via the BVC model with 1–3-month lead times during the driest and wettest seasons consistently outperformed that RF model for diverse hydrological stations. For the 1–3-month lead streamflow predictions via the BVC model during the driest and wettest seasons, the minimum values of R2 (NSE) all exceeded 0.84 (0.82) at these hydrological stations. Moreover, the BVC model, for the 1–3-month lead times during the validation period (2007–2016), outperformed RF and LSTM models in these hydrological stations on the basis of R2, NSE, and RMSE. Our findings promote the development of theoretical framework in streamflow prediction, and can serve as a guidance for water resources management and risk assessment.
    January 12, 2023 , DOI:
    Abstract:
    As the most prominent ecological environment problem in the Loess Plateau, soil erosion seriously threatens ecological balance and food security, restricts economic and social development, and frequent human activities are drastically changing the spatial pattern of land use in the region. Therefore, it is of great significance to propose a soil erosion prediction method that is easy to evaluate soil erosion in the Loess Plateau under different land use management strategies in the future for soil erosion control and regional coordinated development. In this study, the Jiuyuangou watershed was used as the research object, and the FLUS model was used to predict the spatial distribution pattern of land use in different scenarios in the future. Based on this, the vegetation coverage factor B and the tillage measure factor T in the future scenario were calculated. The CSLE model was used to evaluate the soil erosion status in the historical period ( 2010-2020 ), and combined with the B and T factors in the future scenarios to predict the soil erosion status under different land use change scenarios in 2025. Based on the soil erosion status under different land use change scenarios in the future, the response of different land use types and soil erosion status is analyzed, which provides scientific reference and suggestions for the formulation of future land use management strategies in the watershed. The results show that: (1) The main land use types in Jiuyuangou watershed are grassland (62.23%) and forest land (28.41%), followed by cropland, buildings, and water . From 2010 to 2020, the spatial distribution pattern of land use has undergone great changes, with the area of forest and grassland increasing by 8.36% and the area of cropland decreasing by 30.3%. (2) The average values of soil erosion modulus in the three years of 2010, 2015, and 2020 are 19.49t hm-2 yr– 1, 15.83t hm– 2 yr– 1, and 20.7t hm– 2 yr– 1 respectively, showing a trend of first decreasing and then increasing. The soil erosion modulus of different land use types is cropland (40.56 t hm– 2 yr– 1)>grassland (18.79 t hm – 2 yr– 1)>building (10.25 t hm– 2 yr – 1)>forest land (8.02 t hm– 2 yr– 1). (3) Under the ecological protection scenario, the area of forest and grassland will increase by 1.63% and 5.06% respectively compared with the natural development and economic growth scenarios in 2025, and the area of cropland will decrease by 1.2% and 14.73% respectively compared with the natural development and economic development scenarios. (4) In 2025, the soil erosion modulus under the natural development, economic growth, and ecological protection scenarios of the watershed will be 24.3t hm– 2 yr– 1, 22.9t hm– 2 yr– 1 and 18.3t hm– 2 yr – 1 respectively. Taking an active ecological protection development mode and appropriately expanding the building area can meet the needs of ecological protection and economic development. The research results provide scientific reference for the future land use planning and soil and water conservation management of the watershed and provide a fast and efficient soil erosion prediction method for different future land use scenarios.
    January 12, 2023 , DOI:
    Abstract:
    Nano-selenium, as a kind of new functional nanomaterials, has attracted wide attention from all over the word. Compared with inorganic selenium, organic selenium or elemental selenium, nano-selenium has a lot of outstanding features, including high biological activity, low toxicity, and large surface area. Biosynthetic process is regarded as a relatively efficient and environment-friendly pathway to produce nanomaterials. Our previous study found that Bacillus subtilis subspecies stercoris strain XP, as a biocontrol bacteria strain, not only had strong resistance to selenium or salt, but also had strong ability of transform inorganic selenium with higher toxicity into selenium nanoparticle (SeNP) with higher bioactivity and safety. Furthermore, the strain XP has been confirmed to have higher safety and bioactivity compared to those identified strains. But so far, the SeNP yield from selenite reduction by strain XP metabolism is inefficient, which seriously hinders the wide application of this technology. As we all known, fermentation process parameters have great influence on the selenite reduction and SeNP yield. Choosing appropriate parameters can increase in the SeNP production, as well as reduce the cost of SeNP synthesis. Response surface methodology (RSM) has been considered to be an effective method of process parameter optimization. In this study, the synthesis conditions (e.g., selenite concentration, speed of cultivation, dosage of inoculation) were further optimized to improve the biological efficiency of SeNP synthesis by strain XP. The fermentation conditions were optimized by single factor test, Box-Behnken design (BBD), and response surface methodology. Firstly, the effects of different initial Se (IV) concentrations (1~8 mmol/L) in the culture medium, shaker speeds (120~200 r/min), and the amounts of strain XP inoculation (0.5~10%) on SeNP production were tested by single factor experiment. The production of SeNP increased first and then decreased with gradual increase of initial Se (IV) concentrations. With the shaking speed going up from 120 r/min to 200 r/min, SeNP production also increased first and then decreased. When the inoculum amount of strain XP was between 0.5% and 10%, the yield of SeNP enhanced rapidly along with the increase of inoculum amount. The results showed that each selected experiment parameter had a strong influence on the SeNP production within their scopes: 1~4 mmol/L Se(IV), 120~180 r/min, and 2.5%~10%, respectively. Based on it, the optimal range of each indicator was confirmed. Meanwhile, the above three factors were taken as the influencing factors and SeNP production was used as the response index. Secondly, the Box-Behnken response surface methodology (RSM) was applied to optimize the fermentation conditions of strain XP used for SeNP biosynthesis. Finally, the optimal theoretical value of fermentation condition obtained through response surface experiments were verified by actual experiments. The results indicated that the optimal fermentation condition for SeNP biosynthesis by Bacillus subtilis XP were as follows: initial Se (IV) concentration of 3.4 mmol/L, shaker speed of 157 r/min, and inoculum amount of 9.9%. The SeNP production was 1.82 mmol/L under the optimum condition, which was increased by more than 60% over that under normal condition. Moreover, the seed germination experiment was conducted for confirming the bio-activity of SeNP biosynthesis under optimized culture condition. Application of SeNP could effectively stimulate the Indian lettuce seed vigor and promote the germination process.
    January 09, 2023 , DOI:
    Abstract:
    Rural governance is the cornerstone of national governance. Research on the strategy of rural governance modernization is of great significance to clarify the medium and long-term strategic deployment direction of China's rural governance and help the modernization of national governance system and governance capacity. Based on the perspective of engineering science and technology innovation, this paper scientifically analyzed the strategic needs of rural governance modernization, and analyzed the strategic ideas, key tasks and policy suggestions for China's rural governance modernization enabled by engineering science and technology in detail. The research conclusion showed that China had entered to a new stage of development, and promoting the modernization of rural governance had the engineering science and technology foundation, but at the same time, it was faced with the problems of lagging application of modern governance means, non coordination of governance subjects, low governance efficiency and so on. Facing 2050, in the process of transformation from rural China to urban China, from traditional society to information society, and from an all-round well-off society to common prosperity, it is suggested to focus on the important fields and key links of rural governance such as rural public service, public management, public security and environmental governance, and build a "policy environment support, modern science and technology support, engineering project support and high-quality talent support". Through a series of policy arrangements such as strengthening top-level design, strengthening scientific and technological support, adhering to the guidance of Party construction, highlighting the main body of farmers, exploring business governance and implementing classified promotion strategies, which can help to achieve the goal of modern governance of rural autonomy, rule of virtue, rule of law and intellectual governance under the guidance of Party construction, and supporting the Rural Revitalization Strategy and the realization of common prosperity.
    January 06, 2023 , DOI:
    Abstract:
    Soil salinization is a critical issue which needs to be solved urgently for sustainable agricultural development in arid irrigation districts. Drip irrigation with plastic-film mulching with suitable irrigation regime for water-saving and salinity control can effectively ameliorate soil salinity in crop root zones and then increase crop yields. In this study, based on the maize field experiments, which were conducted under mulched drip irrigation at the Hetao Irrigation District (HID), in the upper Yellow River Basin, the agricultural hydrological process model (Agro-Hydrological & chemical and Crop systems simulator, AHC) was used to simulate the soil salt stress and crop yield corresponding to different irrigation regimes, and in turn to obtain the suitable irrigation patterns of water-saving and salinity control for maize under mulched drip irrigation in saline soils. Results showed that for low saline soils, at the lower limit for irrigation with the matric potential of -20 kPa, the average salt stress coefficient, maize yield, and water use efficiency in the treatment with salt-leaching were respectively 12.4%, 16.9% and 2.2% higher than those in the treatment without salt-leaching. For moderate saline soils, at the lower limit for irrigation with the matric potential of -15 kPa, compared the treatment without salt-leaching, the salt-leaching treatment increased average salt stress coefficient and maize yield by 25.2% and 31.1%, respectively. For high saline soils, at the lower limit for irrigation with the matric potential of -10 kPa, the treatment with salt-leaching could improve the average salt stress coefficient and maize yield by 50.2% and 74.1%, in comparison with the treatment without salt-leaching. In conclusion, mulched drip irrigation at the lower limit of matric potentials of -20 kPa, -15 kPa, and -10 kPa addition to salt-leaching was recommended for maize cultivation in low, moderate, and high saline soils, respectively, in HID. This study can provide scientific implication for soil water and salt regulation and irrigation management in HID and other irrigation districts with similar conditions.
    January 06, 2023 , DOI:
    Abstract:
    Salty peanut is one of our most popular snack foods in China. The raw material characteristics vary considerably between different peanut varieties, with varying degrees of influence on the processing quality of salty peanut. In order to obtain the peanut varieties suitable for processing salty peanut, this experiment was conducted to prepare salty peanut from 14 kinds of peanuts. Then, the peanut raw materials were screened by correlation between the physical and chemical characteristics of peanuts and the processing quality of salty peanut by principal component analysis and cluster analysis. The results showed that the cumulative variance contribution of the 3 principal components of the composite index of salty peanut reached 87.50%, and the top 3 peanut varieties in the composite score were LanShanHongZi , DL123 and SiLiHong. By the cluster analysis, the 14 kinds of salty peanuts can be divided into 3 categories, with the highest combined scores of LanShanHongZi , DL123 and SiLiHong all in the same category. These peanuts are characterised by medium to small peanut kernels, high protein and ash content and medium to high fat content, which can provide a theoretical reference for the selection of raw materials for the processing of salty peanut.
    January 06, 2023 , DOI:
    Abstract:
    Brown rice is a kind of rice grain with only the shell removed and not polished. It retains most of the rice bran layer, germ and endosperm. It has high nutritional value. However, because the brown rice bran layer contains bran wax, phytate and high fiber, the brown rice has some problems, such as compact texture, difficult cooking and rough feeling. Therefore, combined with modern processing technology, preparing brown rice products with good taste and convenient consumption is the key to enhance the value of brown rice and comply with people"s modern fast paced lifestyle and healthy diet concept. Since ancient times, China has a tradition of drinking porridge for health preservation. Instant brown rice porridge is in line with the modern Chinese concept of healthy and fast diet. The twin-screw extrusion method can carry out high temperature, high pressure and high shear on brown rice flour, make its starch gelatinize and protein denatured, and re granulate it into rice type to prepare instant brown rice porridge. In this process, the ratio of amylose and amylopectin of raw materials can be prepared to improve the water absorption capacity of instant brown rice porridge, reduce rehydration time and improve sensory quality. Phosphate modifiers such as sodium pyrophosphate, sodium tripolyphosphate and sodium hexametaphosphate were added to improve the gelatinization temperature and water absorption capacity of rice flour; Reduce the dissolution rate of starch during brewing and improve the sensory quality. High temperature drying can quickly dry the moisture of instant brown rice porridge, form a large number of microporous structures and increase the gelatinization degree. In order to solve the problems of bad taste and inconvenient to eat brown rice. These papers used brown rice and indica rice as raw material. Through twin screw extrusion method and high temperature drying, instant brown rice porridge with excellent sensory quality and short rehydration time was prepared. The effects of screw speed, die temperature, material moisture, compound improver dosage, amylose amylopectin ratio, drying temperature and drying time on sensory score and rehydration time of instant brown rice porridge were studied by single factor experiment. On the basis of single factor experiment, the effects of above seven factors on sensory score and rehydration time of instant brown rice porridge were evaluated and four significant factors (amylose amylopectin ratio, compound improver dosage, material moisture and drying temperature) were selected by Plackett-Burman experimental design. And the results of analysis of variance were intuitively shown by Pareto Diagram. Then, four significant factors were further optimized by Box-Behnken design. The optimum preparation conditions were as follows: amylose amylopectin ratio 0.26, compound improver dosage 0.65%, material moisture 35.4%, drying temperature 165 ℃. Combined with the results of single factor experiment,crew speed is 150 r/min, die temperature is 70 ℃, and the drying time is 60 min. Under these conditions, the sensory score of instant brown rice porridge was 94 and the rehydration time was 5.3 min. The model validation test error is within 2.0%. This indicated that the process model is accurate and reliable. The structural characterization of instant brown rice porridge was analyzed by differential scanning calorimeter (DSC) and scanning electron microscope (SEM). The DSC experimental results showed that compound improver and starch amylose amylopectin ratio could increase the gelatinization temperature and reduce the enthalpy change and made starch more stable and easier to gelatinize. The SEM experimental results showed that Compound improver and starch amylose amylopectin ratio could increase promote the formation of porridge holes, improve its water absorption capacity and shorten the rehydration time of rice porridge.
    January 06, 2023 , DOI:
    Abstract:
    Hot air assisted radio frequency (RF-HA) drying with multistage tempering was applied for post-harvest treatment of rough rice. The effects of RF-HA drying were explored about various parameters such as electrode gap (100 mm, 110 mm, 120 mm), drying temperature (50°C, 55°C, 60°C) and air velocity (0.5 m/s, 1.5 m/s, 2.5 m/s) along with hot air (HA) drying on milled rice quality. In this study, optimal HA-RF drying condition was recorded at electrode gap of 110 mm, temperature of 60°C and hot air velocity of 2.5 m/s. After milling, the head rice yield (HRY), broken percentage, chalkiness, length to width (L/W) radio, percentage of unsound kernels, fatty acid content and degree of freshness were estimated. Results indicated that RF assistance significantly enhanced HRY and degree of freshness while reducing the broken percentage by up to 16.21%, 36.48% and 42.24% respectively, as compared to HA drying. Yellowness, length to width ratio and fatty acid content of RF-HA and HA dried samples were statistically no significant, while chalkiness of RF-HA dried rice was slightly higher than HA dried samples. The research findings are critical for application of RF-HA drying on industrial scale to improve the quality of milled rice.
    January 03, 2023 , DOI:
    Abstract:
    The object detection of Ochotona Curzoniae is the basis to count the population and study the population dynamics. In addition, the object detection model based on deep convolutional neural network requires a lot of sample training.However, the habitat environment of Ochotona Curzoniae is harsh and sensitive to changes in the external environment, so it is difficult to collect images, resulting insufficient training data of Ochotona Curzoniae.The data augmented method based on GAN can generate new object images with the same distribution as the original data set, which can effectively solve the problem of insufficient training data of target detection model. However, when the object image generated by GAN is fused with the background image, the method of adding pixel by pixel or directly replacing pixel to generate a new image will cause the edge of the fused image to protrude, and when the color difference between the fused target image and the background image is large, the object color of the fused image will be inconsistent with the actual scene. To solve the above problems, this thesis proposes an adaptive image fusion data augmentation’s method based on multi-scale gradients for generative adversarial networks. Firstly, object images are extracted from the training samples and used to train MSG-GAN to generate new object images. Secondly, color histogram is used to select object image and background image with similar color adaptively. Then, Poisson fusion method is used to fuse the adaptive object image and background image to get a new image, so that the object boundary of the fused image is smoother and the color difference between the object and background is reduced. Finally, the fusion image is added to the original training set to obtain the augementated training set, and the object detection model is trained. Experimental results of Ochotona curzoniae object detection in natural scenes show that: The average accuracy of the target detection model trained by the data augmentation method proposed in this paper is 89.3% which is higher than the average accuracy of the non-data augmentation method.
    January 03, 2023 , DOI:
    Abstract:
    Rice fields are an important source of agricultural methane emissions. The deletion of applicability assessment of emission reduction technology limited the formulation of accurate carbon reduction policy for regional rice production and the improvement of the “1+N” system of China’s carbon peaking and carbon neutrality strategy. Based on the analysis of rice production status in Hunan and the regional applicability evaluation of Alternate wetting and drying(AWD)methane(CH4)emission reduction technology, this study aims to provide precise cooperative measures for high yield and emission reduction in major rice producing areas in Hunan. The rice production data of Hunan in 2016-2019 and meteorological data of various cities in many years(1960-2017)were collected, and the applicability of AWD technology in Hunan rice area and its weighted CH4 emission reduction potential were evaluated by using the AWD applicability evaluation method based on rice field water balance model and GIS tools. The method assumes that without irrigation, rainfall is the only input water source. Meanwhile, the required data is highly accessible. Therefore, this method has wider applicability. Soil texture is an important factor affecting this method. In the future, more normalized and scientific management are needed in data collection. And the water balance model also needs to be improved by inputting other relevant data. The result indicate that:From 2016 to 2019, the sown area of rice in Hunan showed a downward trend and double-season planting is gradually replaced by single-season planting. The yield per unit area of rice increased steadily, and the annual yield of single-cropping rice was 483.92kg/mu in four years, which was 21.69% and 13.19% higher than that of double-cropping early and late rice respectively. At the city and county level, there was a significant temporal and spatial differences about the applicability of AWD technology. The most suitable city is Zhuzhou to implement AWD measures. This may be due to its low precipitation and high soil permeability. Compared with early rice and single-cropping rice, late rice is more suitable to carry out AWD technology. Rainfall is the key factor to affect the applicability of AWD technology. Less precipitation and higher temperature during late rice in Hunan provide the basis for the implementation of AWD measures. And soil texture is also an important factor affecting the suitability of AWD. Rice soil will form a “hard pan” after some years. The “hard pan” will influence percolation rate compared with other. Therefore, the differences in soil physicochemical properties may also be the reason for the differences. AWD measures have great emission reduction potential(51.16%)in Hunan rice area, Considering the applicability scenario, AWD weighted emission reduction reached 471,300 ton, accounting for 5.29% of methane emission from nationwide paddy fields. In order to ensure the rice supply, implementing dynamic AWD precise control technology according to local conditions is the key measure for low-carbon transformation and high-quality development of rice production in Hunan.
    January 03, 2023 , DOI:
    Abstract:
    Due to the extensive use of chemical fertilizers in agriculture in southern China, the utilization rate of phosphorus is low and the agricultural non-point source pollution is serious. Ecological ditch is an important measure to intercept nitrogen and phosphorus pollution from agricultural non-point sources. Influenced by the characteristics of ecological ditches and environmental factors, the removal efficiency of ecological ditches in different studies varies greatly.Through the literature retrieval platform CNKI and Web of Science, relevant literatures on the migration and transformation process of phosphorus in ecological ditches were collected. After screening under the following conditions (dynamic experiments, outdoor single ecological ditches, etc.),an ecological ditches database was established, which contained a total of 81 experiments and 334 items of data. Statistical analysis showed that the average removal efficiency of TP by ecological ditches was 47.16%. Based on the Mann-Whitney U test and K-W test, the effects of different factors (vegetation type, ditch material type, strengthening measures, climate temperature, hydraulic retention time) on the TP removal efficiency of ecological trenches were analyzed.The results showed that the mean rank of the removal efficiency of TP in the ecological ditches covered with selected vegetation was 170.99,and the average removal efficiency was 47.97%, which was higher than that of the ecological ditches covered with natural vegetation, the mean rank was 132.10, and the average removal efficiency was 38.98%.The mean rank of the TP removal efficiency of the ecological ditches covered with various selected vegetation was 193.69, and the average removal efficiency was 53.93%, which was significantly higher than the values corresponding to single selected vegetation, various natural vegetation, and single natural vegetation type.The mean rank of the TP removal efficiency of the semi-lined ecological ditches was 183.85, and the average removal efficiency was 51.04%, which was higher than that of the whole soil ecological ditches, the average rank of TP removal efficiency was 137.18, and the average removal efficiency was 39.98%.The mean rank of the TP removal efficiency of the semi-lined ecological ditches was 131.31, and the average removal efficiency was 58.22%, which was significantly higher than the values corresponding to the ecological ditches with fully lined slope and the ecological ditches with semi-lined slope and bottom.The mean rank of the TP removal efficiency of the ecological ditches with artificial substrates was 116.12, and the average removal efficiency was 53.53%, which was higher than that of the ecological ditches with interception type.When the climate temperature was between 25 and 35°C, the average rank of the TP removal efficiency of the ecological ditches was 119.85, and the average removal efficiency was 57.18%, which was significantly better than the corresponding values of the ecological ditches at >0~15°C and >15~25 °C. In different hydraulic retention time ranges, the mean rank value of TP removal efficiency for ecological ditches over 24h was 84.80 and the average removal efficiency was 72.12%, which was significantly higher than the mean rank value and average removal efficiency of TP for ecological ditches with hydraulic retention time of >0~12h and >12~24h.The research results of this paper can provide technical support for the assessment of phosphorus interception effect in ecological ditches and the design of ecological ditches.
    January 03, 2023 , DOI:
    Abstract:
    In recent years, diseases and pests have caused a huge loss in agricultural production. Accurate identification of crop diseases and timely protection are important measures to ensure crop yield. Traditional methods of diagnosing agricultural diseases typically depend on the expertise and judgment of specialists. This approach is dependent on human subjective perception, which is prone to error and cannot ensure timeliness. The optimal time to cure agricultural illnesses may be missed by traditional methods, which might result in financial losses. The rise of neural networks and the development of deep learning have brought new technologies to the appraisal of agricultural diseases. However, certain large-scale neural networks cannot be implemented on mobile terminals to accomplish crop disease detection in realistic settings due to the low identification accuracy and a huge number of parameters. To address the problems of large size and low accuracy of traditional crop disease recognition models, we proposed a Lightweight Multi-scale Attention Convolutional Neural Networks (LMA-CNNs) to solve the above problems. First, in order to reduce the number of parameters and make the model lightweight, the main structure of the network adopt depthwise separable convolution; secondly, the residual attention module and multi-scale feature fusion module were designed on the basis of depthwise separable convolution; at the same time, the Leaky ReLU activation function was introduced to enhance the extraction of negative-valued features. The residual attention module enhanced the weight of useful feature information and weakened the weight of interference information such as noise by embedding channels and spatial attention mechanisms, and improved the recognition of important features by the network model. Residual connections could effectively prevent network degradation. The multi-scale feature fusion module use its convolution kernels of different scales to extract disease features of multiple scales, which improve the richness of features. The experimental results showed that the accuracy of the LMA-CNNs model on the test set of 59 types of disease images was 88.08%, and the number of parameters was only 0.14×107. Through comparative experiments, the LMA-CNNs model outperformed ResNet34, ResNeXt, ShuffleNetV2, MobileNetV3, and the more popular Vision Transformer recently. This study also further verified the effectiveness of the LMA-CNNs model by comparing the network models designed by different researchers under the same dataset. Comparative experiments showed that the LMA-CNNs model reduced the number of model parameters on the premise of improving the accuracy. Because of the problem of poor interpretability of the neural network model, this study used Grad-CAM to visualize the features extracted by the middle layer of the model and explained the model through the visualization results to obtain different feature information on different convolutional layers. As the number of layers increased, the LMA-CNNs model paid more attention to the diseased area. In summary, the LMA-CNNs model could extract more disease feature information, better balanced the model complexity and model recognition accuracy, and provided a reference for mobile crop disease recognition. In the future, we will continue to optimize the algorithm, then deploy the model to the mobile terminal to detect crop diseases in real field scenarios, and improve detection accuracy and efficiency.
