Abstract: Many links and complex cooperative operations have posed a great challenge to the autonomous harvesting between rice harvester and transfer vehicle. In this study, a cooperative operation strategy was designed for the autonomous rice harvester and transfer vehicle using Finite State Machine (FSM). The cooperative mode was then divided into four links: independent harvesting, waiting for calls, cooperative truck unloading grain, and transportation. An FSM model was also established to construct the basic components of a collaborative harvesting state machine. After that, the state information matrix was defined to design the specific flow of basic action execution, including the harvester starts harvesting, stops harvesting, starts unloading grain and stops unloading grain. The transfer vehicle was then driven at the waiting point to cooperate with the alignment, then to start or stop grain unloading. As such, the state transition chain of collaborative work was constructed to clarify the transition relationship and trigger conditions between the states in the process of collaboration. The cooperative control logic framework involved the harvester and transfer vehicle, according to the state transition chain architecture. Stateflow tool was selected to simulate and verify the compiled logic framework in the MATLAB platform. The sequential execution was also simplified to introduce the timing and signal transmission delay of internal execution. The simulation results show that the states of the harvester and transfer vehicles were transferred orderly, particularly with the correct conversion of the trigger signal. The test results also show that the control logic strategy performed better for cooperative harvesting. A crawler-type rice collaborative harvesting system was constructed to verify the actual operating performance of the logic strategy, including the crawler rice harvester (Weichai Lovol Heavy Industry RG70V4G-014) and crawler rice transfer vehicle (Weichai Lovol Heavy Industry RG70V4G-015). Among them, the two intelligent agricultural machines adopted the fully electronically controlled chassis with the wire-controlled clutch, header, grain cylinder, and crawler driving system. The dual antenna BDS positioning system (Sina K726) was also equipped, where the data transfer unit (USR-G781) was used in the communication between two computers in the fixed-point cooperative experiment of rice harvesting. The 4/5 G data transfer unit (DTU) with human cloud was adopted at the same time. The autonomous control module was communicated with the control terminal through RS-232. A Self-control terminal (eAgri-800-RS) was installed in the two computers for the harvesting self-control, which communicated with the chassis Electronic Control Unit of the two computers through CAN bus. The software system was developed by Keil uVision 5. The linear path tracking was adopted to follow the model control in the navigation system. The two-computer alignment control was adopted to deal with the position error PID. The collaborative system test was carried out in the Zengcheng Experimental Base of South China Agricultural University. The harvester and transfer vehicle were designed to independently work in the field from the hangar of the base. Specifically, the harvesting speed and width were set at 0.8 m/s, and 1.9 m, respectively. The continuous cooperative working time was more than 120 min. 0.73 hm2 of rice were automatically harvested by the ferrule path. Six operations of the automatic cooperative transfer system were carried out to transfer the grain to the truck during this period. The transfer truck waited on the tractor road, and then transferred the harvested grain to the roadside truck, according to the designed fixed-point cooperative operation strategy. The harvester and transfer vehicle returned to the hangar in sequence after harvesting the whole farmland. The harvest and transportation path were also designed in the test plan. Among them, the specific harvesting path was designed to cover the field, where the outer ring was harvested first and then parallel rings, according to the size of the field. The cooperative path was selected on the short-side tractor road. A balance was obtained on the short-side straight-line paths of the harvesting operation. The transfer vehicles only needed to plan a reusable path. The grain alignment transfer work was completed to advance or reverse this path in the whole field. The specific transfer points were calculated from the coordinates issued by the harvester, all of which were located on this path. Consequently, the fixed-point cooperative operation was also realized using the autonomous harvester and the transfer vehicle, according to the predetermined path. The logic signals were successively recorded to normally trigger during network communication under the predetermined logic framework in the test. The whole cooperative process was aligned accurately to successfully complete the fixed-point cooperative harvesting operation and return to the hangar. Therefore, the cooperative operation strategy of double machines for rice harvesting was effective and reliable under the configuration, and the harvesting efficiency was 0.35 hm2/h. The finding can also provide strong support for the cooperative operation of autonomous full coverage harvesting in rectangular rice regions.
Abstract: Numerous geometrically ordered micro-basins can be formed in the soil surface layer during tillage operation. Micro-topography preparation aims to collect and hold water in place during rainfall, thus allowing it to infiltrate into the soil. Consequently, the surface runoff can be reduced to mitigate the erosion of the high water infiltration rate. Among them, the shovel-type rolling component has been typical soil-engaging equipment used for micro-topography preparation. This equipment is assembled with a series of peripheral shovel blades that circumscribe the rolling wheel. There are some arrays of consolidated discrete and small micro-basins, when hauling and rolling across the soil surface. Accordingly, the farming land can be restructured to prepare the desired form for the soil surface area in contact with water. The water-holding capacity of the prepared micro-basin can often be used to evaluate the performance of micro-topography preparation under shovel-type rolling components, together with the forward resistance against the soil. This is because the shape and capacity of micro-basins can be required for superior performance during run-off collecting, particularly for the applicability, workability, and effectiveness of soil imprinting. In addition, there is the inevitable reduction of the tillage resistance in the hilly sloping farmland of southwest China, due to the limited traction power of tractors. It is a high demand to design the effective shovel-type rolling component. Fortunately, the computational simulation can be expected to serve as an effective approach in this case. The purpose of this study was to conduct a systematic investigation to explore the interaction mechanism between the shovel-type rolling component and soil for the micro-topography preparation. Taking the shovel-type rolling component as an object of research, a discrete element model was proposed to investigate the interaction between the rolling component and soil using coupled discrete element and multibody (DEM-MBD). Firstly, the classical mechanics' derivation and computer simulation were integrated to establish the theoretical interaction model between the soil and rolling components. Then, the model was improved after the experimental measurement. Secondly, the optimal theoretical model was selected to guide the design practice. Thirdly, the working mechanism of the rolling component was further optimized using the coupled EDEM-RecurDyn software simulation. Specifically, the horizontal resistance and volume of the micro-basins were then determined, where the operating speeds of the rolling component (0.6, 1.0, and 1.4 m/s) were the experimental factors. Finally, the accuracy of the simulation model was verified by the field experiments. The simulation results showed that there was an increase in the horizontal resistance in the x-axis direction, and the vertical force in the z-axis direction with the increase in the operating speed. The volumes of micro-basin that formed on the soil surface were 3 310.91, 3 325.96, and 3 384.47 mL, respectively, after the operation of the rolling component at the speeds of 0.6, 1.0, and 1.4 m/s, respectively. The formation mechanism of soil micromorphology during the operation was clarified via the soil compression force, particle flow direction, and kinetic energy. A comparison was also made between the bench test and the simulated one. Specifically, the relative errors between computational and measured horizontal resistance were 5.01%, 4.58%, and 4.10%, respectively. The relative errors in water-holding capacity of micro-basin were 6.23%, 7.09%, and 5.64%, respectively. It infers the higher reliability of the improved EDM-MBD coupled model than before. Consequently, the DEM-MBD coupling model can provide theoretical and technological references to explore the interaction between the shovel-type rolling component and soil, in order to optimize the geometric structure of the shovel blade of this component for the ideal operating parameters.
Abstract: Sufficient clearing time, lower impurity content, and loss rate are highly required in the cleaning device of the harvester. The higher generality, larger size, and sieve surface of the device are also demanded during the clearing operation of the two crops of soybean and corn. In this study, an improved cleaning bench was optimized for the 4LZ-3.0Z small self-walking combined grain harvester. A testbed was also built for the cleaning device of soybean and corn. Firstly, the discrete element model was established for the main explants of corn cleaning using EDEM software. Secondly, the EDEM-Fluent coupling simulation was conducted to determine the trajectory and velocity changes of materials in the sieving box during cleaning. A comparison was made on the original sieve box A (Straight upper sieve and lower sieve), the improved sieve box B (Upper sieve section and lower sieve concave surface), and the improved sieve box C (Concave surface is larger). Thirdly, the force analysis was then verified to be the optimal design. The experimental factors were selected as the vibration frequency of the vibrating sieve, the inclination angle of the upper sieve, and the inclination angle of the lower sieve, particularly for the generality and performance of the cleaning device. The single factor test and response surface method (RSM) were carried out for the soybean and corn, with the impurity rate and the loss rate of the cleaning as the experimental indexes. Finally, the best parameter combination was obtained to clarify the influence of experimental factors on the indicators in the cleaning device for two crops. The simulation results showed that the grain movement in the process of cleaning was consistent with the force analysis. Specifically, there was miscellaneous accumulation in the sieve box C. Much more contribution of cleaning was achieved in the grain penetration area and the material movement trend in the sieve box B, compared with the box A and C. The test results of the two crops showed that the three selected test factors presented a significant influence on the parameters (P<0.05). Once the vibration frequency increased, the loss rate and impurity rate of the grain cleaning showed a trend of first decreasing and then increasing during the cleaning of the two crops. By contrast, the impurity content decreased first and then increased, while the loss rate continued to decrease, as the inclination angle of the upper and lower sieve increased significantly. The RSM showed that the optimal working parameters of the equipment for the soybean cleaning were the vibration frequency of 5.9 Hz, the inclination angle of the upper screen at 10.5°, and the inclination angle of the lower screen at 6.5°. The optimal cleaning was achieved in this case, where the average impurity rate and loss rate were 0.622% and 0.439%, respectively. In corn cleaning, the optimal working parameters of the cleaning device were the vibration frequency of 4.7 Hz, the inclination angle of the upper screen at 10.3°, and the inclination angle of the lower screen at 8.6°. Correspondingly, the optimal cleaning was achieved, where the average impurities rate and loss rate were 0.956%, and 0.771%, respectively. Therefore, the impurity content and loss rate of the improved soybean cleaning were reduced by 38.8% and 45.9%, respectively, compared with the original. In corn cleaning, the impurity content and loss rate were reduced by 29.9% and 30.1%, respectively. This finding can provide a theoretical basis for the design soybean and corn combined harvester in the soybean and corn intercropping.
Abstract: The Diameter at Breast Height (DBH) (at a height of 1.3 m on the bole of a tree) has been one of the most important indicators during tree measurements in forestry resource inventory. However, the current DBH measurement cannot fully meet the requirement in recent years, due to the low portability, precision, efficiency, applicability, and stability, together with the complex operation, rudimentary software, high costs, and short range. In this study, an innovative device was developed to accurately, efficiently, and conveniently measure the tree DBH suitable for the complex tree shapes and the different diameter classes, while cost-saving in the office-field work survey. The specification of the device was as follows (size: 8.35 cm×5.80 cm×5.55 cm; weight: 230 g; resolution: 0.01cm; linear range: 0-150 cm; battery: 4 000 mAh; micro-processor chip: STC15W4K48, 8 bits; encoder type: PD-1503-SDI, 12 bits). A Tunnel Magneto-Resistance (TMR) rotary encoder was also combined with the low-cost, small size, and light weight electro-mechanical structure, and high-resolution processing. As such, the measurement device was achieved in the electronization, digitization, portability, and integration of office and filed work for the tree DBH. A supporting system software was also developed, including the embedded software, mobile terminal application, and Web terminal application. In the process of an individual tree survey, the electro-mechanical structure of the device firstly converted the mechanical parameter of tree DBH to the magnetic signal, and then the magnetic signal was converted to an electrical signal. Secondly, the electrical signal was converted into the DBH measurement data using the processing integrated into the embedded software. Thirdly, the operation flow was better applied to measure the trees with special shapes and large diameters using multi-function key combinations. After all individual tree surveys, the DBH measurement data was transmitted by Bluetooth in the device to the Android application, and then uploaded to the database managed by the Web application. The measurement accuracy and operation efficiency of the device were verified to select the 196 standing trees with many tree species and a small sample plot of 42 standing trees in the Botanic Garden of Beijing Forestry University, China. The test results showed that the device presented a higher accuracy to measure the standing trees of different diameter classes than before. The total tree DBH measurement data from different diameter classes (weight: 1 092 g; resolution: 0.001 cm; linear range: 0-500 cm) indicated the mean absolute error (MAE) of 0.22 cm, Mean Absolute Percentage Error (MAPE) of 0.89%, Root Mean Square Error (RMSE) of 0.42 cm, and Relative Root Mean Square Error (RRMSE) of 1.23%, compared with an electronic draw-wire displacement sensor. In addition, a high measurement efficiency was achieved, where the average measurement time per person of each tree was 9.3 s from the efficiency test. The devices demonstrated nearly two times faster than the traditional diameter tape (weight: 42 g; resolution: 0.01 cm; linear range: 0-200 cm), while one time faster than the electronic draw-wire displacement sensor. Additionally, the price of the device was only 260 RMB, due to a 12 bits encoder (price: 135 RMB). In conclusion, this device behaved at a low cost and less labor consumption, fully meeting the technical requirement of accuracy for the Continuous Forest Inventory (CFI) in China. Therefore, the finding can provide broad application prospects in forestry resource inventory.
Abstract: Raw grain generally refers to the unprocessed cereal in agricultural production. In general, the raw grain can be packed from autumn after harvested in northern China. A bag opening mechanism has been one of the most important components in raw grain packing machines. Different cylinders can be usually utilized to drive the bag clamping and opening mechanisms. The performance of this mechanism directly dominates the quality of raw grain packaging. However, the slow action or even failure of pneumatic parts can result in the reduced synchronization and efficiency of machines, due to the condensation at low temperature and the environment of heavy dust. In this study, a bag opening mechanism driven by a cam that moved synchronously with the bag clamping mechanismwas designed. The synchronous actions of bag opening, clamping, and resetting were also realized using one motor to drive the planar six-bar-linkage. A systematic investigation was then made to clarify the working requirements, structural composition, and working principle of the bag clamping and opening mechanisms. A sinusoidal acceleration motion was selected as the movement rule for the cam driven bag opening mechanism. The geometric coordinate transformation and the vector method were established for the parameter equation of the cam working profile and the pressure angle solution of the spatial cam mechanism. A single factor test was also carried out to evaluate the performance of the cam driven bag opening mechanism using the influencing factors of the pressure angle. An optimal combination was achieved, where the radius of bag opening rod was 6 mm, the angular displacement of bag opening rod was 4.5°, the swing distance of the contacting point was 120 mm, the initial positional angle of the contacting point was -180°, and the positional angle of the contacting point was -170°. A linear fitting was obtained between the angular displacement of bag opening rod and the positional angle of the contacting point. The maximum pressure angle of 23° was less than the allowable pressure angle. Finally, the specific parameters were determined for the movement of cam driven bag opening mechanism, the cam working profile, and the relational expression of the pressure angle. A 3D model was constructed for the cam driven bag opening mechanism. The motion of the cam driven bag opening mechanism was also simulated using ADAMS platform. The theoretical calculation and simulation show that the bag opening movement was basically the same, fully meeting the actual requirements of mechanism. In addition, the physical prototype was manufactured for the bag opening mechanism. A comparative test was performed on the bag clamping and opening mechanisms that driven by cylinders and motor. Consequently, the productivity of 10 bags/min was obtained on the motor-driven type, which was much higher than the cylinder-driven one. The feasibility and accuracy of the cam driven bag opening mechanism were verified to fully meet the requirements of packaging process. This finding can also provide a new idea and theoretical analysis to design the raw grain packing machine in the cold regions.
