Abstract: At this stage, the domestic development of apple tree seedling planting machines is still in its infancy, and few planting machines had been developed for apple trees. Planting apple trees requires a large amount of labor, but the current shortage of labor is a prominent contradiction. The problem of non-mechanized planting of apple tree seedlings urgently needs to be solved. In order to solve the problems in the apple planting process under the current high density dwarfing orchard cultivation mode: low manual planting efficiency, unsatisfactory erection of fruit seedlings with the developed machines, and slightly higher coefficient of variation of plant spacing caused by the slippage of the clamping belt. Under the guidance of agricultural machinery and agronomic integration technology, a two-point clamping apple seedling planting machine was developed by a combination of extensive research, virtual design, prototype manufacturing, and field trials. This machine is based on the existing continuous ditching fixed-distance planting machine previously developed by the same team, and implements structural improvements and performance optimization. Firstly, the fruit seedling clamping device is improved, and the fruit seedlings are clamped at the upper and lower points. On top of the previous generation planting machine, a layer of clamping and conveying device is installed above the lower clamping and conveying device, and the upper and lower layers are perpendicular to each other. The distance is set to be 50cm, which is based on the comprehensive consideration of the height and status of the apple tree seedlings and the comparison of the planting effectiveness at different distances. The upper and lower clamping points work with each other during the transportation of apple tree seedlings to clamp the apple tree seedlings together. The apple tree seedlings will not rotate during operation and maintain a good initial status. It overcomes the problem that it is difficult to guarantee the initial angle of the tall seedlings relative to the ground because of the original one-point clamping, and significantly improves the perpendicularity after planting; Secondly, the transportation method is improved and the coefficient of variation of plant spacing is reduced. Considering that the trunk and bark of apple tree seedlings should not be damaged during the clamping and conveying process of the transplanter, the solution was still sought in the belt category. The initial idea was to add more tension wheels to change the belt slippage. However, the experimental results observed showed that this method makes almost no effect on reducing the belt slip rate. The timing belt can ensure that the apple tree seedlings are protected from damage during the clamping and conveying process, and it has a good transmission effect with little sliding. In order to improve clamping, the conveying mode adopts two synchronous belts to clamp and convey apple seedlings, which has a lower slip rate than the original V-belt clamping and conveying, and significantly reduces the coefficient of variation of the plant spacing; in addition, the power matching is optimized by the corresponding calculation formula. The depth-limiting wheel is installed to improve the stability of the planting depth, and the ditching machine, plant spacing control and other parts follow the first-generation machine plan. According to the planting requirements of different varieties of seedlings, the depth and width of the ditch can be adjusted, and the planting distance can also be adjusted as needed, and the adjustment is simple and convenient. Field tests showed that the qualified rate of apple seedlings planted by the machine is increased from 90.63% to 97.14%, the average planting depth qualified rate is increased from 91.43% to 93.33%, and the average plant spacing coefficient of variation is reduced from 5.03% to 3.74%, and the planting efficiency is increased from 11.89 plants/min to 12.26 plants/min, which was 37 times faster than that of manual planting. Compared with the existing machines, all performances have been improved, laying a solid foundation for the subsequent mechanization of apple's production.
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: Coating has widely been a commonly-used way to prevent corrosion failure of machinery parts. Coating of agricultural machinery parts is also conducive to improving the working reliability and service life of machinery. Drying is thus the key link of parts coating. However, improper drying can cause the reduction of film stress, film cracks, shrinkage, and pinholes. In this study, a side air supply drying room was designed suitable for the drying of agricultural machinery parts. The circulation of hot air was used to exchange the heat with the workpiece, further to reduce the moisture content of the coating, and finally to realize the curing of the coating. Computational fluid dynamics software was selected to numerically simulate the velocity and temperature field of the drying room for agricultural machinery parts. The working parameters of the drying room were also optimized to clarify the influence on the velocity and temperature field. As such, the working performance of the drying room was improved to clarify the influence of air supply mode, the number of air supply outlets, and air supply angle on velocity and temperature distribution. The results show that the unilateral air supply performed better than that of the double, indicating better gas circulation in the drying room. The uniformity of speed and temperature was better, particularly with the higher speed of return air and excellent gas circulation, when the number of air inlets was 8 rather than 6 and 10. Furthermore, the uniformity of speed and temperature was better, when the air inlet angle was 15° rather than 0° and 30°, where the return airspeed and temperature were higher. Therefore, an optimal parameter combination of drying room was achieved, where the unilateral side air supply, 8 air supply outlets, and air supply angle of 15°, indicating excellent gas circulation, as well as the better uniformity of speed and temperature. The measured values of each index were in good agreement with the theoretical optimization, where the temperature error was less than 1.68%, and the wind speed error was less than 33%, indicating reliable and effective simulation. At the same time, the overall coefficient of temperature inhomogeneity was less than 6%, where the designed drying room worked stably and reliably for agricultural machinery parts, fully meeting the design requirements. This finding can provide a strong reference for the design of the subsequent drying rooms.
Abstract: Current vertical disc hole seed-metering device has been limited to the low seed picking performance and high damage rate in recent years. In this study, a double-chamber turntable and vertical disc-hole seed-metering device was designed to combine the cotton precision hole sowing. First of all, the silo structure of seed picking and seeding was introduced to clarify the different work processes in the double warehouse, namely the completion of seed filling and clearing in the seed taking warehouse, then passing the cotton seed to the seeding warehouse through the warehouse transfer area, finally realizing the whole workflow of seeding in the seeding area. A double-bin separated structure was also designed for seed-carrying to reduce the damage of cotton seed. Secondly, a new equation was established for the time in a single seeding unit, thereby determining the way to take the side lying during precision hole-sowing. Specifically, the diameter of the seed disk was 220 mm, the length, width, and height of the seed hole was 9.2×6×4 mm, as well as the number of seed holes was 16. The seed tray was adopted the working mode of seeding from one side and different sides, in order to ensure that the seeding chamber was not interfering with the precision of seeding during the seed extraction stage. As such, the placement angles of the seed metering cavity and seed holes were staggered by a certain angle during design. Correspondingly, the cotton seeds were slid into the seeding chamber in time during the warehouse transfer stage, where the damage rate of cotton seeds was reduced significantly. Specifically, the steepest drop line was selected to calculate the falling angle of seeds, where the falling angle was determined to be 48°. Further, a mechanical model for the injury to the seed was established to analyze the force and movement state of cotton seeds in the warehouse transfer area, where the minimum seeding gap was 1.47 mm. As such, the optimal matching parameters of relevant components were determined to reduce the damage rate in the warehouse transfer stage. A mechanical model was also established to clarify the effect of seed hole offset angle and disc rotation speed on the seed picking performance in the seed collection area. Finally, Design Expert 8.0 software was used for the Box Benhnken design, where the rotating speed of the seed disk, the offset angle of the socket hole, and the seeding gap were the influencing factors. Subsequently, a three-factor three-level quadratic regression orthogonal test was carried out to optimize the single grain rate and the broken rate. Experiments show that the primary and secondary influencing factors of single-grain rate in the process of seeding were the offset angle of seed hole, the seeding gap, and the speed of seed disk. The better seeding performance was achieved in the combination of the seed disk rotation speed 23.9r/min, seed hole offset angle of 31.7°, seed metering gap of 2.08 mm, At this time, the single-grain rate was 96%, and the damage rate was 0.13%. Field experiments were also performed to verify the optimal combination. Correspondingly, the single-grain rate was 94.3% and the breakage rate was 0.09%, fully meeting the agronomic requirement of cotton precision sowing. This finding can provide a strong reference for the structural design of vertical disc hole seeding and metering device for cotton..
Abstract: Mechanizedfertilization has widely been one of the most important steps for the highyield of crops.In this study,a centrifugal side throwing fertilizer spreader was designedforthe lotus root field. Firstly, atheoretical model was established for the force of a single fertilizer particle on the blade. The main parameters were then determined for the particle motion,such as the rotating speed of the fertilizer tray, theblade inclination angle, and the blade deflection angle. Secondly, EDEM discrete element simulation software was utilizedto optimize the performance of the spreader.A single factor test was carried out, where the fertilizer feed rate and the above factors were taken as the influencing factors. The results showed thatthe weightdistributionof fertilizer increasedfirst and then decreasedin a single statistical area when taking the center of the spreader as the originalong the throwing direction. Specifically, the quality of fertilizer with the most distribution in a single statistical region was called the peak value, and the distance between this region and the fertilizer spreader was called the peak distance, to accurately quantify the distribution index of fertilizer. The rotating speed of the fertilizer tray and the blade inclination angle poseda significant impact on the peak value and peak distance of fertilizer distribution, whereas, the blade deflection angle and feed rate onthe peak value.An orthogonal rotation simulation test was carried out with the uniformity variation coefficient and peak distance as the evaluation indexes.It was found that there was an extremely significant influence on the uniformity variation coefficient (P<0.01), including the rotating speed of fertilizer tray,the blade inclination angle, the blade deflection angle,the interaction between them,the interaction term between the inclination angle of blade and feed rate,as well asthe quadratic term of blade inclination angle.There was an extremely significant effect on the peak distance (P<0.01), including the rotating speed of fertilizer tray, the blade inclination angle, and the quadratic term, the quadratic term of feed rate.Design-Expert software was utilized to optimizethe structure of the spreader.The blade structure parameters were then calculated to minimize the uniformity variation coefficient, when the peak distance was 10 and 21 m, the blade inclination, and deflection angle were 8.5°, 17.5°, 11.5°, and -1.9°, respectively.Subsequently, the simulation and actual fertilizer application were carried out to evaluate the performance of the fertilizer spreader with the optimalstructural parameters.The simulation results show that the uniformity variation coefficient, peak distance, and working width were 19.43%, 21m, and 29m, respectively,when the rotating speed of the fertilizer tray was 1 250 r/min, and the feed rate was 0.316 kg/s. By contrast, the specific parameters in an actual contrast testwere 21.95%, 18.6m, and 24.5 m, respectively, wherethe errors with the simulation were 12.95%, 11.42%, and 15.51%, respectively. A performance test of fertilizer spreader was carried out with large particle urea, compound fertilizer, and phosphorus fertilizer commonly used in lotus root field topdressing. The results showed that the operation effect of large particle urea was better at 1 300 r/min, feed rate of 0.15kg/s, and operation width of 24m. At this time, the uniformity variation coefficient was 24.56%. The analysis of variance showed that the rotating speed of fertilizer tray,feed rate, fertilizer type, and the interaction term between fertilizer type and feed ratepresentedan extremely significant impact on the coefficient of variation (P<0.01). The rotating speed of fertilizer tray, feed rate,and type presentedan extremely significant impact on the operation width (P<0.01).The finding can provide an important reference for the design of fertilizer spreading machinery in the lotus root field.
Abstract: Hydraulic capsule pipeline refers to the new type of transportation for goods in hollow containers in low carbon and environment-friendly way, particularly for agricultural products. Specifically, the farm products were sealed in airtight containers for point-to-point transportation through fixed pipelines, where the water pressure was taken as the power. Since the guide vanes are added around the capsule body, the water flow will generate circumferential velocity. Therefore, the length of guide vanes inevitably poses a great influence on the distribution and size of circumferential velocity. In this study, experimental and theoretical analysis was used to investigate the velocity characteristics of spiral flow in the cross section of the capsule with the length of the guide vane as the control variable. The results show that the axial velocity distribution of each cross-section was all the same with different lengths of guide vane. Specifically, the fluctuation of axial velocity decreased in each section between capsules, indicating the more uniform distribution of axial velocity, with the increase in the length of the guide vane. There was no major change in the axial velocity, but positive and the same as the water flow direction, with the increase in the length of the guide vane. Furthermore, the circumferential velocity gradient along each section between capsules first decreased, and then increased with different guide vane lengths, while the maximum and minimum circumferential velocity appeared near the upstream capsule. More importantly, the length of the guide vane presented the greatest influence on the circumferential flow velocity. The circumferential flow velocity increased with the increase of guide vane length, with a maximum of up to 1.2 m/s. The value of circumferential velocity was positive or negative, indicating that the circumferential velocity was divided into two directions, clockwise and counterclockwise along the circumference. The radial velocity gradient was the largest in the area near the upstream capsule, while smaller in the middle section between capsules under different guide vane lengths. There was a gradual decrease difference between the maximum and minimum radial velocity in the same section, where the radial velocity value was more uniform, with the increase of guide vane length. Compared with the circumferential velocity, the radial velocity was less affected by the length of the guide vane, and the radial velocity was positive or negative, indicating that the radial velocity was directed to the center of the circle and away from the center of the circle. The axial, circumferential, and radial velocity distribution on the same measuring ring was wavy under different guide vane lengths, ranging from -1.2 to 3.5 m/s, -0.6 to 1.2 m/s, and -1.6 to 1.2 m/s, respectively. The axial, circumferential, and radial velocity values were at the polar angle of 60°, 180°, and 300°. The peak value appeared at all the positions. The finding can provide a strong theoretical basis for the optimal design of capsule pipeline hydraulic transportation.
Abstract: A highly urgent need has been concerned to more conveniently monitor the moving speed of dunes along the Yellow River in the Ulan Buh Desert. Taking the coastal dune in Ulan Buh Desert as the research object, the seasonal geomorphological process and influencing factors were investigated using image data acquisition through UAV in this study. Results showed that: 1) The annual movement speed of dune was 1.08-2.27m/a, the multi-year average sand Drift Potential (DP) was 78.82 VU, and the annual Resultant Drift Potential (RDP) was 25.96 VU. It indicated that the study area was in a low wind energy environment. The 8-12 m/s level of sand DP accounted for 73.24% of annual sand DP. The intermediate directional wind variability (i.e. RDP/DP) was around 0.30-0.46. The average Resultant Drift Direction (RDD) was 88.40°, which was consistent with the dune movement direction. The westerly wind contributed 52.09% of the variation of the annual sand DP, indicating the main driving force for the annual movement of dunes. 2) The dune movement speed presented obvious seasonal characteristics. Specifically, the fastest was observed in spring, followed by late winter to early spring, and the slowest in summer. In late autumn to late winter, spring and autumn, the sand DP was around 8.48-20.49 VU, the RDD was 90.02°-95.54°, and the RDP/DP was 0.3-0.8, indicating an intermediate rate of directional wind variability. The westerly wind presented a significant effect on dune movement, particularly compatible with the annual RDD and dune movement direction. In late winter to early spring and late spring to summer, the dune with a relatively low movement speed usually adapted to the wind direction through morphological changes under the northeasterly wind (NE) and southerly wind (SSE, S, and SSW). The seasonal sand DP was mainly composed of 8-10 m/s level wind speed, accounting for 40.76%-56.93% of the whole season. 3) Overall, the seasonal and inter-annual sand DP was linearly positively correlated with dune movement distance. The fitting equation was y=1.02+0.006 62x (R2=0.339, F=5.615 9, P=0.045 26). The fitting equation reached a significant level, indicating that the sand DP can be used to characterize the dune movement distance in the area. The comprehensive landscape was achieved for the dune movement monitored by UVA. Consequently, the wind speed above 8 m/s in the Westerly Group was the main driving force for dune movement in the study area. When the wind direction variability and the RDP were consistent with the movement direction of dunes, the dunes moved faster, otherwise, the dunes moved slowly. Anyway, UAVs can provide more convenient monitoring services for the movement of dunes on a larger scale. This finding can also provide a strong reference for UVA monitoring of dune movement in similar areas.