    December 16, 2022 , DOI:
    Abstract:
    Climate change has significantly changed the heat resources and spatial distribution of Spring Maize in Inner Mongolia, and has an impact on the water demand and yield of spring maize. Based on 113 meteorological stations and statistical crop coefficient values in Inner Mongolia, this paper analyzes the spatial changes of accumulated temperature (≥ 10 ℃) and spring maize cultivation mode (early maturing, medium early maturing, medium late maturing and late maturing) under the background of climate change, calculates the effective rainfall and crop water demand in spring maize growth season, and analyzes the impact of climate change on spring maize yield. The results are as follows: 1) from 1959 to 2018, the accumulated temperature in Inner Mongolia showed an increasing trend. From 2009 to 2018, the accumulated temperature increased by 307 ℃ compared with 1959-1968, and the accumulated temperature contour shifted significantly. The boundary line of spring maize with different maturity types moved northward and expanded eastward obviously, and the Spring Maize in the Middle East changed from unsuitable planting area to early maturing type and Medium Maturing type. 2) From 1959 to 2018, the effective rainfall during the growth period of spring maize was 114mm, showing a downward trend as a whole. The crop water demand is 481mm, showing a significant increasing trend as a whole. The coupling degree between crop water demand and effective rainfall and groundwater recharge is between 0.02 and 0.40, showing a downward trend as a whole. 3) Among the meteorological factors, the temperature showed an upward trend, and the other factors mainly showed a downward trend. Stepwise regression analysis showed that rainfall was the main factor affecting the yield of Spring Maize in this area. This study can provide a reasonable basis for the spatial layout of spring maize and the allocation of water resources in Inner Mongolia.
    December 16, 2022 , DOI:
    Abstract:
    In the China Pakistan Economic Corridor, which is the pilot and key area of China's "the Belt and Road" initiative, extreme precipitation events are the main cause of frequent floods. Therefore, it is necessary to carry out research and analysis on extreme precipitation events to promote the effective risk management and the smooth implementation of China's "the Belt and Road" strategy. In this paper, the daily precipitation data set of 0.25°×0.25° of CPEC was used to identify extreme precipitation events from three aspects, such as intensity, area and duration, and by analyzing the correlation between the three-dimensional characteristics of IAD envelope of extreme precipitation events, the change trend of extreme precipitation in China Pakistan Economic Corridor over the years was analyzed. The results showed that: 1) There were significant differences in the duration of extreme precipitation in different regions, which could also show that the extreme degree of precipitation in different regions were different. 2) From 1961 to 2013, the annual average temperature in the study area increased at the rate of 0.415 ℃/10a, and the annual precipitation in China Pakistan Economic Corridor showed a fluctuating upward trend; 3) The frequency of extreme precipitation events had obvious double peaks within one year. The dry and rainy seasons from February to April and July to August were the high incidence periods of extreme precipitation events, accounting for 68.8% of the whole year. The number of extreme precipitation events fluctuated and increased year by year, but the increasing trend was not significant; 4) The single impact area of extreme precipitation events lasting for 1d showed an obvious upward trend, the other events were in a fluctuating state, while the trend was not obvious, and the impact range of extreme events was further expanding with the passage of time; 5) At the same time, the relative intensity of extreme precipitation events lasting for 1d had an obvious increasing trend, and the relative intensity of extreme precipitation events lasting for 3d was also increasing, but not obvious. The relative intensity of events lasting for 5d and 7d had no significant trend and fluctuates. On the whole, the intensity of extreme precipitation events increased. 6) In contrast, the impact area of extreme precipitation events lasting for 1 day was the largest, while the average impact area was about 1.5 times that of other time scales and the event intensity was the smallest. The correlation coefficient between extreme precipitation event intensity and impact area was 0.47 for 1d, 0.58 for 3d, 0.49 for 5d and 0.47 for 7d. It could be seen that the intensity area relationship of extreme precipitation events in the case of continuous 3d could better reflect the relationship characteristics of extreme events, which was more representative. The continuous 3d rainfall could be used as an important index for risk assessment of extreme precipitation events. This paper is helpful to enhance the understanding of the temporal and spatial distribution law of extreme precipitation events in China Pakistan Economic Corridor in different durations, and will play a great guiding role in the natural disasters caused by extreme precipitation events and provide a scientific basis for the research and prediction of precipitation in the Indus River basin to a certain extent.
    December 08, 2022 , DOI:
    Abstract:
    The demand for accurate and real-time detection of meat adulteration has been gradually high. However, the existence of mutton flavor essence and dye makes the detection more difficult than before. To realize the classification of mutton adulteration, a residual network (ResNet) model based on Convolutional Block Attention Module (CBAM) combined with inverted residual (Invert) was proposed. Meanwhile, a fast and accurate classification application software was also developed based on smart phones. Firstly, a method called Hough circle detection was used to remove the background of original mobile phone images of mutton, three parts pork and adulterated mutton. The data augmentation methods such as rotation, offset and mirroring were used to expand the sample images and 6800 images were acquired. In this study, two thirds of the images were used as the training dataset and testing dataset. Furthermore, the training dataset was three times larger than the testing dataset. Then the remaining third were used as the independent validation dataset. Secondly, the original residual structure of residual network framework was replaced by inverted residual structure to reduce the number of network parameters and accelerate the convergence speed. At the same time, CBAM was introduced into the inverted residual structure to strengthen the feature difference by redistribution of the feature weights in the spatial and channel. Then the proposed convolution neural network (CBAM-Invert-ResNet) was developed based on the samples data. Furthermore, the MobileNet and resnet50 were also developed based on the same data for comparing the convergence speed and accuracy. Finally, the CBAM-Invert-ResNet network model was transplanted to mobile phones by TensorFlow Lite framework and Android Studio development environment to realize the mobile terminal classification. The results showed that the the CBAM greatly enhanced the feature difference among different categories, while the inverted residual significantly reduced the parameters and size of the network so that the convergence speed was accelerated. The parameters of CBAM-Invert-ResNet50 model is 10.02×106, and the model size is 19.11MB. which were reduced by 57.52 % and 57.43 % compared with the ResNet50 model, respectively. The convergence speed of CBAM-Invert-ResNet50 model was more faster than that of ResNet50 model. The mutton, adulterated mutton and pork of feature visualization using ResNet50 have very little difference. However the three meats of that using CBAM-Invert-ResNet50 model have obvious differences in color. The classification accuracies of CBAM-Invert-ResNet50 model for pork adulteration with loin, hind shank, fore shank and mixed parts wrere 95.19 %, 94.29 %, 95.81 % and 92.97 % in validation dataset, which were improved by 5.61%、2.57%、13.59% and 2.58% compared with the ResNet50 model, respectively. Compared with MobileNet, the classification accuracies of CBAM-Invert-ResNet50 model improved by 12.44, 9.6, 13.73, and 4.87 percentage points, respectively. Moreover, the application software using the CBAM-Invert-ResNet50 model was developed to quickly and accurately classified mutton, pork and mutton adulteration with different pork. The detection time of each picture was about 0.3 s in the mobile terminal. This method realized the rapid and accurate classification of mutton adulteration with pork under the effect of mutton flavor essence and dye. The study provides technical support for maintaining market order and ensure food safety.
    December 08, 2022 , DOI:
    Abstract:
    Taking the new apple variety ‘Venus Gold’ as the test material, the fruits of three harvest periods (the growth and development period were 185d, 192d, and 199d respectively) were treated with the control CK group with a concentration of 0 μL?L-1and a concentration of 1.0 μL?L-1 of 1-MCP group treated with postharvest senescence and quality changes at room temperature (20±0.5)℃. The results showed that harvesting at the right time (harvest stage II) could effectively inhibit the postharvest physiological metabolism of ‘Venus Gold’ apple fruit, and maintain higher fruit firmness and quality; early harvest (harvest stage I) fruit the firmness remained high, but the SSC and Vc were relatively low; the SSC of the late harvested (harvest period III) fruits remained high, but the firmness, TA and Vc decreased rapidly in the middle and late storage period, and the storability was poor. The effect of 1-MCP treatment on fruits is closely related to the harvest time. During 25 days of normal temperature storage, there is no significant difference in the mass fraction of Vc of fruits in harvest I and SSC of fruits in harvest III of 1-MCP treatment and CK, but 1-MCP can significantly maintain SSC and the mass fraction of Vc of fruits in harvest II in the middle and late stage of storage. Compared with CK, 1.0 μL?L-1 1-MCP treatment (hereinafter referred to as 1-MCP treatment) could significantly (P< 0.05) reduce the ethylene release rate and respiratory intensity of fruits at the third harvest, and significantly inhibit or delay the respiratory peak and ethylene peak. From harvest to the end of storage, 1-MCP treatment had no significant difference with CK in starch content, amylase activity, cellulose mass fraction, cellulase activity, malondialdehyde content and hydrogen peroxide content of early harvest (harvest stage I) and late harvest (harvest stage III). However, 1-MCP treatment could maintain high fruit hardness and protopectin content in three harvest stages, and significantly delay the rise of soluble pectin content and PG enzyme activity. It can significantly inhibit the increase of amylase activity, cellulase activity, malondialdehyde content and hydrogen peroxide content, delay starch transformation and cellulose decomposition, so as to better delay the softening and senescence of fruits in harvest II. Comprehensive analysis showed that ‘Venus Gold’ apples in Rongcheng area were harvested in period II (harvested on November 10, and could be harvested 2-3 days later) combined with 1.0 μL?L-1 1-MCP treatment with the best storage and preservation effect, suitable for long-term storage can not only effectively delay fruit softening and senescence, but also maintain high fruit quality.
    November 21, 2022 , DOI:
    Abstract:
    Ecological protection and restoration of territorial space is an important guarantee for maintaining national ecological security patterns, and scientific zoning and manage the key areas for protection and restoration is of great significance to maintain regional ecosystem function and sustainable development. Taking Shanghang County in Fujian Province as a typical study area case, this study constructed a multi-dimensional ecosystem measurement framework of "Ecosystem Importance - Ecosystem Fragility - Ecosystem service value" based on integrating ecosystem integrity, systematisms, and ecological benefits. And then, we analyzed the multi-dimensional characteristics of the regional ecosystem and the relationship of trade-offs and synergy between measure factors. At last, spatial clustering method (Grouping analysis) was used to delineate the ecological protection and restoration space, and the zoning management and control strategies were proposed based on the spatial heterogeneity and ecosystem structure characteristics of each zone. The results showed that: 1) The ecosystem has strong spatial heterogeneity, showing a spatial differentiation ecosystem pattern with high importance, low fragility, and high service value in Shanghang County. 2) There were synergistic and tradeoff relationships among all ecosystem measure factors in study area. The relationship of comprehensive importance, fragility and service value are all synergistic, which may lead to high overlap between ecosystem conservation and restoration areas. 3) According to the results of CONTAG and COHESION index with different number of clusters, 6 was determined as the optimal number of clusters, indicating that the cohesion degree and connectivity among groups in the study area were the strongest, which was conducive to the stable and healthy development of the ecosystem. The study area can be divided into six zoning: III-I-V(Importance level III- Fragility level I-Value V), III-III-V(Importance level III- Fragility level III-Value V), III-II-V(Importance level III- Fragility level II-Value V), III-III-IV(Importance level III- Fragility level III-Value IV), II-III-I(Importance level II- Fragility level III-Value I) and IV-I-I(Importance level IV- Fragility level I-Value I), the zoning of III-I-V and III-II-V have large areas and are the ecosystem functional bases for regional development. The composition of land cover types in each zoning has obvious spatial heterogeneity and the forest, shrub, cropland, and garden were the dominant land cover types. 4) According to the characteristics and spatial distribution and internal structure of each zoning, we proposed targeted and differentiated ecological and economic management policies and environmental protection and restoration measures. The study area was further divided into ecological protection area (Ecological conservation area, green development area, Moderate development area) and ecological restoration area (Ecological restoration area, Protection and restoration coordinated development area) according to the ecological protection and restoration measures. The multi-dimensional ecosystem measurement "I-F-V" aims to identify important ecosystems, damaged areas of ecosystems and integrate ecosystem services benefits. While considering the integrity and systematisms of ecosystems, it also emphasizes the coordination of ecosystem protection and restoration costs and development opportunities. It effectively assesses the resilience and sustainability of ecosystems and the economic activities and human well-being they support, which can be widely used in ecosystem measurement and ecological conservation and restoration research and practice. The research results would provide scientific and comprehensive research ideas and practical reference for regional planning and construction of territorial space protection and restoration planning and construction, ecological security pattern maintenance.
    November 16, 2022 , DOI:
    Abstract:
    Water, energy and food are indispensable resources in terms of human life and development, the shortage and matching dislocation of water resources and energy can hinder the growth rate of food production to a certain extent. In this paper, Lorentz curve and Gini coefficient are used to evaluate the matching degree between water-grain and energy-grain in the Yellow River Basin. Based on Cobb-Douglas function, the grain growth damping model is applied, and the restriction degree of water resources and energy on grain production in the Yellow River Basin is calculated. The results show that: 1) The Gini index of water resources and energy to grain in the Yellow River Basin has decreased first and then increased, and the matching degree of which in the lower reaches of the Yellow River is more reasonable than that of the upper and middle reaches. In 2019, the Gini index values of water resources to grain in the Yellow River Basin and the upper, middle and lower reaches were 0.365, 0.379, 0.336 and 0.122 respectively, while the Gini index values of energy to grain were 0.194, 0.218, 0.206 and 0.118 respectively, it indicated that the matching degree of water resources and energy to grain show high matching status in the lower reaches. The water resources and energy in the upper and middle reaches are generally matched with grain. 2) The damping coefficient of water resources to grain production fluctuates greatly in the Yellow River Basin, and the variation range of damping coefficient is 0.005~0.032. Besides, the damping effect of water resources on grain growth basically presents a 6-year cycle with a decrease-increase-decrease situation. While the damping effect of energy on grain shows a steady increase situation, and the energy damping coefficient increased rapidly after 2015. Under the constraints of water resources and energy in 2019, the annual grain output growth in the Yellow River Basin reduced by 0.76% and 5.28% respectively compared with the previous year. 3) The damping effect of water resources and energy has a certain degree of agglomeration, the damping coefficient of water resources in the Yellow River Basin presents the situation of small in the West and large in the East. The energy damping effect presents a medium and high constraint state, which is concentrated in the eastern and lower reaches of the upper reaches, and the low constraint state is concentrated in the middle reaches of the Yellow River. In addition, the damping coefficient of water resources and energy in the Yellow River Basin has typical spatial agglomeration characteristics. The H(High)-H(High) agglomeration area of water resources damping effect is mainly distributed in the lower reaches of the Yellow River, the L(Low)-L(Low) agglomeration area of energy damping effect is distributed in the northern part of the middle reaches. It is hoped that this study can have a certain reference basis for the stable growth of grain and the effective allocation of resources in the Yellow River Basin.
    October 27, 2022 , DOI:
    Abstract:
    Wheat stripe rust and wheat yellow dwarf have posed a great threat to the yield and quality of wheat. Early identification of these two diseases has important implications for the prevention and control of wheat diseases. Drought, nutrient deficiency and bacterial disease can lead to chlorosis and yellowing of plant leaves. These phenotypic symptoms are similar to infected leaves of wheat stripe rust and wheat yellow dwarf. In addition, the infected leaves of these two diseases are similar to healthy leaves because of indistinct phenotypic symptoms in the early stage of diseases. It is difficult to quickly and accurately distinguish them by existing identification methods. In this study, an improved Faster Regions with CNN Features (Faster-RCNN) disease identification method was proposed. There are two improvement strategies in our proposed method. Firstly, in order to enhance the fine feature extraction capability of the entire network and reduce the number of model parameters, three 3×3 grouping convolutions and down-sampling delay were employed to optimize the Deep Residual Neural Network (ResNet-50), which was designed as the backbone feature extraction network. Secondly, ROI Align was employed instead of ROI pooling to reduce the feature error problem caused by double quantization. It is helpful to solve the difficult problem of distinguishing subtle differences. Meanwhile transfer learning was employed to improve the training speed of the model and data augmentation was utilized to reduce over-fitting problems, which can further enhance recognition performance and generalization ability of our method. Experiments were carried out on a self-built data set of disease leaf images covering more than 200 wheat varieties showing different resistance and susceptibility to diseases while covering various symptoms at different disease stages. Performance indicators such as loss function convergence curve and mean mean precision (mAP) were selected to evaluate the effectiveness of the improved strategy. The experimental results showed that the mAP of the improved Faster-RCNN identification method proposed in this paper was 9.26% higher than the SSD, 7.64% higher than the YOLO, and 14.97% higher than the Faster-RCNN. The mAP of our proposed method reached 98.74% for wheat stripe rust, wheat yellow dwarf, healthy wheat and wheat with other etiolation symptoms. Moreover, in order to predict the diseases as early as possible, the early identification of disease infection was strengthened in this study. Our dataset contains 683 and 630 mild symptom photos of these two diseases respectively. The mAP for mild and severe symptom identification of these two diseases reached 91.06% by utilizing our proposed method. In addition, the value of the loss function decreased faster, as well as model performed better overall. Finally, In order to implement the deployment and application of our proposed method, the intelligent recognition system of wheat disease was developed, and WeChat applet was used to identify wheat diseases in the field. Under the condition of maximum concurrent access of 100, the average return delay was 5.024 seconds, and the success rate of recognition return was 97.85%, and the average accuracy of the recognition of two kinds of wheat diseases and their subdivision was 93.56%. The system can effectively meet the practical application requirements and be employed to guide the scientific prevention and control of diseases.
    March 14, 2022 , DOI:
    Abstract:
    Abstract:Planting area of fruit trees in Xinjiang accounts for about 13% of the national planting area, which is the main fruit trees producing area in China. With the help of suitable climate condition and resource advantages, the four prefectures of Southern Xinjiang around the Tarim River Basin have become the main producing area of Xinjiang specialty fruit (e.g. walnut, jujube, apricot, fragrant pear and apple). The fruit planting area here accounts for more than 80% of the total fruit planting area in Xinjiang. Real-time and accurate acquisition of fruit tree type and area information under the pattern of forest and crops interplanting is significance to improve the quality and efficiency of specialty fruit industry in southern Xinjiang. It will be conducive to improvement local farmers’ income, stabilize the achievement of poverty alleviation and promote rural revitalization. This study is to take the continuous area of forest and crops interplanting in Hotan Oasis of southern Xinjiang as an example. It proposes a method for extracting the structure information of fruit trees that integrates high-resolution remote sensing image data with abundant texture and spectral characteristics and medium-resolution sensing image data with multi-temporal characteristics. Firstly, it used object-oriented methods to extract high-precision boundary of fruit trees parcel based on GF-2 (PMS) image data. The classification rules of GF-2 image data are divided into winter (February) and summer-autumn (July-September). By analyzing Normalized Difference Vegetation Index (NDVI), spectral characteristics and texture feature information between target objects and other ground objects, it identified the correspondence between feature information and ground objects, and the classification of four plots was obtained by gradually eliminating non-target ground categories. Then, it constructed NDVI time series products based on multi-temporal Sentinel-2 image data, and established a decision tree model based on the characteristics of phenology to extract interplanting walnut orchard, pure walnut orchard, jujube orchard and grape orchard. The NDVI time series of fruit trees was analyzed, and it found that NDVI time series curve had many peaks and troughs in one year. The peak would represent the flourishing period of fruit trees growth, and the trough reflected the orchard management (such as irrigation and pruning branches). Although the NDVI timing series of pure walnut, interplanting walnut, jujubes and grapes are rarely staggered and overlapping, there are still obvious and different time windows. These differences contribute to the fruit trees classification. Finally, the multi-phase orchard classification results were overlay the high-resolution of fruit trees parcel to obtain the distribution of fruit crops in Hotan Oasis. The research results show that the area of major fruit was 4.29×105 hm2 here, with 3.31×105 hm2 of walnut orchard (including interplanting and pure walnut), 8.29×104 hm2 of jujube and 1.40×104 hm2 of grapes.The area of interplanting walnuts accounts for 63.8% of total fruit area,followed by jujube (19.38%) and grapes (3.3%). The user accuracy and overall classification accuracy are both exceed 90%, and the Kappa coefficient is 0.95 which would meet the accuracy requirements of agroforestry classification at the county and city level. Compared with the forestry survey results in 2019, the relative accuracy of walnuts jujube and grapes based on remote sensing extraction results was 62.1%, 97.8%, and 85.2%, respectively. The results show that the area of jujube and grape based on remote sensing extraction is close to the forestry survey datas. The walnut planting areas in Hotan area are mainly distributed in the upper reaches of Yurunkax River and Karakax River with suitable soil and water conditions. The jujube trees are mostly distributed in the downstream oasis desert ecotone and the grapes are mostly distributed in the sandy desert of lower reaches of Karakax River,. This method could provide valuable reference for the research of fruit tree type extraction under the pattern of forest and crops intercropping.
    May 12, 2021 , DOI:
    Abstract:
    Wolfberry (Lycium barbarum) is a traditional Chinese medicinal and edible plant. It contains a variety of functional ingredients and has various functional activities such as anti-aging, immune regulation and anti-atherosclerosis. Hubei hybrid wolfberry is a researcher who induced and doubled Ningxia wolfberry, and then crossed it with the local wild wolfberry in Hubei, and was later introduced to Jianshi County, Enshi Prefecture. It has become one of the important industries in the local poverty alleviation. Compared with Ningxia wolfberry, Hubei hybrid wolfberry has a higher moisture content. The previous study found that it is not suitable for processing into traditional dried wolfberry products. It is urgent to develop new processed wolfberry products to improve the conversion rate of Hubei hybrid wolfberry and the economic benefits of the industry. Using lactic acid bacteria to ferment characteristic fruits can not only give the product a unique flavor, but also transform or increase the types and content of active substances in it, and improve the nutritional value and health benefits of the product. However, there are few reports on the effects of different lactic acid bacteria fermentation on the nutritional quality of wolfberry juice. Therefore, this study used Hubei hybrid wolfberry as raw material and used 6 kinds of lactic acid bacteria (Lactobacillus plantarum, Streptococcus thermophilus, Lactobacillus acidophilus, Lactobacillus rhamnosus, Lactobacillus casei and Lactobacillus fermentum) for fermentation. The physicochemical properties, main active components and antioxidant activity in vitro of wolfberry juice before and after fermentation were studied. And establish a method to comprehensively evaluate the quality of fermented wolfberry juice using principal component analysis, in order to select the most suitable lactic acid bacteria strain for wolfberry juice fermentation. The results showed that the 6 kinds of lactic acid bacteria could grow well in wolfberry juice, which the viable count can reach above 10.0 Lg CFU/mL. After fermentation, the total sugar and reducing sugar content in the juice is significantly reduced (P <0.05). Lactobacillus plantarum and Streptococcus thermophilus has better acid production capacity, and the total acid content had 6.74 g/kg and 6.07 g/kg. Compared with unfermented wolfberry juice, the total phenol content in wolfberry juice fermented by Lactobacillus plantarum, Streptococcus thermophilus, Lactobacillus rhamnosus and Lactobacillus fermentum increased by 13.76% to 28.07%, while there was no significant difference in the content of total phenols in goji juice fermented by Lactobacillus acidophilus and Lactobacillus casei (P>0.05). And the total flavonoids content increased by 55.80% to 161.97% after fermentation. The antioxidant activities of fermented wolfberry juice were also significantly improved (P<0.05). Correlation analysis results show that the increase in antioxidant activity is significantly related to the content of total phenols and total flavonoids. Based on principal component analysis, three principal components were extracted, covering three levels of fermentability, nutritional quality, and functionality. They comprehensively reflect the quality of fermented wolfberry juice. The cumulative variance contribution rate is 82.344%. The comprehensive score ranking shows that the quality of wolfberry juice fermented by Lactobacillus plantarum and Lactobacillus fermentum is better, and they are suitable as a starter for developing high-value green processed beverages of wolfberry.