Abstract: Maize tassels play a very important role in the process of maize growth. It is a high demand to realize the accurate identification and counting of maize tassels in the complex field environment. In this study, a complete detection and counting system was established for the farmland maize tassels using unmanned aerial vehicle (UAV) remote sensing and computer vision, in order to promote the application of intelligent agriculture during maize production. The UAV images were also collected during the maize heading stage in the experimental field. Three target detection networks of Faster R-CNN, SSD, and YOLO_X were selected to realize the high-precision recognition of maize tassels using transfer learning. Specifically, the UAV was firstly utilized to collect the RGB images of maize tassels with a height of 10 m on August 9, 2021. Secondly, the UAV images of maize tassels were cut into 600 x 600 pixels. The same number of samples were then selected for the training set, verification set, and test set, according to each variety and planting density. Finally, the weight of training on the public dataset was transferred to the target model using transfer learning. The recognition performance of maize tassel was compared before and after transfer learning. The experimental results show that the average precision, the recall rate, and the accuracy rate of Faster R-CNN target detection networks increased by 16.41, 21.86, and 10.01 percentage points, respectively, compared with the Faster R-CNN, SSD, and YOLO_X. By contrast, the average precision, recall rate, and accuracy rate of the SSD increased by 3.05, 1.76, and 1.29 percentage points, respectively. The average precision, the recall rate, and the accuracy rate of YOLO_X increased by 3.56, 4.51, and 3.21 percentage points, respectively. Among them, the recognition precision, average precision, accuracy, and LAMR of YOLO_X after transfer learning reached 97.16%, 93.6%, 99.84%, and 0.22, respectively, compared with the Faster R-CNN and SSD networks. The best performance was achieved for the detection of maize tassel. In addition, the Faster R-CNN, SSD, and YOLO_X were also utilized to determine the adaptability of the model under the five varieties of maize tassels. The results showed that the maize tassels of Zhengdan958 were easier to be tested, indicating the best adaptability to the model. Nevertheless, there was a low correlation between the true and prediction on the number of frames of Jingjiuqingzhu16 maize tassels, indicating the low detection performance. The training datasets of this variety were then suggested to be expanded and suitable for the model in the future. In addition, five varieties were also tested at four planting densities using the YOLO_X model after transfer learning. The experimental results show that the detection error of the model for the maize tassel significantly increased with the increase in planting density. The density of maize tassel was also estimated to effectively obtain the agronomic phenotype of maize for the prediction of maize yield. A systematic investigation was made to clarify the influence of the difference between varieties and planting density on the model detection. Many factors were determined for the model detection, such as the plant type of maize, the parameters of the model, and the feature extraction network. Therefore, the finding can also provide strong support for the intelligent production of maize and agricultural modernization.
Abstract: The simulation of crop yield is of great significance to develop irrigation scheduling and planting patterns, in order to ensure water and food security in the world. The AquaCrop-KR model has been commonly used as the non-linear equation to fit the relationship between the aboveground biomass and crop transpiration, as well as the water production functions. The harvest index was simulated for the higher prediction accuracy of the crop yield under different water regimes. However, the planting density cannot be considered in this model. The objective of this study was to modify the AquaCrop-KR model, and then simulate the hybrid maize seed yield under different water regimes and planting densities in an arid region of Northwest China. Two field experiments were conducted at the National Field Scientific Observation and Research Station on the Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province of China (37°52′N, 102°50′E) from 2013 to 2016. In the first experiment, six planting densities were set as 6.75, 8.25, 9.75, 11.25, 12.75, and 14.25 plants/m2 from 2013 to 2015. In the second experiment, there were 12 treatments in 2015, with three irrigation levels (full irrigation, 2/3 of full irrigation, and 1/3 of full irrigation) during the growing season, and four planting densities (8.25, 9.75, 11.25, and 12.75 plants/m2). Specifically, 1/3 of full irrigation was replaced by 1/2 of full irrigation in 2016. But, the rest of the irrigation levels were consistent with 2015. Some parameters were collected in both experiments, including the soil water content, evaporation, aboveground biomass, grain yield, and weather data. After that, the planting density factors were introduced to modify the normalized water productivity and harvest index in the AquaCrop-KR model. The calibration results showed that there was a parabolic relationship between harvest index and planting density, which first increased and then decreased. There was an increase in the water sensitivity indexes of harvest index at the vegetative, flowering, and reproductive stages, as the planting density increased. In addition, the normalized water productivity showed a unimodal change with first increased and then decreased with the increasing cumulative normalized crop transpiration. By contrast, the maximum of the normalized water productivity decreased with the increasing planting density, whereas, there was an increase in the corresponding cumulative normalized crop transpiration. The validation results showed that the modified AquaCrop-KR underestimated the grain yield by 5%, compared with the measurements, with the determination coefficient, relative root mean square error, average relative error, modeling efficiency, and agreement index were 0.87, 0.079, 0.057, 0.750, and 0.94, respectively. It infers that the modified model can be used to simulate the grain yield of hybrid maize. This finding can also provide a theoretical reference to predict the crop yield under different water regimes and planting densities.
Abstract: The special microstructure of loess has often posed a great risk on the slope in the loess areas. The loess structure can suddenly collapse, due to the complete loss of strength, particularly when the loess is wetted by water or subjected to a strong earthquake. The loess slope can usually be triggered by the slope surface erosion under the action of rainfall. The local failure of the slope body can often occur under heavy rainfall. There is a serious threat to the overall stability of the slope. For instance, hundreds of slope shallow failures have occurred in the Chinese Loess Plateau every year, as one of the regions with the thickest loess deposition in the world. The loess slope shallow failure can cause the loss and destruction of land sustainable productivity in the loess region. Fortunately, the slope protection with vegetation can be expected to alleviate the current slope shallow failure. A reasonable numerical simulation has been used to analyze the mechanism of root reinforcement soil, providing a strong theoretical basis for the application of slope protection with vegetation. This study aims to explore the protection time effect on planting alfalfa on the loess slope with shallow failure. The example was set as the loess slope with the alfalfa in different growth periods (0, 60, 90, 120, and 150 days). The rainfall infiltration was also considered in this case. A series of tests were carried out using the indoor planting of PVC pipe soil samples, including the quick direct shear tests, consolidated undrained (CU), and unconsolidated undrained (UU) triaxial tests. The physical and mechanical parameters were measured for the root-soil composite under different conditions. The slope stability was analyzed using the infinite slope model with the plant roots and the numerical simulation. The results show that three stages were divided for the loess slope under different conditions in the process of shallow failure. Firstly, a shear yield plastic zone parallel to the slope surface was formed at the maximum infiltration depth of precipitation. Secondly, there was a small amount of soil in the middle and upper position of the slope surface, due to the tension action. Thirdly, the shear yield zone gradually moved along the slope surface toward the slope shoulder. The loess slope was in a stable state under natural conditions. The potential sliding surface was at a deep position inside the slope. Therefore, the rainfall infiltration was attributed to the potential sliding surface of the slope transferring from the inside of the slope to the maximum infiltration depth of rainfall. The soil strength gradually increased in the shallow portion of the slope with the growth of vegetation on the slope. The potential sliding surface of the slope gradually shifted to the inside of the slope. The slope stability coefficient increased with the growth of vegetation, according to the strength reduction of numerical simulation. A comparison was made to determine the slope stability coefficient from the infinite slope model and the numerical simulation. The loess slope was in a stable state, when the plant roots grew to 1.0 m, either under natural or rainfall conditions, whereas, in an unstable state, when the plant roots grew to 0-0.8 m under rainfall conditions. The slope stability coefficient went down and then gradually increased with the growth of vegetation. The overall trend was all the same. The herbaceous plants were used to significantly inhibit the loess slope surface erosion under rainfall conditions, particularly with the extension of the growing period. Consequently, the herbaceous roots can be expected to improve the stability of the loess slope. Once the growth time of herbaceous plants reached 150 days, the loess slope surface erosion was effectively prevented for the better stability of the loess slope. Therefore, the first five months of herbaceous plant growth can be the key period to improving the stability of the loess slope in this case. The finding can provide the theoretical reference and application for the shallow failure protection of the loess slope in the sustainable development of the loess areas.
Abstract: Rocky desertification and water and soil loss are prominent ecological problems in karst area of Southwest China, which restrict the development of social economy. At present, the coupling relationship between rocky desertification and soil loss has not yet systematically proven, and how the interaction of rocky desertification intensity evaluation factors-vegetation coverage, soil layer thickness and bedrock exposure rate affects soil loss is ill-informed. Based on the investigation of the current situation of rocky desertification, the RUSLE model, spatial association index Getis-Ord Gi* analysis, Spearman correlation analysis, geographic detector and other methods were used to calculate the soil loss status in karst area of Guizhou Province(103°36′-109°35′E、24°37′-29°13′N), identify the distribution of cold and hot zones, quantify the relationships between rocky desertification intensity evaluation factors and soil loss, and analyze the interactive effects of factor combination on soil loss. The results showed that: 1) The soil erosion in karst area of Guizhou was dominated by moderate and micro erosion, with a total of 65 469.32 km2, accounting for 58.71% of the total study area, and with an average soil loss rate of 17.69 t/(hm2·a). Erosion hot zones (major prevention and control area) were mainly in the relatively underdeveloped areas in western Guizhou, such as the eastern part of Bijie City, the western part of Anshun City, the central part of Liupanshui City and the junction of Bijie and Liupanshui, and the total area of erosion hot zones was 31 617.18 km2, accounting for 28.35% of the total study area; while erosion cold zones (slight area) were mainly in relatively economically developed areas such as Zunyi in northern Guizhou and Guiyang in central Guizhou, with a total area of 22 533.26 km2, accounting for 20.21%. 2) Soil loss had a significant negative correlation with vegetation coverage and soil layer thickness, and had a significant positive correlation with the exposure rate of bedrock. The correlation coefficients were -0.067, -0.022 and 0.025, respectively. The relationship between rocky desertification and soil loss was a complex nonlinear relationship. Among them, the relationship between vegetation coverage and soil loss was optimal by a cubic curve function. The relationship between soil layer thickness and soil loss could be described by an exponential function. And the arcsine function had the highest goodness of fit between the exposed rate of bedrock and soil loss. 3) The explanatory power of the evaluation factors of rocky desertification intensity on the spatial differentiation of soil loss was the highest by vegetation coverage, followed by bedrock exposure rate and soil layer thickness. The interaction effects of the factor combination on soil loss were all non-linear enhancement, among which the interaction between the exposed rate of bedrock and vegetation coverage had the strongest explanatory power for the spatial difference of soil erosion, playing a leading role in the spatial differentiation of soil erosion. It was followed by the thickness of soil layer and vegetation coverage, with the least explanatory power for exposed rate of bedrock and soil layer thickness. The results provide valuable information for the coordinated prevention and control of water and soil erosion and rocky desertification in karst area.
Abstract: Continuous rotary tillage has posed a great challenge to the high yield, efficiency, and quality cultivation of japonica rice. The purpose of this study was to explore the effects of tillage methods and plant growth regulators (PGRs) on the photosynthetic characteristics and the yield of high-quality japonica rice under continuous rotary tillage. The experimental materials were selected as the Suijing18, Kendao12, and Sanjiang6 under the field conditions from 2018 to 2019. Deep tillage (DT) and rotary tillage (RT) were performed during three rice-growing seasons. An investigation was then made to determine the effects of two tillage practices on the yield formation of high-quality japonica rice. At the same time, three PGRs Diethylaminoethyl caproate (DA-6), 6-benzylaminoadenine (6-BA), and spermidine (Spd) were sprayed at the flag leaf expansion stage, in order to analyze the effects of PGRs on the yield formation and dry matter transport characteristics of high-quality japonica rice after the full heading stage. Clear water was used as the control. After that, an analysis was made to clarify the regulatory effects of deep tillage and PGRs on the yield formation and photosynthetic matter production characteristics of high-quality japonica rice in the middle and late growth stages. The results showed that the DT treatment significantly increased the biomass, leaf area index, population growth rate, and stem-sheath matter transport capacity after the full heading stage, while the leaf SPAD (Soil and Plant Analyzer Development) value, and net photosynthetic rate at the full heading and wax ripening stage, but prolonged the duration of green leaf area after the full heading stage, and increased the effective panicle number per square meter, grain weight per panicle, 1 000-grain mass, harvest index, and grain yield under different tillage practices, compared with the RT. Specifically, the yield increased by an average of 5.15%-14.54% in two years. In PGRs, the 6-BA spraying greatly contributed to the increase in yield. The reason was the increase in the net photosynthetic rate and SPAD value after the full heading stage, and the seed setting rate, harvest index, grain number per panicle, and grain weight per panicle. There was an average yield increase of 4.93%-13.88% in two years, compared with the CK. The interaction between tillage practices and PGRs presented significant effects on harvest index and yield at maturity stage. Among them, the highest yield was achieved in the treatment with DT×6-BA, in terms of the interaction effect. Therefore, the increased yield was attributed to the duration of green leaf area after full heading and increased biomass, ratio of grain to leaf, net photosynthetic rate, and SPAD value after the full heading under the premise of a higher effective panicle number. The formation of high light efficiency population after the full heading, the number of grains per ear, and harvest index all increased to varying degrees. As such, the synergy and complementarity of yield characters were realized to promote the yield. The second yield was achieved in the DT×DA-6 treatment. Furthermore, the yield of RT×6-BA treatment was 8.83%-13.88% higher than that of RT×CK in two years. To sum up, the one-time deep tillage and foliar spraying 6-BA in the continuous rotary tillage rice field can be expected to improve the photosynthetic matter production capacity and the yield of high-quality japonica rice. A sustainable tillage system and effective cultivation measures can then be taken to improve the high yield and efficient cultivation of high-quality japonica rice in this region.
Abstract: Plastic film mulching and drip irrigation have been the main measures to cope with the water resources shortage for better crop productivity in the arid region of Northwest China. This study aims to explore the dynamic response of root distribution and yield of seed-maize to the plastic film mulching and irrigation amount under drip irrigation. The field experiments were conducted in the Shiyang River Basin located in the arid region of Northwest China in 2017 and 2018. Six treatments were set, including two levels of film mulching (full-mulching (M1) and non-mulching (M0)), and three levels of irrigation amount (WF, WM and WL: 100%, 70% and 40% of the irrigation water requirement, respectively). The distribution of soil water, the heat and root length density were monitored during the seed-maize growing season, whereas, the aboveground dry matter and yield were monitored in the mature period. The results showed that the average soil moisture contents of 0-60 cm soil layer were 0.21, 0.18, 0.16, 0.20, 0.19, and 0.17 cm3/cm3, respectively, under the M1WF, M1WM, M1ML, M0WF, M0WM, and M0ML treatments at 75 day after sowing (DAS). It indicated that the soil moisture content of 0-60 cm soil layer increased with the increase of irrigation amount under the same film mulching condition. Specifically, the soil moisture content of the 0-60 cm soil layer under the M1WF treatment was higher than that under the M0WF treatment in the same irrigation condition. The soil moisture contents of the 0-60 cm soil layer under the M1WM and M1WL treatments were lower than that under the M0WM and M0WL treatments, respectively. Film mulching significantly increased the soil temperature by 1.4-3.4℃ before 75 DAS, and there was no effect on the soil temperature after 75 DAS, indicating that the temperature-increasing effect of film mulching mainly appeared during the early growth stage. The root length density decreased with the deepening of soil depth under different film mulching and irrigation treatments in the various growth period of seed maize. Furthermore, 86.3%-96.7% of the roots were distributed in the 0-60 cm soil layer at 95 DAS of seed maize. The root length density was higher than 1.0 cm/cm3 in the 0-30 cm soil depth and 0-15 cm from the horizontal direction of the plant base, while lower than 1.0 cm/cm3 outside the spatial range. The root length density at 10 cm soil depth under WL treatment was 19.6%-32.5% lower than that of WF and was 0.2%-41.9% higher at deeper layer at various growth period, which showed that full irrigation was conducive to the root growth in shallow layer, while water deficit was conducive to the root growth in deeper layer. The yield and aboveground dry matter increased with the increase of irrigation amount. And the root length density at 10 cm soil depth under M1 treatment was 4.4%-69.2% higher than that of M0 treatment under different irrigation treatments, and the yield was 24.9% higher. The aboveground dry matter and yield of seed maize were closely related to the root length density at the 0-20 cm soil depth at the 75 DAS and 95 DAS, where the correlation coefficients were more than 0.883 and 0.804, respectively. Consequently, the favorable soil environment can be expected to promote the root growth for the aboveground growth of seed maize. The finding can provide a theoretical basis to implement the irrigation and film mulching measures in the Shiyang River Basin.