Abstract: Monitoring the crop growth by using Unmanned Aerial Vehicle (UAV) based remote sensing technique is one of important directions for the development of precision and smart agriculture in China. In recent years, the development of UAV technology has greatly promoted the timely and rapid acquisition and long-term dynamic monitoring of agricultural and forestry ecological environment elements such as crop vegetation, water and soil. Compared with the data acquisition methods of satellite remote sensing and aerial remote sensing, UAV has the advantages of flexibility, convenience, low data acquisition cost and high image resolution. UAV remote sensing image is gradually becoming the main data source for the development of intelligent agriculture and forestry. In order to explore the inversion potential of Leaf Area Index (LAI) and chlorophyll content (SPAD) of wheat from UAV multi-spectral images, the multispectral images at three levels of flight altitudes (30, 60 and 120 m) by using the DJI Phantom4-M UAV platform which integrated five multispectral sensors (blue, green, red, red edge and near infrared) and TimeSync time synchronization system were collected to achieve centimeter-level positioning accuracy with more than 2 million pixel resolution, in Yuanyang wheat breading based, Xinxiang City, Henan Province. Based on the collected multispectral images, four different kinds of spectral indexes including: DSI (Difference Spectral Index), Ratio Spectral Index (Ratio Spectral Index), Normalized Spectral Index (NDSI) and empirical vegetation Index (EDVI) were used to compute the wheat canopy LAI and chlorophyll content (SPAD). The correlation analysis between different spectral index from different height UAV images and in-situ measured LAI and SPAD data were applied to select the optimal spectral index at different height. The Multiple Linear Stepwise Regression (MLSR), Partial Least Squares Regression (PLSR) and Artificial neural network (BP) model were constructed respectively for estimation of LAI and SPAD values. The experimental result showed that: 1) At 30 m height, the correlation coefficient between the green-red ratio spectral index and wheat LAI was the highest, with the value of 0.84. At the height of 60 m, the correlation coefficient between red-blue ratio spectral index and wheat chlorophyll content was the highest, with the value of 0.68. 2) At the height of 60 m, the correlation between empirical vegetation Index (EDVI) and LAI and chlorophyll content of wheat were both good, and the maximum correlation coefficients were 0.77 and 0.5, respectively. 3) The accuracy of wheat LAI inversion using partial least squares regression was the highest, with a determination coefficient of 0.732 and a root mean square error of 0.055. The accuracy of chlorophyll content inversion using artificial neural network model is the highest, the determination coefficient is 0.804, and the root mean square error is 0.135. This study provides a theoretical basis for high-throughput crop monitoring based on UAV platform, and provides an application reference for selecting UAV multi-spectral bands to achieve rapid estimation of crop growth parameters.
Abstract: Mulch drip irrigation has great benefits to save water for high cotton production in Xinjiang, China. Among them, freshwater has widely been used in agricultural irrigation. Highly efficient exploitation and utilization of saltwater resources have been the potential urgent to alleviate the ongoing freshwater shortages. In this study, a three-year growing season field experiment was conducted with different salinity level water irrigation, thereby analyzing the soil salt content within the different soil layers during the whole growth period of cotton. A salinity threshold of cotton was determined under saltwater mulch drip irrigation. An HYDRUS-2D model of soil salt was also built in cotton field under saltwater drip irrigation using the theory of soil water and solute movement. A numerical simulation was conducted for the distribution and accumulation characteristics of soil salt. The experiment was carried out at the Key Laboratory Test Base of the Modern Water-saving Irrigation Corps of Shihezi University, China. The base presented an average altitude of 450.8 m and a geographical location of 85°59′47″ E, 44°19′26″ N. Cotton was planted in each plot with the size of 2 m × 2 m× 2 m. The irrigation water was treated with five salinity levels: 2, 3, 4, 5, and 6 g/L. The ratio of chemicals NaHCO3, Na2SO4, NaCl, CaCl2, and MgCl2 were 1:7:8:1:1, according to the composition of local groundwater. The results showed that: 1) The salt accumulated less under 2, 3, and 4 g/L salinity treatments, where the plant height, chlorophyll, and yield of cotton were higher than those under 5 and 6 g/L salinity treatments. Therefore, 4 g/L salinity level was the threshold of irrigation water. 2) The soil salt gradually accumulated with the growth period of irrigationand reached the peak at the opening period. The soil electrical conductivity at the emitter increased at first and then decreased with the peak value in 60-70 cm soil layer, as the soil depth increased. The soil electrical conductivity of different salinity treatments were 3.04, 3.18, 3.15, 3.00, and 3.12 dS/m, respectively. 3) There was a more obvious accumulation trend with the increase in the salinity of irrigation water sources. The simulated salt accumulation was ranked in the order of 30 cm > 50 cm > 10 cm soil layers. There was in good agreement, where the mean absolute error of (MAE)<0.168, mean relative error of (MRE)< 15.321, root mean square error of (RMSE)< 0.2, Coefficient of determination R2 > 0.79 between the measured and simulated values of different soil layers. Therefore, the 4 g/L salinity level was suitable for the mulch drip irrigation of cotton using saline water. The finding can provide promising guidance for further exploitation and utilization of saltwater resources, particularly for the sustainable development of irrigated agriculture in semi-arid and arid areas.
Abstract: Agricultural drought has posed a serious threat to the national food security, social, environmental, and economic sustainable development in China over the last 20 years. The average annual disaster area has been accounted for more than 50% of natural disasters against climate warming and intensive human activities. Therefore, it is highly urgent to clarify the drought evolution and driving mechanisms for scientific drought prevention. More importantly, the Yellow River Basin provides the water supply for about 140 million people in the region, where about 15% of the total irrigated land was for agricultural irrigation in the country. However, the Yellow River Basin has historically been frequently experiencing serious droughts. For example, the disaster area caused by agricultural drought after 2000 was nearly six times that before 2000. Therefore, taking the Yellow River Basin as a study area, the main objective of this study is to comprehensively analyze the temporal and spatial evolution characteristics and driving mechanisms of agricultural drought. Six sub-basins were divided according to the climatic and topographic characteristics. The standard soil moisture index (SSMI) and threshold method were used to identify the duration, intensity, and drought events under different drought levels. A systematic analysis was also made on the agricultural drought characteristics and event frequencies in different zones in the study area on the annual and seasonal scales. A SWAT model in a simulation scheme was then selected to quantify the impacts of climate and land use land cover (LULC) change on agricultural drought in the study area. Results showed that: 1) The fewer frequencies occurred for the agricultural drought with longer duration, as the cumulative time was much longer. The duration of the agricultural drought was then remarked by SSMI-1, SSMI-6, and SSMI-18 corresponding to about 1-8, 1-12, and 1-22 months, respectively. The beginning and end time of agricultural drought was mainly concentrated in spring and summer. 2) The most serious agricultural drought occurred in the study area during 1981-1990, where that was greatly alleviated in most zones during 2001-2010. Specifically, Zone C and A were the most vulnerable to severe and extreme agricultural drought in the 1990s and 2000s, respectively. 3) Climate change was the main factor that caused the agricultural drought in the study area with a contribution rate of about 50%-90%, while the impact of LULC change was relatively weak with a contribution rate of about 10%-50%. Consequently, the greatest driving impacts of climate and land use were about 60%-90% and 10%-50%, respectively, on the frequency of agricultural drought in the study area. The findings can provide much more accurate information for actual management and disaster prevention of agricultural drought.
Abstract: Irrigation of crops can effectively increase yields and reduce inter-annual fluctuations in yields, thus mitigating the adverse effects of climate change on food production. However, there are significant differences in climate among different regions of China, and water and soil resources are not balanced among regions of China. The degree to which increasing irrigation in different regions can alleviate the impact of climate change is unknown. Therefore, in this study, the yield datasets under different climate scenarios published by ISIMIP were used to study the yield increase effect of irrigation expansion in different regions of China. Firstly, the irrigation water consumption of three crop models (GEPIC, PEFIC and LPJml) driven by four climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CAM5-LR, MIROC5) was evaluated using the actual irrigation water consumption in different regions of China from 2006 to 2019. Secondly, the first five model combinations with better simulation results were selected according to the skill scores S1 and S2. Then, the ensemble mean of the first five combinations with better performance was carried out to analyze the yield changes of maize, rice, soybean and wheat in China from 2021 to 2050 under RCP2.6 and RCP6.0 scenarios. Finally, the yield increase effect of irrigated area expansion under the assumption on the irrigation of rain-fed land in different areas was evaluated. The results showed that the increase of precipitation from 2021 to 2050 would increase the yield of rice and soybean, corn and wheat in northern China, among which about 80% of maize area in Northeast China and 70% of maize area in Northwest China would have the increasing of the maize yield by 0.2 - 0.8 t/hm2. About 85% of rice area and soybean area in Northeast and Northwest regions would have the increasing of the yield by 1.0 t/hm2 and 0.5 t/hm2, respectively. About 90% of wheat area in Northeast and 75% of wheat area in Northwest regions had the increasing of the by 1.0-2.0 t/hm2 and 0.5-1.0 t/hm2, respectively. The decrease of precipitation resulted in the decrease of maize and wheat yields by 0.2 t/hm2 in the 45% area of south southwest of China. Under the condition of expanding the irrigated area, the crop yield in Northwest and Southwest China would increase greatly during 2021-2050. Under RCP2.6 scenario, maize (northwest: 48%-60%; southwest: 7%-40%) was the highest, followed by soybean (northwest: 42%-62%; southwest: 2%-16%) and wheat (northwest: 11%-18%; southwest: 12%-33%); Under RCP6.0, maize (northwest: 43%-56%; southwest: 7%-39%) was the highest, followed by soybean (northwest: 38%-58%; southwest: 2%-23%) and wheat (northwest: 10%-18%; southwest: 15%-32%). The total yield of rice (soybean) in Northeast China increased significantly from 2021 to 2050. Under RCP2.6 and RCP6.0 scenarios, the total yield increased by 3%-10% and 3%-13% (7%-23% and 7%-23%), respectively. In terms of yield increase potential per unit irrigation amount, the expansion of irrigated area of wheat in Northeast China and North China during 2021 and 2050 had obvious yield increase benefit. Under RCP2.6 scenario, the wheat yield increase efficiency of irrigation was 0.18 and 0.12 kg/m3, respectively. The wheat yield increase efficiency under RCP6.0 scenario was 0.25 and 0.13 kg/m3, respectively. The irrigation area expansion of maize (rice) in central region (east) had obvious yield increase benefit. The maize (rice) yield increase efficiency under RCP2.6 and RCP6.0 scenarios was 0.1 and 0.09 kg/m3 (0.08 and 0.07 kg/m3), respectively. Therefore, the expansion of irrigated area for wheat in northern China can effectively cope with the adverse effects of climate change.
Abstract: Purple soil erosion of slope land has posed a serious threat to the operation safety of the Three Gorges Project in recent years. Fortunately, the hedgerow has widely been one of the most important measures for soil and water conservation on slope land. Most studies have also demonstrated that the hedgerows can effectively reduce the runoff and sediment of the slope. However, the specific reduction was still lacking on the aboveground and underground part of hedgerows. Taking the purple soil of slope land in the Three Gorges Reservoir Area as the research object, this study aims to clarify the effects of Vetiveriazizanioides L. hedgerow on the erosion of purple soil. Simulated rainfall experiments were also conducted at 2 slope gradients (15o and 25o), 2 rainfall intensities (60 and 120 mm/h), and 3 slope conditions (CK-Control check, P-Hedgerow, and R-Only hedgerow roots). The specific characteristics were analyzed for the initial runoff time, runoff, and sediment with rainfall duration under different slope conditions. The results indicated that the average contribution rates were 48.28% and 51.72% of the aboveground and underground parts to the increase of initial runoff time, respectively. The runoff production showed a trend of first increasing and then fluctuating, finally stable under different rainfall intensity and slope conditions. In sediment yield, the erosion rate of slope always kept a fluctuating and stable trend under the condition of P slope, whereas, there was a slow increase at first and a rapid increase under the condition of CK and R slope. The runoff reduction efficiency of hedgerows ranged from 11.20% to 26.19%, while the sediment reduction efficiency of hedgerows ranged from 71.54% to 83.63%. The average benefits of sediment reduction, underground and aboveground parts were 75.59%, 29.45%, and 46.13%, respectively, which were 4.79, 4.60, and 4.92 times of the average. The average contribution rates were 62.25% and 37.75% for the aboveground and underground part of hedgerows to the runoff reduction, respectively, while the average contribution rates were 60.44% and 39.56% to the sediment reduction, respectively. Correspondingly, the hedgerows greatly contributed to delay the runoff generation, where the contribution rates were not significant for the aboveground and underground part of hedgerows to the initial time of runoff generation. Meanwhile, the hedgerows can be expected to effectively reduce the runoff rate and erosion rate, where the effect of the aboveground part was greater than that of the underground part. Consequently, there was a more obvious effect of hedgerows on sediment reduction. More importantly, the effect of the aboveground part on runoff and sediment reduction was greater than that of the underground part. Anyway, Vetiveriazizanioides L. hedgerow can widely be expected to prevent the erosion process of purple soil in slope land. The finding can also provide a scientific basis for the prevention and control of soil and water loss on purple soil slopes in the Three Gorges Reservoir Area.
Abstract: Severe non-point source pollution has widely resulted from the nitrogen losses in paddy-field drainage in southern China, due mainly to excessive application of chemical fertilizers and unreasonable irrigation. The goal of this study was to improve the water use efficiency, while mitigating the reactive nitrogen losses in paddy fields. A controlled drainage system (CD) was designed to combine the subsurface pipe and open drainage ditches, with an open-ditch controlled drainage system (OD) as a control group. Specifically, the CD system consisted of a controlled drainage ditch and three field plots (CD1, CD2, and CD3) with a controlled subsurface pipe. By contrast, the three-field plots (OD1, OD2, and OD3) were free subsurface pipes in the OD system, where the field water freely drained into the drainage ditch through lateral infiltration. The drainage intensity and nitrogen concentration were monitored in various forms at the outlets of subsurface pipe and open ditch with a high frequency in six selected irrigation-induced drainage events, including three irrigation-drainage events with the fertilization (F1, F2, and F3) and three irrigation-drainage events without fertilization (D1, D2, and D3). The results showed that the drainage loss induced by six irrigation-drainage events accounted for 44.0% of the total amount of irrigation water in the OD system, indicating low water use efficiency. The combination of controlled drainage between the subsurface pipe and the open ditch greatly changed the drainage from the paddy field to the open ditch in the CD system. In all irrigation-drainage events except F3, the start time of open ditch drainage was later than that of subsurface pipe drainage, whereas, the peak of the intensity in the open ditch drainage was synchronized or significantly later than that of subsurface pipe drainage. Furthermore, the drainage peak and intensity of the open ditch in the CD system were much lower than those in the OD system among all six irrigation-drainage events. Specifically, the drainage peak of the latter was 1.3 to 8.2-fold that of the former, where the average drainage intensity was 1.5 to 4.4-fold. Compared with the OD, the CD decreased the drainage peak, intensity, duration time, as well as total drainage loss, where the proportion of drainage amount in the total amount of irrigation water dropped to 24.4%, indicating an effective role in drainage mitigation. In the irrigation-drainage event F1, F2, and F3, the concentrations of ammonium (NH4+) and total nitrogen (TN) in the drainage from the outlets of subsurface pipe (CD1, CD2, and CD3) and open ditches (CD and OD) gradually increased over time until the end of the drainage. Nevertheless, the concentrations of NH4+, nitrate (NO3-), and TN in the drainage from these same outlets gradually increased over time in the irrigation-drainage events D1, D2, and D3. Furthermore, the average concentrations of NH4+, NO3- and TN in the drainage from F1, F2, and F3 were much higher than those from D1, D2, and D3, indicating that the nitrogen loss was effectively reduced during the drainage management in a certain period after fertilization. As such, the open ditch in the CD system significantly intercepted a large number of nitrogen loads from subsurface pipe drainages. The nitrogen losses in the forms of NH4+, NO3- and TN from open ditch drainage in the CD system greatly decreased by 42.6%, 70.7%, and 39.3%, respectively, compared with the OD system. Consequently, the CD system can be expected to significantly reduce drainage loss and control non-point source pollution. This finding can also provide promising drainage control for the paddy field in southern China.