    May 12, 2021 , DOI:
    Abstract:
    Abstract: Solar greenhouse has been widely used in China, and improving the heat storage and release ability of the rear wall of solar greenhouse has always been a research hotspot. The application of PCM in solar greenhouse wall can effectively improve the heat storage and release performance of the wall. Three PCM walls were studied in this experiment. First we tested three kinds of phase change materials in laboratory ability of heat accumulation of single block cement module. The heat storage per unit volume of F1 cement module increased from 6.4℃ to 35℃ is 92.6MJ/m3; the temperature of F2 cement module increased from 7.6℃ to 35℃,the heat storage per unit volume is 102.1MJ/m3; the temperature of F3 cement module increased from 8.3℃ to 32°C,The heat storage per unit volume is 95.1MJ/m3. The temperature of F1 cement module decreases from 35℃ to 5.4℃ and the heat release per unit volume is 75.8MJ/m3; the temperature of F2 cement module decreases from 35℃ to 5.9℃ and the heat release per unit volume is 92.5MJ/m3; the temperature of F3 cement module decreases from 32℃. The heat release per unit volume to 7.8°C is 84.2MJ/m3. Under sunny conditions in winter, the heat storage per unit area of the 0.08mF1 wall is 4469.0kJ/m2; the heat release per unit area is 2343.2kJ/m2; the heat storage per unit area of the 0.08m thick F2 wall is 4571.0kJ/m2. The heat quantity is 3214.6kJ/m2; the heat storage per unit area of 0.08mF3 wall is 4830.7kJ/m2, and the heat output per unit area is 3960.9kJ/m2. Compare with the heat storage and release performance of other wall materials. The heat storage per unit area of the 0.6m thick soil wall is 3357.2kJ/m2, and the heat release per unit area is 811.7kJ/m2. When the wall thickness is only about 14% of the soil wall, the heat storage performance of F1, F2 and F3 is better than 0.6m soil wall, the gap is obvious, 0.08m F1, F2, F3 phase change material cement module unit The area heat storage is 1.3 times, 1.4 times and 1.4 times that of the 0.6m soil wall; the heat release performance gap is even greater. The 0.08m F1, F2, F3 phase change material cement module emits 2.9 heat per unit area of 0.6m soil. 2.9 times, 4.0 times and 4.9 times the wall. The 0.48m red brick wall stores 5490 KJ of heat per unit area during the day and 2140kJ/m2 of heat per unit area. The three types of heat output per unit area also have huge advantages. Therefore, we applied the phase change material cement module to the solar greenhouse on a large scale. The total area accounts for about half of the wall area. The results show that the phase change material wall absorbs a large amount of excess heat inside the greenhouse during the day on a sunny day in summer. F1 The wall absorbs a total of 35614.8KJ of heat, the F2 wall absorbs a total of 72788.4kJ, and the F3 wall absorbs a total of 57153.6kJ; the three absorb a total of 165556.8kJ and emit 72718.8kJ at night; summer is cloudy, the F1 wall totals Absorb heat 1,2589.2KJ, F2 wall absorbs a total of 24310.8kJ, F3 wall absorbs a total of 22338.0kJ; the three absorb a total of 5,9238.0kJ, and emit 37809 kJ at night; on sunny days in winter, the phase change material wall absorbs during the day Heat, the three absorb heat 203158.2kJ and release a lot of heat at night, F1 wall releases a total of 36442.8KJ heat, F2 wall releases a total of 49993.2kJ heat, F3 wall releases a total of 51333kJ kJ of heat, and releases heat at night 137769kJ; On cloudy days in winter, the phase change material wall absorbs heat during the day. The three absorb heat 117,069kJ and release a large amount of heat at night. The F1 wall releases a total of 1,7035.2KJ, the F2 wall releases a total of 37260kJ, and the F3 wall releases a total of 37260kJ. The heat is 49542kJ kJ, and the heat is 103837.2kJ at night.Applying phase change materials to sunlight greenhouses, with the aid of natural ventilation measures in summer, can absorb a lot of heat, effectively reduce the temperature peak of the greenhouse, and release a lot of heat in winter to increase the night temperature of the greenhouse. This also provides new ideas and solutions for improving the greenhouse environment and regulating temperature.
    February 24, 2021 , DOI:
    Abstract:
    In order to explore the pyrolysis characteristics and synergy of single and mixed samples of corn stalks and municipal sludge, based on thermogravimetric analysis, at different heating rates (10℃/min,、20℃/min, and 30℃/min), the Corn stalks, municipal sludge and their mixed samples (mass ratio 9:1, 3:7, 5:5, 7:3, 1:9) were used for thermogravimetric test, and Coats-Redfern integration method was used to study kinetic characteristics . The results show that the difference in pyrolysis characteristics of corn stalks and municipal sludge is large, the residual rate differs by 18.57 percentage points, the comprehensive pyrolysis index differs by 35.73×10-05, and the activation energy E differs by 35.31kJ/mol~46.88kJ/mol. With the content of municipal sludge from 10% to 90%, the initial pyrolysis temperature decreased from 360.3℃ to 440.3℃, the main pyrolysis interval of mixed samples became longer from 277.7~360.3℃, and shifted to the high temperature zone. The residual rate increased from 33.69% to 45.83%, the maximum weight loss rate decreased from 7.88%·min-1 to 3.11%·min-1, and the comprehensive pyrolysis index decreased from 8.5×10-05 to 1.7×10-05. It shows that the municipal sludge improves the pyrolysis starting temperature of mixed samples, but at the same time it also widens the pyrolysis interval, increases the residual rate, slows the weight loss rate, and decreases the comprehensive pyrolysis index. The comprehensive pyrolysis index (D) of mixed samples is lower than the corresponding theoretical value to varying degrees, indicating that the co-pyrolysis of the two has an inhibitory effect. The activation energy required for the individual pyrolysis process of corn stalks is greater than the activation energy required for the individual pyrolysis process of municipal sludge. The activation energy E of corn stalks and municipal sludge under different heating rates showed that increasing the heating rate increased the activation energy of the low temperature section and the high temperature section to different degrees. As the proportion of municipal sludge increased from 10% to 90%, the pyrolysis activation energy decreased from 66.01~46.16kJ/mol to 44.47~17.04kJ/mol. The research provides theoretical basis and technical support for the effective utilization of corn stalks and municipal sludge.
    January 26, 2021 , DOI:
    Abstract:
    In order to realize the real-time on-line detection of grain protein content and record the sampling geographical location information during combine combine-harvester harvest grain, an in-line detection system of grain protein content based on the principle of near-infrared spectroscopy was developed, which was mainly composed of near-infrared spectral sensor module, spiral sampling and conveying mechanism, control module, GPS/Beidou positioning module, industrial display integrator, etc. When the grain combine-harvester near-infrared spectral protein content in-line detection system was working, when the grain discharged by the combine-harvester grain outlet was through the spiral sampling and conveying mechanism, the stepper motor of the sampling mechanism was controlled by the controller according to the detection rate requirements and intermittent grain transmission, the controller system also controls the near-infrared spectral sensor to sample the spectral when the stepper motor stops turning, and the data such as the grain near-infrared spectrum and the positioning signal of GPS/Beidou positioning module were transmitted to host computer by RS485. The control and data processing analysis software of near-infrared sensor and sampling mechanism was compiled, and the grain protein, sampling location information, etc. were displayed and saved in real time after the grain protein prediction model. In order to verify the performance of grain protein content prediction model and online detection system, indoor calibration and field system dynamic testing were carried out, and the decision coefficient of wheat protein content prediction model was 0.865, the absolute error range was -0.96 to 1.22, and the relative error range was -7.30% to 9.53%, the root mean square error of prediction(RMSEP) was 0.638, the decision coefficient of the rice protein content prediction model was 0.853, the absolute error range was -0.60 to 1.00, the relative error range was -8.47% to 9.71%, and the RMSEP was 0.516. The results of the system dynamic field test shows that the maximum relative error of wheat protein content was -6.69%, the maximum error of rice protein content was -8.02%, the system was not significantly affected by sampling and analysis interval, and the system stability and detection accuracy meet the need of grain protein online detection in the field, which provides a scientific basis for precision agricultural operation.
    January 26, 2021 , DOI:
    Abstract:
    The aim of this study was toevaluate the effect of fermentation conditions on the cumulative esterase activity of Oenococcus oeni(O.oeni) autochthonous strains in Hexi Corridor region, and influences in the aromaticesters of Chardonnay dry white wine during the malolactic fermentation(MLF). Two O.oeni autochthonousstrains GF-2, ZX-1 were identified and preserved by Gansu Key LabViticulture and Enology and one commercial strain VP41 were used to test strains. The esterase activity of different carbon chain length substrates (C2, C4, C6) were detected in the simulated wine during MLF process.To analyze and compare the effects and characteristics of different fermentation conditions (initial pH value, ethanol concentration, SO2addition and fermentation temperature) on the production of esterase by the O.oenistrains. The modification effect of the tested strains on the aroma quality of Chardonnay dry white wine was studied by microvinification experiment. The esterase activities of O.oeni autochthonousstrains were significantly higher than that of commercial strainVP41under different pH values, and the maximum esterase activity of ZX-1 was about 63.42% higher than that of VP41. When the concentration of ethanol was 8%, all the tested strains produced the maximum esterase activity, and theO.oeni autochthonous strain hadstronger esterase producing ability. Underthedifferent SO2additions, the cumulative esterase activities of two O.oeni autochthonous strains were significantly higher than that of VP41 (P<0.05), and the esterase activity of GF-2 was significantly higher than that of strain VP41 at 18 ℃ and 22 ℃ (P<0.05) .Results of compound fermentation showed that the total esterase activity originatedfrom ZX-1 was the highest, followed by GF-2and VP41.Although the major and secondary factors affecting the esterase activity of each strain were different, the optimum conditions for esterase production of all tested strains were ethanol concentration 12%, pH 3.6, SO2addition 30 mg/L and fermentation temperature 22 ℃. The highest esterase activity of ZX-1 was 620.973 mU/mL,which indicatedthat ZX-1 had strong adaptability towine habitat.The analysis of microvinification of chardonnay dry white wine showed that six esters (amyl acetate, heptyl acetate, ethyl 3-hydroxybutyrate, ethyl myristate, ethyl trans-2-hexenoate and ethyl trans-4-decenoate) were identifiedin the wine samples after MLF, and two aromaticesters (isoamyl lactate and octylformate) were onlydetected in the wine samples fermented by O.oeni autochthonous strains. Compared with commercial strain VP41, thewines fermented by autochthonousstrains GF-2 and ZX-1 have rich variety aroma and good fragrancepersistence. Both O.oeni autochthonous and commercial strains can successfully complete MLF, especially ZX-1 has strong esterase production capability and is significantly affected by fermentation conditions, which can effectively improve the content of fruit and floral aroma compoundsin Chardonnay dry white wine, significantly enhance the regional microbial terroir characteristics of wines. The O.oeni autochthonous strain ZX-1 is more suitable to be used as MLF starter of dry white wine in Hexi Corridor of Gansu Province.
    November 04, 2020 , DOI:
    Abstract:
    The use of recycled manure solids (RMS) as dairy bedding material has become a promising technology with the merits of sustainable manure management and cost saving for purchasing traditional bedding. However, cow dung contains certain amounts of pathogenic bacteria, thus the use of RMS would increase the risk of direct contact of pathogens with cows’ udder. Such serious problem has undermined the use of RMS as dairy bedding material. Drum fermentation for the bedding production has many advantages (i.e. high temperature, short time), thereby it is getting more and more attention. The objective of this study was to investigate the stability and biological safety of RMS production process using drum fermentation in different seasons, and to clarify the factors affecting the growth of pathogenic bacteria in the dairy cows’mastitis. The drum-type RMS producing system employed was composed of a two-stage solid-liquid separator, a horizontal-rotation drum fermentation tank, as well as feeding and discharging components. The automatic control system monitored equipment operation and temperature changes in real time. The drum temperature was obtained by the temperature sensors installed on the inner wall of the drum including inlet, center, and outlet. Samplings were performed from the inlet, 1/3, 2/3, and outlet of the drum. The plate culture method was used to detect the main mastitis pathogenic bacteria (i.e., Eschrichia coli, Staphylococcus aureus, Streptococcus, and Klebsiella) at different positions within the drum during the summer and winter. At the same time, the physical and chemical properties (water content, pH, total carbon, total nitrogen, ash, particle size distribution, roller temperature) of RMS were also tested. Additionally, the main factors affecting the growth of mastitis pathogens was investigated via Pearson correlation analysis.The results indicated that the fermentation temperature during the production process was stable and maintained above 65 oC both in summer and winter, and the final moisture content at the drum outlet was less than 45%. In both seasons, the particle size distribution at different positions of the roller was mainly concentrated at 0.5 mm to 2.0 mm. With the fermentation process, the large particle size gradually converted to small and medium particle size. The number of mastitis pathogens in summer and winter was highest at the drum inlet, and gradually decreased at higher fermentation temperature. At 1/3 of the drum, the number of major mastitis pathogens was significantly reduced. Streptococcus. and Klebsiella. were not detected at the drum outlet in both seasons. However, the number of Eschrichia coli and Staphylococcus aureus at the outlet of the drum in summer was about 3 lgcfu/g higher than that in winter. It may be related to the moisture content of the cow dung at the inlet of the drum. Therefore, the moisture content of the inlet of the drum should be strictly controlled between 50% and 65%. Using the Pearson correlation analysis, it was found that the major factor affecting main mastitis pathogen was drum temperature, followed by total carbon. From the security point of view, RMS should be used immediately after production to avoid environmental impacts. The results found in this study can provide deep insight for the application of drum fermentation technology to produce safer RMS.
    October 21, 2020 , DOI:
    Abstract:
    To promote the development, automation, and standardization of Chinese cuisine, it is necessary to carry out a systematic and in-depth study so as to obtain the inherent principles of heat transfer and the corresponding quality changes during the cooking process. Chinese stir-frying is one of the most distinctive and widely used cooking method, and numerical simulation is the only way to study the heat transfer process of food particles during the Chinese stir-frying. In order to study the mechanism of heat and mass transfer and the changes of maturity and quality of food particles during the Chinese cuisine process, a heat and mass transfer model including multiphase coupling phase transition and shrinkage was developed to simulate the Chinese stir-frying process of food hygroscopic porous medium based on the porous media theory, Fourier's law, Newton's cooling law, and Darcy's law. The non-equilibrium evaporation formulation, shrinkage formulation, energy, momentum and mass conservations of water, and gas governing equations were considered in this model and it was finally solved using finite element method. The temperature history, moisture content, and volumetric shrinkage rate of the Chinese stir-fried pork loin were used as comparations to validate the model accuracy. The results indicated that the accuracy and robust properties of this model was greatly increased after considering the shrinking process. To reveal the mechanisms of heat and mass transfer inside food particle, water evaporation rate of particle surface, volumetric shrinkage rate, pressure variations, moisture content and temperature distributions were all simulated for Chinese stir-frying process. The simulation results showed that the water loss, which was induced by strong convection heat transfer, was the main reason for shrinkage. The moisture loss rate and volumetric shrinkage rate were increased by the surface evaporation rate, and the particle internal pressure was affected by volumetric shrinkage.Since the volumetric shrinkage rate was similar to water loss rate, the moisture content and shrinkage were associated as an important indicator for evaluating cooking quality of food particles. Additionally, the heat transfer efficiency of particles was greatly enhanced by shrinkage because of the increasing surface area to volume ratio. The shrinkage could be used to improve the overall moisture content of food particles if evaluated from the perspective of cooking quality optimization. Combined with the maturity value theory, the effect of controlling methods of “Huohou” on the maturity and quality of food particle were further explored in this study. The simulation results indicated that the increase of the efficiency of heat and mass transfer and internal heating rate, and the decrease of average moisture content were mainly affected by the finer cutting technique of food particles, the higher preheat oil temperature, and the more vigorous stirring operations. The food particles could reach its maturity values before the average moisture content rapidly decreased under the appropriate “Huohou” controlling. Thus, the average time of food particles reaching cooking maturity termination was significantly decreased. “Huohou” controlling exhibited a significant (P <0.01) effect on the cooking quality and could bring significant advantages for obtaining food particles with better cooking quality.
    September 15, 2020 , DOI:
    Abstract:
    Technology of straw bale combustion is one of the effective ways to realize the clean utilization of agricultural residue, which has aroused widespread concern. In this paper, the latest research progress of straw bale combustion was reviewed, the reaction principle and combustion characteristics of straw bale combustion were described, the generation and emission of particulate matter in the process of straw bale combustion were analyzed, such as NOx, CO and particle. And the research progress of straw bale combustion types, principles and characteristics were systematically summarized. According to the technical characteristics and heating scale, we divided straw bale combustion into two types, one was continuous bale combustion, which can realize continuous feeding and ash cleaning in the combustion process, maintain a stable combustion state in the combustion chamber, and was suitable for the central heating area with large heating area, that mainly included cigar-bale combustion and reciprocating grate combustion. The other was sequential batch combustion technology, which had advantages in small floor area, simple and convenient operation, usually used for small heating mechanism, and it included forward combustion technology and reverse combustion technology. Based on the global literature search, the research hotspot, institutions and development trend of straw bale combustion were analyzed. The running cost of straw baled heating was evaluated. It was found that the straw bale combustion has the characteristics of simple heating process and low operation cost. The operation cost was 19.8 yuan/m2, which was suitable for the industrialization promotion of clean heating in villages and towns. Straw bale combustion technology had gradually attracted the attention of scientific researchers. Developed countries in Europe had made some progress in the field of straw bale combustion, such as combustion mechanism, boiler structure, reduction of flue gas emission, etc. And at present, the research of combustion technology had focused on flue gas emission reduction and environmental impact assessment. The existing straw bale combustion technology still has some problems, such as insufficient combustion, unclear generation mechanism of flue gas pollutants, higher NOx and particle emission. It was suggested that we should pay more attention on research of pollutant emission characteristics, and it is encouraged to reduce the generation of flue gas pollutants from the source.
    August 05, 2020 , DOI:
    Abstract:
    National policies promote the rapid development of electric vehicles, agricultural vehicles are becoming more and more electric. In general, when the battery is used as a power supply, a lot of heat will be generated. In addition to the more complex working conditions of agricultural vehicles and the compact layout of battery packs, it is inevitable to cause the thermal accumulation of batteries, resulting in the battery temperature exceeding the optimal operating temperature range and damaging the battery. At this time, an appropriate thermal management strategy is needed to control the battery temperature and make it work within a reasonable temperature range. Therefore, based on the principle of phase change heat transfer and pump-free circulation, a power battery thermal management system with cooling or heating functions is presented. Taking ternary lithium batteries as the research object, the two-way working modes of thermal management system were tested under cooling or heating conditions. Under the cooling condition,The cooling capacity of the two thermal management systems under natural convection cooling and forced convection cooling conditions was studied when the initial temperature of the battery box was 40, 50, 60 and 70 ℃. And for the thermal management system two, the influence of the inclination angle on its heat dissipation and temperature uniformity was studied. Under the heating conditions, the heating capacity of two thermal management systems was studied, and then for the thermal management system two, the initial temperature of different batteries and the heat exchange uniformity of the thermal management system two were studied. The results show that the system can realize the operation switching management of cooling and heating two-way modes based on high or low temperatures. In other words, the switch of thermal management can be realized by controlling the opening and closing of the valve at the right temperature. The test results show that, under the cooling condition, thermal management system two provides better heat transfer, It can also be interpreted as the heat dissipation capacity of the heat exchanger plate with four vertical tubes is stronger than that of the single serpentine tube, compared with natural convection, forced convection on the condenser side can increase the heat transfer power of system 1 by 10% ~ 44.2%, and system 2 by 20% ~ 48.6%; when the temperature of the battery box is 60℃, the maximum temperature difference of the heat exchange plate of the natural convection heat dissipation system is less than 2℃, and the maximum temperature difference of the heat exchange plate of the forced convection heat dissipation system is less than 1℃; at an initial battery temperature of 25°C and a discharge rate of 1C, 2C, and 3C, forced convection heat dissipation at the end of discharge can reduce the average temperature of the battery box by 2.1, 3.9, and 4.7°C, respectively. Under the heating condition, the power of the battery box in many groups of experiments is consistent. Considering the tilting effect of the heat exchanger plate in the vehicle driving, it is restricted by the flow distribution of the working fluid, and the temperature uniformity is better than the heating condition in the heat dissipation condition.
    April 17, 2020 , DOI:
    Abstract:
    The mechanical properties of gypsum board was low, and cannot be used as load-bearing materials in construction. Plant fibers can be employed as the reinforcement to increase the mechanical properties of the gypsum board, but the improvement increment on the mechanical properties was limited because of the addition of gypsum retarders during the preparation of general particle-gypsum composites. The gypsum retarder solution deteriorated the morphology of gypsum crystals, and the gypsum crystals became shorter and wider, and then the overlapping area decreased among them. The general particle-gypsum composites still cannot be used in structural application. In order to increase the mechanical properties of the particle-gypsum composite, a two-step preparation process including pre-forming molding and moisture-curing was proposed in this study. The particle-gypsum composites with different MUF content and the particle/gypsum ratio was prepared, and the physical and mechanical properties was tested. The effects of melamine-urea-formaldehyde (MUF) content and the particle/gypsum ratio on mechanical properties of the particle-gypsum composites were analyzed by one-factor experiment. The results in the present study were compared with the requirements in three product standards and that in the reported literatures. The test results showed there was a positive relationship between the MUF content and the mechanical properties of the particle-gypsum composites, and the particle/gypsum ratio had a slight impact. The mechanical properties of the particle-gypsum composites with 15% and higher MUF content met the requirements of Standard LY/T 1598 (2011), and the values, except longitudinal modulus of rupture, were in accordance with the requirements of Standard LY/T 1580 (2010) when MUF content was 21% and above. The mechanical properties of the particle-gypsum composites reached E5.0-F16.0 grade according to the Standard GB/T 35216 (2017), when 33% and higher MUF content was used. The curves of bending load with deformation of gypsum boards exhibited linear elastic behavior due to the brittleness of gypsum crystals. All particle-gypsum composites in bending tests exhibited obvious non-linear behavior before the maximum load was reached, and the failure was ductile. The strengths of the composites in the present study were all higher than that in the reported literatures. Therefore, the particle-gypsum composites can be used as structural boards in construction. Based on the combination of mechanical properties and costs, the performance of the particle-gypsum composites with 33% MUF content and a particle/gypsum ratio of 0.30 were better, and the internal bond strength, modulus of rupture, modulus of elasticity, displacement ductility coefficient and 24 h thickness swelling of the particle-gypsum composite were 1.28 MPa, 16.5 MPa, 7350 MPa, 1.64 and 1.23%, respectively. After the new preparation process was employed, the mechanical properties of the particle-gypsum composites were increased greatly due to the increase of the strength of the gypsum continuous phase and the obvious improvement of the interfacial bonding strength between the particle reinforcement and the gypsum continuous phase. The microscopic images by Scanning Electron Microscope indicated that gypsum crystals in particle-gypsum composites were slender, when the new preparation process was employed. The gypsum crystals interlaced among them, and the contact area of the gypsum crystals was increased greatly with the increase of MUF content. Therefore, the gypsum continuous phase was strengthened. The amount of the gypsum on the surface of the wood particles was significantly increased with the increase of MUF content due to the bonding performance of MUF resin.
    March 25, 2020 , DOI:
    Abstract:
    In order to make full use of solar energy and improve the energy efficiency of solar heat pump system, an energy storage solar heat pump water heating system with inserted oscillating heat pipe is proposed, which integrates solar collector, energy storage tank and oscillating heat pipe together reasonably and effectively. The system can store solar energy with the phase change materials (PCM) filled in solar collector, transfer heat efficiently by oscillating heat pipe and switch operation mode according to solar radiation, and can realize the maximum utilization of solar energy in different seasons. In summer, enough heat is transferred or stored during the day to release at night by PCM in solar collector, which is directly used to heat the circulating water through the oscillating heat pipe heat exchanger. In winter, the heat transferred or stored during the day to release at night by PCM in solar collector is low, and the heat is transferred to the heat pump evaporator by the oscillating heat pipe heat exchanger to improve the evaporation temperature of the heat pump, and thus the overall performance of the system is improved. A test rig has also been established for the performance measurement of energy storage solar heat pump water heating system with inserted oscillating heat pipe. Paraffin is chose as phase change material of the system under the consideration of capacity, phase change temperature and latent heat of phase change. Experimental study has been carried out for two years under winter conditions in Nanjing, one year for the test rig without PCMs and another year with PCMs. Under similar environmental conditions (solar radiation intensity, fluctuation and ambient temperature), the variations of the instantaneous collecting efficiency, average collecting efficiency, COP (coefficient of performance) and water temperature of the system filling or not filling PCM with the fluctuation of solar radiation are compared and studied. The comparison and experimental results show that in winter daytime under similar solar radiation intensity, fluctuation and ambient temperature, the instantaneous collecting efficiency fluctuation with PCM is 61.5% less than that of the system without PCM, which can overcome can overcome the instantaneous influence of the fluctuation of solar radiation intensity on the system. And the average collecting efficiency with PCM is 25% higher than that of the system without PCM. At winter night, under similar operation conditions, COP of the system filled with PCM is over 3.0, which is nearly twice as high as that of the system without PCM, and make water temperature reach 50℃ in a shorter time, shortening the time by more than 20%. The results can provide theoretical basis for the popularization and application of solar energy heat pump system.