Abstract: A long-term in situ measurement cannot fully meet the requirements of soil nitrate measurement in recent years, due to the high cost and the inability. In this study, a measurement method was proposed to collect the soil solution using the titanium sintering filter cartridge, in order to detect the nitrate concentration in the soil solution under near-infrared spectroscopy. Correspondingly, the detection device was also designed in this case. Therefore, it was demonstrated that the nitrate was suitable for the analysis at 1 250 to 1 860 nm. The commercially available Near-Infrared (NIR) Light-Emitting Diode (LED) products were combined with the 940, 1 050, 1 200, 1 310, 1 350, 1 450, and 1 550 nm NIR LED. Simulated experiments of soil solution collection were carried out using self-made soil columns. Titanium sintering filter cartridge was selected as the soil solution sampler to collect the soil solution. The results show that the soil solution collection was positively correlated with the water content of the soil, but negatively correlated with the burial depth and the clay content of the soil. It infers that the titanium sintered cartridge was suitable for sandy or clayey soils with low clay content. Once the soil moisture content exceeded 20 %, the collection time was selected as 30 min. But the collection time needed to be extended, when the moisture content was low. A systematic evaluation was made to consider the volume of solution required for the test chamber and the vertical distribution characteristics of soil nitrogen. More importantly, the optimal collection time of the soil solution was required over 60 min, where the burial depth was 10 to 40 cm. In addition, the comparative tests confirmed that the titanium sintered cartridge presented a greater capacity for soil solution collection than the LLYQ-P02 soil solution sampler, suitable for lower soil moisture contents. Finally, the BP neural network was trained using a Bayesian regularisation, with the voltage data at different wavelengths as the input layer and solution nitrate-nitrogen content as the output layer. Specifically, 70 % of all data were randomly used as the training set and the remaining 30 % as the validation set to complete the training of the nitrate-nitrogen prediction model. The feasibility and stability of the detection device were tested through the performance tests (including stability, resolution, dynamic response, and field comparison tests). The results show that the voltage tended to increase with the increasing nitrate concentration, while the voltage was lower at 1 310, 1 450 and 1 550 nm. Therefore, the presence of a large absorbance confirmed that the absorption at 1 310 and 1 550 nm was influenced by the nitrate and at 1 450 nm by water. The Pearson's correlation coefficients were 0.997 and 0.995 for the training and test set of the nitrate nitrogen prediction model, respectively. The root mean square error of prediction was 3.43 during this time. The improved prediction model of nitrate nitrogen performed the best prediction than before. The relative deviations of the measuring device from the ion electrode and the colourimetric were 5.9% max. and the absolute deviation was 9 mg/L max., respectively, fully meeting the requirements for the in-situ monitoring of nitrate nitrogen in soil solution. The new device can serve as fully automatic, non-destructive (no interference with the original soil structure), long-term, and in-situ, not available with the current nitrate ion electrodes and soil nutrient quick testers. An optimal combination of operational performance was achieved, where the standard deviation of the output voltage was 0.006, the resolution was 2.3 %, and the dynamic response time for a single wavelength was 1.4 s during the long-term operation of the detection device. The finding can provide a feasible solution for the long-term automatic measurement of soil nitrate nitrogen and the construction of a water-fertilizer integration system.
Abstract: This study aims to explore the effects of different vegetation blanket covers on the nutrient and enzyme activities of open-pit coal mine soils in arid areas. The research object was taken as the Dafeng mine in Ningxia Helan Mountains Nature Reserve. Three vegetation blanket covers were set as straw, straw-coir, and coir. Some parameters were measured, including the organic carbon, total nitrogen, total phosphorus, urease, protease, and alkaline phosphatase, as well as the peroxidase and ecological stoichiometric ratios of the mine soils. The results showed that: 1) The vegetation blanket covered with different materials increased the organic carbon and total nitrogen content of the surface layer of the soil. Specifically, the maximum content was achieved in the soil covered by the coir vegetation blanket. By contrast, there was no significant change in the total phosphorus content, and the organic carbon. Among them, there was the total nitrogen, and total phosphorus content of the soil from 10 to 20 cm. Only the organic carbon content of straw-coir vegetation blanket cover soil decreased with the increasing soil depth in the vertical direction. There was no change in the organic carbon, total nitrogen, and total phosphorus of the rest of the vegetation blanket-covered soil, as the soil depth increased. 2) The vegetation blanket cover with different materials increased C/P and N/P ratios. The maximum was also the soil covered by the coir vegetation blanket. There was no significant change in the C/N. Moreover, there was no change in the C/N, C/P and N/P, as the soil depth increased. 3) The urease and alkaline phosphatase activities of the vegetation blanket-covered soil were significantly higher than those of the bare ground. The soil from 0 to 10cm was greater than that from 10 to 20cm. There was no change in the protease activity with the depth of the soil layer. Furthermore, the catalase activity was significantly higher only in the soil from 0 to 10cm of the coir vegetation blanket than in the soil from 10 to 20 cm. 4) The correlation between soil enzyme activity and environmental factors showed that the total phosphorus of soil and C/N were the main influencing factors to govern the enzyme activity, whereas, the N/P and the total nitrogen of soil were the main factors to drive the enzyme activity. The nutrient content of the soil surface layer increased after the three vegetation blankets were mulched, which also increased the C/P and N/P of the soil surface layer, thus promoting surface soil enzyme activity. In addition, there was a significant positive correlation (P<0.01) among the four enzyme activities. The coir vegetation blanket was more capable to provide soil nutrients, compared with the straw and straw-coir vegetation blankets. The redundancy analysis of soil enzyme activities and environmental factors showed that the total soil phosphorus of soil and C/N were the main influencing factors to govern the enzyme activities, while the N/P and the total nitrogen of soil were the main factors driving the enzyme activities. Consequently, the vegetation blankets cover increased the nutrients in the surface layer of the soil. At the same time, the enzyme activity was also promoted in the surface soil. The findings can provide a strong theoretical basis to implement the ecological restoration of vegetation blankets for the open-pit coal mine soil in arid areas.
Abstract: Weeds have been one of the main factors to affect the growth of crops in the seedling stage. Timely weeding is a necessary measure to ensure crop yield. An intelligent field weeding equipment can also be a promising potential deployment in the unmanned farm system at the current stage of intelligent agriculture. Effective recognition of crops and weeds has been a high demand to promote the development of intelligent weeding equipment. Previous research was focused mainly on object detection and semantic segmentation using deep learning. A great challenge is still remained in the performance of target detection, in the case of overlap images between the crops and weeds under the complex field. The reason was that the different target areas cannot be further divided when the generated anchor box overlaps in a large area. The pixel level annotation can also be required to train the semantic segmentation, where the data samples cannot be easy to obtain. The weak real-time performance cannot be conducive to practical application. In this study, an improved model was proposed using shifted window Transformer (Swin Transformer) network, in order to enhance the accuracy and real-time performance of crop and weed recognition. The specific procedure was as follows. 1) A semantic segmentation model of corn was established for the real and complex field scene. The backbone of the model was the Swin Transformer architecture, which was denoted by Swin-Base. The full self-attention mechanism was also adopted to significantly enhance the modeling ability in the Swin Transformer using the shift window division configuration. Self-attention was then calculated locally in the non-overlapping window of the segmented image block, where the cross-window connection was allowed. The computational complexity of the backbone presented a linear relationship with the image size, thereby elevating the inference speed of the model. The hierarchical feature representation was constructed through the Swin Transformer for the dense prediction of the model at the pixel level. 2) The unified perceptual parsing network (UperNet) was used as an efficient semantic segmentation framework. Among them, the feature extractor was the Feature Pyramid Network (FPN) using the Swin Transformer backbone. The multi-level features obtained by Swin Transformer were used by the FPN to represent the corresponding pyramid level. An effective global prior feature expression was added in the Pyramid Pooling Module (PPM). Better performance of semantic segmentation was achieved using the fusion of the hierarchical semantic information. The Swing transformer backbone and UperNet framework were combined into one model through the Decoder-Encoder structure, denoted by Swin-Base-UN. 3) The structure of the Swin-Base backbone was improved to enhance the inference speed. The number of network parameters and calculation cost were reduced to decrease the number of hidden layer channels, headers, and Swin Transformer blocks. Therefore, four improved models were generated, including the Swin-Large-UN, Swin-Small-UN, Swin-Tiny-UN, and Swin-Nano-UN. The model size and computational complexity of improved models were about 2, 1/2, 1/4, and 1/8 times of Swin-Base-UN, respectively. 4) Taking the segmentation of corn morphological region as the case study, an improved image morphological processing combination was established to recognize and segment all the weed regions in real time. The segmentation of corn was also used to segment the weeds. The weed pixel annotation was removed from the training data of the model. As such, a large number of annotation data at the pixel level was obtained in the semantic segmentation of the improved model, compared with the original one. A comparison was made on the performance of all models in training, validation, and testing. Consequently, the Swin-Tiny-UN was determined as the best model to achieve the optimal balance between accuracy and speed. Specifically, the mean Intersection over Union (mIoU) and mean Pixel Accuracy (mPA) on the test set were 94.83% and 97.18%, respectively, which increased by 3.27 and 4.71 percentage points, respectively, compared with the RestNet-101-UN using traditional Convolutional Neural Networks (CNN) backbone. The inference speed of the model was achieved by 18.94 frames/s, which increased by 24.36% than before. The best model of semantic segmentation was superior to the traditional one, in terms of the region segmentation accuracy, pixel recognition accuracy, and inference speed. The image segmentation showed that the improved model can be expected to accurately recognize and segment maize and weeds in complex field scenes. The average correct detection rate of the improved model was 95.04% for the video stream data in the process of field work, whereas, the average detection time per frame was 5.51′10-2 s. Consequently, the improved model can be expected to detect the corn and weeds in the process of field work, indicating higher accuracy and real-time performance under practical application conditions. The findings can provide a strong reference for the development of intelligent weeding equipment.
Abstract: Wheat production is closely related to the food security in world. The yield forecast of wheat can provide a strong reference for the agricultural production and management, particularly for the decision-making on the rural land policy and grain market. Among them, the number of wheat ears per unit area is one of the most important indicators to estimate the wheat yield, including the crop phenotypic parameters, yield prediction, and field management. However, the traditional image processing and manual counting of wheat ears cannot fully meet the large-scale production in recent years. Particularly, the manual counting is cumbersome, labor-intensive, and highly subjective. It is a high demand to improve the detection accuracy of the traditional image processing. A generalized model is also required for a lot of experience, the robustness to lighting, and sufficient soil conditions in complex scenes. Much effort has been made to combine the deep learning for the detection and counting of the wheat ears per unit area, particularly with the rapid development of crop phenotype research. It is still lacking on the recognition accuracy of dense and occluded wheat ears under complex conditions. Taking the image of wheat ears per unit area as the research object, this study aims to accurately obtain the number of wheat ears per unit area using the improved YOLOX. Firstly, a simple sampling frame was designed to directly realize the counting of wheat ears per unit area. The corner detection network was trained to identify the sampling frame, further to extract the unit area of wheat. The Content-Aware ReAssembly of Features (CARAFE) map was used in the feature fusion layer of the wheat ear detection network. Secondly, the sampling was replaced with the up-sampling in the YOLOX-m model. The iterative attention feature fusion module was also used to increase the extraction of spatial information and semantic information of wheat ears. Thirdly, the wheat canopy images captured by the smartphone were taken as the research object. The images were selected at the wheat grain filling and mature stages under three weather conditions of clear, overcast, and cloudy. A total of 600 images of wheat ears without the sampling frame (image resolution of 4 000 × 3 000 pixels) were collected, where the original images were randomly cropped into the 3 072 images of wheat ears of 800 × 800 pixels. Fourthly, the dataset was augmented after the mirroring and rotation operation, where the image data of the training set was expanded from 3 072 to 9 216 images. There were 218 wheat ears images with the sampling frame (image resolution was 4 000 × 3 000 pixels). Among them, the sampling frame was contained 350-520 target wheat ears. Finally, the performance of the model was evaluated using the precision, recall, Average Precision (AP), F1 score, Frame per Second (FPS), determination coefficient (R2) and Root Mean Square Error (RMSE). The experimental results show that the improved YOLOX-m model was significantly improved the detection performance of dense and occluded wheat ears. Specifically, the AP value was improved by 10.26, 8.2 and 1.14 percentage points, respectively, compared with the SSD, CenterNet, and original YOLOX-m model. Consequently, the wheat ears per unit area were accurately detected and counted in the natural environment. The finding can provide a strong reference for the intelligent counting of wheat ears in the actual production of wheat yield prediction.
Abstract: Crop yield has been one of the most prominent issues in the world in recent years. However, crop diseases have posed a great threat to crop yield. It is a high demand to timely and accurately detect crop disease types and the degree of damage. The manual recognition can rely only on skilled technicians. But, the visual fatigue of humans can easily lead to reduce the accuracy rate. The current machine learning cannot consider the correlation between the attributes in the data set, resulting in low recognition accuracy. In this study, a network model was proposed to identify the damage degree of multiple crop diseases using deep transfer learning and improved RegNet. The model contained four aspects as follows. Firstly, an online data enhancement was carried out at the input side of this model. Nine strategies were selected for the data enhancement, such as the HSV color variation, grayscale transformation, and Gaussian noise. The diversity of data samples increased while reducing the time and space for the data set collection expansion. As such, the over-fitting of the network was alleviated during this time. Secondly, the Ef?cient Channel Attention (ECA) mechanism was introduced into the feature extraction layer of the model for the cross-channel interaction. The model was then improved to extract more subtle features, particularly for the crop disease features. As such, a higher accuracy of recognition was achieved for the crop disease damage, which increased by 1.5 percentage points, compared with the original model at the same model size. The F1 score also increased by 2.2 percentage points, compared with the previous one. In addition, a multi-scale feature fusion was introduced into the classification layer of the model. A spatial pyramid pooling was adopted to highly improve the accuracy of the model. The degree of crop disease damage was classified at different scales, especially for the fine-grained features. Correspondingly, the accuracy of crop disease damage recognition increased by 2.4 percentage points, and the F1 score increased by 1.5 percentage points more than before. Finally, deep transfer learning was used to optimize the overall performance of the model. The convergence speed was accelerated to improve the generalization ability of the model. The recognition accuracy was improved by 2.7 percentage points, compared with the strategy without deep transfer learning. The experimental results show that the improved RegNet network model achieved 94.5 percentage points accuracy on the dataset of crop disease damage level, which was 10.4 percent higher than the original one. The recognition accuracy of the improved model was improved by 2.1, 6, 3.7, and 1.6 percentage points, respectively, while the model sizes were reduced by 35.8, 458.1, 35.4, and 52.1MB, respectively, compared with the commonly-used classification network models, such as ResNet50, VGG16, InceptionV3, and ConvNeXt. Consequently, higher accuracy of recognition and smaller model size were achieved in the improved classification model, compared with the rest. The better performance of feature extraction and stronger classification ability were also obtained for the fine-grained features during this time. The finding can also provide a promising way to identify the crop disease types and the degree of damage.