Abstract: Precipitation has widely been recognized as a fundamental component of the global water cycle. Accurate measurement of precipitation is very necessary for the main input into hydrological models. Hydraulic structures are then required to adequately design for efficient management of water resources. Several types of automatic rain gauges have been used in recent years, such as ultrasonic and laser rain gauges, but tipping-bucket rain gauges are still the common choice. Particularly, the tipping-bucket rain gauge can provide a better temporal resolution for the rainfall intensity. However, questions still remain on the accuracy of graphical representation for the actual rainfall. In this study, a real-time and automatic monitoring instrument was developed for the weighing rain gauge with high precision for precipitation. Three parts were composed of collector, weighing, measurement, and control subsystem. These subsystems were applied to multi-scenario conditions and performed well under the complex field. As such, the instrument was able to realize sample collection and measurement, data transmission and calculation, remote control, and diagnosis synchronously, compared with the traditional. The A/D conversion chip was utilized in the STM32 single-chip microcomputer to amplify the voltage signal of the weighing sensor. Subsequently, two important parameters of rainfall and rainfall intensity were achieved at a minute level with a resolution of 0.01 mm. Finally, a peristaltic pump was selected to verify the calibration of the developed instrument. The target intensities of rainfall were set as 0.02, 0.08, 0.17, 0.25, 0.50, 0.67, 0.83, 1.67, and 3.33 mm/min. The samples with the rainfall intensity of 0.83 mm/min were measured 30 times, and the rest were run five times. The results showed that the average rainfall intensity was 0.85 mm/min, where the histograms of target rainfall intensity presented a normal distribution, indicating higher precision of developed instrument than before. The best fitting linear regression was also represented by a slope with the R2 value close to 1. Additionally, the average error of the designed instrument was -1.32%, while the highest accuracy was 98.67%, and the relative error of less than 5% accounted for more than 85% of the total samples. The measured data of the developed instrument was also much larger than that of the tipping-bucket rain gauge under simulated rainfall conditions. The high resolution and sensitivity to light rain were contributed to the increase of effective rainfall rate and total rainfall. Finally, the performance of the developed instrument was verified under field conditions in the Wangdonggou watershed for one consecutive year. It was found that the annual rainfall was 522.80 mm, particularly concentrated from May to September. Correspondingly, the single rainfall less than 5 mm was the predominant contributor in natural precipitation, accounting for 74.11% of the total number of rainfall events, whereas, the single rainfall of 10-25 mm was the most important to total rainfall. Consequently, the self-designed instrument can widely be expected to automatically monitor the large variation of rainfall in most complex fields.
Abstract: A long-term site-specific experiment of fertilizer recommendation from 2012 to 2020 was conducted to evaluate the comprehensive effects of nutrient expert decision support system on yield, benefit, fertilizer use efficiency, and soil nutrient of spring maize in northeast China. Five treatments included no-fertilizer (CK) as the control, currently traditional farmers' practices (FP), fertilizer recommended using a nutrient expert system (NE), slow/controlled-release nitrogen fertilizer using the same rate as NE treatment (NER), and conventional fertilizer recommendation using soil testing (ST). The current study also investigated the long-term changes of maize yield, benefit, fertilizer use efficiency, the contents of inorganic N, available P, and available K in the soil, as well as the balance of nutrient input/output during the nine-year period. The results showed that the maximum, minimum, or mean values of fertilizer inputs in NE, NER, and ST treatments were all significantly lower than that of FP treatment (P<0.05), respectively. In different nutrients, NE, NER and ST treatments significantly reduced the amounts of nitrogen (N) and phosphorus (P) fertilizers application (P<0.05), but significantly increased the amount of potassium (K) fertilizer application (P<0.05), compared with that of FP treatment, respectively. Compared with FP treatment, NE, NER, and ST treatments significantly improved the stability of maize yield and net income, where increased by 5.6%-11.0% and 8.3%-14.3%, respectively. The NE treatment achieved the highest value, followed by ST and NER treatment. The recovery efficiency, agronomic efficiency, and partial factor productivity in the NE, NER, and ST treatments were significantly higher than those in FP treatment, where increased by 29.0%-40.1%, 31.3%-44.3%, and 22.0%-31.7%, respectively. Specifically, the highest value was observed in NE treatment, followed by NER and ST treatments. Compared with FP treatment, NE, NER and ST treatments significantly improved the inorganic N content in 0-30 cm soil layer (P<0.05), but significantly reduced inorganic N content in 30-90 cm soil layer (P<0.05) and available P content in 0-30 cm soil layer (P<0.05). But the soil available K content wasn't significantly different (P>0.05) among different fertilization treatments. The contents of soil inorganic N, available P, and available K in NE treatment were close to the initial testing values before planting. The nutrient input/output balance was obtained during the nine-year period, where the N and P balances were surplus under all fertilization treatments, whereas, the K balance was deficient. But the surplus of N, P, and the deficiency of K in NE treatment attained the lowest values, followed by NER and ST treatments. In conclusion, compared with farmers' practices and the conventional fertilizer recommendation system, the NE fertilization recommendation system fully met the nutrient requirements of maize, with optimal fertilization rate, time, and ratio. Consequently, the NE fertilization recommendation system has the potential to improve maize yield, benefits, and fertilizer use efficiency, thereby maintaining the soil nutrient stability under the reduction of fertilizer application amount, compared with farmers' practices. However, the simplified fertilization of slow/controlled-release nitrogen fertilizer in the NE fertilization recommendation system also obtained higher benefits, but reduced labor cost. Therefore, the NE system is an appropriate fertilizer recommendation for maize in northeast China.
Abstract: Excessive irrigation and fertilization in the traditional planting of Panaxnotoginseng have often caused the direct waste of water and fertilizer resources, high incidence of diseases, the decline in quality and yield, even environmental pollution. These also limit the sustainable development of Panaxnotoginseng planting in modern agriculture. In this study, an optimal coupling scheme of water and fertilizer was therefore proposed to realize green production of Panaxnotoginseng using yield, quality, and use efficiency. Three irrigation levels (low water W1:0.5 of field capacity, medium water W2:0.7 of field capacity, high water W3:0.9 of field capacity) and four fertilization levels (Annual fertilizer application was 1440kg/hm2. According to the different fertilization ratios in each breeding period, set as F1 (seedling period: flowering period: fruiting period: root weight gaining period= 25%: 25%: 25%: 25%), F2 (25%: 30%: 25%: 20%), F3 (30%: 30%: 25%: 15%) and F4 (40%: 20%: 30%: 10%) were set up with two-year-old Panaxnotoginseng as experiment materials in a field experiment. Each treatment was performed on two field blocks, each of which was about 15 m long and 2 m wide. The surface of the block was covered with 5mm thick pine needles, where the blocks were separated by plastic films buried underground to prevent the cross penetration of water and fertilizer. An analysis was made to clarify the effects of water and fertilizers, and their coupling effects on the yield, quality, and Water Use Efficiency (WUE) and Partial Factor Productivity of Fertilizer (PFP) of Panaxnotoginseng. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was also used to evaluate the comprehensive quality of saponins content. A scoring method was applied to evaluate the comprehensive performance in the growth and management model of each treatment. The results showed that the appropriate increases in the water stress and fertilizer during the seedling and fruit periods were beneficial to improve the yield, the content of notoginseng saponins, but reduce the incidence of disease. Nevertheless, the low-water treatment was not conducive to the yield, whereas, high-water treatment was not conducive to the quality of Panaxnotoginseng. More importantly, the greatest impact of irrigation presented on the WUE during the growth period, while the fertilization in different proportions performed the greatest impact on PFP. The effects of Panaxnotoginseng quality were ranked in the order of water and fertilizer coupling, moisture, as well as fertilizer. Additionally, the accumulation of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re and ginsenoside Rd treated with W2F4 were significantly higher than others among the five saponins. Specifically, the content of notoginsenoside R1 treated with W2F4 was the highest, while the content of ginsenoside Rb1 treated with W1F4 was the highest. In comprehensive scoring, the W2F4 treatment presented the highest comprehensive score, where the incidence rate was 12.97 %, the yield was 2 976.42 kg/hm2, WUE was 1.65 kg/m3, and PFP was 1.09 kg/kg. The W2F4 treatment also scored the highest of 0.815 in the TOPSIS quality analysis. Consequently, the optimal mode of coupling between variable fertilization at different growth stages and irrigation was achieved, where the irrigation level of 0.5 FC, the fertilization ratio in the seedling, flowering, fruiting, and root gaining period of 40%: 20%: 30%: 10%. The finding can provide a strong theoretical basis and technical reference for the formulation of irrigation and fertilization system during Panaxnotoginseng planting.
Abstract: Mechanical stability of soil structure determined the scour resistance, erodibility, collapsibility, slope stability, and foundation stability of the soil, even the large-scale agricultural instruments, as well as irrigation and water conservancy projects. Alternatively, rheology has widely been one part of soil physical characterization under deformation. The rheological parameters can be utilized to clarify the highly complex soil process, including the most significant soil aggregation factors, such as soil bulk density and water content. In this study, the widely distributed Lou soil and loessal soil on the Loess Plateau were selected as the research objects. An amplitude scanning test was selected to simulate the oscillation load process. An investigation was made on the effect of soil bulk density and water content on the mechanical stability of soil structure under the oscillation load. The results show that: 1) The soil density increased the contact point between soil particles, leading to the increasing cohesion and friction between particles. The shear strength parameters were all increased, including the shear stress at the linear viscoelastic region, the shear stress at yield point, the maximum shear stress, and the storage modulus at the yield point, as the increase of soil bulk density, indicating the increase in the stability of soil structure. In terms of viscoelastic parameters, the shear strain at the linear viscoelasticity region and the maximum shear stress decreased, whereas, the shear strain at yield points and integral zone increased first and then decreased, with the increase of soil bulk density. Soil particles were under the most stable way of organization and combination (1.3 g/cm3). Shear strength parameters with the change of soil bulk density were more sensitive than viscoelastic parameters. 2) As the increase of soil water content, the shear strength parameters presented the decreasing trends, including the shear stress at the linear viscoelastic region, the shear stress at yield point, the maximum shear stress, and the storage modulus at the yield point, indicating the decreased stability of soil structure. In viscoelastic parameters, the shear strain at the linear viscoelasticity region increased with the increase of water content, but the shear strain at yield point and integral zone decreased. It indicated that the cohesion and friction between soil particles decreased, with the increase of soil water content. The higher water content of soil particles decreased the relative sliding resistance between particles, leading to the deterioration of soil structural stability. 3) The elasticity and shear strength of Lou soil was higher than that of Loessal soil. This was mainly because Lou soil contained a higher content of clay, organic matter, cation exchange capacity, and specific surface area than those of Loessal soil, indicating the improved cementation strength between soil particles. Consequently, the rheological parameters from the amplitude scanning test in the rheometer can be used to quantitatively characterize the mechanical stability of soil structure, providing for rich evaluation parameters to further understand the micromechanical properties of soil. The finding can provide a shred of strong scientific evidence for agricultural water and soil engineering design, as well as the prevention and control of landslide and geological disasters in the Loess Plateau.
Abstract: The number of spikes per unit area is a key yield component for cereal crops such as wheat, which is popularly used in wheat research for crop improvement. With the fast maturity of smartphone imaging hardware and recent advances in image processing and lightweight deep learning techniques, it is possible to acquire high-resolution images using a smartphone camera, followed by the analysis of wheat spikes per unit area through pre-trained artificial intelligence algorithms. Then, by combining detected spike number with variety-based spikelet number and grain weight, it is feasible to carry out a near real-time estimation of yield potential for a given wheat variety in the field. This AI-driven approach becomes more powerful when a range of varieties are included in the training datasets, enabling an effective and valuable approach for yield-related studies in breeding, cultivation, and agricultural production. In this study, we present a novel smartphone-based software application that combines smartphone imaging, lightweight and embedded deep learning, with yield prediction algorithms and applied the software to wheat cultivation experiments. This open-source Android application is called YieldQuant-Mobile (YQ-M), which was developed to measure a key yield trait (i.e. spikes per unit area) and then estimate yield based on the trait. Through YQ-M and smartphones, we standardized the in-field imaging of wheat plots, streamlined the detection of spikes per unit area and the prediction of yield, without a prerequisite of in-field WiFi or mobile network. In this article, we introduce the YQ-M in detail, including: 1) the data acquisition designed to standardize the collection of wheat images from an overhead perspective using Android smartphones; 2) the data pre-processing of the acquired image to reduce the computational time for image analysis; 3) the extraction of wheat spike features through deep learning (i.e. YOLOV4) and transfer learning; 4) the application of TensorFlow.lite to transform the trained model into a lightweight MobileNetV2-YOLOV4 model, so that wheat spike detection can be operated on an Android smartphone; 5) finally, the establishment of a mobile phone database to incorporate historic datasets of key yield components collected from different wheat varieties into YQ-M using Android SDK and SQLite. Additionally, to ensure that our work could reach the broader research community, we developed a Graphical User Interface (GUI) for YQ-M, which contains: 1) the spike detection module that identifies the number of wheat spikes from a smartphone image; 2) the yield prediction module that invokes near real-time yield prediction using detected spike numbers and related parameters such as wheat varieties, place of production, accumulated temperature, and unit area. During our research, we have tested YQ-M with 80 representative varieties (240 1 m2 plots, three replicates) selected from the main wheat producing areas in China. The computed accuracy, recall, average accuracy, and F1-score for the learning model are 84.43%, 91.05%, 91.96%, and 0.88, respectively. The coefficient of determination between YQ-M predicted yield values and post-harvest manual yield measurement is 0.839 (n=80 varieties, P<0.05; Root Mean Square Error=17.641 g/m2). The results suggest that YQ-M presented here has a high accuracy in the detection of wheat spikes per unit area and can produce a consistent yield prediction for the selected wheat varieties under complex field conditions. Furthermore, YQ-M can be easily accessed and expanded to incorporate new varieties and crop species, indicating the usability and extendibility of the software application. Hence, we believe that YQ-M is likely to provide a step change in our abilities to analyze yield-related components for different wheat varieties, a low-cost, accessible, and reliable approach that can contribute to smart breeding, cultivation and, potentially, agricultural production.