    October 16, 2019 , DOI:
    Abstract:
    Column chromatography is based on the difference of physicochemical properties of each component in the mixture. The mixture is separated and purified after multiple distributions by using the different distribution coefficients of each component in the stationary phase and mobile phase. The starch was hydrolyzed by amylase after retrogradation under high pressure and humidity. The hydrogen bond of retrograde starch was opened in alkali solution to dissolve the retrograde starch, and the solution was adjusted to neutral next. Amylose with narrow molecular weight distribution was obtained by adding n-butanol to the precipitate. While, amylopectin with narrow molecular weight distribution was prepared by adding ethanol to the supernatant. In order to narrow the molecular weight distribution of amylose and amylopectin in sweet potato furtherly, column chromatography was used to separate them respectively. The results show that the artificial zeolite with 1-3 mm particle size is suitable for the separation of amylopectin, while artificial zeolite with 4-6 mm for amylose. After separated by column chromatography, the yields of both amylose and amylopectin were more than 2.4% respectively. In the course of separation, amylose with higher DP adsorbed on the macrozeolite surface. It was eluted out from the mixture first for the weaker adsorption force. Amylose with lower DP entered into the small holes of macrozeolite, and was eluted out subsequently for the stronger adsorption force. When separated by small zeolite column chromatography, the amylopectin components of F1b with small molecular weight and high homogeneity were eluted out first. While, amylopectin components F2b with large molecular weight and low homogeneity were eluted out first, indicating that the branching degree of amylopectin also played a certain role in the separation of starch components by zeolite column chromatography. X-ray diffraction showed that there were strong peaks of amylose components at the diffraction angles (2??? of 18.9°, 23.4°, 27.2°, 29.3°, 32.3°, 33.8°. There were obvious peaks of amylopectin components at around 21.6°, 22.9°, 23.9°, 26.5°, 27.1°, 29.3°, 34.1°, 35.8°, 39.5°. The molecular weight distribution index (PDI) of sweet potato amylose was close to 1.0 at the same time. Sweet potato amylopectin with extreme narrow molecular weight distribution can be prepared by artificial zeolite column chromatography. These kinds of starch exhibits X-ray diffraction peaks similar to metal salts, which can be used as materials to study the spatial structure of starch macromolecule in depth. Micrographs showed that amylose was composed of many linear molecules and presents typical linear “wicker-like” morphology, while amylopectin showed “branch-like” shape. The results provide a simple and efficient method for the preparing of amylose and amylopectin with extreme narrow molecular weight distribution. It brings about favorable conditions for further exploring morphological changes of starch macromolecules during aggregation progress.
    October 16, 2019 , DOI:
    Abstract:
    Vinegar plays an important role in our daily diet. Solid-state fermentation of vinegar using reactors has several advantages over the traditional methods, which include shorter fermentation process, and good controlled working environment. In order to fully understand the dynamic changes of main components and flavor compounds during the solid-state fermentation of vinegar in rotary drum reactor, samples were taken throughout the fermentation process. Alcohol, total acid, reducing sugar, amino nitrogen, organic acid and volatile flavor in the process of vinegar fermentation were studied by high performance liquid chromatography, solid-phase microextraction, and gas chromatography-mass spectrometry. Meanwhile, principal component analysis was carried out to explore the difference of volatile flavor in vinegar at different fermentation stages. The results showed that the fermentation process can be divided into three stages: starch saccharification, alcohol fermentation, and oxidation of ethanol to acetic acid. The alcohol content increased rapidly within 0-4 days of fermentation, then decreased gradually to zero until the end of fermentation. The total acid content showed a sharp increase tendency first, followed by a slight increase at the late stage of fermentation. The reducing sugar content decreased rapidly at first, then gradually increased during acetic acid fermentation, and finally gradually decreased. The amino nitrogen increased rapidly at first, followed by a gradual decrease at the end of fermentation. Seven organic acids were detected in our research, including acetic acid, lactic acid, oxalic acid, succinic acid, tartaric acid, citric acid, and malic acid. Among them, acetic acid and lactic acid were the main organic acids in the whole fermentation process. The lactic acid content increased rapidly first, and became the dominant organic acid in the alcohol fermentation stage. Then it showed a gradual decrease until the end of fermentation. For acetic acid, a gradual increase tendency was observed during the whole fermentation process, which accounted for 64.87% of all the organic acids contents. Compared with those, the content of other organic acids was less, and the variation during fermentation was relatively small. These organic acids were also crucial for the formation of characteristic taste of vinegar. A total of 64 flavor volatile substances were detected, including 25 esters, 12 alcohols, 6 acids, 5 phenols, 5 aldehydes, 6 ketones and 5 heterocyclic compounds. The principal component analysis results showed that the most dominant ones responsible for volatile flavor in the early, middle, and later stage of fermentation were alcohols, esters and aldehydes, and acids, respectively. Other volatile compounds, such as aldehydes, phenols, ketones, heterocycle, were present in small amounts during vinegar fermentation based on the reactor. However, they also play a vital role in the formation of special flavor for vinegar. This is the first report to study the dynamic changes of vinegar quality during fermentation process based on a reactor. The results would enhance our understanding of the fermentation property of rotary drum solid-state fermentation vinegar reactor, which may be helpful for the improvement and effective management of reactor to promote its industrial application.
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    2010,26(11):1-7, DOI:
    [Abstract] (32974) [HTML] (0) [PDF 0.00 Byte] (9769)
    Abstract:
    The problems and challenges for agricultural water management are markedly different from 50 years ago. To meet the increasing global demand for food, new challenges have been coming: increasing farmers’ income, boosting rural economy, reducing poverty, adapting climate change and protecting the ecological environment, under the conditions of the scare water resources. Therefore, the improvement of strategies and countermeasures relevant to the development of agricultural water management is nessary starting from the thinking of interdisciplinary and various sectors. The strategies include that developing water-saving agriculture, maintaining the service functions of the ecological system, increasing investment in irrigation, promoting rain-fed agriculture, improving and increasing water productivity, reducing poor population, preventing and alleviating the degradation of land and water environmental quality, reducing the risk in waste water irrigation, and strengthening policy and institution building. The efforts in improving agricultural water management and increasing agricultural productivity depend on the rational selection of the above strategies and the benefit tradeoffs.
    2013,29(14):203-209, DOI: 10.3969/j.issn.1002-6819.2013.14.026
    [Abstract] (27007) [HTML] (0) [PDF 392.78 K] (6832)
    Abstract:
    Abstract: The arable land per capita among the rural migrants located in the Three Gorges Reservoirs Area is only about 386.7 m2. The contradiction between people and their land is severe. After the impoundment of the Three Gorges Project, the water flow and the self-purification ability of the Yangtze River got slowed and declined which resulted in an overmuch growth of the green algae in main tributaries of the Yangtze River. Besides, to meet the electricity generation need in the dry winter or spring, and to prevent the deluge in the rainy summer, the Three Gorges Reservoir impound in the winter and spring, disembogue in the summer. Owing to this, the hydro-fluctuation belt along the river always outcrop into land in the hot and humid rainy summer, hence the hydro-fluctuation belt fail to intercept, absorb and filtrate the agricultural surface source pollution, which cause the increased pollution in the Yangtze River. The contradiction of the economic development and the environmental protection is severe.This research considered the Three Gorges Reservoir Area, the hydro-fluctuation area and the ecological barriers area as an entirety, and combined the specialty agriculture industries, such as: citrus, livestock and fishing industry with the newly developed agricultural technologies, like the orange residue self-drying and high temperature fermentation under aerobic environment technology along with its dedicated organic fertilizers, the biogas slurry pipeline irrigation fertilization integrated device, citrus nutrition diagnosis testing fertilization technology and the new variety of submergence-tolerant pasture, on the basis of the principles of ecological agriculture and recycling economy. A recycling agriculture ecosystems demonstration area was built in the Dachang town, Wushan county, the hinterland of the Three Groges. Relying on the greening the Yangtze River citrus belt project, the hydro-fluctuation belt management project and forced removal of the cage fish culture facilities along the river project, we build three ecological economic zones which are reservoir bank citrus plantations, hydro-fluctuation belt wetland pastures and natural fishery around the reservoir bank to develop specialty industry economy.In this project we integrated "pig-biogas-fruit-residue-feed", "fruit-residue-fertilizer", "livestock-biogas-fruit-grass" and water cycle, developing a new four-chain crossed recycling economy networking mode, and an anti-season hydro-fluctuation area ecologically recycling agriculture progression mode. By using the farming manure as the fertilizer and the irrigation water of the citrus, and using the waste of citrus processing or hydro-fluctuation belt pasture as the feedings of the livestock, we established a system that using the waste of the previous level as the production resource in current level. Due to this system we set up a citrus, pigs, grazing livestock, Yangtze fish and other specialty industrial that industrial symbiosis, coupling elements, the overall recycling and comprehensive utilization of industrial ecological chain in the very area. Also by building biogas project, citrus barrier forest, cut flood engineering, wetland pastures and fishery as 5-layer intercept network, we can block, absorb and digest the area source pollution. With this project we are able to increase the vegetation coverage of the reservoir bank, the income of the migrants and protect the environment of the Three Gorges Reservoirs Area.The established specialty recycling agriculture ecological demonstration area in Dachang Lake, Wushan county will cover the core area of 135 hm2. The 2 km long hydro-fluctuation area will be fully covered by the pasture and the cover ratio of the forest will be over 80 percent. The whole area will be fully covered by plants, and those wastes like farming excrement, waste straw, citrus residue will be completely reutilized and achieve the accomplishment of zero emission. Besides, the citrus yield in the demonstration area will be about 30 tons each hectare and the yield of pasture will be about 33 tons each hectare, which means that the output value per hectare will be over 150,000 Yuan. This area is showing the possibility that increasing the migrants' income and purifying the Yangtze River synchronously.
    2007,23(5):150-153, DOI:
    [Abstract] (21244) [HTML] (0) [PDF 0.00 Byte] (8363)
    Abstract:
    Apple storage quality properties(including hardness, moisture, soluble solid, total acid) were estimated through the mechanical properties of apple(including the maximum of compression, the yield force, the elastic modulus). An artificial neural network model of storage quality properties was built by the optimization algorithm of L-M(levernberg marquardt) BP neural network. The mechanical properties and the apple storage quality properties measured in the experiment were adopted as input and output to establish the BP neural network. The simulated results show that this neural network make a good estimation of apple storage quality properties through mechanical properties. When tested by five groups of Non-sample data, the relative error between the estimation of this model and the measured value is below 5%, which meets the accuracy requirement of apple storage quality properties in engineering application.
    2007,23(2):1-5, DOI:
    [Abstract] (18231) [HTML] (0) [PDF 0.00 Byte] (6085)
    Abstract:
    In the research of the soil erosion and soil losses, the runoff velocity of slope is an indispensable hydrodynamic parameter in the runoff computation and the soil erosion forecast. There is still no special instrument which is widely used to measure runoff velocity. It is very significant to construct a fast measurement instrument on runoff velocity. On the basis of correlation theory, the runoff velocity measurement system was established based on virtual instrument LabVIEW. The system uses the conductance sensor to acquire signal. Effect of the space between conductance sensors on the measurement system and the runoff velocity under five sediment concentrations were studied. Results indicate that the suitable sediment concentration scope of the measurement system is 0~250 kg/m3 and the greatest relative error of the system is 4.5%. While taking the flow velocity measured by the dye tracer technique as standard value to correct the correlation velocity, the greatest relative error of the proved velocity reduces to 3.81%.
    2016,32(1):46-53, DOI: 10.11975/j.issn.1002-6819.2016.01.006
    [Abstract] (17901) [HTML] (0) [PDF 5.12 M] (4201)
    Abstract:
    The application of the path tracking technology on agricultural vehicle makes the robot replace farmers for field operation, and the accuracy, production efficiency and dependability about farming automation are improved effectively.Meanwhile the labor time, labor intensity of drivers and the production cost are saved.The path tracking of agricultural vehicle was studied in an operating condition, and a variety of sensors were installed on the car features of the external environment.Then it generated a four-element in state space by the target path which was given for controling the agricultural vehicles to track the target path automaticly according to the theory of optimal navigation control.The location method of GPS/INS was selected, the navigation system was developed, and the experiment was finished in 2014.According to the needs of automatic walking positioning system, a variety of sensors has been chosen, including the inertial sensor, angle sensor and GPS sensor.Then the serial program was writen to collect the signal from the sensors and calibrate them.In order to meet the requirements of vehicle navigation system, the positioning system with low cost and high precision was developed.The hardware of the system consisted of two GPS modules, two Zigbee wireless transmission modules and an inertial sensor.The data from the sensors are filtered and fused, and finally accurate, reliable vehicle position data was got.The tracking controller based on preview control was designed to obtain the future values and target values of the vehicle.With the target path and its curvature, the feed forward control value was got.There was an error between the current state and the state of vehicle target path that was needed to use LQR for elimination.The performance of the path following controller was simulated by Matlab, then the maximum lateral error was 0.16 m and 0.27 m at the speed of 0.5 m/s and 1 m/s respectively.The results showed that the control method was feasible.The steering control system was designed based on steer-by-wire(SBW) after the study of vehicle navigation control principle.SBW removed out mechanical connection between steering wheel and steering front wheel.It used motors to control front wheel angle and simulated force characteristic.Compared with traditional steering system, SBW had characteristics of ideal steering ratio and active steering control according to vehicle state parameters, and improved safety of driving and handling stability.The strategy of BLDCM was designed in order to make actual front angle follow the desired angle better.PID control and sliding mode variable structure control were applied in strategy of BLDCM and the result of simulation showed that sliding mode variable structure control was better than PID control.This paper designed the electronic control unit of SBW based on chip of MC9S12XET256, mainly including peripheral circuit of MCU, CAN communication circuit, drive circuit of BLDCM, power circuit, signal acquisition and processing circuit, current sampling circuit of motor.Based on the requirement of joint simulation, we designed a bench test for control strategy and hardware, software of ECU in 2015.The results of test bench showed that angle correction was similar with the result of simulation and sliding mode variable structure control was better than PID control in following front angle.Finally, the vehicle steering control test and the vehicle path tracking control test were carried out based on vehicle test platform, which was built personally.The vehicle path tracking system was based on the Windows platform, using Microsoft Visual Studio as the development environment.The integrated navigation system was validated and the test data showed that the integrated navigation system had a high positioning accuracy and the steering system had a reliable tracking performance.The final navigation and positioning accuracy of integrated navigation system was around 0.1 m to 0.5 m and the response speed of the whole system was about 0.1s .The results proved that the system could meet the requirements of agricultural vehicle path tracking control system.
    2019,35(18):143-150, DOI: 10.11975/j.issn.1002-6819.2019.18.018
    [Abstract] (17660) [HTML] (0) [PDF 3.96 M] (6218)
    Abstract:
    Rosa roxburghii is widely distributed in warm temperate zone and subtropical zone, mainly in Guizhou, Yunnan, Sichuan and other places in China. Panxian and Longli are the most abundant the most varieties and the highest yield Rosa roxburghii resources in Guizhou. The harvesting of Rosa roxburghii fruit is the most time-consuming and labor-consuming work in Rosa roxburghii production, and its labor input accounts for 50%-70% of the production process. Hand-picking of Rosa roxburghii fruit is of high cost, high labor intensity and low picking efficiency. In recent years, convolutional neural network has been widely used in target recognition and detection. However, there is no relevant literature on the application of neural network in Rosa roxburghii fruit recognition. In this paper, in order to realize rapid and accurate identification of Rosa roxburghii fruits in natural environment, according to the characteristics of Rosa roxburghii fruits, the structure and parameters of VGG16, VGG_CNN_M1024 and ZF network models under the framework of Faster RCNN were optimized by comparing them. The convolutional neural network adopted bilinear interpolation method and selected alternating optimization training method of Faster RCNN. ROI Pooling in convolutional neural network is improved to ROI Align regional feature aggregation. Finally, VGG16 network model is selected to make the target rectangular box in the detection result more accurate. 6 540 (80%) of 8 175 samples were selected randomly as training validation set (trainval), the remaining 20% as test set, 80% as training set, the remaining 20% as validation set, and the remaining 300 samples that were not trained were used to test the final model. The recognition accuracy of the network model for 11 Rosa roxburghii fruits was 94.00%, 90.85%, 83.74%, 98.55%, 96.42%, 98.43%, 89.18%, 90.61%, 100.00%, 88.47% and 90.91%, respectively. The average recognition accuracy was 92.01%. The results showed that the recognition model trained by the improved algorithm had the lowest recall rate of 81.40%, the highest recall rate of 96.93%, the lowest accuracy rate of 85.63%, the highest 95.53%, and the lowest F1 value of 87.50%, the highest 94.99%. Faster RCNN (VGG16 network) has high recognition accuracy for Rosa roxburghii fruit, reaching 95.16%. The recognition speed of single fruit is faster, and the average recognition time of each Rosa roxburghii fruit is about 0.2 seconds. The average time has some advantages, which is 0.07 s faster than the methods of Fu Longsheng. In this paper, a Faster RCNN Rosa roxburghii fruit recognition network model based on improved VGG16 is proposed, which is suitable for Rosa roxburghii fruit recognition model training. The algorithm proposed in this paper has good recognition effect for Rosa roxburghii fruit under weak and strong illumination conditions, and is suitable for effective recognition and detection of Rosa roxburghii fruit in complex rural environment. This paper is the first study on the depth extraction of Rosa roxburghii fruit image features by using convolution neural network. This research has high recognition rate and good real-time performance under natural conditions, and can meet the requirements of automatic identification and positioning picking of Rosa roxburghii fruit. It lays a certain foundation for intelligent identification and picking of Rosa roxburghii fruit, and opens a new journey for the research of automatic picking technology of Rosa roxburghii fruit.
    2016,32(9):130-135, DOI: 10.11975/j.issn.1002-6819.2016.09.018
    [Abstract] (17393) [HTML] (0) [PDF 361.61 K] (2960)
    Abstract:
    Abstract: To assess the effects of different straw return modes on the content of soil organic carbon and the fraction of soil active carbon, we investigated 4 different straw return modes, non-straw return (CK), direct straw return (CS), straw return after mushroom cultivation (CMS), and straw return after livestock digestion (CGS) using field plot experiment. The results showed that different straw return modes all increased the content of soil organic carbon, but the increases in soil organic carbon content by different straw return modes did not exhibit significant difference (P>0.05). The increases in soil organic carbon content were found in the order of CGS > CMS > CS > CK. In comparison to CK mode, the contents of soil organic carbon with CS, CMS and CGS modes increased by 9.0%, 23.9% and 26.7%, respectively. In addition, different straw return modes all improved the content of soil active carbon. Under different straw return modes, the contents of dissolved organic carbon (DOC) were in the order of CS > CMS > CGS > CK, and significant differences were observed among different return modes (P<0.01). Compared to CK mode, the contents of DOC in the treatments of CS, CMS and CGS increased by 64.6%, 29.4% and 8.9%, respectively. The contents of microbial biomass carbon (MBC) followed the order of CMS > CGS > CS > CK, and their differences were significant (P<0.05). The contents of MBC in the treatments of CS, CMS and CGS increased by 28.9%, 84.7%, and 59.3%, respectively, compared to the CK treatment. Similarly, the contents of soil easily oxidizable carbon (EOC) were in the order of CMS > CS > CGS > CK, and their differences were significant (P<0.01). Compared to CK mode, the contents of EOC in the treatments of CS, CMS and CGS increased by 24.1%, 55.7%and 9.3%, respectively. Straw return modes also significantly affected the fraction of soil active carbon in the soil total organic carbon (TOC) and changed the quality of soil organic carbon. Under different straw return modes, the ratios of DOC/TOC, MBC/TOC and EOC/TOC were in the orders of CS > CMS > CK > CGS, CMS > CGS > CS > CK and CMS > CS > CK > CGS, respectively. From the perspective of improving soil quality, CMS is the recommended mode, which has the greatest ratios of MBC/TOC and EOC/TOC, as well as a higher soil carbon effectiveness that facilitates the carbon utilization by the microorganisms, thus benefiting the growth of crops. On the other hand, from the perspective of soil carbon sequestration, CGS is the recommended mode, which has the lowest fraction of DOC/TOC and the highest content of soil organic carbon, thus facilitating the carbon sequestration. The results of the study can provide the basic data for the rational and efficient utilization of straw, as well as the improvement of the quality of agricultural soil carbon pool.
    2015,31(16):78-85, DOI: 10.11975/j.issn.1002-6819.2015.16.012
    [Abstract] (17131) [HTML] (0) [PDF 522.80 K] (3185)
    Abstract:
    A typical dynamic characteristic of horizontal axis wind turbine shows up under yaw condition. Prediction accuracy is low for momentum-blade element theory and related engineering prediction model. In order to improve the prediction accuracy of dynamic load characteristics, the whole wind turbine models, based on the experiment about MEXICO (model experiments in controlled conditions) rotor in 2006, are established by three-dimensional software called Pro/E. under different yaw conditions, i.e. yaw angle of 0, 15, 30 and 45 degree. ICEM CFD (integrated computer engineering and manufacturing code for computational fluid dynamics) is applied to grid division. The rotating domain containing rotor part is meshed into hexahedral grids, and the static domain containing part of wheel hub, tower and outflow field is meshed into tetrahedral grids. When the grid size of the first layer of blade surface is set as 5×10-6 m to ensure the first dimensionless size near the wall Y+<0.5 on the wall, the 2 numbers of grids are determined by the error of axial load on the airfoil in the 60% section of blades, which respectively are 6 572 451 and 2 961 385. The aerodynamic performance of models under rated condition is simulated by ANSYS CFX with the turbulence model of SST (shear stress transport), high resolution is chosen as advection scheme, and transient rotor stator as the domain interface method. The results are converted into data, processed and analyzed by MATLAB. Finally the following conclusions are drawn. The distributions of pressure coefficients along the airfoil chord in different blade sections calculated by CFD method are in good agreement with the experimental measurements, and the error on the suction surface of airfoil is mainly caused by stall separation occurring on the pressure surface of airfoil. With the increasing of yaw angle, the pressure coefficients of the suction side are increasing and the location of minimum pressure coefficient moves to airfoil trailing edge slightly. For the pressure side, the pressure coefficients increase at first and then decrease, and the location of maximum pressure coefficient moves to airfoil leading edge slightly. The axial load coefficients and tangential load coefficients of blades first decrease and then increase and then decrease again with the increase of the azimuthal angle. With the increase of the yaw angle, the axial and tangential load coefficients are both reduced. When the yaw angle is within 30°, the relative error of axial load coefficients is in the range of ±5% and the relative error of tangential load coefficients is in the range of ±15%. CFD method is higher than BEM (blade element momentum) method in forecasting accuracy of dynamic load calculation. Under yaw condition, the hysteresis characteristic of airfoil lift and drag in blade root is more remarkable than blade tip, while the variation range of the angle of attack in blade root is much less than that in blade tip. This characteristic must be considered when BEM method is used to predict wind turbine performance. For axial inflow condition, CFD method can well predict the average speed, but restricted by turbulence model and the wake model, CFD calculation did not show the velocity characteristics of rotating vortex shedding from wind turbine impeller under yaw condition. The study provides a data support to build up the forecast model on the engineering and provides the basis for wind turbine design under yaw condition.