Abstract: Digitization has been one of the significant directions in the rural land governance reform in the future. However, it is still lacking in the logical concepts and framework for the digital governance of rural land. In this study, a three-dimensional system framework of "demand-baseline-function" was established using the perspective of the transaction cost. An emphasis was also put on the construction of the digital system for land acquisition and relocation. Firstly, the basic, core and conflict needs of the participants were clarified ranging from the government, land users, and the original land stakeholder. Secondly, the bottom line was defined as the legal, spatial, and regulatory governance. Thirdly, the digital system was classified to design various digital realities. The future functional modules were selected to entirely reduce the transaction costs, thereby integrating the multiple sharing systems for the overall operational efficiency. In addition, Zhejiang Province of China was selected as the experimental area for the system design. The reason was that Zhejiang Province has been the representative region in the digital reform of land governance in recent years. Nevertheless, there was a high transaction cost in the process of land acquisition and relocation. It is also a high demand to effectively build a digital system during this time. As such, the actual system was designed to combine with the improved the digital framework. The result showed that the "demand-baseline-function" framework effectively guided the development and design of the "intelligent land acquisition and demolition" digital system in the actual application situation. The transaction costs were also reduced to fill the logical blank for the previous system of land digital governance. The demand analysis demonstrated that the improved system provided the port to fully meet the basic and core needs of the government, land users, collectives, and farmers. The information asymmetry, discourse game, and conflict transmission effectively reduced the transaction cost of the game between the subjects. The bottom line was clarified for the implementation boundary of the law and space of the land requisition and relocation process. The whole supervision system of land requisition and relocation was constructed to stabilize the land requisition and relocation environment. The functional analysis revealed that the improved system coordinated the actual and upgrade function of the "intelligent land acquisition and demolition" digital system. The logical framework effectively reduced the negotiation and decision cost, while the implementation and supervision cost, as well as the management and sunk costs in the land acquisition and demolition. Therefore, the "demand baseline function" framework can provide a strong reference for the transaction cost in the digital reform of land governance. Anyway, the underlying construction logic of the framework can also be applicable to the other areas without the digital construction guidance, providing for the most general transaction cost in the rural land governance. In addition, the logical framework of the system can also provide a strong reference for the digital transformation of rural land governance in the future, in order to improve the digital level of land space and the modernization of governance capacity.
Abstract: Typical behavior of herd pigs is one of the most important indicators to evaluate the adaptability of pigs to the environment. This study aims to improve the accuracy and efficiency of herd behavior recognition. A novel recognition system was proposed for the typical behavior of herd pigs (such as eating, lying, standing, and fighting) using an improved frame differential-deep learning. The video image data was collected from two pens of group-fed Landrace pigs. A total of 18 Landrace pigs aged 50~115 days were selected with nine pigs per pen. 1117 video frames were collected. Then, a total of 4468 images were obtained after image enhancement as the dataset. Firstly, five models of typical deep learning (including Faster-RNN, SSD, Retinanet, Detection Transformer, and YOLOv5) were selected for posture detection. An optimal model of posture was determined after the comparative analysis. Secondly, a pixel feature extraction was implemented on the pig activity to promote the traditional frame differential approach, such as, the slow motion pigs were easy to miss the detection, and more holes were detected in the pigs. Finally, the proportion of fighting activities (PFA) and proportion of fighting behavior (PFB) were used to optimize the pig fighting behavior in the recognition model. An optimal behavior model was determined during this time. The result showed that the average accuracy of YOLOv5 reached 93.80% for the typical posture detection of group-reared pigs. Among them, the model size was 14.40 MB, and the detection speed was 32.00 f/s, indicating that the detection speed fully met the demand for real-time posture detection. Once the Intersection over Union (IoU) threshold was set as 0.50, the mean average accuracy of YOLOv5 increased by 1.10, 3.23, 4.15, and 21.20 percentage points, respectively, and the model size was reduced by 87.31%, 85.09%, 90.15%, and 97.10%, respectively, compared with the Faster-RNN, SSD, Retinanet, and Detection Transformer models. Meanwhile, the original frame difference was expanded from the frame difference of 2, to 4 after experimental analysis. The improved frame difference was utilized to effectively eliminate the fine holes that were produced by the slow-moving pigs and background interference, such as lighting, as well as the outstandingly retained pixel characteristics of vigorous movement activities, when the pigs were fighting. The better performance of detection was achieved close to the actual movement targets. The pig eating, lying, and standing behaviors were directly discriminated by the single-frame posture images of pigs. Furthermore, 100 video frames containing fighting behavior (frame speed of 30 f/s, duration of 5~60s) and video frames without fighting behavior were selected to verify the accuracy of the pig fighting behavior recognition. The reason was that the pig fighting behavior was a continuous process. The test results showed that the best average value of typical behavior recognition accuracy was 94.45%, when the two optimized indexes of PFA and PFB were set as 10% and 40%, respectively. Therefore, the high accuracy, small model size, and fast recognition can provide technical support and strong reference for the accurate and efficient identification of typical behaviors of herd pigs in group breeding.
Abstract: A leaf area has been one of the most important indicators of photosynthesis, transpiration, respiration, and yield components of plants. The physiological and ecological indicators can dominate plant growth, fruit development, and quality formation. The purpose of this study is to measure the leaf area of cotton by the thermal infrared and visible images. An accurate, convenient, stable, and nondestructive approach was also proposed for the early leaf area measurement in physiological and ecological research. The experimental cotton was cultivated in the greenhouse of the East Field Experimental Base of Cotton Research Institute, Chinese Academy of Agricultural Sciences from July to September 2021 (On July 20th, the cotton seeds were soaked in the hydrogen peroxide for two hours, and then sown in the pots, one cotton seedling per pot, totally 15 pots). When the cotton was in the seedling stage (August 25th, the number of euphylla was 1-4), the infrared imager T660 was used to take photos at 14:00 pm, where the radiation difference among soil, leaf and shadow reached the outstanding effect. Five pots of cotton seedlings were randomly selected to capture the images. Both thermal infrared and visible images were obtained eight from each pot. Taken together, 16 images were obtained from each cotton pot. A hand-held standard board with a circular reference was used to hold the inclined leaves in each capture, in order to reduce the distortion of cotton leaves in the image. Hough circle detection was used to extract the region of reference substance in the visible image. The GrabCut was used to extract the leaf regions in the thermal infrared image. The capture and thermal infrared images were firstly adjusted by the FLIR tools. After that, the pixel values of leaf regions of the two images were assigned the weights and then superimposed. The color filling was carried out using a 4-connected field, in order to eliminate the isolated pixels near the leaf regions. The pixel value of the leaf area was defined after the color filled the connected area. The leaf regions were converted into white (pixel value is [1, 1, 1]), whereas, the rest was converted into black ([0, 0, 0]), according to the pixel values of the leaves. The following step was to convert the 3-channel image with the leaf information into a single-channel image. Then, the contour was extracted from the reference substance and the leaf regions. The leaf area was then calculated, according to the multiple relationships of the number of the pixels. The study-cutting weighing and Image Pro Plus image were used to measure the five pots of cotton seedlings for eight times after capture. The correlation analysis showed that there was a significant linear correlation (r1=0.992, P1<0.01; r2=0.996, P2<0.01). The difference between the method proposed in this paper, weighing, and Image Pro Plus method are all in the 0.67%-6.73% range. Additionally, the higher stability of the measurement was achieved, where the average coefficient of variation was 0.782%. Therefore, an accurate, stable, rapid, and nondestructive method can provide a promising convenience for physiological and ecological research in the early leaf area measurement.
Abstract: The phenotypic information of soybean has been one of the most important indicators for the variety selection of soybean. Most research has been focused on soybean pods for phenotypic traits at present. However, the phenotypic information of soybean plants can also be a very important indicator for soybean seed breeding. Furthermore, the current manual measurement cannot fully meet the large-scale production in recent years, due to the time and labor-consuming. More recently, computer technologies have been started to automatically acquire the soybean phenotypic parameters. For instance, some shallow machine learning and image description were used for the image feature extraction and target detection, such as the Scale-Invariant Feature Transform (SIFT), Histogram of Oriented Gradient (HOG), and Support Vector Machine (SVM). Although the automatic acquisition of phenotypic data was realized to a certain extent, the high generalization ability can be a high demand suitable for practical application scenarios. In this study, an improved model was proposed to rapidly and accurately acquire the soybean plant phenotype using Re-YOLOv5 and area search algorithm. The circular smooth labels were also introduced in the Re-YOLOv5 to process the angle information for the detection of the rotating objects. The angle regression was then converted into a simple classification. As such, the rotating objects were accurately detected to reduce the redundant information in the detection area during object detection. In addition, the Coordinate attention mechanism was added to the Neck part of YOLOv5 (CSL). The cross-channel information was then obtained to capture the position and orientation information. As such, the improved network was used to more accurately locate and recognize the soybean branching than before. The weights greatly contributed to the YOLOv5 on the processing of feature-related parts. More importantly, the original 3х3 convolution kernels were placed in the backbone with a RepVGG block structure. The feature information was then fused to extract using different convolution modules. The information extraction of the overall structure was enhanced for the parallel fusion of the multiple convolution layers while reducing the number of model parameters. Taking the detected branch as the search area, an area search algorithm was also proposed to input into the algorithm, in order to extract the relevant information of the stem nodes in the area, and then connect the nodes in sequence. Thus, the soybean skeleton was reconstructed to obtain phenotypic information about soybean. The experimental results showed that the improved Re-YOLOv5 performed better to detect the rotating objects in various phenotypic indicators, compared with the YOLOv5. Specifically, the mAP of the improved Re-YOLOv5 increased by 1.7 percentage points, the number of parameters decreased by 0.16M, and the detection accuracy of stem nodes was improved by 9.9 percentage points. An excellent ability was also achieved to detect the small targets suitable for the acquisition of the soybean plant phenotype information. Among them, the average absolute errors of plant height, and the number of stem nodes and branches were 2.06 cm, 1.37, and 0.03, respectively, fully meeting the accuracy requirements of actual collection. At the same time, the detection area search algorithm can also be expected to accurately locate the stem nodes on each branch for the single-, double-, and complex-branched soybean plants, and then reconstruct an accurate soybean skeleton. Anyway, the improved model can also be used to accurately and efficiently acquire the phenotypic information of soybean branch angle, and soybean plant type. The finding can provide a strong reference for the subsequent acquisition of phenotypic information during soybean production.
Abstract: An intelligent question-answering of agricultural knowledge can be one of the most important parts of information agriculture. Among them, named entity recognition has been a key technology for intelligent question-answering and knowledge graph construction in the fields of agricultural domain. It is also a high demand for the accurate identification of named entities. Furthermore, the Chinese named entity recognition can be confined to the location and semantic information of characters, due to the long length of agricultural entity and complex naming. Therefore, it is very necessary to improve the recognition performance in the process of named entity recognition, particularly for the sufficient capture of character position, contextual semantic features, and long-distance dependency information. In this study, a novel Chinese named entity recognition of agriculture was proposed using EmBERT-BiLSTM-CRF model. Firstly, the Bidirectional Encoder Representation from Transformers (BERT) pre-trained language model was applied as the layer of word embedding. The context semantic representation of the model was then improved to alleviate the polysemy, when pre-training the depth bidirectional representation of word vectors. Secondly, the language masking of BERT was enhanced significantly, according to the characteristics of Chinese. An Entity-level Masking strategy was utilized to completely mask the Chinese entities in the sentence with the consecutive tokens. The Chinese semantics was then better represented to alleviate the bias caused by incomplete semantics. Thirdly, the Bidirectional long short-term memory network (BiLSTM) model was adopted to learn the semantic features of long-sequence using two LSTM networks (forward and backward), considering the contextual information in both directions at the same time. The long-distance dependency information of text was then captured during this time. Finally, the Conditional random field (CRF) was used to learn the labelling constraint in the training data. Among them, the learned constraint rules were used to detect whether the label sequence was legal during prediction. After that, the CRF also utilized the information of adjacent labels to output the globally optimal label sequence. Thus, the output of the model was a dependent label sequence, but an optimal sequence was considered the rules and order. A focal loss function was also used to alleviate the unbalanced sample distribution. A series of experiments were performed to construct the corpus of named entity recognition. As such, the corpus contained a total of 29 790 agricultural entities after BIO labelling, including 11 057 crops, 8 121 pesticides, 4 505 diseases, and 6 107 pest entities, in which the training, validation, and test set were divided, according to the ratio of 7:2:1. Four types of agricultural entities from the text were identified, including the crop varieties, pesticides, diseases, and insect pests, and then to label them. The experimental results show that the recognition accuracy of the EmBERT-BiLSTM-CRF model for the four types of entities was 94.97%, and the F1 score was 95.93%. Which compared with the models based on BiLSTM-CRF and BERT-BiLSTM-CRF, the recognition performance of EmBERT-BiLSTM-CRF is significantly improved, proved that used pre-trained language model as the a word embedding layer can represent the characteristics of characters well and the Entity-level Masking strategy can alleviate the bias caused by incomplete semantics, thereby enhanced the Chinese semantic representation ability of the model, so that enabling the model to more accurately identify Chinese agricultural named entities. This research can not only provide arelatively high entity recognition accuracy for tasks such as agricultural intelligence question answering, but also offer new ideas for the identification of Chinese named entities in fishery, animal husbandry, Chinese medical, and biological fields.
Abstract: Rubber has been one of the most important cash crops in recent years. It is of great practical significance to segment the satellite images of rubber plantations using deep learning for agricultural refinement. In this study, a novel strategy was proposed to improve the residual network and its variant (ResNet-ve) for the segmentation. The study area was taken as the Rubber Plantation in Xuwen County, Zhanjiang City, Guangdong Province of China. The dataset was constructed using the Sentinel-2 multispectral satellite images as the data source. The OCRNet was used to incorporate an improved residual network. Inspired by Deeper Bottleneck Architectures proposed by Kaiming He, the modification strategy was established to modify path B in the Down Sampling module of each stage in the ResNet_vd middle layer. Specifically, the mean pooling module with 2×2 steps of 1 was replaced with a most-valued pooling module with 2×2 steps of 1, and then to add a 1×1 convolution before (called Deeper Bottleneck Pooling Architectures-like). The same modification strategy was applied to the other residual modules of the same stage, after which these modules were sequentially cascaded to form the improved stage. After that, the activation function was modified into the PReLU function to compare the network performance of the backbone network using the improved ResNet_ve. The improved residual network ResNet50_ve and basic ResNet50_vd network were used as the backbone networks of the four models. Among them, the student model was obtained to distillate the ResNet50_vd on ImageNet1k classification dataset using migration learning. A pre-trained model was then injected into the network training weight parameter for the modified ResNet_ve backbone network and ResNet_vd baseline backbone network to start the four networks. The results show that the ResNet50_vd network with the medium number of layers converged better than the ResNe101_vd network with the deeper layers on the training set of small-scale satellite images, and the OCRNet network on ResNet50_vd outperformed the DeeplabV3, DeeplabV3+, and PSPNet networks in all aspects. The OCRNet network with ResNet50_vd was used as a baseline for the subsequent experiments. The OCRNet with ResNet50_ve as the backbone network was achieved in the mIoU of 0.85, pixel accuracy of 97.87%, and a Kappa coefficient of 0.90 on the validation set. Therefore, an OCRNet with ResNet50_ve as the backbone network presented the best fineness of the internal boundary of the prediction graph among the four networks. There were also the least amount of time resources and the least number of parameters among the four networks. The OCRNet with the ResNet_ve as the backbone network was increased by 0.01 in the mIoU, and 0.01 in the Kappa coefficient, compared with the OCRNet with the ResNet_vd as the backbone network. By contrast, the accuracy metrics of the other three networks cannot be improved much using the ResNet_ve as the backbone network. The other three networks only improved the index data, in terms of the Kappa coefficient and mIoU index. Among them, the most obvious improvement was achieved in the DeepLabV3p. The OCRNet model with the improved residual network used the contextual and the deepest pixel features for the weighted splicing without the contextual information loss, while explicitly enhancing the pixel contributions from the same class of objects. As such, the background noise cannot be introduced, when extracting the multi-scale information. Thus, better performance was achieved in the accurate extraction of rubber distribution.