Abstract: Intelligent feeding has widely been used to determine the amount of feed from a smart prediction about the hunger degree of fish, thereby effectively reducing the waste of feed in the modern aquaculture industry, especially for outdoor intensive fish breeding environments. However, redundant data collected by mobile monitoring devices has caused a huge calculation load for most control systems. An accurate classification of the hunger degree of fish still remains an unsolved problem. Taking the captive perch as the tested object, this work aims to design an image capture system for the perch feeding using MobileNetV3-Small of lightweight neural network. The system also consisted of 2 captive fonds, a camera, and a video recorder. In the test, 4202 perches were randomly fed with adequate or inadequate feed, where a camera was selected to record the water surface every day. 10 000 images were collected after 2-week monitoring to record the perch ingesting condition in the period of 80~110 seconds after per round feeding condition, where 50% belonged to "hungry" condition, and the rest was "non-hungry" condition. These initial images were then divided as training, validation, and testing set, according to a rate of 6:2:2. Four image processing operations were applied on the training set, containing random flipping, random cropping, adding Gaussian noise, and color dithering, thereby expanding the training set from 6 000 to 12 000 images. As such, the more generalized model greatly enhanced the image features and training samples. Next, a MobileNetV3-Small of lightweight Neural Network was selected to classify the ingesting condition of perches. The model was trained, tested, and established on the Tensorflow2 platform, where the images of the training set were selected as the input, whereas, the ingesting condition as the output. Finally, a 2-week feeding contrast test was carried out in the outdoor culture environment to verify the accuracy of the model. Two groups were set for 4202 perches in this test, 2096 of the test group and 2106 of the control group, where the amount of feed was determined according to the classification of model and conventional experience. Meanwhile, the total mass and quantity of the two groups were recorded at the beginning and end of the test, as well as the total amount of consumed feed. Correspondingly, it was found that the MobileNetV3-Small network model achieved a combined accuracy of 99.60% in the test set with an F1 score of 99.60%. The MobileNetV3-Small model presented the smallest Floating Point Operations of 582 M and the largest average classification rate of 39.21 frames/s, compared with ResNet-18, ShuffleNetV2, and MobileNetV3-Large deep learning models. Specifically, the combined accuracies of the MobileNetV3-Small model were 12.74%, 23.85%, 3.6%, and 2.78% higher than that of the traditional machine learning models KNN, SVM, GBDT, and Stacking. Furthermore, the test group of perch was achieved a lower Feed Conversion Ratio of 1.42, and a higher Weight Gain Ratio of 5.56%, compared with the control group, indicating that the MobileNetV3-Small model performed a better classification on the ingesting condition in a real outdoor culture environment. Consequently, the classification of the ingesting condition can widely be expected for the efficient decision-making for the amount of fish feed, particularly suitable for the growth of fish. The finding can provide a further reference for efficient and intelligent feeding in an intensive cultural environment.
Abstract: The complex working environment of picking robots has limited the picking speed and equipment memory resources in the intelligent harvesting of Lingwu long jujubes. Therefore, it is necessary to meet the requirements of lighter network structure and higher detection accuracy, particularly for the visual recognition system. A pre-train model has widely been loaded almost all the object detection at present, due to high initialization performance and convergence speed. However, two challenges are still remained: 1) The network structure cannot be changed on the limited memory resources of the device; 2) There may be great differences between the ImageNet dataset and the dataset to be trained, leading to the low training effect. Taking the SSD model as the basic framework, this research aims to propose a lightweight object detection for the images of Lingwu long jujubes. The excellent performance was achieved without loading the pre-train model. Firstly, data augmentation is performed on the collected 1 000 images to obtain 5 000 images. Data augmentation operations include random cropping, random vertical or horizontal flipping, random brightness adjustment, random contrast adjustment, and random saturation adjustment. Secondly, the Lingwu long jujube dataset was established, including 3 500 training images and 1 500 test images. The resolution of images consisted of 3 016×4 032, 4 068×3 456, and 2 448×3 264. The models of smartphones for image acquisition included HUAWEI TRT-AL00A, Vivo Y79A, and Xiaomi 2014501. The images were uniformly scaled to the resolution of 300×300, in order to meet the input requirements of image size in the SSD object detection. Data augmentation included random cropping, random vertical or horizontal flipping, as well as random adjustment of brightness, contrast, and saturation. The format of the PASCAL VOC dataset was also adopted. Labelling software was used to label the images, and then the marked images were stored in the label folder in XML format. Secondly, the improved DenseNet was utilized the Convolutional Block Attention Modules and two dense blocks with convolution groups of 6 and 8. Taking the improved DenseNet as the backbone network, the improved SSD model was obtained to combine with the multi-level fusion structure, where the first three additional layers were replaced in the SSD model with the Inception module. In the improved SSD model without loading the pre-train model, the mAP was 96.60%, the detection speed was 28.05 frames/s, and the number of parameters was 1.99×106, particularly 2.02 percentage points and 0.05 percentage points higher than that of the SSD and SSD model (pre-train), respectively. Correspondingly, the parameter of the improved SSD model was 11.14×106 lower than the SSD model, fully meeting the requirements of the lightweight network without loading the pre-train model. This finding can provide a strong visual technical support for the intelligent harvesting of Lingwu long jujubes, even medical and multispectral images detection tasks.
Abstract: Accurate identification of target depth is the critical premise for the manipulator of fruit and vegetable picking in intelligent agriculture. However, the general ranging of fruit has posed a great challenge on that the orchard in the mountain areas, due mainly to the light change, as well as the branch and leaf occlusion. In this study, a novel imaging algorithm was proposed to detect the monocular distance between the pomelo fruits and camera using target pixels change. The pomelo fruit off the tree in the orchard was chosen as the samples for data collection. Multiple regression was also established to verify the number change of pixels in the target areas and imaging distance. Furthermore, the pomelo fruit on the tree was involved to test the applicability in the samples. Additionally, a systematic investigation was made to explore the influences of initial imaging distance and step interval on prediction accuracy. The specific procedure was as follows. A single camera was utilized to capture the imaging data of the sample fruit side within the imaging distance ranging from 25 to 150 cm, where the common range of picking operation was set at the step interval of 2.5 cm. Therefore, there were 51 images side for each fruit for one group of data. 20 pomelo fruits with the representative shape and size were selected for the imaging data collection, including 14 off-tree and 6 on-tree. In the pomelo fruits off the tree, the surface was equally divided into four sides, where one group of data was acquired from each side. As such, a total of 56 data groups were collected from the samples of the tree. Subsequently, the 40 data groups were randomly selected to establish the multiple regressions between the imaging distance and the number of pixels change in the target area on the image, while the rest 16 data groups were used to optimize the algorithm. In the pomelos fruits on the tree, only the side towards the outside of the canopy was shot as one sample side, where 6 data groups were collected for testing. The numbers of pixels were then measured for the target areas in the image using Photoshop software. MATLAB 2018 platform was finally utilized to calculate the regression and curve fitting. The results showed that the error of predicted distance decreased gradually, as the camera approached the fruit target from 150 to 120 cm. In the fruit samples off the tree, the accuracy of distance prediction was at the medium level closer than 130 cm at the high level of about 120 cm. The relative ranging errors of 16 samples off-tree were less than 5% within the imaging distance of 120 cm, when 150 cm was as the initial distance, indicating that an excellent detection performance of imaging distance between the target and camera. In the fruit samples on the tree, the ranging accuracies were set as 137.5-125 cm and 125.0-25.0 cm for the medium and high levels, respectively. Correspondingly, the relative ranging errors of 6 samples on the tree were less than 5% within 125 cm imaging distance, fully meeting the accuracy requirements of target positioning for the picking manipulator. In addition, there was a significant effect of initial imaging distance on the measurement accuracy. Consequently, the measurement method of monocular distance can widely be expected to realize the rapid prediction of the distance between the fruit target and camera in the complex orchard environment, especially in the hilly mountain areas. Meanwhile, the finding can also provide a feasible scheme for the accurate recognition of fruit targets for picking manipulators in modern orchards.
Abstract: Rumination enables cows to chew grass more completely for better digestion, thereby closely relating to the health, production, reproduction, and welfare of cows. To perceive ruminant behavior has widely been one of the most important steps in modern dairy farm management. However, the traditional monitoring ruminant behavior of cows depends mainly on human labor, time-consuming and laborious. In this study, feasible intelligent monitoring was proposed for multi-target automatic tracking mouth and ruminant behavior of cows in the complex environment of dairy farms using the Kalman filter and Hungarian algorithm. The upper and lower jaw regions of cow mouths were firstly recognized by the YOLOv4 model. Subsequently, the region of the upper jaw was tracked by the Kalman filter and Hungarian algorithm. The chewing curve of the mouth region was then obtained to match the upper and lower jaw regions of the same cow. Finally, the related rumination information was achieved to further realize the mouth tracking and ruminant behavior monitoring of multi-target cows. As such, the unmatched tracking boxes were remained and expanded to deal with the identity change of cows caused by rapid head swing or shed railing occlusion. 66 videos were collected for ruminant cows in the actual farm environment, where 58 videos were divided into frames to make the dataset for the YOLOv4 model, and the remaining 8 videos were used to verify the tracking and rumination behavior. Videos data was involved sunny, cloudy, and rainy days, in which the number of cows varied from 2 to 3. Lying or standing was included in the ruminant posture of cows. Additionally, there were some interference factors, such as the rapid head swing of ruminating cows, shed railing occlusion, and the movement of other cows. Two indexes were selected to evaluate the detection performance of the YOLOv4 model, including average precision and mean average precision. 6 400 images of the dataset were trained, and 800 images were tested. The results showed that the average precisions of the YOLOv4 model were 93.92% and 92.46% for the detection of the upper and lower jaw region, respectively. The mean average precision of YOLOv4 reached 93.19%, which was 1.04, 4.25, and 1.74 percentage points higher than that of YOLOv5, SSD, and Faster RCNN models, respectively. Four indexes were selected to verify the performance of tracking and rumination behavior under different environments, including the rate of identity switch, the rate of identity match, the detection rate of chewing times, and the tracking speed. It was found that the YOLOv4 model realized the stable multi-target tracking of mouth regions of cows in complex environments, while effectively alleviating the identity change of cows resulted from the rapid head swing and shed railing occlusion. The average rate of identity match was 99.89% for the upper and lower jaws, and the average tracking speed was 31.85 frames/s. The average detection rate of chewing times was 96.93% after the evaluation of rumination behavior, and the average error of rumination time was 1.48 s. This finding can provide a strong reference for the intelligent monitoring and ruminant behavior of multi-target cows (or moving parts of animals) in actual breeding.
Abstract: Automatic navigation can be used to significantly improve the operation accuracy and efficiency of agricultural machinery. Particularly, machine vision-based automatic navigation can greatly contribute to crop row detection. In this study, a novel crop row extraction was proposed using regional growth and mean-shift clustering, especially for higher accuracy of crop row extraction under different crop types, the number of crop rows, and growing backgrounds. Firstly, the a and b components of an image were obtained in the Lab color space, and then the maximum entropy values of a and b components were calculated for the optimal segmentation threshold, after which the image was segmented by the threshold for the binarization image. Secondly, the vertical projection operation was performed on the top strip of the binary image, where the mean value of the vertical projection curve was calculated to distinguish crop and non-crop areas. The minimum distance between crop areas was selected as the bandwidth of the crop clustering window. The top center pixel of the whole image was selected as the initial center point of the clustering window. The clustering center point moved from the center to both sides of the top of the image with the iteration of crop row clustering, where the shift vector was calculated in the clustering window. The clustering center point moved along the shift vector in single row clustering, where the edge of the clustering window was used as the seed point for regional growth. As such, all crop rows were obtained by the movement of clustering window and regional growth, while, the clustering center points of each crop row were grouped into a cluster. Lastly, least-squares fitting was performed on these clustering center points to obtain crop row lines. A total of 170 seedling images of five crop varieties were obtained to verify the feasibility of the method, including garlic, corn, oilseed rape, rice, and wheat. Hough transform and projection-proximity classification were also used to extract crop rows for comparison. Experimental results showed that more satisfactory performance of segmentation was achieved for the images with less significant color difference between crops and growing background using the maximum entropy of a and b components in the Lab color space, compared with the conventional segmentation using an excess green index. Furthermore, the crop row extraction for tested five crops performed better than that of Hough transform and projection-proximity classification fitting, in terms of row recognition rate, mean error angle, and mean processing time. The mean row recognition rate for the 170 tested images was 98.18%, the mean error angle of extracted straight lines of all crop rows was 1.21°, and the mean processing time for each image was 0.48 s. This finding can provide a more robust for crop row extraction under the influence of multi factors in the field using machine vision, particularly on real-time embedded platforms in practical applications.
Abstract: Digital imaging has widely been used to detect pest diseases for crops in modern agriculture, particularly on deep learning and intelligent computer vision. However, accurate and rapid detection of insect pests in images still remains a great challenge in the crop field. In this study, a task-specified detector was developed to accurately detect vegetable pests of sticky trap images using an attention-driven deep network from saliency maps. Prevailing pest detectors were mainly adopted anchors to detect pests in sticky trap images. Nevertheless, the anchor-based detection accuracy depended mainly on the balance between positives and negatives, as well as the model training, due mainly to the relatively small sizes and distribution of crop insect pests in the sticky trap images. Therefore, a saliency map was established to filter simple background regions. An attention-driven neural network was also selected to better focus on key regions and then accurately detect crop insect pests of sticky trap images. Firstly, saliency maps and threshold-based techniques were employed to construct masks for rough region proposals, according to connected graphs of acquired masks. Secondly, two fully convolutional neural networks were used in a sliding window fashion to produce refined region proposals from rough region proposals, in order to deal with occlusion issues. Thirdly, each refined region proposal was then classified as one target pest category with a convolutional neural network classifier, thereby detecting the bounding boxes of target vegetable pests. Finally, an enhanced non-maximum suppression was utilized to eliminate the bounding boxes of redundant detection, where a target pest was captured by only one detection bounding box. As such, the target pest number was easily obtained to count the bounding boxes of rest detection during automatic management of vegetable insect pests. Furthermore, a piece of specific monitoring equipment was designed to evaluate the vegetable pest detector, where sticky trap images of two vegetable pests were collected, including Plutellaxylostella (Linnaeus) and Bactroceracucuribitae (Coquillett). Several experiments were also conducted on the labeled data set of collected images. The results demonstrate that the vegetable pest detector achieved a mean average precision of 86.4% and an average mean absolute error of 0.111, indicating better performance than the commonly-used pest detectors, such as SSD, R-FCN, CenterNet, Faster R-CNN, and YOLOv4. In addition, two ablation experiments were carried out to verify the attention mechanism of saliency maps and the enhanced non-maximum suppression. It was found that the attention mechanism remarkably contributed to the detection accuracy and the performance of enhanced non-maximum suppression. In the future, both top- and low-level feature maps were required in a convolutional neural network, further enchancing the robustness of the attention mechanism in the vegetable pest detector.
Abstract: Composting has historically been carried out by farmers for manure management, which is a reliable way to recycle manure for use on croplands in sustainable agriculture. However, poor management of the composting process can result in un-mature compost product, which inhibits plant growth and deteriorates soil condition. The seed Germination Index (GI), an authoritative parameter to evaluate the maturity of compost, has been widely utilized in evaluating the phytotoxicity and other aspects of composting process. However, there are still lack of unified standards for the measurement method of GI and the representative type of experimental seed until now, which leads to the diverse results of GI (fluctuated from 20%-217%), and the newest standard of organic fertilizer (NY525-2021) requirements GI≥70% of organic fertilizer. Thus, it is meaningless to compare these values between different studies in related fields and urgently for public to provide a reference measurement process for GI during composting. Therefore, this study protocoled four treatments, composting chicken manure with or without auxiliary material (carbon additive) for different phytotoxicity compost, and selected four types of seeds for sensitive assays according to previous studies, mainly included cucumber, radish, Chinese cabbage and oil rape. Besides, in the process of germination experiments and indexes calculation, detailly instruction for the whole process of GI determination and calculation was documented, which stipulated the definition of radical length for 0 mm, 1 mm and the start position for measure (with diagram). Furthermore, systematically detecting the response relationships between influenced parameters and GI of different composting treatments. The results showed that, according to the GI of final compost, the maturity increased in the order of pure pig manure treatment (26.54%-80.49%), pure sheep manure treatment (16.71%-92.98%), pig manure and straw treatment (28.28%-110.74%), sheep manure and straw treatment (43.38%-119.69%). Carbon additive of straw could significantly improve temperature of composting systems and further maturity of the final products. Increasing pH and decreasing phytotoxicity of electronical conductivity, low molecular organic acid and organic matter contents at the same time. Seeds' GI decreased with the order of radish (≤130%), cucumber (≤100%), oil rape (≤0%), Chinese cabbage (≤45%). The sensitives were reflected with correlation analysis, which between physical and chemical indicators (temperature, oxygen, pH, carbon and nitrogen ratio) and biological toxicity factors (electronical conductivity, ammonium nitrogen, organic acid and organic matter) and GI with different seeds (cucumber, radish, cabbage, rape) of four composting processes, and fond the factors influenced GI with the sequence of NH4+, pH value, O2, VS, VFAs, EC, C/N, temperature, which was in accordance with the affected sequence of radish seed. Besides, radish seed showed the highest responsivity (3.69, r=0.96) of GI for influenced factors, which was the most scientific and representative type of seeds for comprehensively reflecting maturity and phytotoxicity of compost of discrepancy qualities compost. Furthermore, radish has been widely studied for the reasons of fasting germination speed, moderating molecular size, obtaining easily and lowering price. These results can provide scientific references for the determination and comparation of GI, the establishment of organic fertilizer standards and the safe application of compost in farmlands.