    2015,31(15):201-207, DOI: 10.11975/j.issn.1002-6819.2015.15.028
    [Abstract] (16846) [HTML] (0) [PDF 772.45 K] (2869)
    Abstract:
    Abstract: At present, large quantities of straws are burned in field in China, which not only wastes a renewable resource, but also causes serious air pollution. Anaerobic digestion of straws is an alternative method that may produce a clean fuel for energy generation. Currently, more research on impact of digestion for quality content of total solid of manure or mixed materials for the fermentation substrate has been studied, but research is limited in continuous stirred tank reactor for a single type of feedstock. Although the characteristics of anaerobic digestion and properties of gas production at the process of continuous stirred tank reactor and semi- continuous feeding mode has been examined for crushed straw and silage straw as the fermentation substrate, but the operation parameters of such system has not been determined. Thus, in order to obtain the corresponding relationship between solid matter retention time for substrate and the characteristics of gas production, a comparative study to determine biogas production in batch fermentation and semi-continuous fermentation process was carried out under medium temperature conditions with rice straw as feedstock. The effect of quality content of total solid in the batch and continuous biogas fermentation of straws was studied. The volume of gas production rate and the rate of raw material gas production were used as characteristic indicators in order to obtain parameter on optimum quality content of total solid and solid matter retention time for biogas plant with straws. The results showed that fermentation concentration of single straw type used for anaerobic fermentation raw material influenced the gas volume rate under the condition of batch fermentation. With the increase of total solid concentration, the volume of gas production rate was increased in batch fermentation process, but the trend of the increase was gradually decreasing. The volume of gas production rate was improved under condition of intermittent stirred compared with static batch fermentation. Especially, the improving effect was more obvious for the group of high-concentration of TS. However, the volume of gas production rate was more improved for the group of high-concentration of TS under semi-continuous feed conditions, but with the solid matter retention time (SRT) shortened, the rate of raw material gas production with every treatment was gradually decreased. Considering the characteristics of gas production and engineering applications, it was recommended that the concentration of batch fermentation should not exceed 8% for pure straw. For semi-continuous fermentation, if the straw composition in total solids content was 8%, SRT was designed as 20 days (the volume of gas production rate of 1.00 m3/(m3·d)). If the total solids content was 6%, SRT was designed as 15 days (the volume of gas production rate of 0.75 m3/(m3·d). The operating parameters provided an operational reference for biogas plant only with straw.
    2015,31(9):201-208, DOI: 10.11975/j.issn.1002-6819.2015.09.031
    [Abstract] (16787) [HTML] (0) [PDF 3.61 M] (4258)
    Abstract:
    Abstract: As one of the most effective cooling method, the fan-pad evaporative cooling system has been widely used to provide a suitable growth environment for greenhouse crops. An optimization method of the fan-pad cooling system based on computational fluid dynamics (CFD) was proposed to improve the cooling performance inside the greenhouse in summer. The Reynolds-averaged Navier-Stokes equations were solved using finite volume method (FVM). Due to the remarkable effect of gravitation on the microclimate distribution inside the greenhouse, the Boussinesq hypothesis was taken into account. The standard k-ε turbulent model was selected to predict the distribution of air flow. Solar ray tracing was applied to load the solar radiation model, while the discrete ordinate model was selected for considering the effect of thermal radiation. Crops in the greenhouse were regarded as the porous medium, which was governed by the Darcy-Forcheimier equation in the CFD model. A three-dimension greenhouse model was developed to simulate the microclimate distribution and air circulation inside the greenhouse adopting fan-pad cooling system. The verification experiment was conducted in a Venlo-type greenhouse in the campus of Zhejiang University of Technology (30°14′N, 120°09′E) from 12:30 to 13:30 on July 23, 2012. Thirteen observation points of T1-T10 and TH1-TH3 were set up in the experimental greenhouse to validate the simulated air temperature and velocity. The errors between simulated and measured air temperature at the observation points varied from 0.7 to 2℃, and the errors of air velocity were less than 0.13 m/s. Compared with the measured values, the absolute mean errors of simulated temperature and air velocity were less than 4% and 6% respectively. It proved that the CFD method is reliable to estimate the distribution of air velocity and temperature in the greenhouse. The validated CFD model was then used to further analyze the cooling performance of different greenhouse cases in terms of the greenhouse lengths, the evaporative pad areas and the greenhouse ventilation rates. The indoor environment with the temperature of below 30℃ and the velocity of below 1 m/s was suitable for crop growth, and this condition was used as a criterion for optimal design. Based on the orthogonal test method, greenhouse cases with different greenhouse lengths, evaporative pad areas and air velocities of fans were classified and simulated to analyze their relations. The simulations illustrated that the greenhouse ventilation rate of 153.1 m3/(m2·h) and the minimum pad area of 6 m2 can meet the cooling requirement in a Venlo-type greenhouse with 24 m length and 9.6 m width. In contrast with greenhouse of 70 m length, the maximum pad area of 13.5 m2 had to be configured, because the greenhouse with smaller evaporative pad need combine with the fan's velocity of more than 105 m3/(m2·h). According to the relations among greenhouse length, evaporative pad area and fan's velocity resulted from CFD analysis; the fitted results could be achieved to design the fan-pad evaporative cooling system in the greenhouse in eastern China. The fitting optimization showed good agreement with the previous corresponding research results, which demonstrated that CFD technique was rational and reliable to design the fan-pad evaporative cooling system in the greenhouse.
    2015,31(16):96-101, DOI: 10.11975/j.issn.1002-6819.2015.16.014
    [Abstract] (16616) [HTML] (0) [PDF 395.08 K] (2762)
    Abstract:
    High-speed solenoid valve (HSV) is the key component of electronic control fuel injection system for diesel engine. Improving the dynamic response speed of HSV will be able to achieve higher injection precision and more flexible fuel injection law, thus reducing gas emissions of diesel engine and improving its fuel economy. However, HSV is the complex coupling system of electric field, magnetic field, mechanical movement and flow field, and the interactions of multiple parameters exist between the fields for HSV. To improve the dynamic response speed of HSV is a complex optimization problem of multiple physical field and multiple parameters. A zero-dimensional approximation coupling model of HSV can be developed instead of the CAE (computer aided education) models or physical experiments, which conduces to achieve the efficient prediction and global optimization of performances. So the approximation model method was employed in this paper. First, the structure and principle of HSV for electronic unit pump of diesel engine were presented. Second, the three-dimensional (3D) finite element model of HSV was developed to calculate the electromagnetic force, and its accuracy was verified by means of the comparison with experimental data. Third, 3 major methods of experimental design, i.e. central composite faced-centered design (CCF), central composite inscribed design (CCI) and optimal latin hypercube design (OLH), and 3 typical approximation methods, i.e. quadratic polynomial response surface model (RSM), Kriging model (KR) and radial basis function model (RBF) were introduced. Fourth, 6 key parameters including 2 field coupling parameters, i.e. working air gap and drive current, and 4 structure parameters, i.e. coil turns, side pole radius, thickness and radius of armature were determined for establishing the approximate models. Next, 6 groups of sample points were designed, whose response values of electromagnetic forces were obtained by the 3D finite element model of HSV. Four of the groups were designed with different sizes by the OLH, and the other 2 groups were designed by the CCF and CCI. Then, 18 groups of electromagnetic force approximation models were developed by combining the 6 groups of experimental design with the 3 typical approximation methods introduced. To compare the accuracy of approximation models, 3 kinds of evaluation indices were introduced. They were multiple correlation coefficient, average absolute error and root mean square error respectively. In the end, the effects of different sample point sizes, experimental design methods and approximate methods on the accuracy of electromagnetic force approximation models were analyzed in detail. It is concluded that the accuracy of approximate model doesn't increase monotonically with the increase of the set size of sample points, and too many sample points maybe leads to the decrease of the accuracy of approximate model; the OLH has good adaptability with the KR and RBF, and can be given priority for developing approximation models. In addition, the best solution for establishing electromagnetic force approximation model of HSV is the combination of the KR and OLH, whose size of sample points is 1.5 times of the minimum sample points required by the quadratic polynomial response surface model. Its multiple correlation coefficient, average absolute error and root mean square error are 0.97, 0.06 and 0.09 respectively. It provides a theoretical guidance for the establishment of the zero-dimensional approximation coupling model and the optimization of HSV.
    2015,31(18):34-40, DOI: 10.11975/j.issn.1002-6819.2015.18.006
    [Abstract] (16537) [HTML] (0) [PDF 8.13 M] (3701)
    Abstract:
    Abstract: In China, corn harvest gradually tends to mechanization, and corn threshing is the most important section in the process of corn harvest, which is directly affecting the damage level of corn seed. Manual threshing often chips away a row of corn ear with an awl firstly, and then it's easy to thresh other kernels. Based on this, some agricultural experts put forward a process of "pre-dispersion and post-threshing". Besides, the study found that after the long-term evolution, beak has not only excellent ability to insert into corn kernels, but also strong ability of dispersing kernels with low damage. To explore the movement law of corn ear kernels and low damage in the discrete process of corn ear, this paper had an experimental study on the beak to peck the corn kernel using the discrete test system with high-speed photography. The variety of experimental corn was Zhengdan 958 and the common domestic chicken was selected for testing. Self-made corn discrete test system was used in this experiment. The whole system consisted of mechanical data acquisition system and high-speed photography system. Due to the randomness of chicken pecking corn, firstly, the high-speed camera was fixed to the bracket, and then the best angle was selected to shoot at the beginning of discrete process. The shooting in the test was mainly from the ahead, the side and the back side of the test equipment with the shooting angle of 45°. The sensors were installed on the fixture to measure the forces in 3 directions respectively. Through observing the photos, we found that the closer the kernel was from beak, the larger the horizontal component of thrust was, the more obvious the movement was, and the easier kernel was to disperse from ear; on the contrary, the further the kernel was from beak, the smaller the horizontal component of thrust was, and the more difficult kernel was to disperse from ear. The kernels followed the "arrangement law" to deliver forces, whose range was approximate to a "tower", and the movement of kernel separated from corn ear was similar to oblique throwing movement. According to the data measured, the maximum force on the corn ear was in x direction, second in y direction, and the force in z direction was the minimum. The resultant force of x and y direction had a great influence on the number of the kernels separated from the corn ear. The results of verification test were that the average discrete rate was 67.53% and the damage rate was 0.16%, which showed that the beak had a significant effect on dispersing corn ear, and the damage rate was low. The study will provide a bionic thought on designing corn threshing system with low damage.
    2017,33(7):164-170, DOI: 10.11975/j.issn.1002-6819.2017.07.021
    [Abstract] (16409) [HTML] (0) [PDF 6.90 M] (3786)
    Abstract:
    Abstract: Planting area and spatial distribution information of crops are vital for guiding agricultural production, taking effective management measurements, and monitoring crop growth conditions. Numerous crop classification algorithms have been developed with rapid development of different remote sensing data. However, distinguishing of corn and soybean cropping areas still remains a difficult challenge due to their similar growth calendar and spectral characteristics. In this study, we tried to identify corn and soybean cropping area using random forest (RF) classifier which has been proved to be an effective method in land cover classification based on multi-temporal GF-1 WFV (wide field of view) imagery. We selected Nenjiang County, Heilongjiang Province in China as the study area which was called the Town of Soybean. Seven GF-1 WFV time-series images (April 14th, May 20th, June 26th, July 16th, August 26th, September 4th, and September 29th), from which the key growth stages could be extracted and the effects of clouds could be avoided, were chosen to classify main crops. First, we conducted atmospheric and geometric corrections on multi-temporal GF-1 imagery. In order to improve the accuracy of distinguishing corn and soybean cropping area, the parameters of RF classifier were input, which included normalized difference vegetation index (NDVI), wide dynamic range vegetation index (WDRVI), enhanced vegetation index (EVI), and normalized difference water index (NDWI), and hundreds of field sample points were collected in the field survey. Also, it’s necessary to evaluate the importance of different combination of these indices. The results showed that the combination of NDVI, WDRVI and NDWI achieved the best accuracy with the producer accuracy of 91.14% for soybean and 91.49% for corn, and with the user accuracy of 82.76% for soybean and 93.48% for corn. Then, the support vector machine (SVM) and maximum likelihood (ML) supervised classifiers were also used to map corn and soybean cropping areas; the classification results from the SVM and ML methods were compared with that from the RF approach with the Nenjiang Farm as the case study. The comparisons showed that the crop classification from the RF classifier had the higher accuracy than the others. Our results indicated that GF-1 data had particular advantages in mapping cropping area with its higher spatial and temporal resolutions, and could provide more effective remote sensing data during crop growth season. The temporal changes of main crops showed the best classifying date was September 29th when soybean has been harvested but corn hasn’t, and their vegetation indices showed the maximum difference. The multi-temporal imagery contributed to the separation of different spectral feature curves of different crops in the growth stages when crops had similar temporal variation profiles, which helped to decrease the omission and commission errors of the resultant mapping. The results also showed that the extracted spectral information of water and construction land was very different from vegetation and could be easily masked. Comparing the SVM and ML classifiers with RF classifier, the results suggested that RF classifier could successfully distinguish corn and soybean, and its overall accuracy reached up to 84.82%. This study provides important reference for crop mapping in other agricultural regions.
    2015,31(20):268-273, DOI: 10.11975/j.issn.1002-6819.2015.20.037
    [Abstract] (16218) [HTML] (0) [PDF 6.48 M] (5713)
    Abstract:
    Abstract: For detecting the quality of pork, traditional optical equipment has high accuracy, whereas heavy weight, large size and high price make it difficult to use widely. The purpose of this research was to develop a portable optical device for detecting pork quality based on visible/near infrared spectroscopy and embedded system. This paper mainly explained the models building and the development of application software. Firstly, a compact and flexible system was made. Halogen lamp is as light source. To adapt to various complex environments, its hand-held probe can form black room on the surface of pork. Micro spectrometer (USB4000) receives and measures reflected light. ARM (advanced RISC machines) processor controls all parts in device and analyzes spectrum data. Based on Linux embedded operation system, liquid crystal display (LCD) touch screen interfaces with users. The whole weight of 3.5 kg makes it convenient for users. Secondly, collect the spectrum reflected from pork samples and build the partial least squares regression (PLSR) model. Before these, spectrometer parameters should be set, so that it works under the best conditions. Integration time of USB4000 was set to 7 ms, pixel boxcar width zero. Thus the reflection intensity of standard white plate was about 80% of spectrometer scale span. During experiment, after acquiring white and black spectrum data, detection probe was put on the surface of pork samples. Spectrum data in the wavelength range from 400 to 1 000 nm were collected from the surfaces of 39 pork samples, 29 spectra of which were as calibration, while others as validation. The acquired spectrum data were then processed by standard normalized variables (SNV) and Savitzky-Golay filter (S-G) to eliminate the spectra noise. After collecting the spectrum data, reference pH values of pork samples were immediately tested by pH meter (METTLER TOLEDO FE20, Switzerland), and color parameters (L*, a*, b*) were measured by precision colorimeter (HP-200, Shanghai, China). The partial least squares regression (PLSR) was applied to establish the prediction models. Experiment results showed that prediction correlation coefficients of pH value, L*, a* and b* were 0.94, 0.98, 0.95 and 0.85, and standard deviations of pH value, L*, a* and b* were 0.17, 1.19, 0.42 and 0.61, respectively. Thirdly, application software was designed and developed for detecting the quality of pork. It consisted of spectrometer control unit, spectrum data acquisition unit, spectrum analysis unit, and displaying and saving unit for prediction result of pork quality. Particularly, in spectrometer control unit, all parameters of USB4000 were set as the same as those when building the PLSR models. The coefficients matrixes of models were loaded into pork quality detection software in spectrum analysis unit. After debugged, the application program detecting the quality of pork was cross-compiled, and downloaded into the device. Finally, the accuracy of models were tested. The reflect spectra of external 41 pork samples were collected and analyzed with the device. At the same time, the real values of these samples' pH, L*, a* and b* were measured. For the pH value, the prediction model could give satisfactory results with the correlation coefficient (Rv) of 0.88 and the standard error of prediction (SEP) of 0.19. For the color L*, a* and b*, the prediction models could gain prediction results with the Rv of 0.90, 0.97 and 0.97, and the SEP of 1.77, 1.17 and 0.63, respectively. In conclusion, the field application results indicate that this portable device can satisfy the requirements of meat quality detection with high accuracy and good performance.
    2014,30(8):257-264, DOI: 10.3969/j.issn.1002-6819.2014.08.030
    [Abstract] (16090) [HTML] (0) [PDF 4.73 M] (3396)
    Abstract:
    Abstract: During aqueous processing of peanuts for simultaneous oil extraction and protein recovery, large amounts of emulsion could be formed and after enzymatic demulsification, substantial amounts of oil would be recovered while stubborn emulsions still remain. The destabilization of the stubborn emulsion is the key to improve the total free oil yield. Before its utilization and further destabilization, studying the characterization of the stubborn emulsion, especially its surface protein, which may play an essential role in emulsion stabilization, was necessary. The surface protein was extracted and its electrophoresis property, hydrophobicity, emulsifying activity, as well as emulsifying stability were studied. Confocal laser scanning microscopy (CLSM) was used to investigate its microstructure. It was found that, though the protein from the emulsion surface had similar subunits (60, 41, 38.5, 37.5, and 18 kDa) with that from aqueous phase, its hydrophobicity and emulsion activity was significantly higher. This could be attributed to the synergistic effect of temperature and pH during the alkaline extraction, which led to the unfolding of some large peanut protein molecules containing hydrophobic basic arachins. This, consequently, caused the exposure of more hydrophobic groups and enhanced the hydrophobic and emulsifying properties of the protein. Thus emulsion formation was promoted. After enzymatic treatment, the protein in the emulsion was hydrolyzed into short peptides and no subunits with molecular weight higher than 20 kDa had been detected in Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). However, in non-reducing PAGE, except for the conarachin band of 60 kDa, protein from the stubborn emulsion surface showed similar bands with that from the emulsion surface and aqueous phase. This indicated that the hydrolyzed protein could still gather on the stubborn emulsion surface and contributed to its stability. Due to the hydrolysis of protein molecules, the hydrophobic property and emulsifying activity of protein from stubborn emulsion was lower than that from an untreated emulsion surface. CLSM observation showed that stubborn emulsion had less oil droplets and that their size was lower, while the surface protein concentration (Γ) was higher, as compared with untreated emulsion. This explained the high stability of stubborn emulsion, though its surface protein has lower surface activity. To demulsify the stubborn emulsion, various treatments, including ultrasound, freeze-thaw, heating, extreme pH value, phase inversion, or ethanol addition were attempted. Free oil was obtained after centrifugation and total free oil yield was calculated thereafter. The microstructure of the stubborn emulsion after different treatments was also observed with CLSM. Results show that freeze-thaw and ethanol addition could remarkably aggregate the oil droplets in stubborn emulsion, especially after 50% ethanol addition, most oil droplets were combined and 90% of the oil in stubborn emulsion could be recovered. Under this condition, the total free oil yield could be increased to 93% from 88% in the overall process.
    2016,32(12):107-114, DOI: 10.11975/j.issn.1002-6819.2016.12.016
    [Abstract] (16058) [HTML] (0) [PDF 413.47 K] (2364)
    Abstract:
    Abstract: Rapid population growth and economy development has led to increasing reliance on water resources. It is even aggravated for agricultural irrigation systems where more water is necessary to support the increasing population. In this study, an interval-parameter two-stage Fuzzy-stochastic optimization model was developed for dispatching the underground and surface water systems for different crops in Hong Xinglong irrigation of China under the conditions of uncertainty and complexity. In the model, the maximal system benefit was regarded as the objective function and 3 methods of probability density function, discrete intervals and fuzzy sets were introduced into the two-stage linear programming framework to resolve uncertain issues. The model allocated a predefined water to crops in the first stage, according to benefit and punishment for water shortage condition to adjust the water supply in the second stage, making the system reach the balance of systems benefit and the risk of punishment, the process of water allocation for multiple corps was simulated, meanwhile, the allocation of water from various sources was optimized. Because inflows water was of obvious probability characteristics in irrigation area, the model took into account of the random of inflow, and assumed that the probability of occurrence for high, middle and low levels were 0.2, 0.6 and 0.2. Since the quantity of stream flows, water requirement of crop and available water supply were uncertain, and uncertainties might also exist in system benefits and costs, the uncertain parameters of above-mentioned were described by interval variables. The available water in the irrigation area was represented by fuzzy sets based on credibility theory. The different probabilities, discrete interval number and fuzzy sets together were used to build the irrigation multi-water resource, multi-crop water distribution model. The model was solved by the method of linear programming, the optimal distribution scheme of water was achieved and the maximum benefit was 1 355.144×106-2 371.792×106 RMB. It could reflect not only uncertainties in water resources system, but also provide an effective linkage between conflicting economic benefits and the associated penalties attributed to the violation of the predefined water distribution target. Meanwhile, the results were presented in the forms of interval number, proving a more broad decision space for decision makers. Moreover, the results indicated that farmer planted a large number of high-yield and high water consumption of crops such as rice and corn in irrigation area and single planting structure would lead to the risk of the decrease of crop production in dry year, the model was valuable for supporting the adjustment or justification of the existing irrigation patterns and identify a desired water allocation plan for agricultural irrigation under uncertainty. Compared with the other traditional two-stage model, this model had advantages: 1) it considered uncertain factors as much as possible, made the model more close to actual condition; 2) The model effectively relieved groundwater pressure of water supply by utilizing surface water and groundwater; 3) The model results would suggest managers reducing planting area of high water consumption crops; 4) Water resources management by system benefit would stimulate employee enthusiasm; and 5) The model data was relatively easy to access.
    2017,33(12):66-73, DOI: 10.11975/j.issn.1002-6819.2017.12.009
    [Abstract] (16044) [HTML] (0) [PDF 5.69 M] (3619)
    Abstract:
    Abstract: The droplet quality of hydrodynamic ultrasonic atomization nozzle is better than the ordinary two-phase nozzle. And the atomization amount is larger than the piezoelectric atomization nozzle. High-quality droplet and high atomization amount are both required in the field of aeroponics. Therefore, it is necessary to develop a hydrodynamic ultrasonic atomizing nozzle suitable for large-scale aeroponics. Based on the basic principle of the Hartmann resonator, in this study, the mechanism of ultrasonic vibration of resonant cavity and the atomization mechanism of resonant cavity supersonic nozzle were analyzed theoretically. The Hartmann low-frequency ultrasonic atomization nozzle with stepped resonator and adjustable structural parameters was designed, including the Laval tube, the stepped tube, and conical shield. The influence of the structural parameters on the resonant state of the resonator was studied by means of CFD software transient numerical simulation. In order to make the spraying angle controllable, active flow control was used in the atomizing area, namely, adding a conical shield at the exit of the nozzle. The oscillation characteristics of the stepped resonance tube were further studied parametrically by numerical simulation methods. Numerical simulation of three kinds of atomizing nozzles including cylindrical tube, stepped tube and stepped tube with conical shield was carried out. The parameters which were studied were as follows: the distance between Laval outlet and inlet of stepped tube, depth ratio of the second stepped hole and the first stepped hole, conical cover, diameter ratio of the second stepped hole and the first stepped hole. Numerical simulation results showed that: (1) If the depth ratio of the stepped tube exceeded 2, its resonance frequency reached 1.6 to 1.7 times of the cylindrical one under the same working parameters; (2) The conical shield can make the pressure oscillation amplitude in the cavity bigger; and (3) The diameter ratio of the stepped resonator had a great influence on the resonant state of the resonator. The variation of diameter ratio of the stepped resonator changed the resonant mode of the stepped resonator from one mode to another. It also can make the resonance phenomenon disappear. As such, the key dimensions of the stepped resonator were determined accordingly. And an optimal diameter ratio was selected for trial production. And the optimal distance between Laval tube outlet and the resonant inlet 5.5 mm were selected as the initial structural parameter values of the spray test. The droplet size of three kinds of atomizing nozzles was tested and the test of droplet size was carried out with distance between Laval tube outlet and the resonant inlet, depth ratio of the second stepped hole and the first stepped hole, and other factors as variables. Moreover, its atomization properties were tested contrastively under different conditions. Research results showed that: (1) Start-up properties of oscillation can be optimized due to the main frequency unaffected by the conical shield;(2) The diameter ratio of stepped resonance tube was a quite sensitive parameter influencing the resonance state. The variation of diameter ratio can make the resonance mode change from 'jet regurgitant mode' to 'jet scream mode' or make the oscillation disappear; (3) Atomization properties of Hartmann atomization nozzle with a stepped resonance tube was better than those of Hartmann atomization nozzle with a cylindrical one; (4) If the air supply pressure was low, the droplet size was more sensitive with the pressure after adding a conical shield, while the gap of the average droplet size between the nozzle with stepped tube and that with traditional tube was not obvious under the condition of high air supply pressure. The distance between the Laval tube exit and the resonance tube was another sensitive parameter influencing the droplet size. An optimal distance, where the minimum droplet size can be acquired, was 6.5 mm. The droplet diameter increased gradually no matter the distance was bigger or smaller than the optimal distance. However, the droplet diameter varied slightly with the distance near the optimal point.