Abstract: Body temperature is an important physiological indicator to measure the health status of livestock and poultry. It is critical to a fast and accurate method of temperature measurement for disease monitoring and diagnosis. Some automatic temperature measurements can be expected to replace the traditional rectal temperature measurement commonly used in livestock and poultry production, due to the current time-consuming, laborious, and posture dependency. Usually, the rectal temperature cannot be directly taken by the automatic temperature measurement. It needs to collect the temperature of other body parts, and then establish the relationship with the rectal temperature for the core temperature. In this study, the automatic temperature measurement was divided into two types: the vivo and the vitro. A systematic review was also made of the technology and development history, in order to compare two types of temperature monitoring currently used in the livestock and poultry breeding industry (e.g., pig, cows, and chickens). An intelligent device (such as a capsule or chip) was normally implanted into an animal for long-term temperature monitoring in vivo temperature measurement, indicating the popular trend for high accuracy and stability. However, the invasive devices inevitably caused animal discomfort during the implantation process, which was harmful to animal welfare. In vitro detection was also divided into contact and non-contact temperature measurement. Specifically, the contact one was simple and easy to operate, but difficult to wear on the animal body, and highly sensitive to the complex environment of animal houses. The infrared-based temperature detection provided a non-invasive body surface temperature measurement, which was characterized by rapidity, high efficiency, and no stress. But, it was normally required for the temperature compensation between the body surface and thermal environment, due to the interference by environmental factors (e.g., temperature, humidity, CO2, light intensity, and ventilation). Therefore, the prediction model was mostly focused on the relationship between the core body temperature and measured temperature derived from the parameters. As such, these important points were necessary, whatever the automatic temperature measurement was used. It was a high demand to minimize the stress response of animals for the non-invasive monitoring of body temperature. A reliable prediction was then required to establish the monitoring temperature and the core temperature of animals. Correspondingly, the environment of livestock and poultry house was tunable controlled, as the changes in the monitoring temperature of animals. These methods have been widely used in animal farming for production performance, health, and behavior monitoring. Finally, the existing technology of automatic temperature measurement was summarized for the key points of improvement research. An emphasis was posed on the commonly-used infrared temperature measurement, due to its high efficiency, convenience, no stress, and easy detection of the automatic body temperature for animal groups or flocks. The infrared temperature measurement can be expected to dominate the promising research and application of body temperature monitoring on animal farms.
Abstract: The bioconversion technique is one of the important methods for producing environmentally friendly bioenergy from lignocellulosic biomass. The objective of this study is to explore the effect of different mechanochemical combined pretreatments on the enzymatic hydrolysis of corn stalks at room temperature. In this study, corn stalk was used as biomass material, lower load of NaOH with mass fractions 0, 1%, 2%, and 3% was used in the groups of NaOH pretreatment alone, the dry NaOH/ball milling combined pretreatment and the wet NaOH/ball milling combined pretreatment, respectively. The following 72 h enzymatic hydrolysis experiments for different pretreated corn stalks were carried out by using the enzyme CellicCtec2 (Novozymes, Denmark). The particle size, crystallinity, surface micromorphology, lignocellulosic composition, and the functional group changes of the pretreated corn stalk samples were systematically characterized. The effects of the different NaOH/ball milling combined pretreatments on samples' physicochemical properties on enzymatic hydrolysis yield and their correlations were further investigated and discussed in detail. The results showed that both dry and wet NaOH/ball milling combined pretreatment significantly improved the corn stalk glucose yield compared with NaOH pretreatment (P<0.01). And with the increase of NaOH mass fraction (from 1% to 3%), the glucose yield of corn stalk with dry and wet NaOH/ball milling combined pretreatment increased clear (P<0.01). When the mass fraction of NaOH was 3%, the glucose yield of the dry and wet NaOH/ball milling combined pretreatment reached 71.0% and 73.1%, respectively. The dry NaOH/ball milling combined pretreatment effectively reduced the particle size and crystallinity of the corn stalk, compared with the NaOH pretreatment. Once the NaOH mass fraction was 0, the particle size and crystallinity of the corn stalk treated by the dry NaOH/ball milling were the lowest, 15.8μm and 25.9%, respectively. But, the particle size and crystallinity of the corn stalk pretreated by the wet NaOH/ball milling were higher than those of the dry NaOH/ball milling combined pretreated samples. The cellulose mass fraction of different combined pretreatment samples gradually increased, with the increase of NaOH mass fraction. There was no significant difference in the cellulose mass fraction between the two pretreatment samples under the same NaOH loading conditions. The cellulose mass fraction was up to 48.5% in the wet NaOH/ball milling combined with pretreated samples, when the NaOH mass fraction was 3%. The lignin mass fraction decreased significantly with the increase of NaOH mass fraction (P<0.01). The lignin mass fraction of corn stalk with the wet NaOH/ball milling combined pretreatment was lower than that of dry ones. Once the NaOH mass fraction was 3%, the lignin mass fraction of the wet NaOH/ball milling combined pretreatment was the lowest at 14.9%. Regardless of the dry and wet NaOH/ball milling combined pretreatment, the enzymatic glucose yields were significantly positively correlated with cellulose mass fraction and average particle size D50 (P<0.01), and significantly negatively correlated with lignin mass fraction (P<0.01). The dry NaOH/ball milling combined pretreatment significantly reduced the crystallinity of the corn stalk, thereby enhancing the yield of enzymatic hydrolysis of the corn stalk to a certain extent (P<0.05). This study provides data support to help further reveal the mechanism of biomass mechanochemical combined pretreatment behind.
Abstract: Cost-effective bamboo strip composite materials have been developed with the low energy consumption, excellent product quality, and high utilization rate, due to the refinement, homogenization, and standardization of bamboo strip. However, there is the low interface compatibility between polar hydroxyl groups on the surface of bamboo strips and non-polar resin matrix. The purpose of this study is to fabricate the structural or sub structural bamboo strips composite materials. The alkali solution was used to treat the bamboo strips for the penetration of resin on the interface and the mechanical properties of composite materials. A systematic investigation was made to clarify the effect of NaOH alkali treatment concentration on the properties of bamboo strips and the epoxy resin composites. The bamboo strips were used as the reinforcement phase, whereas, the epoxy resin as matrix phase. The composites with an average content of 75% bamboo strips were then prepared by hot pressing. Four concentration gradients of NaOH solution were set in the treatment. The properties of bamboo strips and their epoxy resin composites were characterized by means of Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope (SEM), Thermogravimetric Analysis (TG), and Dynamic Mechanical Analysis (DMA). The experimental results showed that the alkali treatment efficiently removed some impurities, such as lignin, hemicellulose, and wax on the surface of bamboo strips, further to enhance the tensile strength and thermal stability of bamboo strips. SEM results show that the surface fiber morphology of bamboo strips tended to be regular after the proper alkali treatment. Specifically, the fine and smooth microstructure was conducive to the resin penetration. The polarity of bamboo strips first increased and then decreased with the increase of NaOH solution concentration. The crystallinity increased from 60.0% to 63.6% after treatment. The TG analysis demonstrated that there were the lower end degradation temperature of alkali treated bamboo strips, and the lower maximum decomposition rate, indicating the better performance of thermal decomposition. More importantly, the best properties were achieved at the concentration of NaOH solution of 2%, including the tensile property of bamboo strips, the interfacial bonding property with the epoxy resin, and the shear strength. Specifically, the tensile strength of bamboo strips, the shear strength of the composites increased by 52.11%, and 55.24%, respectively. The DMA test results showed that the bamboo strip/epoxy resin composites after the alkali treatment presented the better structural stability under dynamic load in the single frequency (1 Hz) test condition in the range of 30-90 ℃. Once the concentration was 2%, the maximum storage modulus of the bamboo strip/epoxy resin composite was 1.3 times that of the untreated. There was no outstanding difference of storage modulus before and after treatment in the range of 9-140 ℃. A downward trend was found in the loss modulus and loss factor of the composites after alkali treatment in the range of 60-140 ℃. Consequently, the alkali treatment can be expected to enhance the thermal stability and tensile strength of bamboo strips. The interface strength between bamboo strips and epoxy resin was improved, together with the static and dynamic mechanics of bamboo strips reinforced epoxy resin composite resin. The improved composites can also be used in the outdoor agricultural engineering, buildings, and outdoor gardens, in order to reduce the production cost and the comprehensive utilization rate of bamboo strips.
Abstract: Many environmental factors have posed an important impact on crop growth in a greenhouse. Among them, the temperature is often the dominated factor in the greenhouse production. Water is also suitable for the medium of heat transfer or storage. Most research has been focused on the active heat collection and release system using water circulation and heat storage for nighttime warming in the greenhouse. A fan-coil units-heat pump combined heat collection system (FUHPS) has been developed, where a heat pump has been added to the fan-coil units and heat storage pool for the heat collection (TSFU). A systematic investigation has been made to explore the performance under three modes of heat collection in different sizes of horticultural facilities. However, the water temperature of the storage tank cannot be raised by more than 12°C from the beginning to the end of the heat collection process in the field test. The reason was that the water temperature of the storage tank was not high enough to cause a small temperature difference between the water and gas during the heat release. As such, there was a relatively small Coefficient of Performance (COP) of heat release. Therefore, it is necessary to improve the heat release COP of the system. The initial water temperature of heat release can be expected to effectively improve the heat release performance of the TSFU. Furthermore, the heat release performance of the FUHPS with the same heat release mode can also be used to increase the initial water temperature of heat release. It is probable to reduce the actual water storage capacity of the heat storage pool. This study aims to improve the heat release performance of the FUHPS, and then further optimize the heat collection system. The actual water storage capacity was firstly calculated at the target water temperature. Secondly, an analysis was made to clarify the impact of water storage capacity on the heat release performance of the system. Thirdly, the exergy analysis was carried out under two kinds of heat collection modes and one kind of heat release mode, in order to determine the specific location and main reasons for the loss of exergy. Finally, optimization was proposed for each component of the FUHPS. The results show that the heat release power and COP of the optimized system were 27.1 kW and 6.2, respectively, which increased by 33.5% and 37.8% than before. The overall performance coefficient was also improved after optimization. The exergy analysis demonstrated that an excellent energy utilization quality was achieved in this case, indicating the highest exergy efficiency of the water pump. Specifically, the exergy efficiencies of the heat-collecting device and fan-coil units were 89.3%, 87.8%, and 60.1% under the fan-coil units' heat collection mode, combined heat collection mode of fan-coil units+heat pump, and heat-releasing mode, respectively. In addition, some consideration was made for the irreversible loss caused by heat transfer temperature difference. Nevertheless, the lowest exergy efficiency was obtained in the heat pump unit, which was the key point of the energy-saving transformation of the system. This finding can provide a new idea to optimize and improve the performance of the active heat collection and release technology.
Abstract: Electric heating drying system has been widely used for structural drying, sanitizing with heat, and space heating at present. The metal steel plate can often be the main material of the heating box and air duct of the dryer in the mechanical arrangement. Nevertheless, a large heat transfer coefficient can make it easy to lose heat, when converting the electric current to the heat in the system. The insulation material can normally be laid on the outer layer of the steel plate. However, the traditional configuration cannot recover the heat, although the heat loss can be prevented in this case. Alternatively, thermoelectric power generation has attracted extensive attention in the field of heat recovery, because it can directly convert temperature differences into electricity. In this study, an energy-saving mode was proposed to recover the heat of the dryer using a thermoelectric generator (TEG). A thermoelectric power generation system was designed and developed for the dryer to directly recover the heat. In addition to recovering the heat of the metal wall of the dryer, the thermoelectric cell was also used to recover the part of the heat of the hot air, resulting in a decrease in the hot air temperature. Therefore, the Fluent software was firstly used to simulate the temperature field of the dryer before and after the installation of TEG. The measured parameters were combined to evaluate the impact of TEG installation on the dryer. Secondly, the output electric energy was controlled to obtain stable electricity in the thermoelectric power generation device. The reason was that the cold end, hot end, and power generation performance of TEG fluctuated dynamically, due to the heating power. The STM32F334 was used as the controller to realize the DC-DC conversion function. The test was also carried out to verify the performance of raising and lowering the voltage of the controller. As such, the battery was charged to fully meet the requirements of the TEG for the heat recovery of the dryer. Finally, the test platform of TEG was built for the heat recovery of the dryer. A systematic evaluation was made of the hot air temperature of the dryer before and after the installation of TEG, as well as the parameter characteristics of the power generation system. The test results showed that the installation of TEG presented no outstanding impact on the dryer. The better performance of the dryer was achieved under different operating conditions of thermoelectric power generation. Specifically, the power regulator and frequency converter were utilized to control the heating power and the wind speed of the centrifuge. There was a significant variation in the output power of thermoelectric power generation, the consumption power of the water pump, and the net output power with the cooling water flow. Among them, the water pump was controlled by the DC power supply. Consequently, there was optimal water flow to maximize the net output power under the different working conditions. An optimal parameter combination was achieved, where the optimal water flow rate was 22.3 L/min, the pump power consumption was 6.4 W, the system output power was 31.8 W, the maximum net output power was 25.4 W, and the thermoelectric conversion efficiency was 3.9%, particularly when the heating power was 3.0 kW and the wind speed was 12 m/s. Anyway, the experiment verified the feasibility of the developed device. The finding can also provide a new idea for drying energy-saving technology.