Abstract: A transport container with a controlled temperature was developed, where the temperature was regulated using low-temperature phase-change materials. The cold energy was first stored in low-temperature phase-change materials and then released when the temperature in the container was out of target range under an intelligent control system. However, there were still some issues that need to be solved, such as the difficulties in controlling the release rate of cold energy, the prediction of remaining cold energy during the transportation work. The release rate of cold energy depended directly on the convective heat transfer coefficient between the surface of the cold storage plate and the ambient air. In this study, an experimental platform was developed to investigate the influence of different environments and parameters of cold storage plates on the convective heat transfer coefficient between the cold storage plate surface and the ambient air. A quadratic regression orthogonal experiment was adopted to clarify the coupling effects among the factors, including the air velocity and temperature at the entrance of the cool storage area, heat transfer area of the cold storage plate, and the space between them on the surface convective heat transfer coefficient. After that, the experimental data were analyzed. A second-order prediction model of surface convective heat transfer coefficient was built that the relationships between the influence factors and the surface convective heat transfer coefficient and the factors with significant effects were obtained, as well as the optimal values of such factors. Consequently, there was the most significant interaction between the entrance air temperature and the heat transfer area of the cold storage plate. The prediction model of surface convective heat transfer coefficient built by response surface method presented a higher accuracy, where the best combination of parameters was velocity=4 m/s, temperature=25 ℃, area=0.455 m2, spacing=0.04 m, and the R2 value was 0.927 4 and the coefficient of variation CV was 5.78%. The calculated results of such regression model were in good agreement with the experimental, with the maximum error of 3.58% and an average relative error of 2.69%, indicating that such model can be used to quickly and accurately predict the convective heat transfer coefficient between the surface of cold storage plate and the ambient air under different conditions. The finding can provide accurate control on the release rate of cold energy in the temperature phase-change materials, and the prediction of remaining cooling energy for transport containers with controlled temperature
Abstract: Coal has been widely used in many aspects in northern China. Nevertheless, urgent environmental protection has been required to prohibit the coal combustion for the heating source in winter since 2017. The application of clean energy has been the key issue need to be solved in recent years, particularly on the energy consumption of buildings. Air source heat pump (ASHP) as a piece of clean energy equipment has widely been used in civil and industrial buildings. But there is no application of ASHP in swine houses. It is an urgent need to conserve energy and reduce pollution emissions. In this study, an investigation of ASHP was carried out in the pig house of Shunyi District, Beijing. The experimental size of the pig house was 42 m long and 9.3 m wide. The ASHP heating system was installed in a swine barn. There were 6 pipes to supply water, and other 6 pipes to return water for the heating floor. The monitoring period was selected for the equipment performance: November 20th, 2016-April 16th, 2017. The first stage (January 3rd, 2017-January 8th, 2017): pig house with pig test (two units). The second stage (January 9th, 2017-January 20th, 2017): pig house with no pig test (empty pig unit - unit 2). The energy-saving rate of ASHP and direct electric heating systems were compared to measure the coefficient of performance (COP). ASHP, direct electric heating, liquefied natural gas (LNG), and natural gas heating were compared by the unit energy operating price. The average supply water and return water temperature of ASHP was also measured. The results showed that the COP of the ASHP system was 2.86 when the average outdoor temperature was 0.1 ℃ during the heating period. The energy-saving rate of ASHP was 66%, compared with direct electric heating. The unit energy operating prices of ASHP, LNG, Natural Gas, direct electric, and ASHP were 0.62, 0.34, 0.37, and 0.64 yuan/ kW·h, respectively. The CO2 emission was reduced by 8636 kg during the experiment. The average supply water temperature and return water temperature of ASHP were (37.6±2.4) ℃ and (34.9±2.2) ℃, respectively. ASHP heating system presented the potential to reduce energy consumption and CO2 emission, serving as an economical and clean alternative energy source for pig barns heating. Consequently, the air source heat pump system is suitable for pig houses with solid floors, but not with fully slatted floors.
Abstract: A Venlo-type greenhouse has widely been introduced from Netherland for modern agriculture in China at present. This type of greenhouse is also the largest, most commonly-used, and state-of-the-art glass structure with advanced equipment and control systems for super greenhouses in the world. However, few national standards are released for the structure design of modern agricultural greenhouse, although most industry or group standards in China. Furthermore, the combination of earthquake load other than wind load cannot be usually considered for the structure design in most studies, due to the light-weight components and covering materials in the greenhouse structure. If the greenhouse that designed by the Netherlands was directly introduced to adopt the Dutch structural standards in China, there is a safety hazard of seismic action for the damage of main structure, particularly for nearly half of land areas in high-level zones of seismic intensity in China, even above 7 degrees. Taking a Venlo-type greenhousedesigned by a Dutch company in Shandong province as an example, this study aims to explore the impact of seismic action on structural safety according to the Dutch code, considering the stress diaphragm of covering material on the structural stiffness. A finite element software MIDAS Gen with the response spectrum modal was also selected to simulate the whole structure of the greenhouse with the seismic precautionary intensity of 7 (0.10g), 7 (0.15g), 8 (0.20g), and 8 degrees (0.30g). A systematic analysis was made on the mode periods, vibration patterns, the maximum stresses, and displacements for the structure. The results showed that the longest period of natural vibration was 1.75 s in the greenhouse structure, indicating a relatively flexible performance of the structural system. The first and second vibration patterns were the flat motion in Y and X -direction, especially a similar seismic performance in the 2 principal axes. Additionally, the maximum bearing capacity of the structure was 216.96 MPa for different seismic precautionary intensities under the wind load. The maximum stress was still less than the yield strength of components. When the seismic precautionary intensity exceeded 8 degrees (0.30g), the maximum tensile and compressive stresses of components were 211.95 and 196.02 MPa for the X-directional seismic action, respectively. In addition, the maximum displacement was 31.80 mm under the X-directional wind load without considering seismic action. The structural deformation was also mainly influenced by the seismic load. Specifically, the Y-directional seismic action was about 11.6% than that in the X-direction under the same load combination. Consequently, the greenhouse structure introduced from Netherland can always be expected to fully meet the code requirements within the elastic range of components, when the seismic intensity was lower than 8 degrees (0.30g). Nevertheless, the maximum deformation exceeded the standard requirement of 1/250 of the elastic inter-story displacement angle, according to the code for seismic design of buildings in China.
Abstract: The Yellow River Basin has been one of the most important energy bases in China. The land green use efficiency of resource-based cities directly dominates the sustainable and high-quality development in this region. In this study, taking the resource-based cities in the Yellow River Basin as the case study area, a novel index system of land green use efficiency was developed, where the resource and environmental consumption were as input indicators, while the economic, social, and environmental benefits as output indicators. SSBM model was also used to measure the land green use efficiency of resource-based cities in the study area from 2009 to 2018. A spatial autocorrelation and GTWR model were selected to analyze the spatial evolution characteristics and driving factors of land green use efficiency, respectively. The results showed that: 1) There was a trend of fluctuation on the land green use efficiency of resource-based cities in the study areas from 2009 to 2018. There was also a relatively low proportion of high-value cities in the land green use efficiency, where there was not a significant change over the past 10 years. Furthermore, there was a low growth rate of land green use efficiency with the insufficient rising power in the cities, due mainly to the regional restrictions and economic development. Specifically, the land green use efficiency increased the fastest in Henan and Shaanxi Provinces from 2009 to 2018. Ningxia, Shandong, and Inner Mongolia were in the slow growth stage, while Shanxi and Gansu showed a downward trend. 2) The Global Moran's I index of land green use efficiency was between-0.179 and 0.192 for the resource-based cities in the study area, indicating that the global spatial evolution was ranging from the relatively strong to weak correlation from 2009 to 2018. There were also the small-scale agglomeration and large-scale dispersion in the spatial distributions of land green use efficiency for the resource-based cities in the study area, according to the LISA index. As such, it is necessary to further strengthen the coordinated development among upper, middle, and lower reaches in the study areas. 3) There was spatial heterogeneity in the driving factors of land green use efficiency. The economic and industrial structure factors were consistently dominated the land green use efficiency in the study area. The most critical factor in the main driving factors was gradually shifted to the level of science and technology for different types of resource-based cities in 2018. Furthermore, the growing or declining resource-based cities depended strongly on the economy, industrial structure, and policy. The mature resource-based cities were mainly influenced by technology and urbanization. More importantly, technology and industrial structure posed a strong impact on renewable resource-based cities. Consequently, the finding can widely be used to guide the decision-making for better efficiency of land green use in various resource-based cities.
Abstract: In mountainous and hilly areas, cultivated land resources are scarce, and the phenomenon of cultivated land fragmentation is serious. The long and narrow arable land plots are complex in structure, which makes it difficult to obtain the information of cultivated land at the land level quickly and accurately, and hinders the application of precise digital agricultural services based on high resolution remote sensing images in mountainous and hilly areas. Parcle-level cultivated land information can intuitively show the spatial distribution, boundary details of farmland, and is of great significance for precision agriculture management, distribution of planting subsidies, and agricultural resource survey. Existing edge detection/semantic segmentation networks-based farmland extraction methods ignore the structural features of the parcel, thus have limit performance for handling narrow and small plots, and there is also a blurring boundary problem. To address these issues, we proposed an accurate extraction method of cropland in mountainous area based on geographic parcels. This method combines the advantages of semantic segmentation and edge detection, and effectively extracts and integrates the linear features of the boundary and the internal texture features of the parcel, so as to improve the recognition accuracy of the cultivated land. The main features of the model in this paper are as follows: 1) The edge of cultivated land is regarded as a new class independent of cultivated land parcels, so that the semantic segmentation network can better distinguish the edge and internal area of cultivated land parcels; 2) A cascaded semantic segmentation and edge detection network is introduced to correlate the prediction of cultivated land surface and line, realize the fusion of boundary and texture features of cultivated land parcels and strengthen the edge features of cultivated land, so as to improving the accuracy of cultivated land block edge detection; 3) A focus training technique is proposed to address the problem that the edge pixels of cultivated land are far fewer than non-edge pixels, by enforcing the model pay more attention to the important but underrepresented edge pixels in high resolution remote sensing images in the training process, so as to improve the edge detection accuracy. We conduct experiments in Shaodong County, Hunan Province in the southwest mountainous area, using the Google Earth high-resolution remote sensing images as the data source, with a spatial resolution of 0.53 m. After manual selection, a total of 1000 512×512 image patches are obtained. Among them, 600 pieces are used as the training set, 200 pieces are used as the verification set, and 200 pieces are used as the test set. Experimental results show that the presented model achieves satisfying results with an overall accuracy of 92.91% and IoU (Intersection-Over-Union) of 82.84% on the test set, which was 4.28% and 8.01% higher than the baseline method respectively. Compared with the existing methods, the cultivated land extracted in this study is more consistent with the actual distribution pattern of cultivated land, which provides a practical method for accurate extraction of cultivated land information at the plot scale in mountainous and hilly regions.
Abstract: Accurate and rapid conflict identification of potential land use can effectively coordinate the conflicting land types to deal with the ever-increasingly severe land use in recent years. Taking the main urban area of Anshan as the research object, a multi-objective suitability evaluation was carried out to protect the cultivated land near the main urban areas using ArcGIS software. A mapping function and coupling coordination degree model were also selected to identify the conflict zones. Auxiliary decision-making support was provided to integrate with the third line in the land and space planning, particularly to implement differentiated use and protection of surrounding cultivated land. The research results show that the height suitable for cultivated land was 2459.00 hm2; accounting for 24.72%, and the moderate cultivated land was 7423.05 hm2, accounting for 74.64%, indicating more than 90% of the surrounding areas of the main urban area. The cultivated land presented strong farming suitability. The areas of highly suitable construction and moderately suitable construction were 1736.63 hm2 and 7666.78 hm2 respectively, accounting for 5.43% and 77.09%, respectively. Most cultivated land around the city presented strong construction suitability, indicating a greater risk of potential cultivated land-use conflicts. Cultivated land around the main urban area was divided into 9 types of areas, including 3 types of potential land use conflict zones, accounting for 22.20% of the total area. These lands were mainly distributed around the main urban area and along the main roads, indicating superior natural resource conditions and significant geographical advantages. Geographical location factors, 3 types of farming advantages were non-conflict areas, accounting for 67.33% of the total area. The area presented complete irrigation and drainage facilities, as well as high organic matter content, but it was far away from the main road with low construction suitability, particularly suitable for agricultural purposes. 3 types of construction advantages were conflict-free areas, accounting for 10.47% of the total area. The effective soil thickness of cultivated land in this area was thin, mainly clay soil and lack of irrigation and drainage facilities, but the distance from the central city and roads was relatively short. Recently, good location and high construction suitability were a candidate area for newly-added construction land. Taking into account the natural, geographical and socio-economic conditions of cultivated land around the city, the high-quality contiguous cultivated land in the high and medium potential conflict areas and the farming advantaged areas were designated as permanent basic farmland, particularly benefits to the higher level of mechanization and large-scale agricultural production. There was construct scattered cultivated land in advantageous areas as land for flexible development of urban development boundaries. The land greatly contributed to the vitality of inventory, the degree of land saving, and intensive use in the main urban area, but to reduce the occupation of cultivated land around the city. The cultivated land in the low potential conflict area within the ecological red line was designated as Ecological land to ensure the stability of the ecological security pattern around the city. The finding can provide strong references for the conflict discrimination of suitable types of cultivated land use, while the protection of cultivated land around cities.
Abstract: Higher carving speed and uniform petal size of Hami melon are critical for the robot carving Hami melon. It is very necessary to plan the cutting path of the execution terminal (carving knife) in real-time, according to the three-dimensional coordinates of different processing objects. In this study, a uniform petal carving of Hami melon was proposed using point cloud splicing. The image features were extracted and reconstructed sparsely. The feature parameters of melon were firstly obtained by point cloud coordinates. Secondly, CMVS/PMVS algorithm was selected for dense reconstruction using the sparse points. Finally, the octree and Poisson surface reconstruction were used to obtain the accurate 3D spatial coordinates of melon. Different shapes of Hami melon was led to different reconstructions. Each piece of flesh presented the same volume after carving. The specific procedure was as follows. Firstly, the cutting height and depth of melon were determined to extract the point cloud. An arc function was then fitted to determine the center of the circle, according to the point cloud of the outermost circle of Hami melon. The number of carving petals was divided 360° to determine the pre carving start point, end point, and path. Specifically, the initial triangle was formed to search for the two closest points from any point in the numerous point clouds as the benchmark, and then to expand the triangle outward with the three sides of the triangle as the baseline, where the equal volume of each petal was taken as the objective function, while the equal cutting depth and cutting angle of each petal as the limiting conditions. Until all the point clouds were included in the three-dimensional triangle network, the area of the projected triangle was calculated by the Helen formula, where the average value for the Z coordinates of three projected points was taken as the height, and then to calculate the volume of the triangular pyramid. After depth-first and particle swarm optimization, the optimal solution was found in the coordinates of Hami melon point cloud through continuous recursive iteration. Finally, better cloud coordinates were stored as new datasets and then marked on the outside of Hami melon. As such, the manipulator was controlled to evenly carve the Hami melon. Specifically, the cutter first adjusted to the appropriate posture angle as posture point 2, then moved along the cutter ridge to a certain depth to posture point 1, and retreated to posture point 3, and finally, the cutter moved along the outer surface of Hami melon to the next adjacent posture point 2. These steps were repeated to complete the overall carving of the Hami melon. The regular and irregular models were also selected to verify the accuracy. The calculated volumes of cube, pyramid, and irregular body were compared with the real. Forty eight Hami melons (16 groups, 3 in each group) were divided, where the number of carved petals N was 15-30, and the carving depth H was 1.5, 2.0, and 2.5 cm. It was found that the precision of the group was the lowest with the number of cut petals N equal to 28. The maximum and minimum petal volumes were measured as 3.40 and 3.25 cm3, respectively, where the maximum volume difference was 0.15 cm3, and the error was less than 5.00%. Consequently, the melon petal carving using point cloud splicing presented a higher precision than before. The findings can provide strong technical support for robot carving Hami melon.