    2016,32(8):278-284, DOI: 10.11975/j.issn.1002-6819.2016.08.039
    [Abstract] (16030) [HTML] (0) [PDF 1.43 M] (3113)
    Abstract:
    Abstract: At present, trawl fishing as a traditional method is widely used in shellfish harvesting at home and abroad. However, using this method to catch the scallops has many disadvantages, such as huge energy consumption, high labor intensity, and poor fishing efficiency, which have become the key questions to restrict the sustainable development of marine fishing industry. Therefore, it's very worth researching alternative scallop fishing equipment to meet the requirements of green development. The offshore scallop capture equipment is made up of platform deck, floating body and mooring, which is a kind of floating offshore engineering structure. This equipment occupies multiple functions, such as fishing, sorting, refining, storage and so on. Winch motors (ground net machine and anchor winch), cargo winch, generator unit, scallop separator, working cabin, accommodation and diesel generator were installed on the platform, and solar power as the source of power. In addition, to keep the scallops fresh and achieve the purpose of saving space, 2 shellfish purification storage networks were also set below the platform. Compared with the trawl fishing, it would substantially reduce energy consumption, realize precision fishing, raise fishing efficiency, and decrease the cost of purification. In this paper, based on the comparative methods, the technologic and economic parameters and the economic assessment indices were selected for the establishment of the technical and economic evaluation model, which was to investigate the economy of offshore scallops capture working platform. Firstly, the platform trawling engine power, the platform span, the hauls of platform anchored one time, the lateral movement time of platform anchored one time, the trawling speed of platform and the total construction cost of platform were selected as the technologic and economic parameters. Secondly, the capture fuel consumption per unit area, the unit cost of fishing and the capture efficiency were selected as the economic assessment indices. Next, the technical and economic evaluation model was established according to the technologic and economic parameters and the economic assessment indices. At last, based on this model, the economic calculation of fishing methods including fishing vessels and scallops capture working platform was carried out by using the comparative method. The results showed that when the platform trawling engine power was 400-470 kW, the platform span was 0.5-3.0 km, the lateral movement time of platform anchored one time was less than 2 h, the trawling speed of platform was beyond 1.4 kn, the total construction cost of platform was less than 27.5 million yuan, the scallops capture working platform project had more advantages over the fishing method of fishing vessels. Meanwhile, from these data, it was concluded that the haul of platform anchored one time was not very sensitive to the effect of scallops capture working platform project. The offshore scallops capture working platform conformed the policy of energy saving and emission reduction that was in line with the national "Twelfth Five-Year Plan". By further experimental verification, the analysis model and method can provide the economic theory reference for the fundamental changes in fisheries production mode in China.
    2016,32(5):120-125, DOI: 10.11975/j.issn.1002-6819.2016.05.017
    [Abstract] (16028) [HTML] (0) [PDF 3.29 M] (2901)
    Abstract:
    Abstract: Yanqi Basin is one of the most important oasis agricultural areas of Xinjiang. But the ecological environment of Yanqi Basin is fragile, which depends on groundwater resources greatly. To study the spatial-temporal evolution of total dissolved solids (TDS) of groundwater is of great significance to groundwater exploitation in arid areas with fragile ecological system seriously affected by human. In order to identify the groundwater pollution status in the plain area of Yanqi Basin, 42 groundwater samples was collected in 2014. TDS and concentration of anion and cationic of the 42 groundwater samples were tested. T test was used based on the observed data of groundwater in the different periods of the plain area to determine the variability of TDS. The relationships between TDS and macro anion, macro cation, pH were analyzed with SPSS software. The results showed that TDS of groundwater was mainly affected by SO42-, Cl-, K++Na+, Mg2+ and Ca2+. And the TDS were highly correlated with Cl- and K++Na+. The correlation between the TDS and macro anion was highest, followed by Cl-, SO42-and HCO3-; the correlation between the TDS and macro cation was also high, followed by K++Na+, Ca2+ and Mg2+. Zone map of TDS was drewn by the MAPGIS software. In the temporal scale, the average of TDS of groundwater was increased then decreased and increased again from 1983 to 2014, and the average value was 305.0, 1773.1 and 589.44 mg/L in 1983, 1999 and 2014, respectively. In the spatial scale, the TDS of groundwater evolved horizontally from piedmont to the plain area. The TDS of groundwater increased from upstream to downstream. Influenced by topography and hydrogeology conditions, the main hydrogeochemistry action changed from strong runoff to slow evaporation gradually. Area of groundwater with TDS<1 g/L showed an increasing trend but a decreasing trend from 1999 to 2014, which was consistent with downtrend of the mean value of TDS from 1999 to 2014 increased from 2011.7 to 2229.3 km2. There were 2 main reasons causing that change of groundwater TDS: 1) The groundwater table dropped from 4.98 to 7.34 m from 2000 to 2014, which prompted the solid phase calcium and magnesium soluble salts, insoluble salts and exchangeable calcium and magnesium in the soil and the lower layer sediments transferred to the groundwater; Meanwhile the increase of the groundwater table in the plain area led to high solutes concentration; 2) Urbanization had the great influence on the groundwater system. It changed the original land use patterns, and then the groundwater circulation system. And with the development of urbanization, industrial and domestic waste water increased year by year and could infiltrate into aquifer. The discharge of living and industrial waste water led to groundwater pollution, which was consistent with the dominant role of Cl- and SO42- in TDS. The study provide valuable information for understanding the condition of underground in Xinjiang.
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    2009,25(8):288-293, DOI:
    [Abstract] (2182) [HTML] (0) [PDF 0.00 Byte] (117999)
    Abstract:
    In order to study the feasibility of microwave-assisted foam mat drying method for the dehydration blackcurrant pulp, a reasonable foaming additive formula was determined and the microwave-assisted foam mat drying characteristics of blackcurrant pulp were analyzed. The concentration of glyceryl monostearate (GMS) and soy protein isolated (SPI) with food grade, selected as the foaming additive, had obvious effects on the foaming properties of blackcurrant pulp. A reasonable foaming additive formula for the blackcurrant pulp with optimum expansion and high stability was developed that the 6% GMS and 3% g SPI as foam inducers and the 10 mL carboxylic methyl cellulose (CMC) with concentration of 0.5% as foam stabilizer, accompanying with the stirring time of 6 min. The experimental results of microwave assisted foam mat drying method showed that the drying intensity of foamed blackcurrant pulp increase with the increase of initial microwave intensity and the decrease of thickness of material layer. Contrasting the microwave with conventional hot air as the heat source for the foam mat drying of blackcurrant pulp, the qualities of dried blackcurrant product in terms of drying rate, color and appearance dried by microwave method are superior to that dried by the hot air. The parameters including the initial microwave intensity of 14.0 W/g and thickness of material layer of 5 mm are recommended for the continuous microwave belt dryer to dry the foamed blackcurrant pulp. Therefore, microwave assisted foam mat drying is suitable for the dehydration processing of blackcurrant pulp.
    2021,37(12):20-27, DOI: 10.11975/j.issn.1002-6819.2021.12.003
    [Abstract] (701) [HTML] (0) [PDF 5.55 M] (59139)
    Abstract:
    Abstract: Vibration has been an ever-increasing demand for the operational stability of centrifugal pumps in recent years, especially in most large pumps in modern industry. The internal flows are generally dominated by the characteristics of operation stability and vibration of centrifugal pumps. Nevertheless, the blade and volute structures are dramatically detrimental to the internal flows. The radial force is one of the most significant factors to affect the operation stability, and the pressure pulsation inside the volute, particularly in the tongue areas. A double-volute structure is selected normally to reduce the radial force in commonly-used large pumps, instead of a single-volute structure. But the specific structures are still required to be optimized, such as the arrangement of the rib start point. In this study, a three-dimensional unsteady dynamic was proposed to clarify the influences of rib start point on the hydraulic performance, radial force, and pressure fluctuation in the volute of a large double-volute double-suction pump. The variation of fluctuation amplitude and frequency of radial forces were considered at the different rib start points. Meanwhile, the radial forces of the double-volute pump at various flow rates were also compared with those of the single-volute pump. The experiments of pump performance (head, efficiency, and power) were performed on the large-scale pump platform in KaiQuan Factory in Shanghai of China. The numerical data agreed well with the experiments, same as the grid independence check. The results indicated that the hydraulic efficiency at the design points decreased about 4%-5% in the double-volute structure, compared with the single-volute structure. Periodic variation of radial force was detected in the test, where the blade passing frequency was dominated during a blade revolution. The angle of radial force was also changed periodically. The rib start point significantly determined the radial force, where the minimum appeared when the rib started from 190° and 200°, whereas, the maximum appeared when the rib started from 212°. Seven monitoring points were located in the tongue areas to collect the pressure fluctuations. It was found that all the mean, peak, and fluctuation values at the points behind the tongue were much less than those in the front of the tongue under the different rib structures, only 25%-50% of the corresponding value of points in the front of the tongue. The pressure fluctuations of points in front of the tongue were dominated by the blade passing frequency, whereas, those points behind the tongue were dominated by the double blade passing frequency. More importantly, the pressure fluctuation of points declined dramatically, when the rib start point moved backwards, indicating a cause of double blade passing frequency. Thus, the rib start point should be placed at 200° from the tongue point in the flow direction, where the maximum efficiency and the minimum radial force can be achieved, particularly considering the coupled interaction of hydraulic performance and radial force. The finding can greatly contribute to the hydraulic improvement and structure optimization in large centrifugal pumps. Key words: pumps; experiments; rib location; double-volute pump; radial force; pressure fluctuation
    2021,37(19):7-17, DOI: 10.11975/j.issn.1002-6819.2021.19.002
    [Abstract] (701) [HTML] (0) [PDF 8.68 M] (53840)
    Abstract:
    The fuel efficiency of the engine is only 15%-35% while the tractor is working in the field, and the exhaust energy accounts for 38%-45% of the energy released by the fuel. The recovery and reuse of exhaust heat energy could help improve fuel efficiency and reduce emissions. Studies have shown that the exhaust waste heat energy based on the Organic Rankine Cycle (ORC) is the highest. The evaporator is a key component of the ORC system, analyzing its thermal performance under limited space conditions of the tractor could provide a theoretical basis for the optimal design of evaporator parameters, thereby effectively improving the utilization of exhaust heat. This study according to the actual size of the tractor, a plate-fin evaporator was trial-produced to recover diesel exhaust waste heat. A numerical model of convective heat transfer between evaporator exhaust and working fluid based on moving boundary method was established and was verified the validity by combining with bench test data, the thermal performance of the evaporator under full operating conditions of the diesel engine was quantitatively analyzed; meanwhile in order to improve the heat transfer and scope of application of the evaporator, CFD simulation and BP neural network methods were used to further analyze the heat transfer characteristics of the evaporator under off-design conditions, the structure and working fluid parameters were optimized. The results showed that: 1) the evaporator had better thermal performance under medium and high speed load conditions, and the heat transfer reached a maximum of 69.89 kW under 4 000 r/min full load conditions, and the heat transfer of the evaporator would be unstable under medium and low speed load conditions due to the lower exhaust heat capacity flow rate, heat transfer coefficient, and a larger working fluid mass flow rate, resulting in the flow was difficult to ensure that the working fluid was transformed into superheated steam, so that the heat transfer in the two-phase zone and the superheat zone was zero within the evaporator. 2) in order to improve the distribution and turbulence of the fluid in the flow channel, increasing the pipe chamfer and adopting the corrugated fin shape to promote forced heat exchange, the CFD simulation showed the entire high-temperature area moved forward to the inlet of the nozzle to make the flow channel utilization rate higher and heat transfer more. With the optimized structure of the evaporator, the working fluid had a higher degree of overheating under the condition of the same overall size, the maximum heat transfer increased by 5.2%, the heat transfer area increased by 0.19 m2, and the volume only increased by 0.002 m3. 3) combined with the BP neural network algorithm, the evaporator flow channel length, working fluid flow and inlet temperature were optimized parameters, and the thermal performance of the evaporator under off-design working conditions was further analyzed, and the parameter range under the medium and low speed load conditions is determined. Thus, the selection range of the working fluid flow rate at different speeds was proposed, which effectively improving the thermal performance of the evaporator under low-to-medium speed load conditions, and providing a reference for the selection of the transmission ratio of the booster pump and the output speed of the diesel engine and the selection of the transmission device. For example, when 1 500 r/min was under a medium and high load, the flow rate could be changed from 0.03 kg/s to 0.08 kg/s and the maximum heat transfer up to 19.46 kW; at the same time, the transmission ratio could be set to 0.78-1.88 at 1 500 r/min. The results of the study are of great significance and present the fluid flow and heat transfer characteristics of the evaporator, which provide a reference for the actual use of the evaporator in tractors and matching with diesel engine operating conditions.
    2021,37(1):68-76, DOI: 10.11975/j.issn.1002-6819.2021.01.009
    [Abstract] (1690) [HTML] (0) [PDF 5.45 M] (42208)
    Abstract:
    Citrus fruit, one of the most important economic crops, is playing an important role in the industrial development of modern agriculture in rural China. However, the management mode of most orchards in China is currently undeveloped and extensive, particularly with high dependence on labor force, as well as insufficient scientific and technological support. In recent years, the Unmanned Aerial Vehicle (UAV) monitoring technology has become a significant way to quickly extract the structural parameters in the growth of field crops at the park scale, due to its flexibility, low cost, and high resolution imaging. This study aims to construct a monitoring system for the citrus canopy structure and nutrition information using the UAV digital and multi-spectral remote sensing, to get he with the single tree segmentation. The UAV digital images and watershed algorithm were used to segment the structural dataset of citrus canopy, and then the canopy height model of citrus trees was established to extract the plant height using digital surface module. Structural parameters were also calculated, such as the number of citrus trees, and canopy projection area at the park scale. In addition, the UAV multispectral images were used to obtain eight common vegetation indexes, thereby to predict the nitrogen content of canopy in the citrus trees. The whole subset analysis was used to screen the sensitive vegetation index for the nitrogen content of canopy in the citrus trees. The inversion model of canopy nitrogen was constructed using the multiple linear regression. The remote sensing mapping was carried out to estimate the nitrogen content of citrus canopy in park scale. The results showed that: 1) Since the planting density of fruit trees was low in the experimental area, there was a certain distance between trees that can be clearly distinguished. The watershed image processing was selected to segment the single tree of height model for a citrus canopy. The overall identification accuracy, recall rate, and average F value of the fruit trees were above 93%, 95%, and 96.52%, respectively, indicating that the model was well suitable to monitor the number of fruit trees in the park. 2) The canopy structure parameters of individual fruit trees were obtained in the individual tree segmentation. There was a strong correlation between the plant height of citrus trees extracted by the canopy height model and the measured value, where the R2=0.87, and RMSE=31.9 cm. 3) Using the watershed segmentation, the extracted projection area of crown width per plant achieved a high correlation with the artificial sketching area. The coefficient of determination was more than 0.93 in most cases, except that of orchard A lower than 0.78 in December. Meanwhile, the extraction accuracy of the model depended greatly on the single tree segmentation. 4) In full subset analysis, the sensitive vegetation indexes were selected to determine the nitrogen content of citrus canopy, including the Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), and Structure Insensitive Pigment Index (SIPI), where the R2 and RMSE of the model were 0.82 and 0.22%, respectively. The data demonstrated that the nitrogen content of most fruit trees in orchard B was in the suitable range, while there was excessive application of nitrogen fertilizer in orchard A. Therefore, the UAV technology can greatly contribute to extract the physical and chemical parameters of citrus canopy, further to improve the level of accurate management of citrus on the large-scale orchard.
    2013,29(19):88-97, DOI: 10.3969/j.issn.1002-6819.2013.19.011
    [Abstract] (2678) [HTML] (0) [PDF 560.68 K] (39932)
    Abstract:
    Abstract: Aiming at the main problem that existed in estimating the crop water requirement through multiplying the crop coefficients of main crops determined in the early 1990s by ET0 calculated using the Penman-Monteith equation, the reasons for crop coefficients which need to be revised were analyzed. There is a significant difference in ET0 calculated by using the modified Penman equation and by Penman-Monteith equation, which affects overwintering crops with a longer growth period of greater than summer crops with a shorter growth period. The result showed that the monthly ET0 and ETrad calculated by using Penman-Monteith equation were higher than that by modified Penman equation, and the difference between radiation terms was the main reason that caused the difference between the calculation results by using two equations based on the meteorological data of 18 stations in Henan province. The difference of monthly ET0 and ETrad calculated by two equations in autumn and winter was higher than in spring and summer. The effect of aerodynamic term on ET0 was related to wind speed, and the reason that the effect of aerodynamic term on ET0 is higher than the radiation term maybe caused by high wind speed. Except for the relative humidity, average temperature and sunshine hours, radiation term was affected by the elevation of stations, as for the stations with a higher elevation, the impact of elevation on Penman-Monteith equation was greater than that on modified Penman equation. Using the sensitivity analysis method to evaluate the effect of average air temperature, relative humidity and sunshine hours on ETrad showed that Penman-Monteith equation was better than modified Penman model in calculating ETrad. The ETrad calculated through Penman-Monteith equation was little influenced by seasons and stations, and had a high stability. The results from 18 stations showed that the effect of average temperature on ETrad was the minimal, the impact of relative humidity in January, November and December on ETrad was larger, and the influence of sunshine hours from February to October on ETrad was also greater. Therefore, ET0 in Henan Province was calculated by Penman-Monteith equation instead of modified Penman equation, crop coefficients must be corrected, otherwise it caused the estimated values of crop water requirement to be higher, and its impact on overwintering crops with a longer growing period was greater than that on summer crops with a shorter growth period. Finally, according to the relationship between two difference methods of estimating ET0, the correction method of crop coefficient based on Penman-Monteith equation was proposed. This study has an important significance in improving the estimation precision of crop water requirement.
    2011,27(3):254-259, DOI:
    [Abstract] (2453) [HTML] (0) [PDF 0.00 Byte] (20419)
    Abstract:
    In order to study the related technology for preparing biodiesel by transesterification of cottonseed oil using solid based catalyst, with supported solid base Na3PO4/MgO as catalyst and biodiesel conversion rate as index, the optimum conditions for catalyst preparation were analyzed by single-factor and orthogonal experiments. The catalyst was characterized by methods of XRD, SEM and TG. Furthermore, the transesterification conditions from cottonseed oil to biodiesel were investigated using solid base catalyst. It was obtained that the optimum conditions for catalyst preparation were: 32% of Na3PO4 dosage on MgO, 600℃ of roasting temperature, 3 h of roasting time and 70℃ of blending temperature. Catalytic activity was related to Na3PO4 crystalline phase. The optimal conditions of transesterification with optimized catalyst were: 2.5 h of reaction time, 70℃ of reaction temperature, 15:1 of mass ratio of methanol to oil, 5% of quality ratio of catalyst to oil.
    2011,27(3):242-247, DOI:
    [Abstract] (2290) [HTML] (0) [PDF 0.00 Byte] (20342)
    Abstract:
    The technique for producing a kind of bio-degraded mulch from the straw fiber was studied. It is an alternative to plastic mulch with the same price and weed control, reducing evaporation functions. Rice straw fiber was the main material, and KP (wood fiber) as well as environment-friendly additives such as wet strength agent, rosin and bauxite were added. A central composite rotary orthogonal experimental design of RSM, with five factors and five levels for each factor was employed. Conventional paper producing technology was adopted, and pulp degree, mixture ratio, grammage, wet strength agent and conditioning agents were the input variables, dry tension strength, wet tension strength, sizing value were the response functions. The optimal technical parameters were obtained, the grammage value, conditioning agents content, wet strength agent content, mixture ratio and pulp degree were 90 g/m2, 0.2%, 0.8%, less than 68% and more than 45°SR respectively. Under the condition, dry tension strength of the sample mulch was higher than 30 N, the wet tension stress was higher than 10 N, and the sizing value was higher than 100 s. The sample of mulch made from rice straw fiber could meet the need of mechanical performance for laying field.
    2019,35(2):25-32, DOI: 10.11975/j.issn.1002-6819.2019.02.004
    [Abstract] (1291) [HTML] (0) [PDF 5.26 M] (18072)
    Abstract:
    The double vane pump is a special type of flow vane centrifugal pump. It adopts a design with less blades, which leads to a disadvantage that the performance of the double vane pump is inferior to that of the multi-blade pump at the same specific velocity. Its stability is 3%-8% lower than of a vane centrifugal pump.Therefore, it is necessary to improve the work efficiency by optimizing the hydraulic design. This article took a double-passage sewage pump model 80QW50-15-4 as the research object. The optimization objective was to design the head and efficiency of the flow point. ANSYS CFX(computational fluid dynamics x) was used to perform numerical simulation to obtain performance data. According to the two-dimensional hydraulic drawing of the initial model pump, the three-dimensional modeling software Pro/Engineer5.0 was used to simulate the water body of the impeller and the volute and to perform mesh division and irrelevance verification. The model pump was subjected to numerical simulation and experiment of clear water medium, and the performance curve was obtained and compared. The error analysis showed that the maximum error of head and efficiency was 3.9% and 1.7%, which meant that the performance prediction model established by this method had high accuracy. Partial initial model impeller structure parameters were selected for performance impact analysis. The Plackett-Burman screening test was used to determine the blade wrap angle, blade outlet angle and impeller outlet width were significant factors affecting head and efficiency of design flow. According to Fang Kaitai's unified design table, training samples of RBF(radial basis function) neural network were arranged, so as to establish important structural parameters and performance prediction models, and generated 5 groups of structural parameters random for neural network testing and error analysis. The head and efficiency performance prediction model trained by radial basis neural network was introduced into the particle swarm optimization algorithm as the fitness evaluation model of particle swarm optimization algorithm. The Pareto optimal solution set of head and efficiency was obtained, and the optimal head and efficiency were selected. In addition, this paper also studied the performance and internal flow field differences of the initial individual, the optimal individual of head and the optimal individual of efficiency when transporting different media. It was known from the performance curve that the performance of individuals was improved when transporting different media. The reason for the performance improvement was revealed by the internal flow field distribution map. In order to verify the practicability of the optimization results, a clear water test was performed on the optimal head and the most efficient individual to obtain a performance curve and compared with the performance curve of the initial individual. Among them, the experimental head of the optimal head at the design flow point increased by 0.96 m than the initial individual, the increase rate reached 5.5%, the efficiency increased by 1.6 percentage point; the efficiency of the best individual increased by 10.11 percentage point, the head decreased slightly but met the design requirements. The test proved that the optimization effect was obvious. This optimization method improves the hydraulic characteristics of impeller and the performance of double vane pump.