Abstract: A relatively high proportion of vegetable waste is ever increasing in China in recent years, with the rapid development of agriculture. A large amount of spoiled vegetable waste also continues to accumulate. There is a serious threat to environmental health, due to a huge waste of resources. It is a high demand to treat this vegetable waste. Fortunately, anaerobic fermentation has been an important technical way to treat agricultural waste for clean energy. Meanwhile, the biogas slurry and biogas residue produced by fermentation can also be used as organic fertilizer to improve soil fertility. This study aims to clarify the effect of the additives on the thermostatic anaerobic fermentation and aerobic treatment of the mixed raw materials. The process was realized for the rapid conversion of biomass to biogas and biogas fertilizer. Firstly, the ratio of volatile solid (VS) was selected as 1:1:1 for the cow dung, tomato stems, and leaves. Three devices were utilized in the 0.56 m3 constant-temperature fermentation, including the no-adding, adding mass concentrations of 1 g/L urea, and 1 g/L plant ash. Among them, the total solid (TS) was 8%. The constant temperature batch was set as a fermentation temperature of (26±2)℃ and a period of 54 days during anaerobic fermentation. Secondly, the remaining biogas slurry was treated with the (30±1)℃ and 12 L/min aerobic aeration treatment for 8h. Some parameters were measured in the biogas production, including methane production, pH, electrical conductivity (EC), oxidation-reduction potential (ORP), total dissolved solid (TDS), volatile fatty acid contents (VFAs), NH+ 4-N contents change, biogas fertilizer biotoxicity, and nutrient contents. A comparison was then made to explore the effects of the combination of anaerobic fermentation with different additives and aerobic treatment of biogas slurry on the biogas and fertilizer production performance of the device. The results show that each addition after 28d before the reaction presented a significant effect on the systematic biogas production and methane synthesis. Specifically, the best performance was achieved in the urea group during the anaerobic fermentation phase. The cumulative biogas and methane production were 4 917, and 1 746.4 L, respectively, which increased by 91% and 128.7%, compared with the blank group, whereas, 12.6% and 69.4%, compared with the plant ash group. Furthermore, the methane volume fraction of 50% in the urea group and the total system biogas yield of 80% (namely 5 346 L) were all 5d earlier than that of the blank group. However, the total biogas production and total methane production in the whole cycle blank group were higher than in the other two groups. The fastest time was 1, 4, and 1h during the aerobic treatment phase, respectively, particularly for the complete biogas slurry ripening in the blank groups, plant ash, and urea groups. In this case, the germination indexes (GI) were 98%, 124.5%, and 100.4%, respectively, and the total dissolved solids (TDS) were 5 670, 5 350, and 7 010 mg/L, respectively, while the volumes of NH+ 4-N were 734.4, 538.1 and 862.1 mg/L, respectively. In summary, the best biological effectiveness and production quality of the biogas slurry were achieved in the urea group system. The standard is still needed for the nutrient supplement, or concentrated treatment, compared with the mixed liquid fertilizer. This finding can provide a strong reference to improve the biogas and fertilizer production quality of anaerobic fermentation, in order to reduce the secondary environmental pollution caused by the biogas fertilizer.
Abstract: Biochar has been prevalently recognized as a readily available and environmentally friendly material in recent years. The excellent properties can be a developed pore structure, abundant functional groups, and outstanding cation exchange capacity. Therefore, biochar is often used for the fertilization and/or remediation of water and soil, as well as the long-term sequestration of carbon. Notably, the persistent organic pollutants (e.g. polycyclic aromatic hydrocarbons (PAHs)) are inevitably generated to stagnate in the biochar during the pyrolysis stage. The concentrations and characteristics of these PAHs in the biochar vary significantly, according to the biomass feedstock, pyrolysis temperature, and pyrolysis conditions. Macroalgae plays crucial roles in carbon cycling to slow down eutrophication in the coastal sea ecosystems. Macroalgae can be expected to serve as the precursors for deriving biochars, due to the short growth cycle, abundance, and accessibility. Moreover, the conversion of macroalgae biomass to biochar is beneficial to the waste management and resource usage of macroalgae. However, it is still lacking on the content and toxicity of PAHs in the macroalgal biochars. In this study, the macroalgal biochars were produced from the Sagassum vachellianum, Sargassum fusiforme, Sargassum thunbergii, Grateloupia turuturu, Chondria crassicaulis, and Ulva pertusa at different pyrolysis temperatures (200, 300, 400, 500, and 600 ℃) under oxygen-limited conditions. Sixteen typical PAHs in the macroalgal biochars were extracted and determined using the Soxhlet extraction combined with gas chromatography-mass spectrometry (GC-MS). Their toxicities were evaluated in this case. The results showed that the PAHs were widely distributed in all tested macroalgal biochars. Specifically, the abundance of PAHs in the biochars first increased and then decreased, as the pyrolysis temperature increased. There was the lowest (78.2 μg/kg) total concentration of PAHs in the C. crassicaulis biochar that was prepared at 600 ℃ among the macroalgal biochars. By contrast, the highest (2 244.2 μg/kg) was achieved in the G. turuturu biochar prepared at 300 ℃, indicating the most abundant naphthalene and phenanthrene. The redundancy analysis revealed that there were different effects of pyrolysis temperature on the concentration and proportion of each PAH in the macroalgal biochar. The contents of PAHs in the macroalgal biochars were all lower than the limit value of EBC-AgroOrganic grade (4±2 mg/kg) stipulated in the European Biochar Certificate (EBC, Version 10.1). There were mainly composed of 2 and 3 rings for the PAHs in the macroalgal biochars that were prepared at the pyrolysis temperatures of 200℃-600℃. The 4-ring PAHs were presented in all the macroalgal biochars, whereas the 5- and 6-ring PAHs were detected only in some macroalgal biochars, in which the proportion was very low. In addition, the macroalgal biochars exhibited various toxic equivalence quantity of benzo[a]pyrene (TEQBaP) at different pyrolysis temperatures. This change was attributed to the content, ring number, and type distribution of PAHs in the macroalgal biochars. There was the lowest (0.196 μg/kg) TEQBaP of the C. crassicaulis biochar that derived at 600 ℃ among the tested macroalgal biochars. By contrast, the highest (46.151 μg/kg) was also achieved in the S. thunbergii biochar that was derived at 400 ℃. The TEQBaP of the macroalgal biochars was lower than that of biochars reported previously. The energy consumption of pyrolysis temperature and yield were combined to determine the biochar remediation effect and similar potential environmental risks. Biochar materials with a lower pyrolysis temperature can be selected to provide important guidance for the production and application of macroalgal biochars, thereby improving the utilization of macroalgae.
Abstract: The large-scale breeding level of livestock and poultry industry in Hubei Province has been significantly improved, and the amount of straw resources has been increased year by year. Returning agricultural wastes to the field can not only reduce agricultural non-point source pollution, but also reduce the application of chemical fertilizers. Based on relevant statistical data and literature, this study collected the amount of livestock and poultry (i.e., pigs, beef cattle, dairy cows, sheep, broilers, layers) in stock, market and growth cycle, and the planting area and economic yield of various crops (i.e., the low hilly area in southeastern Hubei, the low hilly area in northern Hubei, the mountainous area in northwestern Hubei, the plain area in central Hubei, and the mountainous area in southwestern Hubei). Based on the statistical data from 2019 to 2020, We calculated the nutrient supply of livestock and poultry waste, and further evaluated whether the current situation of livestock and poultry breeding in Hubei Province exceeded the maximum allowable amount of soil carrying livestock and poultry waste. According to the ratio of straw to grain of different crops and nutrient content of straw, we analyzed the nutrient resources and the theoretical nutrient returning amount of crop straw. The land carrying capacity index of livestock was the highest in Northern Hubei, reaching to 0.35-0.78. The land carrying capacity index of Central Hubei was only 0.17-0.54, indicating that there would be a large space to develop livestock and poultry breeding. In 2019, the nutrient resources of livestock and poultry waste in Hubei Province were 368 900 t N, 140 300 t P2O5 and 520 600 t K2O, respectively. Based on 65% of livestock manure and fertilizer returning to the field, the total nutrient returning to the field of livestock and poultry manure would be 239 800 t N, 91 200 t P2O5 and 337 700 t K2O, respectively, with the ratio of fertilizer replacement of 17.3%, 11.9% and 56.2%, respectively. The total amount of straw resources of main crops in Hubei Province was the highest in Central Hubei and the lowest in Northwest Hubei. At present, the nutrient resources of straw in Hubei province were 310 700 t N, 99 800 t P2O5 and 683 000 t K2O, and the proportion of theoretical fertilizer replacement were 22.5%, 13.1% and 114.0%, respectively. The livestock and poultry production in different regions of Hubei province did not exceed the local maximum carrying capacity. The livestock and poultry breeding volume in different regions of Hubei Province did not exceed the local maximum carrying capacity. The theory of returning major agricultural wastes in Hubei Province can reduce nitrogen fertilizer consumption by 39.8% and phosphate fertilizer consumption by 25.0%. The total K amount from agricultural wastes return to the field could theoretically meet the demand for potassium of main crops. By calculating the nutrient resources of the main agricultural wastes (i.e., livestock and poultry waste, and straw) in Hubei Province, we evaluated the potential of fertilizer reduction of agricultural waste returning to the field and the carrying capacity of livestock and poultry waste soil, providing theoretical basis and data support for agricultural green development in Hubei Province.
Abstract: The cropland can often be converted into non-grain agricultural production, or cropland conversion to non-grain unitization. However, some damage also occurs in the physical and chemical properties of soil, leading to a reduction of the cropland quantity, even threatening the security of the national food supply. Therefore, the consolidation of non-grain cropland for farming can be an important measure to realize the continuing farming of cropland. The consolidation zoning of non-grain cropland for farming is also of great significance to rapidly supplement the farmland resource, and then to improve the quality of farmland fertility and then restore grain production capacity. Taking the administrative village as the evaluation unit, this study aims to improve the scientific and rational zoning of the spatial layout for non-grain field consolidation. A zoning system was also constructed for the non-grain field consolidation integrating the land remediation suitability and urgency. Firstly, nine indicators were selected from the three dimensions of utilization status, site conditions, and tillage conditions. The suitability evaluation model was then constructed for the non-grain field consolidation. Secondly, the urgency evaluation model of non-grain field remediation was constructed using the non-grain ratio of permanent basic farmland, major grain-producing areas, and ecological red line areas. Finally, the suitability and urgency were evaluated on the field consolidation for the four-quadrant spatial zoning. Lingshui County was taken as a case area to carry out the zoning and remediation strategy of non-grain farmland consolidation. The results show that: 1) The core target of non-grain farmland consolidation was determined to restore the land for grain crop cultivation. The scale and quality of stable farmland were also improved to fully meet the regional farmland protection tasks and food supply. 2) It was much more instructive and reasonable for the four-quadrant remediation zoning scheme to integrate land suitability and urgency. The high-quality cultivated land was screened out after the suitability and urgency evaluation of consolidation, further clearing the priority of remediation. As such, the direction of re-cultivation was effectively clarified in the study area. 3) The non-grain farmland consolidation was divided into four types of areas, namely, the priority, the key, the reserve, and the restricted consolidation area. The proportions of non-grain farmland in those areas were 25.44%, 42.39%, 25.70%, and 6.47%, respectively. Differential non-grain field consolidation strategies can be utilized to recover the farming using the different combinations of tillage state, physical environment, and land utilization conditions. The findings can provide a strong reference for the decision-making on cropland protection and the spatial layout of the cultivated land.
Abstract: Cultivated land non-agriculturalization has been a major challenge for the food security in China. The spatial-temporal pattern and evolution of cultivated land non-agriculturalization can be one of the most important steps for the decision-making on land use. The high-resolution satellite images have been widely used in surface remote sensing monitoring. However, it is still lacking on the classification system of non-agricultural monitoring using remote sensing, due to the complexity and diversity of the cultivated land non-agriculturalization types. In this study, a classification system was proposed for the remote sensing interpretation samples of the cultivated land non-agriculturalization, in order to construct the corresponding remote sensing interpretation sample database. At the same time, a fast sample collection was also proposed to improve the efficiency and quality of the sample collection using geographical condition monitoring. As such, high temporal, spatial precision and attribute reliability were achieved to verify the feasibility and effectiveness of the classification system and sample collection. The Hubei Province of China was selected as the study area. Nine types of samples were collected in the cultivated land non-agricultural sample system. The geographical conditions covered the flatland, hill, mountain, high-mountain and other terrains. The sample library was formed after training the deep learning model. The Efficient Net deep learning network was selected to extract the spatial distribution of cultivated land non-agricultural in study area. The result showed that: 1) The sample collection using geographical condition monitoring performed the best in the attribute accuracy. The changing pattern was quickly and accurately located in the more efficient solution for sample collection. 2) The model accuracy was significantly improved, when the number of samples exceeded 5000. The accuracy was verified by the internal visual interpretation and field verification points in the verification area. The positive detection rates were 67.0 % and 76.5%, respectively, and the recall rates were 77.9% and 76.5%, respectively. 3) The sample classification system was also used to train the optimized model. There was a significantly improved accuracy of the non-agricultural cultivated land automatic identification in the study area, compared with the full factor sample training model. The positive detection rate of the five verification areas increased by more than 20 percentage points. Therefore, the classification system can be expected to improve the efficiency and accuracy of remote sensing monitoring of cultivated land non-agriculturalization using deep learning. The improved system can be applied to the seasonal remote sensing monitoring of cultivated land at the regional scale.
Abstract: Microbial preparation refers to the living microorganism as the main component, including inert carrier materials, nutrients, and other accessory ingredients. It is necessary to maintain the vitality and effectiveness of microorganisms in the biocontrol preparations for a long time, particularly in the development of biocontrol products. The storage stability of biocontrol agents can be a key factor to ensure the number of microorganisms and the biological control. Metschnikowia citriensis can be expected to efficiently control the postharvest green mold and sour rot caused by Penicillium digitatum and Geotrichum citri-aurantii on the citrus fruit, indicating its great application and development value. This study aims to develop antagonistic yeast biocontrol agents with a long shelf life and stable biocontrol effect. The wettable powder was also prepared with the M. citriensis as the main active ingredient. The single factor and mixing tests were carried out to optimize the accessory ingredient for the wettable powder. Then, the wettable powder was applied to the citrus fruits. An accelerated storage test was conducted to predict the storage stability of the preparation, and evaluate the control effect of the preparation on the main postharvest diseases of citrus under in vitro and in vivo conditions. The results showed that the carriers, wetting powder, and suspending agent were screened by the single factor test with the mixing test. An optimal combination of the preparation was achieved with the honeylocust powder of 5.69%, dispersing agent NNO of 8.74%, and freeze-dried powder of 85.57%. The number of viable yeast in the freeze-dried preparation reached 4.72×108 CFU/g, and the wetting time was 7.82±1.02 s, while the suspensibility was up to 71.56%±0.06%. The accelerated storage test demonstrated that better storage performance was achieved in the freeze-dried bioformulation. Among them, the wettable powder was stored at four temperatures. The deactivation rate constant of yeast gradually increased in the wettable powder, whereas, the death rate of yeast accelerated with the increase in storage temperature. The viable yeast population in the preparation was estimated to be 4.6×108 CFU/g, when the storage at 4℃ for one year. Therefore, there was an appropriate reduction of storage temperature for better storage ability. In vitro tests and fruit tests were carried out to learn the application effect of the preparation. The experiments showed that the wettable powder effectively controlled the occurrence of postharvest citrus fruit diseases. It was found that there was no significant change in the inhibitory effect of wettable powder on the postharvest pathogen and pigment production capacity of M. citriensis, compared with fresh yeast. Specifically, the inhibition zone reached more than 9 mm. Fresh yeast presented a remarkable control effect on the blue and green mold, and sour rot on the citrus fruits. The formulation reduced the incidence of three citrus postharvest diseases by 40%-70%. To sum up, the preparation treatment of M. citriensis can be expected to effectively retain cell viability and biocontrol efficacy. The wettable powder with the M. citriensis as the main active ingredient indicated a significant decrease in the incidence of postharvest disease on the citrus fruits. The finding can provide the theoretical and practical basis for the application of M. citriensis in the biological control of postharvest citrus diseases.