Abstract: Moisture content is critical in the process of tea hot air drying. Taking green tea as an example, an experiment was performed on the dynamic hot air drying of rolled tea, in order to monitor the dynamic change of moisture content of tea with drying time under different feeding amounts (800-1 200 g), drying temperatures (90-120 ℃) and drum speeds (20-30 r/min). Each significant factor was analyzed to explore the dynamic changes of the water content of tea under different drying conditions. The experimental results show that there were significant effects of temperature, rotational speed, and feeding rate on the drying of tea leaves. The influence was sorted in the descending order of temperature, feeding rate, and rotating speed. Among them, the temperature has posed the greatest influence on drying. In the feeding amount, it was appropriate to cover the drum wall with tea to form a perfect casting curtain. That was because too much feeding amount easily caused uneven heating of tea, and then appeared dry outside and wet inside, even focal point explosion. The decreasing rate of water content in tea leaves showed a trend of first increased and then decreased in the whole drying. As such, the water loss was less at the lower water content, and finally, the water change tended to be gentle. The water content of tea leaves was basically stable at 4%-5% at the end of drying, particularly for convenient transportation and preservation. A prediction experiment was carried out, where the water content of tea drying was taken as the output, while the structure parameters of the dryer, drying temperature, drum speed, drying initial water, and prediction time as the input. BP, Elman, and PARTICLE swarm optimization Elman neural network (PSO Elman) neural network were used to establish the dynamic prediction model of tea moisture content during drying. A comparison was also made on the traditional multiple linear regression fitting model. The results of verification and error analysis of the Linear fit, BP neural network, Elman neural network and PSO-Elman neural network models showed that their determination coefficients R2 were 0.960 9, 0.998 0, 0.998 5, and 0.999 4, respectively. Compared with the traditional linear regression, the neural network was more accurately expressed the linear or nonlinear relationship in the complex system, showing better prediction for the tea drying. In three neural network models, the PSO-Elman model was more accurate than BP and Elman model, indicating better prediction on the change of water content during tea drying. The findings can provide a strong theoretical basis for the hot air drying of tea, therebyguiding tea processing and production for high efficiency and tea quality.
Abstract: Lentinus edodes are favored by consumers, due mainly to the antitumor, immunoregulation, anti-aging, antioxidation, and anti-radiation. However, the drying process can be used to extend the shelf life, because the fresh lentinus edodes are not easy to store. In this experiment, a new infrared-assisted spouted bed drying equipment was used to investigate the drying process of lentinus edodes under the segment variable temperature. An infrared-assisted spouted bed was utilized to improve the high energy consumption and heat loss of infrared drying with uniform distribution. A single factor Box-Behnken Design was used to optimize the response surface experiment. The parameters included the early wind temperature, water content at conversion point, and late wind temperature on specific power consumption, crude polysaccharide content, brightness value L* and shrinkage ratio. The polynomial regression was derived by a weighted comprehensive score to optimize the drying process parameters of an infrared-assisted spouted bed. The results showed that the crude polysaccharide content of lentinus edodes dried by infrared spouted assisted bed gradually increased, with the increase of early wind temperature (A), where the retention rate increased to a maximum of 9.33 mg/g at 60°C. The materials were also heated evenly during drying. The specific power consumption decreased to reach the minimum of 160.95 kJ/g, while the drying time was shortened, with the increase of temperature, when the early wind temperature was 60°C. Brightness value L* and shrinkage ratio showed a trend of first increased and then decreased, with the increase of early wind temperature at the maximum of 55°C. Appropriate early wind temperature could effectively reduce the specific power consumption, thereby maintaining high nutrients for better economic benefits. The content of crude polysaccharide increased significantly, where the maximum was 10.44 mg/g at 70°C, particularly when the late wind temperature (C) was 60°C-70°C. Furthermore, there was an obvious downward trend, when the temperature continued to rise. Excessive temperature could damage the retention of nutrients during drying, due mainly to polysaccharide degradation produced oligosaccharides and partial caramel. The drying rate accelerated, but the specific power consumption decreased, with the increase of temperature. In addition, there was the most obvious shrinkage ratio at 75°C, with the maximum yellow/blue value b* of 19.93, while the brightness value L* value continued to decrease, with the increase of late wind temperature. Correspondingly, there was a significant difference (P<0.05), particularly slightly browning, and yellow color of Lentinula edodes. The specific power consumption decreased gradually, with the increase of water content at conversion point (B). There was also a trend of first increasing and then decreasing in the crude polysaccharide content. The shrinkage ratio and brightness value L* increased first and then decreased, with the increase of water content at the conversion point. The single factor interaction was ranked in the order of AC>AB>BC. The optimal drying parameters were achieved using the response surface method, where the early wind temperature was 56.00°C, the water content at the conversion point was 53.00%, and the late wind temperature was 72.00°C. In this case, the specific power consumption was 143.52 kJ/g, the crude polysaccharide content was 9.98 mg/g, the brightness value L* value was 68.11, the shrinkage ratio was 83.15%, the comprehensive score value was 35.37, and the fitting degree with the predicted value was 99.27%. Consequently, the infrared-assisted spouted bed drying can widely be expected to fully meet the development trend and demand of lentinus edodes products. The finding can also provide a theoretical foundation for the production and processing of dried lentinus edodes products.
Abstract: Sweet taste is one of the most important tastes in food flavor and quality. Sweet molecules that can be used to produce new sweeteners have also been actively explored in food processing. However, the traditional methods cannot meet the rapid development of the economy and market demand, due mainly to time-consuming, laborious, and inefficient methods. Therefore, an effective and reliable strategy is essential to produce the sweet stuff. Currently, machine learning and structure-activity relationship can be utilized to realize accurate predictions of sweet molecules in the food industry. In this study, a new database of sweeteners and non-sweeteners together with the scores of sweetness was established using molecular sweetness and structure-activity correlation between molecular structures. MOE software was selected to compute molecular descriptors, to fully characterize the properties of molecules. These descriptors were then filtered through neighborhood variance screening, collinearity removal, and principal component contribution rate screening. Specifically, the feature descriptors were screened by removing the descriptors with high correlation. 80% of the dataset was then divided into training sets for model construction, and 20% were divided into test sets for model validation. Random forest and support vector machines were utilized to establish a qualitative structure-activity relationship for the prediction and identification of potential sweet molecules. Evaluation indexes were taken as the area under the receiver characteristic curve (AUC) and accuracy rate. The higher the AUC and accuracy rate represented the better classification. As such, the optimal model was obtained. Subsequently, the principal component, K-nearest neighbor, random forest, and partial least squares regression were used to establish the quantitative structure-activity relationship for better prediction of sweet molecules. The determination coefficient R2 and root mean square error (RMSE) were used as evaluation indexes of the quantitative structure-activity model. The higher R2 and lower RMSE showed the better model. The optimal model was obtained to compare the performance. The food composition database (FooDB) was applied to predict the possible sweet food ingredients and the sweetness. Correspondingly, the publicly accessible dataset was established ranging from artificially revised and continuously updated on sweetener, non-sweetener substances, and sweetness values. A new model was established to identify sweet molecules using the random forest. The accuracy of the model was 0.966 on the test set, and the area under the ROC curve was 0.987, indicating excellent predictive ability. The prediction model of sweetness was also established using the random forest. Specifically, the determination coefficient R2 was 0.82 and the root mean square error RMSE was 0.60. A manually modified data set was established to combine qualitative and quantitative sweetener prediction. 542 potential sweetener molecules, including lycopene were discovered in the food composition database. All data and code were then stored at the website of https://gitee.com/wang_lab/EMMSM for a better extension. Consequently, the new model indicated universal applicability and high practical application in searching for new sweet molecules.
Abstract: Biological plane geometry has been unable to meet the harsh requirements of bionic design in most soil contacting parts of tillage machinery in recent years, particularly on the operating speed, energy-saving, and emission reduction. In this study, a bionic investigation was performed on the toe of the foreleg claw in the mole cricket using the three-dimensional (3D) geometry. Projection and segmentation were also used to extract the 3D characteristic curves of claw toe in three orthogonal planes. The MATLAB platform was selected to determine the characteristic curves via the polynomial fitting and smoothing processing. An orthogonal experiment of bionic samples was carried out, where three plane configurations were taken as factors, while the different characteristics of configuration as levels. A total of 16 bionic specimens and 1 wedge-shaped comparison specimen were constructed by SolidWorks software and then fabricated using 3D printing (polylactic acid material). A test system of soil groove was utilized to evaluate the cutting resistance of each specimen, where the soil was assumed as the foamed phenolic plastics, the cutting speed was 10 mm/s, the cutting depth was 15 mm, and the cutting time was 20 s. The explicit dynamic Finite Element (FE) software ANSYS LS-DYNA was used to simulate the cutting process of the specimen, in order to determine the relationship between the 3D geometrical toes of the foreleg claw in the mole cricket and the drag reduction performance. It was found that the cutting process of the specimen was divided into the drag increase and stable phase. Furthermore, the drag reduction performance of specimens with 3D biological geometries was significantly better than that with one- and two-dimension, as well as the wedge shape. All configurations in the three planes also presented a significant impact on drag reduction. Correspondingly, the main influencing factor of drag reduction was the cross-sectional configuration perpendicular to the growth direction of claw toes. More importantly, the cutting resistance of the specimen was reduced up to 56.96% with 3D biological geometries. The FE analysis results showed that the 3D geometrical toes of the foreleg claw in the mole cricket effectively alleviated the accumulation of soil on the tip of the specimen. As such, the soil moved smoothly along the excavation surface, thereby avoiding the accumulation of pressure on the middle and back of specimens. This process was the reason for the reduction of cutting resistance. Furthermore, an optimal configuration of soil-contacting components was also achieved to reduce the cutting resistance, while effectively improving the working efficiency of machinery without the use of external energy and auxiliary devices. Nevertheless, the actual configuration was a 3D structure of soil-contacting parts in farming and engineering machinery, where many interrelated geometric parameters were involved during optimization. Consequently, the biological geometry can widely be expected to optimize soil-contacting parts, whether to project the main configuration of bionic objects in two dimensions, or to directly transplant the 3D biological geometry with 3D reverse. The characteristic curves of 3D biological geometry were also coupled to design bionic specimens. The feasible idea can also provide an insightful promising bionic design on soil cutting parts of tillage machinery, such as openers and subsoilers.
Abstract: Thermal properties of feed and artificial experience have been generally considered, when adjusting the process parameters of hygrothermal treatment in the production of fish feed, including cooling and drying. Specific heat, thermal conductivity, and thermal diffusivity are the important thermal properties of fish feed. In this study, grass carp (adult fish) extruded feed was taken as the research object. The inversion algorithm was established to obtain the temperature distribution of feed using the adjoint equation. A test was also carried out using the self-developed heat conduction device and infrared thermal imager. When testing, the feed was quickly spread on the cast aluminum soaking plate, where the feed was closely arranged in a single layer, with a thickness of about 4mm and a total of about 10 g. The infrared thermal images were captured for the feed layer surface and the upper surface on the cast aluminum soaking plate using the infrared thermal imager (accuracy±0.1℃). SmartView software was selected to process the infrared thermal images for the temperature-time data of the feed sample test surface (x=h) and heating surface (x=0), from the T-t data of x=0 and x=h. MATLAB software was selected first to solve the adjoint equation for the adjoint variables, then obtain the gradient value, and finally obtain specific heat c and thermal conductivity k. As such, the specific heat, thermal conductivity, and thermal diffusivity of feed were obtained, according to temperature distribution with the moisture content of 11%-17% and the temperature range of 20-80℃. The results show that the specific heat of grass carp extruded feed was 1.710-1.840 kJ/(kg·℃). Specific heat of feed increased significantly with the increase of temperature (P<0.05). When the moisture content increased from 11% to 17%, the specific heat of feed increased significantly (P<0.05), indicating a linear law. The thermal conductivity of grass carp extruded feed was 0.086-0.148 w/(m·K). When the temperature increased from 20℃ to 80℃, the thermal conductivity of grass carp extruded feed increased significantly (P<0.05). The effect of water content was also significant (P<0.05). The thermal diffusivity of feed ranged from 5.701 to 10.003 m2/s, depending significantly on temperature and moisture content (P<0.05). At the same time, the specific heat and thermal conductivity of feed were measured by differential scanning calorimetry (DSC) and thermal characteristic analyzer, respectively, where the thermal diffusivity was calculated as the measured value. Before the test, the feed particles needed to be crushed and passed through the 40 mesh screen. The inversion datum was taken as the calculated values. The linear fitting showed that R2 was greater than 0.980, indicating the feasible determination of thermal characteristic parameters of fish extruded feed using the inversion. The finding can provide a new idea for the determination of the thermal properties of fish feed.
Abstract: The Chinese government has stepped up efforts to the environmental protection. Coal, which was widely used in many aspects in northern China, has been prohibited from being used as heating source in winter since 2017. Reducing the energy consumption of the buildings is the issue need to be solved. Improving the application of clean energy is the key to solve energy and environment problems. Air source heat pump (ASHP) as a clean energy equipment has been widely used in civil and industrial buildings. But there has been no research on the application of ASHP in swine house. Pig farms are in urgent need of finding methods to conserve energy and reduce pollution emissions. The research of ASHP was carried out in pig house of Shunyi District, Beijing. The experimental pig house was 42 m long and 9.3 m wide. The ASHP heating system was installed in a swine barn in this test. There were 6 pipes to supply water and other 6 pipes to return water in the heating floor. The test was one period, the equipment performance monitoring period. Equipment performance monitoring period: November 20th, 2016-April 16th, 2017. The first stage (January 3rd, 2017-January 8th, 2017): pig house with pig test (two units). The second stage (January 9th, 2017-January 20th, 2017): pig house with no pig test (empty pig unit - unit 2). The energy saving rate of ASHP heating system and direct electric heating system were compared respectively by measuring the coefficient of performance (COP). ASHP heating system, direct electric heating system, liquefied natural gas (LNG) and natural gas heating system were compared the unit energy operating price, respectively. The average supply water temperature and return water temperature of ASHP were measured. The results showed that: during the test, the COP of the ASHP system is 2.86 when the average outdoor temperature is 0.1 ℃ during the heating period in Beijing. Compared with direct electric heating system, the energy saving rate of ASHP heating system is 66%. The unit energy operating price of ASHP, LNG, Natural Gas, direct electric and ASHP are 0.62, 0.34, 0.37 and 0.64 yuan/ kW·h, respectively. The CO2 emission reduction during the experiment was 8636 kg. The average supply water temperature and return water temperature of ASHP were (37.6±2.4) ℃ and (34.9±2.2) ℃, respectively. ASHP heating system has the potential to reduce energy consumption and CO2 emission, it is an economical and clean alternative energy source for pig barns heating. The air source heat pump system is suitable for pig house with solid floor, but not suitable for pig house with fully slatted floors.