    2020,36(11):39-48, DOI: 10.11975/j.issn.1002-6819.2020.11.005
    [Abstract] (1199) [HTML] (0) [PDF 8.24 M] (17977)
    Abstract:
    Abstract: Accroding to literatures and preliminary tests, the structure of cheaning device of longtitudinal axial flow grain combine harvester had a significant impact on wind speed distribution of upper sieve surface and cleaning effects of the device. In this paper, the RG60 type single longitudinal axial flow grain combine harvester developed by LOVOL Heavy Industry Co. Ltd. was tested in Xichang, Si Chuan Province. In order to analyze the wind speed distribution on the upper sieve surface, 45 measuring points were set up, the measurement results showed that the wind speed on upper sieve surface was uneven, the speed at front air outlet of fan installation, forth and fifth column from left of tail sieve were greater than else, the maximum wind speed was 8.6 m/s which was smaller than floating speed of grain, the wind speed on sieves of 3 and 4 row, 6 and 7 row was 5.8 and 5.9 m/s respectively, the speed on middle sieve surface was the smallest. The wind speed on the right side was greater than that of the left side. In the middle and right of upper sieve surface, there was less accumulation of grain mixture, while there was more accumulation in the left, the distribution of grain mixture was uneven which was not conducive to separation of grain and impurities. In order to solve the problem that wind speed distribution was uneven on upper sieve surface, the force and speed of grain mixture in cleaning device were analyzed. According to the structure of cleaning device, because the right side of centrifugal fan was equipped with power input pulley so the air inlet resistance value was higher than left side, and the dynamic pressure was smaller. In addition, the large transverse width of vibrating sieve lead to uneven distribution of wind speed on upper sieve surface, resulting in more grain mixture on left side of tail sieve. In order to further analyze tje distribution of wind speed in cleaing device and optimize its structure, the simulation was carried out in Hyper Works. The results of wind speed on upper sieve showed that the test results of wind speed change trend of each measuring point were consistent with the simulation results, with an average deviation of 0.293 m/s, which indicated that the simulation can reflect wind speed distribution of the internal flow field of cleaning device. The maximum wind speed at the front of upper sieve surface was 10.024 m/s, the left side in lateral wind speed of upper sieve surface in cleaning area was much smaller than that of the right side. The maximum wind speed at the rear of upper sieve surface was about 8.02 m/s which was less than that of the suspension speed of materials. The wind speed in middle of tail sieve was high which was bad for separation of grain mixture. The wind speed of fourth column from left on front air outlet was 8.184 m/s while it at third column from left and middle of tail sieve was 8.411 m/s, and the speed on sieves of 6 and 7 row, 8 and 9 row were the smallest, this trendy was same as the test results. In longitudinal section X=650 mm of upper sieve surface, the wind direction was gradually to right in the process of blowing to upper sieve surface, and the maximum wind speed is 17.077 m/s. In cross section Z=-450 mm, the range of wind speed was from 6.5 to 10 m/s, the turbulence in wind field in middle of upper sieve surface may result in less effect separation of grain mixture. The reason for this phenomenon was the right side of centrifugal fan was equipped with a power input pulley, which made the direction of air flow generated by fan deviate. Therefore, the structure of cleaning device was improved to eliminate this phenomenon. The simulation experiment was carried out when the wind shield rotated 10°, 20°, 30°, 40° and 50° counterclockwise, respectively. The results of optimization simulation showed that internal flow field was evenly distributed when wind shield rotated 30° counterclockwise. the wind speed of upper sieve left side gradually decreased while right side gradually increased with increase of counterclockwise rotation angle of wind shield, the wind speed in middle of tail sieve was the highest which was within the range of [8.231, 10.289] m/s, about 2 m/s higher than that before the improvement, the phenomenon of uneven distribution of wind speed on sieve surface and large difference on left and right sides was improved. The optimized harvester test results showed that third column from left in front air outlet and sieves of 11 and 12 row, the wind speed increased by 1.9 and 2.8 m/s respectively, and its distribution at left and right sides of rear of tail sieve was the most uniform. the wind speed in middle of front air outlet on upper sieve (third column from left) was the maximum as 8.7 m/s, it in sieves 11 and 12 row was 6.3 m/s, the lowest was 5.0 m/s in tail sieve. The wind speed along left side and right side of upper sieve surface were gradually decreased, and the overall wind speed distribution was uniform The loss rate of wheat and the impurity rate was 0.89% and 0.37% respectively, the loss rate of rice and impurity was 1.85% and 0.51% respectively, the cleaning performance and uniformity of the wind flow field distribution of the cleaning decice was improved. The research results provide a reference for the design and parameter optimization of the cleaning device of single longitudinal axial flow harvester.
    2014,30(3):205-214, DOI: 10.3969/j.issn.1002-6819.2014.03.027
    [Abstract] (2771) [HTML] (0) [PDF 11.40 M] (17780)
    Abstract:
    Abstract: Rural residential areas are an extensive dispersion with localized concentrations, and the area of land utilization per capita is large in Dazhu village in Hechuan of Chongqing. Inefficient utilization of rural residential areas is an adverse process all over China during the urban-rural transitional period, especially in traditional agricultural areas. The space reconstruction of a rural residential area could be a breakthrough in the rational utilization of land resources, advancing new countryside construction, restructuring village space, and promoting urban-rural integration and development.This paper used the symbiotic theory to establish a rural residential restructuring symbiotic system. The system included rural residential areas as a symbiotic unit, and the policy environment and the village-domain environment as symbiotic environment. Due to the mutual functional differences of symbiotic units, village spatial reconstruction should consider a mutually beneficial symbiotic relationship between the units, namely the mutualism mode. The research analyzed a rural residential restructuring symbiotic system, and made clear the restructuring principles and procedure needed to build the space reconstruction strategy of a rural settlement. The thesis selected the demonstration village of the whole village advancement-Dazhu village in Hechuan of Chongqing as the object of empirical study. It built three kinds of functional groups-productivity-oriented, service-oriented, and living-oriented groups, a space representation of which was already presented in the village, and formed the layout of 'one axis and three groups' at the the village scale.The results showed that: first, adopting the rural residential restructuring symbiotic system analysis accords with the reality of Dazhu village to restructure village space. It further showed that the symbiotic theory has strong applicability to space reconstruction of a rural settlement. Secondly, the results of the empirical study showed that the space reconstruction of a rural settlement, which is based on the symbiotic strategy, can both ensure the inter-operability of a rural settlement and respect the principal position of farmers. It realizes 'shared resources, co-constructed environment' and exploits environmental advantages in the village domain. It can also improve the utilization efficiency of rural residential areas. Through the study of the demonstration village, the paper provides a scientific basis for formulating village space reconstruction and a new approach to the whole village advancement in a hilly area and the beautiful village construction. Due to the fact that the factors which influence rural residential restructuring are very complex, the regional social, economic, and environmental development strategies and resource endowment conditions which are expected to be considered comprehensively, need to be studied further. Different types of household willingness and future livelihoods also require deeper study.
    2021,37(16):127-135, DOI: 10.11975/j.issn.1002-6819.2021.16.016
    [Abstract] (1119) [HTML] (0) [PDF 22.64 M] (17137)
    Abstract:
    Abstract: Automatic fruit recognition is one of the most important steps in fruit picking robots. In this study, a novel fruit recognition was proposed using improved YOLOv3, in order to identify the fruit quickly and accurately for the picking robot in the complex environment of the orchard (different light, occlusion, adhesion, large field of view, bagging, whether the fruit was mature or not). The specific procedure was as follows. 1) 4000 Apple images were captured under the complex environment via the orchard shooting and Internet collection. After labeling with LabelImg software, 3200 images were randomly selected as training set, 400 as verification set, and 400 as a test set. Mosaic data enhancement was also embedded in the model to improve the input images for the better generalization ability and robustness of model. 2) The network model was also improved. First, the residual module in the DarkNet53 network was combined with the CSPNet to reduce the amount of network calculation, while maintaining the detection accuracy. Second, the SPP module was added to the detection network of the original YOLOv3 model, further to fuse the global and local characteristics of fruits, in order to enhance the recall rate of model to the minimal fruit target. Third, a soft NMS was used to replace the traditional for better recognition ability of model, particularly for the overlapping fruits. Forth, the joint loss function using Focal and CIoU Loss was used to optimize the model for higher accuracy of recognition. 3) The model was finally trained in the deep learning environment of a server, thereby analyzing the training process after the dataset production and network construction. Optimal weights and parameters were achieved, according to the loss curve and various performance indexes of verification set. The results showed that the best performance was achieved, when training to the 109th epoch, where the obtained weight in this round was taken as the final model weight, precision was 94.1%, recall was 90.6%, F1 was 92.3%, mean average precision was 96.1%. Then, the test set is used to test the optimal model. The experimental results show that the Mean Average Precision value reached 96.3%, which is higher than 92.5% of the original model; F1 value reached 91.8%, higher than 88.0% of the original model; The average detection speed of video stream under GPU is 27.8 frame/s, which is higher than 22.2 frame/s of the original model. Furthermore, it was found that the best comprehensive performance was achieved to verify the effectiveness of the improvement compared with four advanced detection of Faster RCNN, RetinaNet, YOLOv5 and CenterNet. A comparison experiment was conducted under different fruit numbers and various lighting environments, further to verify the effectiveness and feasibility of the improved model. Correspondingly, the detection performance of model was significantly better for small target apples and severely occluded overlapping apples, compared with the improved YOLOv3 model, indicating the high effectiveness. In addition, the target detection using deep learning was robust to illumination, where the illumination change presented little impact on the detection performance. Consequently, the excellent detection, robustness and real-time performance can widely be expected to serve as an important support for accurate fruit recognition in complex environment.
    2018,34(19):266-275, DOI: 10.11975/j.issn.1002-6819.2018.19.034
    [Abstract] (1385) [HTML] (0) [PDF 3.39 M] (16977)
    Abstract:
    Abstract: Human activities within the Nature Reserves are considered a threat to the endangered species. This study takes the land cover/land use as the representative of human activities within the Nabanhe National Nature Reserve. As optical remote sensing images are frequently contaminated by cloud and frog, which will restrict its practicality in monitoring human activities in Nabanhe National Nature Reserve, this study aimed to fuse the multi-resources of optical remote sensing images to build a high spatio-temporal resolution data (30 m daily surface reflectance) for the year 2000, 2004, 2010 and 2015 using the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model). The fused data was assessed during the data fusing procedure, and in a correlation of greater than 0.8 (with P<0.01) with the reference image for each period of time. The fused data was then used to generate the time-series NDVI (Normalized Difference Vegetation Index), which would be used to differentiate each of the 5 land covers (namely natural forest, rubber trees, water, farmland and built-up area) to be classified. Previous to the extraction of the time-series features, denoising of the time-series NDVI was conducted using the double S-G (Savitzky-Golay) filter. 6 features were generated using the denoised NDVI time-series data, and used to classify the 5 land covers above. The Random Forest classifier was used during the classification, and the RF classifier was trained using the reference samples that were selected from high spatial resolution Google Earth images. The overall accuracies of the final classification results were greater than 86.88%, with Kappa values greater than 0.817?6 (the overall classification accuracies for the year 2000, 2004, 2010 and 2015 were 88.13%, 86.88%, 89.38% and 90.63% respectively, and the corresponding Kappa values were 0.834?0, 0.817?6, 0.853?3 and 0.871?1, respectively). This accuracy guaranteed the availability of the classification results in monitoring human activities in Nabanhe National Nature Reserve. The land cover/land use changing trend was analyzed based on the classification results for each period of time, of which the results were as follows: from 2000 to 2004, water area increased mainly due to the conversion of farmland and built-up area, which occupied 0.06% and 0.01% respectively of the entire area of the Nabanhe National Nature Reserve. Farmland area increased, and the increased area was mainly from natural forest and rubber trees. Built-up area increased, and the increased area was from natural forest and farmland. The area of the increased rubber trees is the largest, and the increased rubber trees occupied natural forest and farmland. The only decreased land cover/land use was the natural forest during this period of time. From 2004 to 2010, water areas increased mainly due to the conversion of natural forest and rubber trees, because there was a hydropower station built during this period of time. Increased farmland area was mainly from forest, while increased built-up area was mainly from farmland. Rubber area was increasing due to the conversion of forest, the area of which was decreasing constantly during this period of time. From 2010 to 2015, increased water occupied farmland and the forest was changed to farmland with the largest area (96.47% of all land converted to farmland was forest). Expanded built-up area was from rubber farmland (occupied 76.92% of all land changed to built-up). It was during this time that the farmland changed the most, it was 5.29% of the area of the Nabanhe National Nature Reserve. Obvious land use changing trend corresponding to terrain was found from 2000 to 2015. Built-up distribution changed less, but the corresponding area increased. The rubber was distributed in areas with slopes ranging from 0 to 36 degrees, and it was first expanded from 0 to 12 degrees, and then to 24 degrees and now is distributed to near 36 degrees. The expansion of rubber is pushing the rubber planting to the limit in the Nabanhe National Nature Reserve. Same changing trend was found to the farmland from 2000 to 2015. Both of these land covers are expanding to steeper terrain and larger areas in the Nabanhe National Nature Reserve. The method provided by this study may support the governmental departments in monitoring human activities within Nature Reserves.
    2021,37(1):223-232, DOI: 10.11975/j.issn.1002-6819.2021.01.027
    [Abstract] (1858) [HTML] (0) [PDF 6.54 M] (15348)
    Abstract:
    An improved Convolutional Neural Network (CNN) was proposed to solve the time-consuming and inefficient detection for the surface defect on the Hami melon in recent years. The Hami melons were purchased from 103 Regiment, 6th Agricultural Division, the Xinjiang Production and Construction Corps, China. A total of 200 images of normal Hami melons were taken by a camera in a black box. 100 images of Hami melons were collected with the various surface defects, such as mildew, sunburn and crack. Since it is difficult to collect samples with three defect types, the data enhancement technique was used to expand the dataset. A total of 10 000 sample images were obtained, and then divided into a training and test dataset, according to the proportion of 4:1. A VGG-like model was improved by adding a convolutional layer and a pooling layer at the beginning. As such, the improved VGG-like model included three convolutional layers, three max-pooling layers, a flatten layer, and two fully-connected layers. The softmax classifier was used in the last fully-connected layer. The Rectified Linear Unit (ReLU) function was chosen as the activation function. The Stochastic Gradient Descent (SGD) was chosen as the optimizer. The improved VGG-like model was used to identify four-class defect samples. The optimal hyperparameters in the CNN models were determined via the performance under the different learning rates and epochs. In all established CNN models, the test data showed that the AlexNet model outperformed other VGG-16 models, with the learning rate of 0.001 and the epochs of 500. Moreover, the AlexNet model can achieve the best performance with the accuracy of 99.69% and 96.62% in the training and test dataset, respectively. Three image processing techniques were compared to evaluate the preprocessing impact, including the Principal Components Analysis (PCA), Singular Value Decomposition (SVD), and binarization. The results indicated that the preprocessing provided a better detection performance on the various surface features of Hami melon in image preprocessing. The improved VGG-like model was the optimal to detect four-class defect on the Hami melon surface, indicating the learning rate of 0.001 and the epochs of 500. The prediction accuracy of improved VGG-like model in test set reached 97.14%. A visualization technique was used to analyze the features of convolutional layers, particularly on feature extraction in a CNN model. The visualization results showed that the defect features became more and more obvious with the increase of the convolutional layers. The defect features were the clearest in the captured images by the last convolutional layer. In addition, the convolutional features with the input as the preprocessing images were clearer than before. Finally, the improved VGG-like model was verified by the developed software on the plateform of PyQt5. The developed software functions included Open Camera, Read Image, Image Processing (Gray, PCA, SVD and Binarization), and Image Identification. The detection time of a single image was less than 0.7 s. In each type, 50 images were captured under the same environment. A total of 200 test images were collected. The test results showed that none of normal samples was predicted as defect samples. Only 8 crack Hami melons was incorrectly identified, due mainly to the unobvious feature. The average prediction accuracy of 200 samples was 93.5%. The improved VGG-like model with the preprocessing can be expected to apply for the detection of defects on the Hami melon surface, and other on-line nondestructive detection in the future.
    2013,29(23):268-275, DOI: 10.3969/j.issn.1002-6819.2013.23.037
    [Abstract] (1740) [HTML] (0) [PDF 1.94 M] (14327)
    Abstract:
    Abstract: Clarity of juice is an important factor regarding the quality of the juice as it fetches consumer attention for the product in the market. Clarification is a key step in the processing of fruit juice and is most often achieved through micro filtration, enzymatic treatment, or by using common clarifying aids like chitosan, gelatin, bentonite, silica sol, polyvinyl pyrrolidine, or a combination of these compounds. Chitosan (poly-b(1-4)N-acetyl-glucosamine) being poly-cationic in nature, nontoxic, and biodegradable, has been found to be an effective coagulating agent in aiding the removing pectin and other carbohydrates which are present in the juice. The clarification of ponkan juice by means of chitosan was studied in this paper. In order to obtain the optimal reaction conditions of clarification of ponkan juice by commercially inexpensive chitosan, the process conditions of clarification with chitosan on ponkan juice were optimized by a Box-Behnken center-united experiment design. Taking juice clarification as a dependent variable, the models were obtained by using a response surface analysis of the three factors of chitosan concentration, chitosan treated temperature, and the chitosan treated time based on a single factor experiments. The results indicated that the interaction effect of chitosan concentration and chitosan treated temperature, chitosan concentration, and chitosan treated time on the juice clarification achieved a very significant level. The influencing factors had a complicated relationship with each other. Among these factors, chitosan treated time、chitosan concentration, and the chitosan treated temperature ranked in order. The results from the Box-Behnken center-united experiment showed that the optimum technological condition for clarification of ponkan juice was adding 0.8 g/L chitosan at 59°C for 71 min and its clarification of the ponkan juice was up to 97.8%. The experiment indicated that there was a good fit between the predicted and the experimental values. The mathematical model was also very accurate. Comparing with the original ponkan juice, the contents of soluble solids, vitamin C, and titratable acidity were almost the same after clarification. Removing the pectin, total phenolics, and proteins improved the non-biological stability of the ponkan juice, because of the phenomenon of flocculating with chitosan. According to the non-biological stability tests, the results of stability tests of protein, potassium hydrogen tartaric acid, iron, copper, and oxidation showed negative, and indicated that the non-biological stability of ponkan juice were strengthened by chitosan to a certain extent.This article could provide a theoretical basis for clarifying ponkan juice in manufacture. According to the optimal technological condition of the experiment, clarification of 1 L juice only costs 0.15 yuan. The popularization and application of this technology will bring great economic benefits for the industrial production of juice.
    2021,37(1):213-222, DOI: 10.11975/j.issn.1002-6819.2021.01.026
    [Abstract] (1662) [HTML] (0) [PDF 4.66 M] (13249)
    Abstract:
    Ginger is widely cultivated in temperate zone, tropical and subtropics. China is the largest ginger producer and exporter in the world. Sowing seeds can be the second step in the ginger production, after the soil preparation is ready. It is necessary to lay the ginger flat in the trench, and keep the shoots in the same direction when sowing, in order to ensure that the shoots can emerge in the same direction under the requirement of avoiding light in the production. All the shoots emerge towards the south in an east-west trench, whereas those towards the west in a north-south trench. Therefore, shoots recognition has become a type of key technology to ensure the same direction of shoots, and then realize automatic and accurate sowing. In this study, a feasible way was proposed to realize the rapid recognition and accurate determination of ginger shoots using deep learning. Firstly, the dataset of ginger images was established, including image acquisition, enhancement, and labeling. Secondly, in training a small sample dataset, the data was augmented using online data enhancement to increase the diversity of images, and address the lack of generalization capability. The Mosaic method was used to enrich the background of ginger shoots training without introducing non-informative pixels. Thirdly, the position of ginger shoots regression bounding box directly determined the specific position of shoots, thus DioU (Distance Intersection over Union) bounding box regression loss function was introduced instead of the traditional loss function of IOU, in order to improve the regression effect of regression bounding box. Fourthly, in order to improve the convergence rate of model, the K-means clustering using the IoU measurement was used to derive 9 anchor boxes after linear scaling, indicating more in line with the shoots size. In addition, the Darknet-53 model pre-trained on the ImageNet data set was used for transfer learning, aiming to reduce the training time of model. Finally, after the identification of shoots were completed using the YOLO v3 network, in order to facilitate the selection of the strongest shoot, the area of the prediction bounding box was used as the basis for selection, and only the prediction bounding box with a larger area was retained. A Cartesian coordinate system was established with the center of the image as the origin, and the orientation of shoots was discriminated by calculating the azimuth of the center of prediction bounding box. The average precision and F1 were used to evaluate the performance of ginger shoots recognition model. In test, the IoU threshold and the confidence threshold were analyzed to obtain the best detection effect, while the improved strategies were verified one by one. After training and testing, the detection index was the best, when the IoU threshold was 0.6, and the confidence threshold was 0.001. The average precision and F1 measure reached 98.2% and 94.9% in the shoot recognition model, respectively, where the detection speed was 112 frames/s for a single 416×416 pixels image on the GPU. Compared with the original YOLOv3, the average precision and F1 measure increased by 1.5% and 4.4%, respectively. The recognition model of ginger shoots can be used to achieve significantly excellent recognition, providing a sound theoretical basis to realize automatic and precise ginger sowing.
    2019,35(23):135-141, DOI: 10.11975/j.issn.1002-6819.2019.23.017
    [Abstract] (966) [HTML] (0) [PDF 1.77 M] (12530)
    Abstract:
    The Loess Plateau in China is one of the most severely eroded regions of the world. Since the implementation of "Grain for Green" ecological restoration project, biological soil crusts (biocrusts) were widely distributed in this region, which significantly affected surface runoff. Numerous studies have explored the effect of biocrusts on runoff. However, the conclusions were still widely different. In the Loess Plateau region, rainfall is mostly concentrated in June to September, and the rainfall duration is not fixed, which may affect the runoff characteristics of biocrustal slopes. This study investigated characteristics of runoff from biocrustal slope in different rainfall durations in the Loess Plateau region by using artificial simulated rainfall experiment. The experiment was conducted in the revegetated grassland of northern Shaanxi Provence, China. The experiment site was about 80 m×20 m, and the slope gradient was approximately 15°. The biocrust types were mainly moss crust and moss cyanobacteria mixed crust in this site and their average coverage was 79.2%. The dimensions of the experimental plots were 10 m×2.1 m (length×width).Canopy of higher plants in the plots was removed with scissors. According to the range of local biocrust coverage, two treatments were set: 1) slopes with undisturbed biocrust as a high coverage biocrust (the average biocrust coverage were 79.2%); 2) the slopes with removal of a part of the biocrusts by shovels, which simulated the low biocrust cover situation (the average biocrust coverage were 43.6%). Meanwhile, ploughing plots were set as the control group. The rainfall intensity was set as 90mm/h and the duration was1 hour. The results showed that the initial runoff time of biocrust slope was significantly reduced compared to the bare soil slope. The initial runoff yield time of bare soil was 1.59-3.04 times that of the biocrust slopes. There was a significant negative correlation between biocrust coverage and initial runoff generation time; Conclusion of the influence of biocrusts on runoff yield was contradictory during the first 15 min and 60 min. For 90 mm/h rainfall intensity, runoff from biocrust slope increased by 75.42% compared to bare soil when the rainfall duration was the 15 min. While, runoff from biocrust slope was decreased by 52.42% compared to the bare soil when the rainfall lasted to 60 min; the infiltration rate of soil moisture was affected by biocrusts. The infiltration rate of bare soil slope with 60 min rainfall was 34.30% lower than that with 15 min. The infiltration rate of high coverage biocrust slope with 60 min rainfall was only 6.38% lower than that with 15 min, which may cause the difference of runoff yield between bare soil slope and biocrust slope; the effect of biocrust on slope infiltration and runoff is closely related to rainfall duration. Different periods of rainfall are likely to lead to inconsistent conclusions. Therefore, the duration of rainfall experiment considering the factors of biocrust should be no less than 45 min. The study provides scientific evidences for explaining the differences in the effect of biocrusts on infiltration and runoff, and further clarifies the hydrological effect of biocrusts in arid and semi-arid areas.