Abstract: A fast and accurate detection is one of the most important prerequisites for the apple harvest robots. However, there are many factors that can make apple detection difficult in a real orchard scene, such as complex backgrounds, fruit overlap, and leaf/branch occlusion. In this study, a fast and stable network was proposed for apple detection using an improved RetinaNet. A picking strategy was also developed for the harvest robot. Specifically, once the apples occluded by branches/wires were regarded as the picking targets, the robot arm would be injured at the same time. Therefore, the apples were labeled with multiple classes, according to different types of occlusions. The Res2Net module was also embedded in the ResNet50, in order to improve the ability of the backbone network to extract the multi-scale features. Furthermore, the BiFPN instead of FPN was used as a feature fusion network in the neck of the network. A weight fusion of feature maps was also made at different scales for the apples with different sizes, thus improving the detection accuracy of the network. After that, a loss function was combined with the Focal loss and Efficient Intersection over Union (EIoU) loss. Among them, Focal loss was used for the classification loss function, further reducing the errors from the imbalance of positive and negative sample ratios. By contrast, the EIoU loss was used for the regression loss function of the bounding box, in order to maintain a fast and accurate regression. Particularly, there were some different relative positions in the prediction and the ground truth box, such as overlap, disjoint and inclusion. Finally, the classification and regression were carried out on the feature map of five scales to realize a better detection of apple. In addition, the original dataset consisted of 800 apple images with complex backgrounds of dense orchards. A data enhancement was conducted to promote the generalization ability of the model. The dataset was then expanded to 4800 images after operations, such as rotating, adjusting brightness, and adding noise. There was also a balance between the detection accuracy and speed. A series of experimental statistics were obtained on the number of BiFPN stacks in the network. Specifically, the BiFPN was stacked five times in the improved RetinaNet. The ablation experiments showed that each improvement of the model enhanced the accuracy of the network for the apple detection, compared with the original. The average precision of the improved RetinaNet reached 94.02%, 86.74%, 89.42%, and 94.84% for the leaf occlusion, branch/wire occlusion, fruit occlusion, and no occlusion apples, respectively. The mean Average Precision (mAP) reached 91.26%, which was 5.02% higher than that of the traditional RetinaNet. The improved RetinaNet took only 42.72 ms to process an apple image on average. Correspondingly, each fruit picking cycle was 2.78 s, indicating that the detection speed fully met the harsh requirement of the picking robot. Only when the apples were large or rarely occluded, both improved and traditional RetinaNet were used to accurately detect them. By contrast, the improved RetinaNet performed the best to detect all apple fruits, when the apples were under a complex environment in an orchard, such as the leaf-, fruit-, or branch/wire-occluded background. The reason was that the traditional RetinaNet often appeared to miss the detection in this case. Consequently, the best comprehensive performance was achieved to verify the effectiveness of the improvements, compared with the state-of-the-art detection network, such as the Faster RCNN and YOLOv4. Overall, all the apples in the different classes can be effectively detected for the apple harvest. The finding can greatly contribute to the picking strategy of the robot, further avoiding the potential damage by the branches and wires during harvesting.
Abstract: The integrated light and simplified cultivation of water and fertilizer has been widely applied at the eastern foothills of Helan Mountain in western China. However, it is a high demand for the nitrogen nutrition of wine grapes at the current stage. This study aims to demonstrate the regulation of the foliar nitrogen on wine the grape 'Cabernet Sauvignon' during the veraison period, with the location in the Lilan Winery, Yongning County, Ningxia Hui Autonomous Region, China (38°28′N, 105°97′E). The test material was 8-year-old wine grape 'Cabernet Sauvignon'. A single-factor randomized block design was utilized with the number of blocks equal to the number of replicates. A total of six subjects were chosen for the experiment, including ammonium sulfate, calcium ammonium nitrate, urea, phenylalanine, glutamic acid, and control (water), which were reused three times each. Among them, 20 vines were used per replicate subject and 60 vines per treatment for a total of 18 plots. The amount of nitrogen fertilizer in each treatment was converted to 1.5‰ urea and other quality pure nitrogen. The foliage was firstly sprayed with nitrogen fertilizer three times (July 15, July 31, and August 13) during the veraison period. The photosynthetic indicators of wine grapes were then measured after ten days (August 22), including the net photosynthetic rate, transpiration rate, intercellular CO2 concentration, stomatal conductance, leaf area, water use efficiency, and chlorophyll. Once the wine grapes were ripe (September 23), the morphology and yield were determined, including the particle size, spike length, 100-grain weight, and yield plant. At the same time, the quality indicators of wine grapes were also determined in this case, including the soluble solids, titratable acids, tannins, anthocyanins, total phenols, and yeast assimilable nitrogen. A variance analysis was carried out on the measured photosynthetic, morphological, yield, and quality indicators, in order to evaluate the different treatments, photosynthesis, and quality indicators of wine grapes. Three principal components were then obtained to establish a comprehensive evaluation function. The scores were calculated and sorted for the optimal treatment. The result indicated that all five treatments improved the physiology and quality of wine grapes, compared with the control group. The best performance (up to 29.21%) was achieved by spraying ammonium sulfate on the soluble solids in the berries. Furthermore, the greatest synergy was also obtained in the chlorophyll and yeast assimilable nitrogen under the calcium ammonium nitrate, which increased by 20.22% and 41.95%, respectively, compared with the control. The best effect was obtained under the urea treatment for the net photosynthetic rate, particle size, 100-grain weight, titratable acid, and anthocyanin. Phenylalanine presented the best effect on the leaf area, stomatal conductance, tannins, and total phenols. Glutamic acid improved the morphology and yield of wine grapes. Specifically, the spike length and yield plant significantly increased by 13.61% and 12.66%, respectively, compared with the control group. Three principal components contributed 59.52%, 22.13% and 11.77%, respectively, compared with the nitrogen fertilizer treatment. Phenylalanine and urea gained the highest scores for ten indicators, such as the wine grape physiology and quality. The titratable acid was best treated with urea, indicating the best acid value of 0.68% in the production area. Moreover, the anthocyanin content was as high as 2.28 mg/g under the urea treatment, which was 10.14%-55.10% higher than the rest of nitrogen treatments. There was the best effect of Phenylalanine on the increasing tannin content, up to 19.88 mg/g, which was 5.63%-24.87% higher than that of the rest nitrogen treatments. By contrast, the total phenolic content was as high as 19.56 mg/g under phenylalanine treatment, which was 8.91%-27.34% higher than the others. In conclusion, foliar spraying phenylalanine and urea during the veraison stage can be expected to improve the physiological characteristics of wine grapes and the quality of berries. The traditional cultivation techniques can also be optimized to promote low nitrogen application efficiency. The finding can provide a strong reference for the wine grape production in mountain areas.
Abstract: An accurate forecast can be greatly contributed to the yellowfin tuna fishing ground in the western and Central Pacific. However, a large amount of fishery data, and high feature dimension have posed a great over-fitting on the various classification in recent years. The random forest parallel integration can be expected to achieve the excellent performance of the extreme gradient boosting decision tree algorithm. In this study, a hybrid integration model was proposed to combine the xgboost with random forest (XGBRF) with the random forest and extreme gradient lifting decision tree. The fishery production data was also collected from the operation data of 43 distant-water longline fishing vessels of China Aquatic Group in the western and Central Pacific (0°-30°S; 110°E-170°W) from 2008 to 2019, including catch information, such as amount, job date, as well as the job latitude and longitude. A comparison was performed on the fishery data, including the concentration of chlorophyll a, eddy kinetic energy, sea surface height anomalies, temperature and salinity of the 0-500 m mixed water layer. A total of 36 variable combinations were used as the original data set, including the Southern Oscillation Index (SOI), the Arctic Oscillation Index (AOI), the Pacific Decadal Oscillation Index (PDOI), and North Pacific Gyre Oscillation Index (NPGOI). The original data set was divided into the training set and test set after the screening and normalization of the variance expansion factor, accounting for 80% and 20%, respectively. The training set was used to train eight models, including classification and regression, logistic regression, k-nearest neighbor, adaptive boosting, gradient boosting decision tree, xgboost, random forest, and XGBRF. The five-fold cross-validation was used for each model to determine the optimal parameters. Finally, the model was verified to superimpose the actual fishing ground of the test set. The experimental results showed that: 1) There was a significant correlation between the catch per unit fishing effort and various variable factors. There was also a great decrease in the degree of collinearity between the variables that were filtered by variance inflation factor. 2) The XGBRF hybrid ensemble model also significantly improved the performance of XGBoost and RF models. Specifically, the highest accuracy rate and area under curve (AUC) were 75.39%, and 79.48%, respectively. The receiver operator characteristic (ROC) curve of the XGBRF model was closer to the upper left, indicating the best performance of the forecasting model than before. 3) The sea surface temperature was the most important factor to dominate the distribution of yellowfin tuna fishing ground, accounting for 7.573%. The temperature of the 300 m water layer was equally important for the yellowfin tuna, which was 7.369%. In addition, the greater impact was also found in the salinity of the 50-meter water layer, the SOI, the concentration of chlorophyll a, and the surface salinity. There was a relatively low influence of other large-scale climatic factors, except for the SOI. 4) There was only a small deviation between the fishing ground predicted by the XGBRF model and the actual fishing ground, indicating the high accuracy and reliability of the prediction. Overall, the XGBRF ensemble model performed the best on the fishing ground forecast of yellowfin tuna in the western and Central Pacific. The finding can also provide a strong reference for the fishing ground forecast.
Abstract: Fermentation is a key processing step for the quality of black tea. Tea polyphenols (catechins) are generally oxidized by the polyphenol oxidase and peroxidase to form the theaflavins and thearubigins. In this research, the Yinghong NO.9 of Yingde black tea was collected by the kind of one bud and two leaves. The data was collected during different black tea fermentation time using a portable near-infrared spectrometer and a Charge-Coupled Device (CCD) camera. A discriminant model was established for the black tea fermentation degree using near-infrared spectra, images, and the data fusion of spectra and images. Specifically, 204 samples of black tea at different fermentation time were collected to acquire the near-infrared spectrum and images. The content of tea polyphenols was determined using an ultraviolet spectrophotometer with a detection wavelength of 765 nm. The catechins concentration was measured by High-Performance Liquid Chromatography (HPLC) at a flow rate of 1 mL/min and detection wavelength of 278 nm. The contents of tea polyphenols and catechins decreased rapidly in the early period, tending to be flat at 4-5 h, and continued to fall off after 5.5 h. According to the changes in the tea polyphenols and catechins, the fermentation degree of black tea was divided into three stages: insufficient, moderate, and excessive fermentation. Savitzky-Golay smoothing was adopted to process the rough burrs of the original spectrum that were caused by noise interference. Then, the Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA) were applied to reduce the data dimensionality of near-infrared spectral variables, where the feature wavelengths were selected. Meanwhile, nine color feature variables were extracted from the images after shadow removal. Pearson correlation analysis between chemical components and color variables was conducted to extract the feature variables. In addition, the Principal Component Analysis (PCA) was employed to reduce the data dimensionality for the distribution of black tea fermentation samples. The PCA of spectral and image data showed the similar three fermentation stages were not separated significantly, indicating that PCA cannot effectively discriminate the fermentation stage. Finally, the discrimination models were established using the near-infrared, image, and their data fusion through Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM). The comparison of the model showed that the performance of nonlinear SVM models was better than that of LDA models under the same conditions, indicating the unbalanced process of black tea fermentation. Furthermore, a single sensor failed to discriminate the fermentation degree. There was less performance in the models using a single sensor, due mainly to the complex change of fermentation information. In general, the maximum accuracies were only 83.82% and 73.53% for the prediction set of the discrimination models using near-infrared spectra and images, respectively. The performance of the middle-level data fusion models was significantly improved, compared with the models founded on a single sensor, or the low-level data fusion. The reason was that the low-level date fusion brought the variables irrelevant to the black tea fermentation. Among them, better performance was achieved in the SVM discriminant model that was established by SPA extraction of spectral variables and Pearson correlation analysis extraction of image variables, with 97.06% and 95.59% accuracies of calibration and prediction set. Consequently, a rapid and nondestructive method can be used to evaluate the degree of black tea fermentation under the middle-level fusion strategy using near-infrared spectroscopy and computer vision. A theoretical foundation was laid to establish a grade model and discrimination of black tea fermentation degrees. The finding can provide an important basis for the detection and automation of black tea fermentation.
Abstract: Rural Revitalization in the countryside of China has been incorporated into the national development strategy. It is very necessary to learn from the experiences of the developed countries in the decision-making and practical approaches to rural development. Especially, there are great challenges in the process of rural revitalization. Among them, The Great Britain is first to realize the industrial revolution and urbanization in the world. There is no absolute poverty between the urban and rural areas after the integrated urban and rural development over the last 80 years. Specifically, there is no significant difference in the public facilities and service provision between urban and rural areas. Generally speaking, it takes a long term to achieve common prosperity for the urban and rural areas in the British. Instead, there are also some mistakes that suffered from enormous challenges in history. The rural revitalization policies in China can also be drawn some inspiration to learn the lessons from the mistakes and experiences of the British rural development policies. Therefore, this research aims to explore the policies and specific measures in the process of rural development using the literature and document review, as well as site visits. England was also selected as a case, where the population and economic activities were dominated in the UK. An emphasis was put on the flow of significant factors of production to the rural areas, and the rational space allocation in the process of social and economic transformation for the sustainable rural development of the countryside. The results show that rural development in England was a systematic approach guided by the government's policies, but operating in the market. The influence of government never disappeared, but without dominating rural development. By contrast, the market with high efficiency played a dominant role in the process. Four elements were available to be learned in China, including 1) the environmental protection was treated as a core issue; 2) equal development between the urban and rural without the negative impacts of policies on the rural areas via rural proofing mechanism as a base; 3) the rural markets in towns were the spatial hubs to intensively allocate the resources to save the cultivated land; and 4) the diversification of agriculture to lead the sustainable rural development as the goals. A systematic analysis was then summarized of the rural and agricultural policies in England. Three recommendations were proposed to realize rural revitalization in China, considering the social and economic background at present. They were 1) the delivery of sustainable consumption and production model to promote rural revitalization. The lessons of "environmental protection as a core issue", "diversification of agriculture", and "sustainable rural development as the goals" were the vital components of sustainable consumption and production; 2) the intensive development of townships and rural towns as a pivotal space, in order to promote the diversified development, while strictly protecting the cultivated land. There was also the primary policy in England, since the two countries were similar, in terms of the low level of agricultural land per capita in the world, and 3) the shortage of rural talents should be addressed to achieve endogenous development. It was not an issue in England, due to the development and urbanization stage. However, the outflow of talent is one of the critical challenges in rural China, such as a shortage of skillful talents, technologies, and capital investment. It is suggested to promote the "rural mid-classification" with the Chinese unique land ownership, in order to avoid the "rural gentrification" in western countries. Nevertheless, a rural training mechanism should also be established to improve the skill of local peasants. This finding can provide significant support to the policy formulation for integrated urban and rural development and the process of rural revitalization.