Abstract: In order to understand the reclamation status of Lianghuai coal mine area and its influence mechanism on soil microorganisms, reasonable manual intervention, and quickly and effectively improve the productivity of reclaimed soil, this study takes coal gangue filling reclaimed soil as the research object, adopts field investigation and sampling analysis. Illumina MiSeq high-throughput sequencing analyzes the V4 region of specific gene fragments of soil bacteria, based on non-metric multi-dimensional scale analysis, redundancy analysis, variance analysis, fertility index, and regression model methods. Biodiversity was explored to clarify the soil bacterial community and its response to soil fertility. The research results show that from the analysis of bacterial community composition, different reclamation directions have no significant effect on the distribution of bacterial dominant communities, and the proportions of different reclamation directions are different. Proteobacteria (32.42%~42.97%), Acidobacteria (10.47%~15.87%), Actinobacteria (8.90%~18.28%) are the main dominant bacteria groups. Among them, Proteobacteria occupies an absolute advantage, accounting for more than 30%. Alpha diversity shows that there is no significant difference in the abundance and diversity of bacterial soil samples in different reclamation directions. Shannon_Wiener index ranges from 5.23 to 6.91, Chao1 index ranges from 867.1 to 5436, and the Pielou index of each sample fluctuates around 0.8, Maintain stable changes. Beta diversity analysis showed that there was no significant difference in the composition of bacterial communities in different reclamation directions, and the composition of soil bacterial communities was negatively correlated with soil depth. The surface, middle, and deep soils have different soil bacteria living conditions such as moisture, aeration, temperature, and nutrients, resulting in differences in the composition of soil bacteria. The pH is consistent with the change of the diversity index, which affects the dominant microbial flora and biodiversity to a certain extent, but there is no significant difference in different reclamation directions. A one-way analysis of variance was carried out on soil fertility indexes of different reclamation directions, and it was found that the content of fertility indexes of surface soil was higher than that of bottom soil in general. Based on the evaluation of fertility index, the fertility quality is cultivated land >grassland>forest, and cultivated land is the best reclamation direction. Redundancy analysis shows that TN, SOM, AP and AK are the main fertility factors that affect the composition of soil bacterial communities, but some dominant bacterial communities do not respond to fertility factors significantly, which may be related to the high complexity of the soil microbial community and the regional conditions. The particularity and other factors are related. The regression model showed that the soil fertility index was extremely significantly positively correlated with the relative abundance of the Thaumarchaeota(P<0.01), and Streptomyces was significantly negatively correlated (P<0.05), and the correlation with the main dominant phylum was not strong. It may be caused by the complexity of the soil environment of the coal gangue reclaimed land. Based on the linear regression model and the functional effects of Thaumarchaeota and Streptomyces, the relative abundance of Thaumarchaeota and Streptomyces can be used as important biological indicators to evaluate soil fertility status. The research results can provide theoretical support for improving the fertility quality of Lianghuai mining area by filling the reclaimed soil with gangue at the microbial level.
Abstract: There are hydrophilic clay minerals kaolinite and hydromica in Benggang soil, which can produce obvious shrinkage and cracking phenomenon in the process of water evaporation. Because Benggang soil is a special soil with obvious stratification formed in the process of natural geological evolution, the shrinkage and cracking characteristics of different soil layers are obviously different. In order to study the influence of height-diameter ratio on soil shrinkage and cracking characteristics, this paper selected Benggang soil in Wuli Town, Tongcheng County, Hubei Province, and designed 10 groups of height-diameter ratio. During the experiment, soil samples were configures as supersaturated mud, and water evaporation was accelerated by low wind speed fans. The soil morphology changes before and after dehumidification were photographed at a fixed position, combined with digital image processing technology to carry out quantitative analysis, and discussed the shrinkage and cracking rules of Benggang soil under the condition of controlling height-diameter ratio. Results are as follows: (1) Among the four layers of Benggang soil, the radial shrinkage and cracks development characteristics in the transition layer are the strongest, while that of sandy layer is the weakest. In the vertical section of Benggang soil, the transition layer and sandy layer belong to the lower soil, and they are adjacent soil layer. The large difference between the two soil layers will seriously damage the stability and bearing capacity of Benggang, promote the collapse of Benggang wall. (2) The samples with smaller height-diameter ratio have significant cracks development, but the radial shrinkage is not obvious; the samples with larger height-diameter ratio have no cracks and the radial shrinkage is significant. Among them, the specific critical values of the height -diameter ratio of four soil layers by drying shrinkage cracking state transition to radial shrinkage state are respectively: 0.147～0.160, 0.160～0.183, 0.160～0.183, 0.134～0.147. (3) For the same soil layer, when the height-diameter ratio is same, even though the height and diameter are different, the crack parameters and radial shrinkage ratio are similar, and the axial shrinkage ratio increases with the increase of thickness. From the topsoil layer to transition layer, the crack morphology becomes more complex, and the sandy layer is not significant. (4) With the increase of height-diameter ratio, the shrinkage water content gradually increases, and the crack water content gradually decreases. The difference between the two can represent the tensile strength of the soil during the dehumidification process. The degree of shrinkage cracking, width-diameter ratio, radial shrinkage ratio increase with the increase of height-diameter ratio, while the other parameters show a decreasing trend. Among the four soil layers, the height-diameter ratio has the most significant influence on shrinkage cracking characteristics of transition layer, and the influence of sandy layer is the least. The research results show that the shrinkage and cracking characteristics of 4 soil layers of Benggang, and the influence of height-diameter ratio on shrinkage cracking characteristics. It can provide scientific basis for revealing the collapse mechanism of Benggang, and provide theoretical support for improving the stability of Benggang.
Abstract: To clarify the resources and environmental background of cultivated land and identify the priority areas of fallow in China, in this study, the Nemerow integrated pollution index, the groundwater level variation method, evaluation method of the importance of ecosystem service function and ecological environment sensitivity were used to systematically identify the spatial pattern and differentiation characteristics of ecological stress factors of China’s cultivated land from four dimensions, including status of soil pollution, arable land quality, over-exploited groundwater, and ecological protection red line delineation. And then a multi-criteria optimization of the fallow rule was constructed for identifying the scale of fallow and the spatial distribution of priority areas under the following three scenarios in China, priority to food safety (PFS), minimum production capacity loss (MCL), and priority to ecological security (PES). Especially, each fallow scenario sets low, medium, and high schemes for better prioritizing fallow units. Combining the three fallow scenarios to carry out spatial weighing of all factors to identify the fallow priority areas of cultivated land under resources and environmental constraints, ensuring ensure the optimal matching of the correlation between food production, food quality, and ecological security. The results showed that: 1) The area of arable land within the red line of ecological protection delineation in northern China is much higher than that in the south, and the area of arable land within the first-class and the second-class ecological protection red line delineation accounts for 3.57%, and 1.95%, respectively; 2) the ratios of farmland in China with slight, moderate and severe pollution were 18.56%, 2.31%, and 1.23%, respectively. The overall pollution in the south was higher than that in the north, while the south was partially scattered and the north showed a pattern of spot-like agglomeration; 3) the over-exploited groundwater areas were mainly concentrated in provinces of Hebei, Henan, Jilin, and Jiangsu, with severe over-exploited areas accounted for only 0.68% in total China. While the two provinces of Hebei and Henan have formed severe over-exploited areas with large-scale contiguous patterns, and the areas are 4670km2 and 3950km2, respectively; 4) the total proportions of arable land quality in the grade of the inferior and poor account for 3.69% and 14.0%, respectively, and the proportion of inferior or poor grade shows in northern China with the widely dispersed pattern was significantly higher than that in southern China. According to the comprehensive evaluation of China’s cultivated land ecological status and multi-criteria fallow rules, the total area of priority fallow areas accounted for 23.70%, of which the proportions of the prohibited-planting-fallow zone (I), restricted-planting-fallow zone (II), key-rotation zone (III) and general-rotation zone (IV) are 1.95%, 4.71%, 6.18%, and 10.86%, respectively. Compared with the three fallow scenarios of priority to food safety, minimum production capacity loss, and priority to ecological security, the total area of priority fallow areas is 8.40%, 4.18%, and 3.12% higher. This study shows it is necessary to clarify the background of cultivated land resources and the environment from the perspective of source governance to weigh the urgency of the fallow unit, and then provide technical support for the effective implementation of fallow planning, soil pollution controlling, and cultivated land protection technological innovation at the national level.
Abstract: Based on the analysis of human-earth system evolution of the watershed in Loess Plateau, this paper quantitatively explores the characteristics and rules of the temporal and spatial evolution of agricultural production function under the background of rural transformation and development. The Nianzhuang watershed, located in Baota County, Yan'an city, is chosen as the study area. The data comes from high resolution image interpretation and field surveys during five periods from 1985 to 2018. The results show that: 1) The quantitative diagnosis system of gully agricultural production function can effectively identify the spatial pattern of gully agricultural production function, and the dynamic evolution monitoring model can sensitively reflect the multiple evolution path of gully agricultural production function oriented by "economic-society" and "resource-ecology". 2) During the study period, the function space of gully agriculture in the study area has changed from traditional to modern production, and 2012 is the turning point of gully production function transformation. The traditional agricultural production function of gully is characterized by "small expansion - relatively stable - sharp reduction", while the modern agricultural production function of gully is characterized by "relatively stable - small expansion - sharp increase", and the functional diversity is increasing. The results provide a micro case of agricultural function transformation in the typical gully region of the Loess Plateau. 3) On the whole, the scope and intensity of the traditional gully agricultural production function show a decreasing trend. The functional space of modern gully agricultural production is continuously expanding, and the dominant direction is changing. Microscopically, the traditional agricultural production function takes the location of towns in the basin as the center, showing a concentric belt reduction. 4) The core goal of the high-quality development of gully agriculture in the Loess Hilly and gully region is to promote the "four turns", comprehensively build the "three cycles" model, promote the formation of a new pattern of industrial internal circulation in the Loess Plateau and its mutual promotion and development with the double cycles in the Yellow River basin, and further explore new kinetic energy and new ways to optimize agricultural production mode and innovate management mode. It is of practical significance to optimize allocation of regional land resources and the high-quality development of rural transformation.
Abstract: It is of great significance to establish a regulation system on the basis of quality evaluation for regional cultivated land quality construction. Based on the evaluation results of slope farmland quality in Yunnan Province, this study proposed a zoning regulation model of slope farmland quality based on obstacle factor diagnosis, factor adjustability analysis, factor suitable interval determination and regulation potential calculation. The results showed that: 1) the main types of quality obstacles of Sloping Farmland in Yunnan were erosion degradation type, drought and water shortage type, organic matter deficiency type and nutrient deficiency type. 2) The controllable factors of slope farmland quality are composed of plough layer thickness, soil bulk density, pH value, organic matter, total nitrogen, available phosphorus, available potassium, irrigation guarantee rate and field slope, among which field slope, soil organic matter, irrigation guarantee rate, available phosphorus, available potassium and pH value are the priority factors. 3) The goal of quality control of sloping farmland is to make the adjustable factors in the appropriate range, including two scenarios of ideal state and actual state; the potential of quality control of Sloping Farmland in Yunnan is 0.347 in ideal state, and its quality level can be upgraded from "medium" to "high" in current situation; the potential of quality control of Sloping Farmland in actual state is 0.198, and its quality level can be upgraded from "medium" in current situation Etc. to a higher level. 4) According to the difference of quality grades and obstacle types of Sloping Farmland in different regions, the model of "soil and water conservation tillage + slope water system + soil fertility" is put forward, which is suitable for central and Southeast Yunnan; the model of "slope to terrace + soil and water conservation tillage + ecological rehabilitation" is suitable for Southwest and West Yunnan; the model of "slope to terrace + soil and water conservation tillage + slope water system" is suitable for central and Southeast Yunnan The model of "ecological conversion of farmland + slope to terrace + soil fertility" is suitable for Northeast and Northwest Yunnan. The study can provide reference for the cultivation and management of slope farmland quality at provincial scale.
Abstract: Field crop pest detection is a challenging topic, due to the intra-class and inter-class pests in the field with various colors, sizes, shapes, postures, positions, and complex backgrounds. Convolutional Neural Network (CNN) has excellent performance in complex image detection and recognition, but has no mechanism to adapt to the geometric deformation of pests in the existing CNN models. Based on VGG-16, a Deformable VGG-16 (DVGG-16) model was constructed and applied to field crop pest detection in this study. It consisted of six convolutional layers, four deformable convolutional layers, five pooling layers, and one global average pooling layer. A global average pooling operation instead of three fully connected layers of VGG-16 can speed up the network training. Four convolutional layers in VGG-16 were replaced by four deformable convolutional layers to improve the characteristic expression ability of the network and the practicality of VGG-16 to insect image deformation, and a global pooling layer was used instead of three fully connected layers of VGG-16 to reduce the number of the training parameters, accelerate the network training speed, and avoid the overfitting problem to a certain extent. The offset added in the deformable convolution unit was part of the DVGG-16 structure and was calculated by another parallel standard convolution unit, which also was learned end-to-end through gradient backpropagation. By the offset after learning, the size of the deformable convolution kernels and position were adjusted according to the current need to identify the dynamic image content of the crop pests, which could adapt to different shapes, sizes, and other geometric deformation of the object. Moreover, data augmentation was performed on the original dataset to increase the number of training samples by bilinear interpolation, cropping images, rotating images, and adding salt-pepper noise to the images, improving the generalization ability and robustness of the model. In DVGG-16, a parallel convolution layer was used to learn the offset corresponding to the input feature map. By adding an offset at the corresponding position of each sampling point, the constraint of the regular grid of normal convolution could be broken, and arbitrary sampling was performed around the sampling location. DVGG-16 was adapted to various insect images with different shapes, states, and sizes due to the deformable convolution. It was evaluated on the actual field pest image database and compared with two feature extraction based algorithms and two deep learning-based methods, i.e., Image-based Orchard Insect Automated Identification (IIAI), Local Mean Colour Feature and Support Vector Machine (LMCFSVM), Improved Convolutional Neural Network (ICNN), and VGG-16. The detection accuracy of DVGG-16 was 91.14%, which was 28.60% and 26.97% higher than that of IIAI and LMCFSVM methods, and 7.72% and 9.01% higher than that of ICNN and VGG-16 based methods, respectively. The training time of DVGG-16 was 7.98 h longer than that of the ICNN because the deformable convolution operation was realized by bilinear interpolation, which resulted in the increase of computational complexity and training time of DVGG-16 compared with ICNN. The test time of the DVGG-16 based method was 0.02s and 0.17s faster than that ICNN and VGG-16 based methods, respectively. The results validated that DVGG-16 was effective and feasible to detect the variable pests in the field. The proposed method could provide a reference for the effective detection of pests in the complex field background and realize the feature extraction of irregular field insect images without changing the spatial resolution.