    2016,32(17):127-135, DOI: 10.11975/j.issn.1002-6819.2016.17.018
    [Abstract] (3679) [HTML] (0) [PDF 15.27 M] (12402)
    Abstract:
    Abstract: Remote sensing technology is a major method to obtain spatial distribution and quantity of winter wheat area, and classification method suitable for business operation is a key technology target of annual winter wheat remote sensing monitoring. Aimed at the conditions and demands of winter wheat background survey business operation in agriculture information service, this paper has proposed a weighted NDVI index (WWAI) based on normal difference vegetation index (NDVI) time sequence. By taking the extraction of 2013-2014 winter wheat area of Anping County, Hebei Province as an example, the algorithm is realized by using GF-1/WFV (wide field view) data. The main idea of the algorithm is to amplify the difference between winter wheat land type and other ground object types by establishing a winter wheat area index based on time sequence images, and to differentiate winter wheat land type from the others and thus to obtain the crop area of winter wheat by automated threshold value setting method. The algorithm includes the following 5 parts: acquisition of winter wheat time sequence images, sample points setting based on grid, establishment of winter wheat area index, identifying winter wheat area index estimation threshold value by iteration, and accuracy validation. Acquisition of images is based on the identification of growth time of winter wheat, and the principle is to ensure to get one GF-1/WFV cloudless image each month. Growth period of winter wheat in Anping County is from October 1st to June 30th of the next year, including 9 growing stages, i.e. seeding, germinating, tillering, overwintering, reviving, jointing, head sprouting, milking maturity and maturity. One GF-1/WFV cloudless image is selected in the middle 10 days of each month, and a total of 9 images are selected for pre-processing and NDVI calculation. Meanwhile, the study area is divided into a certain number of grids, and each grid is further divided into 2×2 sub-grids. The ground object types of central points in upper left and lower right grid are identified by visual interpretation, expert knowledge and field investigation. In this paper, a total of 10×10 equal interval grids with the average grid size of 4.1 km × 4.0 km, as well as 400 sub-grids with the size of 2.05 km × 2.0 km are obtained. The average NDVI values of winter wheat and other ground objects on all upper left centers of this period are calculated. If the winter wheat NDVI is higher than that of other ground objects, the weight of the images of the period is set to 1, and otherwise, set to -1. The winter wheat area index images can be obtained by using the weighted average of NDVI images of all time phases. After obtaining winter wheat area index, it is also necessary to set appropriate threshold value for winter wheat area extraction. The paper takes the visual interpretation classification results of lower right grid points as the basis for threshold value extraction. The specific method is to divide winter wheat area index from small to large with certain intervals, and then to make dimidiate extraction of winter wheat area indices of the lower right centers by taking each divided value as the extraction threshold value. By comparing with the visual interpretation result, the result with the highest accuracy is taken as the optimal winter wheat area index extraction threshold value, which is identified to be approximately 1 600 with self-adaptation approach finally. In all grids, accuracy validation is conducted by taking the 10 plots with equal probability. Accuracy validation results show that the overall classification accuracy has reached 94.4%, with Kappa coefficient of 0.88. The area extraction accuracy of this method is about 1.7% higher than that of conventional method based on NDVI time sequence images. By establishing winter wheat area index, this paper turns a complicated multiple-parameter problem into a single-parameter problem with clearly defined agricultural significance. This method is featured with high automatic degree and stable classification results, and it has been widely applied in the crop area remote sensing monitoring practices in China.
    2020,36(23):171-180, DOI: 10.11975/j.issn.1002-6819.2020.23.020
    [Abstract] (936) [HTML] (0) [PDF 3.89 M] (12002)
    Abstract:
    Aiming at the problems of low efficiency of manual grading and inaccurate mechanical grading of peanut pods, a convolutional neural network peanut pod grades image recognition method based on transfer learning was proposed. By using the operations of the flip, rotation, translation, contrast transformation, and brightness transformation, the obtained five grades (first-grade pod, second-grade pod, third-grade pod, fourth-grade abnormal pod, and fifth-grade damaged pod) of peanut pod images were expanded and preprocessed, thus the peanut pod grades image data set was established. The 60% of data was randomly selected as the training set, 20% of data was randomly selected as the validation set, and the remaining 20% as the test set. The performance of peanut pod image classification based on the GoogLeNet, ResNet18, and AlexNet was compared and analyzed. The peanut pod grades recognition model was improved by transferring the AlexNet convolution layers. The local response normalization was replaced by batch normalization, and the activation function was placed in different positions before and after the batch normalization layer, so that four different recognition-training models were designed, including the PA-I model, PA-II model, PA-III model, and PA-IV model. The transfer learning contrast experiments and the hyperparameter optimization experiments of the learning rate carried out for the four improved AlexNet models proposed above. The effects of the unsaturated activation function (ReLU) and improved unsaturated activation function (LReLU) on the performance of the model were studied. The experimental results showed that the training time of the AlexNet model was the least on the basis of satisfying the test accuracy and the learning rate of transfer learning based on the improved AlexNet model was a very important hyperparameter that needed to be optimized. If the learning rate is chosen too high, the model training oscillates seriously and even can’t train normally; if the learning rate too small, the model training slow. An appropriate learning rate can speed up the training and improve the recognition ability of the model. When the learning rate was updated automatically, the model with batch normalization had better performance than local response normalization, which could make the model get higher accuracy and lower loss value. When the coefficient of activation function LReLU was 0.000 1, the performance of the LReLU used in the model was equivalent to that of the ReLU used in the model, therefore LReLU had no substantial impact on the training results of the model. The addition of batch normalization and reduction of parameters in the model reduced 220 s training time and improved the model’s performance. The classification accuracy of the proposed peanut pod grades recognition model for the first-grade pod, second-grade pod, third-grade pod, fourth-grade abnormal pod, and fifth-grade damaged pod was 93.57%, 97.14%, 99.29%, 87.14%, and 100% respectively and the average classification accuracy reached 95.43%, and F1-scores achieved 96.32%, 97.49%, 99.64%, 92.42%, and 94.50% respectively. The model proposed in this study had high classification accuracy for peanut pod grades and could provide a reference for the precise classification of other agricultural products.
    2015,31(z1):237-246, DOI: 10.3969/j.issn.1002-6819.2015.z1.028
    [Abstract] (3146) [HTML] (0) [PDF 10.15 M] (11534)
    Abstract:
    Abstract: The Internet of Things (IoT) technology, based on the perception, is developing rapidly and permeating into every walk of life. IoT of agriculture, including animal husbandry, has been showing a status of rapid development and is urgent in keeping pace with other industries. In this study, livestock coding specification and identification technology, remote monitoring technology of livestock farm environments and animal behaviors, and precise sow feeding equipment and digital network management platform of farms were reviewed to expound the application effects and limitations of IoT in animal husbandry. We found that at the perceptual layer, the international standards for livestock identification mainly included the ISO TC 23/SC 19, which set rules for radio frequency identification (RFID) for livestock management, and it was functionally divided into ISO 11784, ISO 11785 and ISO 14223. The Chinese standards for livestock identification were described in three levels: national standard specifications, local standards, and corporate standards. For example, the three different standards are Ministry of Agriculture Legislation No.67, local standard of identification in Shanghai (DB31/T341-2005), and Xinjiang (DB 65/ T3209-2011), and internal encoding specification of Beidahuang Agriculture Co., Ltd and Yiliyuan Co., Ltd. At the transport layer, the environment parameters of livestock farms like temperature, humidity, illumination intensity, ammonia concentration, and carbon dioxide concentration etc., and animal behavior parameters like body weight and body temperature would be perceived by different sensors and then the data from environment parameters and individual animal behavior data mentioned above would be remotely transferred through a wireless public network (2G/3G/4G). The video data and huge production process data were transferred into internet network databases by wired networks. At the data application layer, the typical application examples were shown below. Firstly, remote monitoring, data collection, and transmission of breeding environment parameters or animal production data were realized by using an intellectual mobile terminal to analyze and give early warning of the collected data. Then, the system will selectively turn on or off the remote intelligent environmental control equipment (draught fan, light, heater, and water pump etc.) based on the analysis results. The second example was the construction of a cloud-computing platform of cow-breeding farms and pig-breeding farms-that is, production data of hundreds or thousands farms were collected by network databases and data was cloud-stored as well as cloud-analyzed in the form of formal meta data, and the platform would give farmers warning information based on the analysis of production and breeding database by data mining technology. The third example was the development and application of automatic electro-mechanical feeding control systems of lactating sows, which was composed of electro-mechanical systems, wireless network technology, mobile SQL Lite network database, electronic data interchange, and feed intake prediction models of lactating sow nutrient requirements. This paper also analyzed the deficiencies of animal husbandry's IoT in technology, product, application, related policies, and people's cognitive from microcosmic to macrocosmic aspects, and suggestions were given based on the above deficiencies. Above all, the modernization development of animal husbandry needs the support of the IoT and IoT in turn is urged to accumulate its positive energy and promote itself better through applications in the different technological fields.
    2008,24(8):232-235, DOI:
    [Abstract] (9585) [HTML] (0) [PDF 0.00 Byte] (11321)
    Abstract:
    The adsorption-desorption characteristics of phosphate by five common substrates (savageness Zeolite, Haydite, Soil, Vermiculite and Gravel) used in soil treatment systems were illustrated in laboratory. The results indicate that phosphorus adsorption capacities of various substrates in the descending order are vermiculite and soil(1.38 mg/g and 1.24 mg/g), then haydite and zeolite(1.12 mg/g and 1.18 mg/g), and then gravel(0.90 mg/g). The five substrates all reach adsorption equilibrium after twelve hours’ shaking time, and the adsorption capacity increases as the original phosphorus concentration in the liquid increases. The results indicate that phosphorus desorption efficiencies of various substrates in the descending order are gravel, soil, zeolite, vermiculite and haydite. Considering the phosphorus adsorption capacities and desorption rates of five substrates in the research, vermiculite is one sound substrate in the soil treatment system for phosphorus removal.
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    2002,18(3):87-91, DOI:
    Abstract:
    Straw is an important biological resource in agriculture, and China is one of the most abundant countries for straw production in the world. This paper introduces the output and distribution of straw in China and discusses its utilization as the raw material in industry, livestock forage in animal husbandry, fertilizer and energy on farms and households in rural areas. This paper also indicates that great progress was made in integrated utilization based on a number of new technologies, marketing, and support from the Chinese government.
    1999,15(1):1-8, DOI:
    Abstract:
    This paper summarizes the research target of recent precision agriculture and its technical ideas and discusses the direction of technical innovations for the supporting technologies. Some proposals for the applied research in the country are presented. Recent research on precision agriculture in the world is still concentrated on precision farming for crop production. The translation of the phrase “precision agriculture” into Chinese shall be implicated in the Site Specific Crop Management. Following the rapid application of information technology to the agricultural sector, the ideas for precision management of agricultural resources and production would be expanded into all fields of agricultural system, such as precision facilities horticulture, precision raising, precision processing to keep high productivity, high efficiency, low cost and less environmental pollution as well as with high value added technology,etc. Then a real precision agriculture system will be established to support overall sustainable agriculture development based on the new information and biological technology revolution.
    1999,15(3):33-38, DOI:
    Abstract:
    Ninety eight observing points by a square of 10m×10m were made in a wheat field approximate 1 hm2. Soil samplers were obtained from each point under two layers of 0~20 cm and 80~100cm with different soil moisture and different time. Ammonia、NO3-N、Olsen-P in the soils of 0~20 cm and 80~100 cm, organic matter and total-N in surface soil (0~20 cm) were measured. The geostatistics theory was applied to analyze the data, the results indicated that both NH-N in bottom soil and organic matter in surface soil showed a normal distribution, others with a lognormal distribution. The rational sample number was determined within a given precision at a known confidence level. Semivariance analysis gave that those nutrients were correlated in a given spatial range. The Kriging method was applied to calculate the unobserved points and generate the contour map. Preliminary analysis was made for the spatial dynamic variability of those nutrients in different time. These results shows some merit in increasing nitrogen use efficient and precision agriculture.
    2002,18(1):1-5, DOI:
    Abstract:
    This paper presents the elementary concept and the developing history of land consolidation and stresses the significance of vigorously promoting land consolidation in China. Meanwhile, it outlines the overall strategy of land consolidation in China and clarifies the primary principles in the course of land consolidation. Some serious issues and problems faced in the current operation of land consolidation in China, which need to be solved in priority, are also stressed in this paper.
    2003,19(3):1-4, DOI:
    Abstract:
    Conservation tillage (CT) has been shown as a wind and water erosion reduction technology from many years, research in developed countries. This program mainly evaluates the suitability of CT to China and what kinds of technology and machinery should be adopted. From 1991, China Agricultural University cooperated with Shanxi Agricultural Mechanization Bureau and so on, commenced systematic CT experiments combined agronomy and mechanization research together. It has been proved that the CT can not only reduce the wind and water erosion, but also increase the crop yield, after 10 years' experiment. Through improvement of CT operations and development of small size CT equipment, the conserration tillage technology with Chinese characteristics is basically formed, which can realize CT in small piece of land with small CT equipment, and can gain higher yield from poor soil. Therefore, it can meet the requirements of protecting environment and increasing farmers' incomes. The study shows that, due to different natural conditions, cropping systems and economical levels, different CT technological systems should be adopted in different regions.
    2003,19(2):210-213, DOI:
    Abstract:
    Analysis on land consolidation benefits is an important part of the study on the land consolidation theory and practice. It can improve land consolidation theory and guide land consolidation practice to an analysis on its on economic, environment and social development. Though the aims and content of land consolidation are different in different countries, the practice showed that it could increase production and income, protect and improve the environment and provide farmers with fine living conditions. So the comprehensive benefits of land consolidation are the aggregation of economic, environmental, social and landscape benefits. The economic benefits of land consolidation are the effect of the practice upon the national economy and the farmers of land consolidation areas. The environmental benefits of land consolidation are the effect of the practice upon the structure and function of natural ecosystem and the environment. The social benefits of land consolidation are the effect of the practice upon the rural environment, and social economy, as well as the reasonable use of natural resources. The landscape benefits of land consolidation is the effect of the practice upon the rural landscape.
    2005,21(8):169-173, DOI:
    Abstract:
    The status quo of agricultural residues was analyzed. As pollutants have four characteristics of huge quantities, bad qualities, low price and excessive danger. As resources have four application practices, namely, biomass energy, fertilizer, feed and biomaterial. The analysis shows that the potential as fertilizer and energy is huge. However, there are some limited factors and technical bottleneck in the future. In combination with socioeconomic developmental objectives, the developing strategy and strategical emphases for the resources of agricultural residues were presented. The direction is to develop Eco-Agriculture and Cyc-Economy, which depend on the policy guidance, technical support and investment to promote agricultural residues used as resource in the future.
    2009,25(12):211-217, DOI:
    Abstract:
    There are some problems such as statistics lacking, unsuitability of the ratio of main product output to that of by-product of the crops in the estimation of straw resources. The paper chooses the revised ratio of main product output to that of by-product of crops and estimates the quantity of straw resource comprehensively and systematically. The estimation results show that the total straw yield in China has a generally increasing trend with the improvement of agricultural comprehensive production capacity, and China is the biggest country in straw resources that its total output of straw resources in 2005 reached 841 831 200 t, which the straw of food crops was the main source. It has a great potential for rice husk, corncob, bagasse to develop new energy.
    2002,18(1):22-26, DOI:
    Abstract:
    Aquasorb is a kind of sodium polymer with characteristic of absorbing and storing water. There are many types and varieties in commercial market. The purpose of this study is to determine the chemical features of sodium polymer and its effect on soil improving, and to analyze the influence on crop yield and fertilizer use efficiency in farming field. The result showed that and electronic conductivity (EC) were increased but not so high when the concentration of sodium polymer was raised. pH value was almost not affected. Ions with two positive charges, such as [Ca2+] and [Mg2+] have a negative impact on drinking water characteristic of sodium polymer markedly, which is stronger than that of one positive or negative charge, such as Na+ and H2PO4-. It does not influence the drinking water of sodium polymer for different concentrations of urea. When soil is added with sodium polymer, the water holding capacity is raised, the aggregate of the soil is increased, this feature on sandy soil is more remarkable than that on clay soil, especially when there is 0.005% to 0.01% sodium polymer in soil. The test indicated that over 90% water holding by the sodium polymer can be used by plant. Based on the current results, it can be concluded that there are four aspects for action of sodium polymer, (1)conserving water by itself, (2)raising water holding by improving soil structure, (3)enhancing growth of plant and raising fertilizer use efficiency, (4)and reducing soil evaporation. The field test result showed that using sodium polymer by hole method at 15 kg/hm2, the yields of corn and potato were increased by 22% and 16%, and the ratios of investment to benefit were 1∶3.5 and 1∶4.2, respectively. When sodium polymer was mixed with urea or with urea and phosphorus fertilizer, the urea and phosphorus fertilizer use efficiencies were increased by 18.7% and 27.1%, respectively.
    2004,20(5):1-5, DOI:
    Abstract:
    Concepts and bounds of terms of biomass, biomass resources and biomass industry were defined in this paper. Developmental potential of biomass resources in China was analyzed. Aiming at the problems of agriculture, farmers and rural development at present and national requirement of energy and environment securities in the next 10 to 15 years, four developmental trends of biomass industry in China and the world, including biomass power, ethanol, biodiesel, biopolymers and dedicated energy crops and trees were discussed. A developmental pattern of bioenorgy of modern biomass industry with agriculture and forestry was briefly introduced. It is significant for development of biomass industry to settle the problem of farms and accelerate the agricultural industrilization and rural development.
    2004,20(1):13-15, DOI:
    Abstract:
    China has already joined the WTO. Standardization of agricultural production is necessary, but the draggling plant protection machinery and its application techniques are not assorted with this situation, the problems are such as low efficiently using, residue of pest, contaminated environment, toxics, etc.. Plant protection machinery is very different with the other agricultural machinery, its quality and application techniques level affect safety of products. In last 1970s, the plant protection machinery was lined in special type gricultural machinery in developed countries, they had special institution and management. After joining the WTO, the plant protection machinery must be tested according to CCC-Standards in China, but until now there is no best way to improve its draggling actuality. The existing problems of machinery and its application techniques were discussed, and the methods to solve those problems were presented.
    2008,24(12):291-296, DOI:
    Abstract:
    According to document analysis and field survey, various evaluating indices of crop straw resource were used to finish the research and evaluation on main crop straw in China. The results showed that the theoretical resource amount of the 5 main crop straws was 433 million tons in China, including 176 million tons for the energy utilization. The resource could be distributed as ‘two-high and two-low’ that per capita amount of the resource was ‘high in north and low in south’ and per planting area of the resource was ‘high in east and low in west’. According to the resource distributing characteristics in each region. The whole country was divided into main developing area (Northeast, Meng-Xin and North region), proper developing area (Southwest, middle-lower Yangtze River and South region) and limited developing area (Loess Plateau and Qinghai-Tibet region). Different developing measures should be used in each region.
    2007,23(9):276-282, DOI:
    Abstract:
    Development trends of biomass energy in the future were analyzed on the basis of comprehensive evaluation of biomass energy resources, industry development and policy environment in China. Biomass resources are rich in China. Biomass energy industry begans to take shape: biogas industry was basically formed, fuel ethanol throughput reached 1.02 million tons per year, the technology that fuel ethanol was produced by use of non-food crops such as sweet sorghum stalks was developed and demonstration project of direct furl-fired generation with straw began to connect to power grid. Macro-policy environment to promote the development of biomass energy industry gradually formed. Therefore, the conclusions were concluded that development emphasis of biomass energy industry in the future in China would focus on biogas and biogas power generation, liquid fuels, biomass solid pellet fuel and biomass power generation; policies for the development of biomass energy industry would be further improved; the technology level would be further improved. There will be more large-scale enterprises to participate in this industry; it is sure that biomass energy industry will become a new growth point of Chinese national economy.
    1999,15(2):74-78, DOI:
    Abstract:
    Water retaining properties of water retaining BP agent manufactured in USA and its effect on soil and crops were studied. The results obtained were as follows: There were strong absorbretaining properties with BP,absorbing capacity in distilled water is 38.7 mL/g, there was a large change of imbibition in the range of 0~0.1 % solution concentration, the imbibition of 0.1 % solution concentration is 63 % in distilled water, the amount of available water absorbed is over 2/3; soil water physical characterictics were improved and water retention power increases as BP is added to soil; in the range of 0.01~1.5 MPa soil water potential, there were obvious increases in sand soil and heavy loam soil compared with that of light loam and middle loam soil; when BP is added to soil saturated hydraulic conductivity will decrease, soil evaporation properties have no obvious change, especially in sand soil; sand soil wheat pot experiment with BP added to soil showed that there were obvious increases in the weight of wheat root, root length and ratio of root and shoot, the nutrition condition of root system was better, and the wheat growth was improved.
    2006,22(11):269-272, DOI:
    Abstract:
    Increasing temperature and keeping soil moisture effect of mulching plastic film have brought a positive and important progress in agricultural productivity, and also the residue of mulching plastic film in the field has already become a negative factor that affected agricultural environment, which destroyed soil structure and harmed growth of crop. Based on results of domestic study on this issue, the authors comprehensively analyzed the application situation of mulching plastic film in agriculture, and the distribution characteristics as well as the influencing factors, the harm ways of the residue of mulching plastic film. According to the actual situation, the techniques of preventing and controlling measures for residue pollution of mulching plastic film were put forward.
    2002,18(4):155-158, DOI:
    Abstract:
    A novel method for measuring individual leaf area of vegetables was developed using digital image processing techniques and scanner. Meanwhile, the measured data from digital image analysis was compared with the values from grid-counting method, leaf-copy and weighing method, instrumental scanning method, etc. The results show that there are close relationships between digital image processing method and the other traditional methods. Relative low variation in measured data was the dominant advantage of image processing method. It can be concluded that digital image analysis technique is suitable to measure leaf area of vegetable in combination with “Maximum length×width”ruler method through correlation and the calibration coefficients for rape (Brassica napus L) and water spinach (Ipomoea aquatica Forsk) were 0.792 and 0.818, respectively.
    2003,19(2):39-44, DOI:
    Abstract:
    With the help of GPS and GIS, spatial variability of soil property was measured and analyzed by using statistics and geo-statistics, which was tested in a 13.3 hm2 field of winter wheat. Sixty three sampling points were collected on a 50 m grid in soil surface (0~20 cm) of the field, and the points were oriented by GPS receipt machine. The soil property included total N, available N, organic matter, available P, available K, bulk density, the moisture content and electrical conductivity, which were studied using spatial distribution maps and semi-variograms that can explicitly express the random and structural of soil property. The research result showed that all soil spatial characters are normal distribution; bulk density exhibited weak spatial variability, and others exhibited moderate spatial variability; the soil organic matter, total-N, available N, available K and electricity conductivity have exhibited strong spatial correlation, and soil bulk density, available P and the moisture content have exhibited moderate spatial variability, and the range of soil properties correlation distance was 246.8~426.8 m. All these results can serve as a basis for precision fertilization, precision irrigation and precision management in farm.
    2002,18(1):165-168, DOI:
    Abstract:
    The research development of recent agricultural land evaluation in China was reviewed. The two method systems, ideological bases and practical significance raised respectively in newly formulated National Rules of Classification and Gradation of Agricultural Land and Rules of Soil Fertility Gradation of Cultivated Land were analyzed and compared. The classification and gradation evaluation of agricultural land developed from such low level researches on natural soil condition investigation for estimating yield, soil nature and basic soil fertility, etc. to management and evaluation of resource value integrated with land and human being. The existing two evaluation methods of agricultural land in China are the gradation system of soil fertility of cultivated land formulated by Minstry of Agriculture and the classification and gradation evaluation system of agriculturall and drafted by Ministry of Land and Resources. There exist differences between the two systems in analyses of evaluation indexes, objective levels of achievement application and links of front and back operation. Currently, the classification and gradation evaluation of agricultural land have been implemented across China, whose method system perfection is of great practical significance.
    2002,18(2):49-52, DOI:
    Abstract:
    Study was carried out on Fluvo aquic soil of low fertility coming from Huanghe River plain for 14 years. The results show that the long term returning straw to soil changes soil properties. Soil organic matter, soil porosity, availible N,Zn,Fe,Mn and enzyme are all positively related to the amount of straw applied remarkably, while soil specific weight is negatively correlative. These indexes are affected by climate, plant growth seasons and soil texture, etc. The result of combination use of straw and fertilizer is better.
    2000,16(5):26-30, DOI:
    Abstract:
    Crop coefficient is the basic parameter for determining crop water requirement. In this paper, two methods proposed by FAO are described. One is time averaged crop coefficient(Kc) approach, which is a simple and useful method. The other is dual crop coefficient approach with more complicated computations but more accurate results. Both approaches were validated with experimental results at Xiongxian Experimental Station, Hebei Province. The results showed that the Kc values calculated by FAO methods are close to that as estimated from experiment data. Both methods are valid to use for determination of crop coefficients on the North China Plain if there are no on site experiment data available.
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