Abstract: Experience of rural transformation in developed countries can greatly contribute to following the laws of rural development in China. Therefore, the main purpose of this study is to propose some suggestions on the path of rural development under the uniqueness of Chinese rural areas. The process of rural transformation was also summarized to extract the common characteristics of rural development in developed countries. Literature and empirical analysis were made in this case. The results show that rural development in developed countries presented some common evolutionary characteristics, in terms of functional value, economic system, settlement space, social structure, and government policies. Specifically, the functional value of the rural was generally included in three stages: from the stage of the "productivism dominated by agricultural functions" to the "post productivism with the rapidly improved ecological and cultural functions", and finally to the stage of "urban and rural equivalence with coordinated development of multiple functions". There were some changes in the rural economic system. Specifically, the industry was dominated by the non-agricultural industry rather than agriculture. The business entities were small business owners, rather than farmers. The economic policies were focused on rural space management rather than agricultural subsidies. There was also a different social structure from the past. Social subjects were changed from the single to the collective. The social structure was changed from tightness to looseness. The social connections were changed from the closed to the open. The social values were changed from homogeneity to heterogeneity. Social management was changed from internal autonomy to external governance. Correspondingly, the overall scale of villages was reduced in terms of village changes, indicating the clustering of village layouts, the differentiation of village types, the hierarchies of villages, and the diversification of village spaces. More importantly, the rural policies were also keeping pace with the change of rural functions: the policy concept was the equalization of urban and rural areas, instead of the countryside serving the city; the policy content was focused on the comprehensive rural regional policies rather than single sectoral policies; the driving force was endogenous development, rather than just exogenous development; the implementation path was the multi-subject synergy rather than top-down. There was a significant difference in rural development, compared with developed countries. It infers that the individual farmers were the main body of rural development in China for a long time. In addition, there were still some difficulties over a long period of time, such as the urban-rural dual structure, single rural industry, the weak county economy, shortage of local jobs, deposited production factors, and hollow villages. The effective supply of food can be the primary and long-term task of rural construction, due to the national conditions of more people and less land. Meanwhile, there is the accelerated diversification of rural social mobility and the transformation of the spatial structure of settlements under the background environment of "new industrialization, informatization, urbanization, and agricultural modernization". Worryingly, there are still institutional obstacles to narrowing the gap between the urban and rural areas for comprehensive rural revitalization. A comparison was made between the rural characteristics in China and developed countries. Some suggestions were proposed for the development of China's rural. 1) The concept of urban-rural equivalence needs to be established for the rural multi-function. 2) Food security should be ensured on the road of agricultural modernization on a moderate scale. 3) The rural secondary and tertiary industries can be introduced in the small towns and industrial parks as the growth poles. 4) The rural space should be optimized with the shrewd shrinkage theory, in order to promote the efficient use of land resources. 5) The local agricultural culture should be consolidated to protect, inherit, develop and utilize. 6) The mechanism and policy should be innovated to activate the rural endogenous power using a regional development policy system.
Abstract: The fragmentation of cultivated land is widely known as one of the key factors restricting the improvement of cultivated land use efficiency and agricultural modernization and transformation in China. Since the year 2014, the central and local governments of China have tried to achieve the goal of reducing cultivated land fragmentation and managing cultivated land on a modreate scale by encouraging the transfer of land management right. However, most relevant studies have been conducted at the local or regional scales, while few studies have analyzed the fine-grained changes of cultivated land fragmentation from a national perspective, and the implementation effect of land management right transfer policy on reducing cultivated land fragmentation is also unclear. In this paper, based on long-term land use data, supplemented by landscape pattern index, trend analysis and dynamic panel model, we analyzes the temporal and spatial variation characteristics of China's cultivated land fragmentation from 1990 to 2020, and identifies its influencing factors near the implementation of land transfer policy (2008-2020). In terms of connotation, cultivated land fragmentation can be roughly divided into ownership fragmentation and landscape fragmentation. This paper focused on the former, that is, the landscape fragmentation of cultivated land (CLF). The results show that: (1) China’s CLF roughly presents a distribution pattern of low in the plain and basin areas and high in mountainous and plateau areas. Specifically, the CLF is relatively low in the Northeast Plain, the Huang-Huai-Hai Plain, the Middle and Lower Reaches of the Yangtze River Plain, as well as the Sichuan Basin, Junggar and Tarim Basin; while the cultivated land in the transition zone of the second and third-level topographic steps, as well as the Loess Plateau, Yunnan-Guizhou Plateau, and the Southeastern Hills, is relatively fragmented. (2) From 1990 to 2020, China’s CLF generally showed a changing trend of continuous fragmentation - improved fragmentation - fluctuating fragmentation. Specifically, from 2004 to 2013, the overall cultivated land showed a trend of landscape fragmentation. More than 70% of the counties had a significant increase in PD/LSI or a significant decrease in AI, which were concentrated in the Huang-Huai-Hai Plain, the Middle and Lower Reaches of the Yangtze River Plain, the Sichuan Basin, and the Guangdong-Guangzhou region. However, from 2014 to 2020, 70% of the provinces have improved the landscape fragmentation of cultivated land. Spatially, the counties with improved CLF, that is, the counties with significantly reduced PD and LSI and significantly increased AI, were mainly located in the the transition zone of the second and third-level topographic steps, the Loess Plateau, northwest Xinjiang, and the Guangdong-Guangzhou region. (3) The land transfer policy has significantly reduced the CLF. In addition, factors such as regional land use change, non-grained utilization of cultivated land, slope, and irrigation conditions are also important factors that affect the change of CLF across China. The purpose of this paper is to analyze the spatial-temporal variation characteristics of CLF in China from a nation-wide scale and reveal the impact of land transfer policies and other factors on CLF, which can provide a new research paradigm for the changes of regional CLF and different land use/ecosystem types.
Abstract: Study on the spatial pattern of carbon transfer and responsibility sharing of provincial scale grain trade has important practical significance for reasonably dividing carbon emission reduction responsibilities and exploring and formulating inter provincial collaborative carbon emission reduction strategies for food security. Using the cross-sectional data of 31 provincial administrative regions in China in 2020, based on the linear programming method of grain trade and the calculation model of carbon emission of grain trade, this article calculated the inter provincial grain trade and its carbon emission, and revealed its spatial transfer. The distribution characteristics of carbon emission responsibility of grain trade in each province were analyzed by using the calculation method of carbon emission responsibility sharing of grain trade. The main conclusions are as follows: (1) In the carbon emission pattern of inter provincial grain trade and grain trade, the export areas were mainly northeast, North China, northwest and central China, and the import areas were mainly southwest, South China and East China. In 2020, the total amount of grain trade in China was 15269.14×104t, Among the grain export areas, the northeast region has transported 71.2654 million tons to other regions, accounting for 46.7% of the total trade. North China has transported 26.1738 million tons to other regions, accounting for 17.1% of the total trade volume. The northwest region has transported 4.5551 million tons to other regions, accounting for 3.0% of the total trade volume. Central China has transported 50.6971 million tons to other regions, accounting for 33.2% of the total trade volume. (2) The carbon emission of grain trade showed the flow pattern of "North carbon to South and China carbon to west" in space, and the carbon emission of grain trade showed the characteristics of small flow from south to North and east to west. Hebei, Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan, Gansu, Ningxia and Xinjiang were the national grain carbon emission export areas, and the carbon emission flow of grain trade in the north-south direction was 9119.82×104t, and the carbon emission flow of grain trade in the east-west direction was 2229.49×104t. (3)In the process of carbon emission transfer of grain trade, the input area should bear greater responsibility for carbon emission reduction than the output area. Economically developed provinces have a relatively large share of responsibility, while those with smaller economies have relatively small responsibilities. The average proportion of carbon emission reduction shared by the output area was 29.5%, and the average proportion of carbon emission reduction shared by the input area was 70.5%. (4) In the principle of shared responsibility, the share proportion of Anhui, Heilongjiang, Jilin, Jiangxi, Inner Mongolia, Shanxi and Xinjiang in the export areas is low, and the share proportion of Gansu, Hebei, Henan, Hubei, Hunan and Ningxia is high. And put forward targeted optimization strategies to ensure regional food security, fair and reasonable distribution of regional carbon emission reduction responsibilities, and promote the realization of the "carbon peak, carbon neutral" strategy in the agricultural field and the win-win situation of food security.
Abstract: The scientific and overall delimitation of "three land spaces and three control lines" was an important prerequisite and foundation for the land spatial planning and land supervision, also was an important measure to implement the strategy of functional zones and build a new pattern for developing and protecting territorial space in China. Aiming at the problems of delineating "three land spaces and three control lines", such as disunity of the base map, inconsistency and crossing of the boundary, a technical route and optimization principles of permanent basic farmland layout were put forward based on overall delimitation of the "three land spaces and three control lines" and the Third National Land Resource Survey data, and the production-ecology-landscape indicators of comprehensive quality evaluation for permanent basic farmland were constructed. The comprehensive quality evaluation indicators were selected based on production function, ecological function, location condition of cultivated land, which were the three primary indicators. Each primary indicator included several secondary indicators, which were indicators of cropland quality, planting suitability, ecological protection importance, ecological regionalization, water environment risk, and cropland contiguity. Each indicator was assigned several classification threshold value and corresponding weight, so that each cultivated land parcal was evaluated and scored. The characteristic of the comprehensive quality evaluation method for permanent basic farmland is to choose water environment risk indicator, which considered the risk of water pollution from non-point source of cultivated land. Then the method was applied in Meihekou City. The resultes showed that: 1) The area of optimized permanent basic farmland was 91 680.82 hm2 with an increase of 1 290.69 hm2. The area of cultivated land quality of level 10 increased by 3523.99 hm2, and that of level 12 decreased by 2 324.85 hm2. The average area of permanent basic farmland patch increased from 1.91 hm2 to 2.61 hm2. After optimization, the area of permanent basic farmland was increased, the quality was improved, and the layout was more stable. 2) The 20.74 hm2 permanent basic farmland within the ecological red lines were kept as permanent basic farmland and the overlapped area was deleted from the ecological red lines, so they were not overlapped spatially. There were 1 388.47 hm2 permanent basic farmland within the urban development boundary which were removed from permanent basic farmland because their low quality. The high-quality permanent basic farmland still within the urban development boundary would be reserved and the overlapped area would be earsed from the urban development boundary, so that the three lines would keep spatially consistent. This method took food security, ecological protection and urban development into consideration. The spatial layout of agriculture, ecology and town space was optimized with coordination. It can provide a method for coordination of " three land spaces and three control lines" and compilation of land spatial planning under the new situation.
Abstract: Methane (CH4) is a potent greenhouse gas, and the concentration of CH4 in the atmosphere is still rising rapidly. Water-unsaturated lands are widely distributed in the world and have been proven to be important CH4 sinks. Improving the understanding of the CH4 uptake characteristics of different types of soils in response to certain environmental factors will help to improve soil CH4 uptake potential and then mitigate global warming effect. In this study, a soil laboratory incubation experiment was conducted to investigate CH4 uptake rates of salt-affected soil at different moisture levels (50% FC (field capacity), 75% FC and 100% FC) and salinity levels (LS1 =0.3 dS/m, LS2=1.0 dS/m, LS3=2.0 dS/m, LS4=3.2 dS/m, LS5=4.9 dS/m and LS6=6.2 dS/m). In order to verify the reproducibility of the laboratory incubation results under natural conditions, a field plot experiment was conducted to observe the CH4 uptake characteristics of soils with three soil salinity levels (PS1=non-saline, PS2=1.0 dS/m and PS3=5.0 dS/m) and their responses to soil moisture dynamics. The results of soil laboratory incubation showed that the cumulative CH4 uptakes of soils (including all six salinity levels) under 100% FC was 1.08-1.39 times those of the 75% FC and 1.27-1.72 times those of the 50% FC, respectively, indicating that soil CH4 uptake capacity increases with the increase of soil moisture within the range of field water holding capacity. Under all three soil moisture levels, as soil salinity increased from 0.3 to 6.2 dS/m, the cumulative soil CH4 uptake decreased with increasing soil salinity. Compared with non-saline soil LS1, the cumulative CH4 uptake of the highest salinity LS6 was significantly reduced by 42.6%, 52.3% and 55.1% under three soil moisture levels respectively. Compared with 50% FC, soil moisture with 100% FC aggravated the decrease of soil CH4 uptake capacity along the salinity gradient from 0.3 to 6.2 dS/m, and there was a significant interaction between soil moisture and salinity on soil CH4 uptake. The field plot experiment under the natural environment conditions validated the results in laboratory incubation experiment. During the observation period of the experiment, soil CH4 uptake rates were significantly positively correlated with soil moisture for all three soil salinity levels (P<0.01). Compared to the non-saline soil PS1, PS2 and PS3 salinity levels both led to significant increases in cumulative CH4 uptake by 17.4% and 40.2% respectively, indicating that high salinity significantly inhibited soil CH4 uptake. The results of this study, based on laboratory incubation and field experiments, indicate that the salt-affected soil is a CH4 sink, and its CH4 uptake capacity is significantly affected by soil moisture and salinity. Increasing the CH4 sink capacity of salt-affected soils should be added as a sub-goal into the water-salt regulation strategy of salt-affected soils that used to be aimed at improving agricultural productivity in salt-affected soils.
Abstract: Rocky desertification and water and soil loss are prominent ecological problems in karst area of Southwest China, which restrict the development of social economy. At present, the coupling relationship between rocky desertification and soil loss has not yet systematically proven, and how the interaction of rocky desertification intensity evaluation factors—vegetation coverage, soil layer thickness and bedrock exposure rate affects soil loss is ill-informed. Based on the investigation of the current situation of rocky desertification, the RUSLE model, spatial association index Getis-Ord Gi* analysis, Spearman correlation analysis, geographic detector and other methods were used to calculate the soil loss status in karst area of Guizhou Province(103°36′～109°35′E、24°37′～29°13′N), identify the distribution of cold and hot zones, quantify the relationships between rocky desertification intensity evaluation factors and soil loss and analyze the interactive effects of factor combination on soil loss. The results showed that: (1) The soil erosion in karst area of Guizhou is dominated by moderate and micro erosion, with a total of 65 469.32 km2, accounting for 58.71% of the total study area, and with an average soil loss rate of 17.69 t/(hm2·a). Erosion hot zones (major prevention and control area) are mainly concentrated in the relatively underdeveloped areas in western Guizhou, such as the eastern part of Bijie City, the western part of Anshun City, the central part of Liupanshui City and the junction of Bijie and Liupanshui, and the total area of erosion hot zones is 31 617.18 km2, accounting for 28.35% of the total study area; while erosion cold zones (slight area) are mainly concentrated in relatively economically developed areas such as Zunyi in northern Guizhou and Guiyang in central Guizhou, with a total area of 22 533.26 km2, accounting for 20.21%. (2) Soil loss has a significant negative correlation with the rocky desertification intensity evaluation indicators—vegetation coverage and soil layer thickness, and has a significant positive correlation with the exposure rate of bedrock. The correlation coefficients are -0.067, -0.022 and 0.025, respectively; which indicated that soil loss decreases with the increase of vegetation coverage and soil layer thickness, but increases with the increase of exposed rate of bedrock. The relationship between rocky desertification and soil loss is not a simple linear relationship, but a complex nonlinear relationship. Among them, the relationship between vegetation coverage and soil loss is optimal by a cubic curve function, R2=0.717, RMSE=3.172; the relationship between soil layer thickness and soil loss is optimal by an exponential function, R2=0.562, RMSE=4.804; and the arcsine function has the highest goodness of fit between the exposed rate of bedrock and soil loss, with R2=0.756, RMSE=4.318.(3) The factor detection results showed that the explanatory power of the evaluation factors of rocky desertification intensity on the spatial differentiation of soil loss is in the order of vegetation coverage > bedrock exposure rate > soil layer thickness. The interactive detection results showed that the interaction effects of the factor combination on soil loss are all non-linear enhancement, among which the interaction between exposed rate of bedrock and vegetation coverage (q=0.36) has the strongest explanatory power for the spatial difference of soil erosion, playing a leading role in the spatial differentiation of soil erosion. This was followed by the thickness of soil layer and vegetation coverage(q=0.23), with the least explanatory power for exposed rate of bedrock and soil layer thickness, q=0.13. The research results can provide theoretical reference for the coordinated prevention and control of water and soil erosion and rocky desertification in karst area.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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%.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 NH４-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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.