Abstract: The number of spikes per unit area is a key yield component for cereal crops such as wheat, which is popularly used in wheat research for crop improvement. With the fast maturity of smartphone imaging hardware and recent advances in image processing and lightweight deep learning techniques, it is possible to acquire high-resolution images using a smartphone camera, followed by the analysis of wheat spikes per unit area through pre-trained artificial intelligence (AI) algorithms. Then, by combining detected spike number with variety-based spikelet number and grain weight, it is feasible to carry out a near real-time estimation of yield potential for a given wheat variety in the field. This AI-driven approach becomes more powerful when a range of varieties are included in the training datasets, enabling an effective and valuable approach for yield-related studies in breeding, cultivation, and agricultural production. In this study, we present a novel smartphone-based software application that combines smartphone imaging, lightweight and embedded deep learning, with yield prediction algorithms and applied the software to wheat cultivation experiments. This open-source Android application is called YieldQuant-Mobile (YQ-M), which was developed to measure a key yield trait (i.e. spikes per unit area) and then estimate yield based on the trait. Through YQ-M and smartphones, we standardized the in-field imaging of wheat plots, streamlined the detection of spikes per unit area and the prediction of yield, without a prerequisite of in-field WiFi or mobile network. In this article, we introduce the YQ-M in detail, including: (1) the data acquisition designed to standardize the collection of wheat images from an overhead perspective using Android smartphones; (2) the data pre-processing of the acquired image to reduce the computational time for image analysis; (3) the extraction of wheat spike features through deep learning (i.e. YOLOV4) and transfer learning; (4) the application of TensorFlow.lite to transform the trained model into a lightweight MobileNetV2-YOLOV4 model, so that wheat spike detection can be operated on an Android smartphone; (5) finally, the establishment of a mobile phone database to incorporate historic datasets of key yield components collected from different wheat varieties into YQ-M using Android SDK and SQLite. Additionally, to ensure that our work could reach the broader research community, we developed a graphical user interface (GUI) for YQ-M, which contains: (1) the spike detection module that identifies the number of wheat spikes from a smartphone image; (2) the yield prediction module that invokes near real-time yield prediction using detected spike numbers and related parameters such as wheat varieties, place of production, accumulated temperature, and unit area. During our research, we have tested YQ-M with 80 representative varieties (240 1m2 plots, three replicates) selected from the main wheat producing areas in China. The computed accuracy, recall, average accuracy, and F1-score for the learning model are 84.43%, 91.05%, 91.96%, and 0.88, respectively. The R2 correlation between YQ-M predicted yield and post-harvest manual yield measurement is 0.8392 (n=80 varieties, p <0.05; RMSE = 17.6413). The results suggests that YQ-M presented here has a high accuracy in the detection of wheat spikes per unit area and can produce a consistent yield prediction for the selected wheat varieties under complex field conditions. Furthermore, YQ-M can be easily accessed and expanded to incorporate new varieties and crop species, indicating the usability and extendibility of the software application. Hence, we believe that YQ-M is likely to provide a step change in our abilities to analyze yield-related components for different wheat varieties, a low-cost, accessible, and reliable approach that can contribute to smart breeding, cultivation and, potentially, agricultural production.
Abstract: It is an important development direction of precision agriculture and smart agriculture to monitor crop growth by using UAV remote sensing. In order to evaluate inversion accuracy of Leaf Area Index (LAI) and chlorophyll based on integrated multi-spectral drones, we collected the multi-spectral images at three flight altitudes (30m, 60m, 120 m). The difference spectral index (DSI), ratio spectral index (RSI), normalized spectral index (NDSI) and empirical vegetation index were constructed based on collected multi-spectral image at three flight altitudes respectively. Correlation analysis was implement on constructed spectral index and ground-measured data. According to the value of determination coefficient, the multiple stepwise regression model, the partial least squares regression model and the artificial neural network model were constructed for evaluating the inversion accuracy of wheat canopy LAI and chlorophyll. The experimental results showed that: at a height of 30m, the green-red ratio spectral index had the highest correlation with wheat LAI, and the red-blue ratio spectral index had the highest correlation with wheat chlorophyll content; at a height of 60 m, the empirical vegetation index had the highest correlation with wheat LAI and chlorophyll content. The best inversion result of wheat LAI was come from the partial least squares regression model. The determination coefficient is 0.732, and the root mean square error of 0.055. The best inversion result of wheat chlorophyll content was come from the artificial neural network model. The determination coefficient is 0.804, and the root mean square error of 0.135. This research provide a theoretical basis for high-throughput crop monitoring based on the UAV platform, and provide a reference for the customized integrated UAV to achieve rapid estimation of crop growth parameters.
Abstract: In mountainous and hilly areas, cultivated land resources are scarce, and the phenomenon of cultivated land fragmentation is serious. The long and narrow arable land plots are complex in structure, which makes it difficult to obtain the information of cultivated land at the land level quickly and accurately, and hinders the application of precise digital agricultural services based on high resolution remote sensing images in mountainous and hilly areas. Parcle-level cultivated land information can intuitively show the spatial distribution, boundary details of farmland, and is of great significance for precision agriculture management, distribution of planting subsidies, and agricultural resource survey. Existing edge detection/semantic segmentation networks-based farmland extraction methods ignore the structural features of the parcel, thus have limit performance for handling narrow and small plots, and there is also a blurring boundary problem. To address these issues, we proposed an accurate extraction method of cropland in mountainous area based on geographic parcels. This method combines the advantages of semantic segmentation and edge detection, and effectively extracts and integrates the linear features of the boundary and the internal texture features of the parcel, so as to improve the recognition accuracy of the cultivated land. The main features of the model in this paper are as follows: 1) The edge of cultivated land is regarded as a new class independent of cultivated land parcels, so that the semantic segmentation network can better distinguish the edge and internal area of cultivated land parcels; 2) A cascaded semantic segmentation and edge detection network is introduced to correlate the prediction of cultivated land surface and line, realize the fusion of boundary and texture features of cultivated land parcels and strengthen the edge features of cultivated land, so as to improving the accuracy of cultivated land block edge detection; 3) A focus training technique is proposed to address the problem that the edge pixels of cultivated land are far fewer than non-edge pixels, by enforcing the model pay more attention to the important but underrepresented edge pixels in high resolution remote sensing images in the training process, so as to improve the edge detection accuracy. We conduct experiments in Shaodong County, Hunan Province in the southwest mountainous area, using the Google Earth high-resolution remote sensing images as the data source, with a spatial resolution of 0.53 m. After manual selection, a total of 1000 512×512 image patches are obtained. Among them, 600 pieces are used as the training set, 200 pieces are used as the verification set, and 200 pieces are used as the test set. Experimental results show that the presented model achieves satisfying results with an overall accuracy of 92.91% and IoU (Intersection-Over-Union) of 82.84% on the test set, which was 4.28% and 8.01% higher than the baseline method respectively. Compared with the existing methods, the cultivated land extracted in this study is more consistent with the actual distribution pattern of cultivated land, which provides a practical method for accurate extraction of cultivated land information at the plot scale?in mountainous and hilly regions.
Abstract: Under the market-oriented economy system, it is of great significance to establish a view of “resource-asset-capital” attributes of cultivated land and promote related cultivated land utilization practices for realizing the efficient utilization and allocation of cultivated land. Based on the idea of “attributes analysis-quality evaluation-zoning management”, this study summarized the connotation of “resource-asset-capital” attributes of cultivated land and used multi-source data to construct the “resource-asset-capital” quality evaluation system based on the attributes connotation analysis in Xundian County, which is a typical agricultural county in mountainous areas of Yunnan Province. According to the spatial agglomeration characteristics of different quality evaluation results in Xundian County, this study also makes a zoning plans of local cultivated land management using the results of local autocorrelation analysis and put forward the targeted cultivated land management measures for each zone. The results show that: 1) The resource attribute of cultivated land refers to people work on agricultural activities to get the agricultural products from cultivated land under a certain of natural conditions, such as light, temperature, water, soil, heat and etc; the asset attribute of cultivated land means the cultivated land resources in social relations can bring benefits to the subject of property rights by determining the ownership through the legal system; the capital attribute of cultivated land is that cultivated land can be traded and circulated in the market to obtain high profits. The resource, asset and capital attributes have the influence on each other and gradually develop, which is the only way for the value of cultivated land resources. 2) There are huge differences among the geographical distribution and spatial pattern of resource, asset and capital quality of cultivated land. Compared to asset and capital quality, resource quality of cultivated land shows a less variation and more stable geographical distribution. In terms of spatial pattern, resource quality of cultivated land in Xundian County presents a "high in the east and west and low in the middle" trend in spatial pattern. However, the asset and capital quality of cultivated land in Xundian County shows a "gradient decreasing towards the urban center" and a "high in the southeast and low in the northwest" patterns, respectively. 3) Taking the administrative village as the basic research unit, this study zoned the Xundian County into four different area based on the comprehensive spatial agglomeration analysis results of different quality of cultivated land, including market-oriented pilot zone, market-oriented cultivation area, efficient upgrading area and remediation concentration area. The differentiated management measures are also put forward for each zone, such as formulate and implement policies and regulations to eliminate the obstacles restricting the entry of high-quality cultivated land resources into the market for market-oriented pilot zone, further improve the property rights system and the income distribution mechanism, encourage and ensure the rational circulation of cultivated land resources for market-oriented cultivation area and etc. This study can provide guidance for the protection and development of cultivated land management in Xundian County and also can provide scientific reference for the practice of cultivated land management in other mountainous areas of Yunnan province.
Abstract: A nutritious and healthy diet can reduce the incidence of disease, and it can also improve the health of the body after the disease occurs. Nutritional diet knowledge was mostly acquired through the Internet. Faced with the huge amount of Internet information, users were difficult to integrate information, search time-consuming, and can’t discern whether the information was reliable or not. It was an urgent problem to integrate the complicated data and construct the knowledge graph of nutrition and health, because the knowledge graph can timely and accurately return the information users need Therefore, it was a key step to accurately identify entities in nutritional health texts and provide effective data support for the construction of knowledge graph. Named entity recognition is an important step in constructing knowledge graph, and location information is effective in named entity recognition task This study first used the BRET+BiLSTM+CRF (Bidirectional Encoder Representations from Transformers + Bi-directional Long Short-Term Memory + Conditional Random Field) model with location information to prove that the precision of this method was 86.56%, recall rate was 91.01%, F1 score was 88.72%, compared with the BERT+BiLSTM+CRF model without location information, precision，recall rate and F1 score were improved by 1.55, 0.2, 0.32 percentage points. The validity of introducing location information was proved. Combining rules with BERT-FLAT (Bidirectional Encoder Representations from Transformers-Flat Lattice Transformer) model, this study proposed a named entity recognition method in the field of human nutritional health, which can accurately obtain six types of entities in text: food, nutrients, population, location, disease and efficacy. Firstly, character information and vocabulary information were stitched together and pre-trained in BERT model to improve the recognition ability of the model to entity categories. Then created a position code for the head position and tail position of each character and vocabulary, located the entity position with the help of position vector, and improved the recognition effect of entity boundary. Using the Transformer model, long-distance dependency can be captured, and the output of the BERT model was embedded into the Transformer as a character-embedding conjunction word, thus character-vocabulary fusion can be achieved. Then the text prediction sequence was obtained from the CRF layer. Finally, seven rules were formulated according to the text characteristics in the field of nutrition and health, and the prediction sequence was modified according to the rules. The experimental results showed that the F1 score of the BERT-FLAT model was 88.99%. Compared with the named entity recognition model without Bert, the recognition performance was the best, which showed that BERT model combined with word fusion can effectively recognize entities. The named entity recognition model in the field of nutrition and health based on fusion rules and BERT-FLAT model proposed in this study had an accuracy rate of 95%, a recall rate of 88.88% and an F1 score of 91.81%. Compared with the BERT-FLAT model without fusion rules, the F1 score was increased by 2.82 percentage points. The study showed that this method was an effective entity recognition method in the field of human nutrition and health, and can provide a new idea for complex named entity recognition in other fields such as agriculture, medical treatment, food safety and so on.
Abstract: Traditional manual measurement was a time-consuming and labour-intensive work with limited sample size, and could not meet the needs of high-throughput phenotyping research for breeding. Therefore, improving the throughput of phenotyping measurement in the field is a big challenge in plant genetics, physiology and breeding. Unmanned Aerial Vehicle (UAV) Remote Sensing had the advantages of high temporal and spatial resolution, fast image acquisition, easy operation and portability, and relatively low cost. At present, UAV had gradually become an important tool to obtain crop phenotypic parameters. And phenotypic researchers paid more attention to pursuing faster image acquisition of UAV. However, the increase in image acquisition could only be realized by increasing the flight height, which would inevitably lead to the reduction of image resolution and measurement accuracy. Efficient techniques were urgently needed to reconstruct the corresponding high-resolution images from the low-resolution images without reducing the measurement accuracy, while increasing the spatial resolution and speeding up image acquisition. In this study, UAV image sequences of maize were obtained at seedling stage, 6th leaf stage, 12th leaf stage, tasseling stage and milk stage. Super-resolution images were then reconstructed combined with wavelet transform and bicubic interpolation. Reconstructed images had higher reconstruction quality, less distortion with peak signal-to-noise ratio of 21.5, structure similarity of 0.81 and mean absolute error ratio of 6.4%. Reconstructed images had lower estimation error for plant height and biomass estimation with root mean square error of 0.39 cm and 0.19 kg. Ground sampling distance of reconstructed image would be twice that of original image with super resolution reconstruction. Ground sampling distance of reconstructed image at a flight height of 60 m was similar to that of original image at a flight height of 30 m. However, UAV at a flight height of 60 m could scan 0.2 hm2 larger fields per minute than at a flight height of 30 m. Plant height, canopy coverage and vegetation index were extracted from the original and reconstructed images. Leaf area index was calculated by the 3-D voxel method based on point cloud. The method of filtering the appropriate voxel size to create 3-D voxels can not only ensure the original shape of the point cloud, but also can compress the data and improve the efficiency of the algorithm. The estimated leaf area index by oblique photography correlated better with measured LAI with slope of 0.72 and with root mean square error of 0.14. All canopy structure, spectrum and population structure parameters were then used to construct estimation models of above ground biomass based on single characteristic parameter and multimodal data using partial least squares regression. Higher above ground biomass estimation accuracy was obtained by multimodal data fusion compared with a single parameter with coefficient of determination was 0.83 and root mean square error of 0.19 kg. Multimodal data fusion can overcome the problem of canopy saturation to a certain extent. Estimation accuracy did not decrease, but slightly improved by combining image super-resolution reconstruction and multimodal data fusion technology. Meanwhile higher spatial resolution and higher estimation accuracy could be improved by super-resolution and multimodal data fusion technology, which could meet the demand for higher data acquisition throughput. Therefore, the results of this study provided a highly effective and novel solution to above ground biomass estimation, could be used to analyze the association between genotype and phenotype, and provided the basis for cultivating high-quality maize varieties adapted to mechanized production.
Abstract: Abstract: The establishment of a diversified fallow ecological compensation system is an inevitable choice for the sustainable development of China's agriculture. It is the key to improve the efficiency of ecological compensation for fallow in arid areas to explore the spatial distribution method of fallow land. Taking the Kaidu-Kongque River basin in Xinjiang as an example, this article aims to determine the spatial layout of fallow and to propose different compensation strategies for different zones, considering cultivated land quality and land degradation risk. The specific procedures were:1) The evaluation index system of cultivated land quality was established to select the indicators from two aspects of soil physical and chemical properties and cultivation convenience. The comprehensive evaluation method was used to evaluate quality of cultivated land;2) Based on the MEDALUS-ESAs model, four main indicators including soil, climate, vegetation and land use and management were selected for estimating potential land degradation risk in the basin; 3) The Z-score method was applied to the standard processing of the cultivated land quality score and land degradation risk index. The standardized value was divided into four quadrants according to the coordinate axis to determine the spatial distribution of fallow. Specifically, the cultivated land with "low quality and low risk" was classified as priority fallow area, “high quality-low risk” was classified as sub-priority fallow area, “low quality-high risk” was classified as restricted fallow areas, “high-quality-high-risk” was classified as fallow area.4) Different compensation strategies for fallow were proposed according to different zones. The results showed that:1) The overall quality of cultivated land in the whole Kaidu-Kongque River Basin is good, but poor in local areas. The spatial pattern of land degradation risk is “low in the northern, high in the southern”;2) The area of cultivated land located in the priority fallow area is 67814.60 hm2, mainly distributed in the western part of Kongque River Oasis and the northeastern part of Bosten Lake. The area of cultivated land located in the sub-priority fallow is 71784.94 hm2, mainly distributed in the northern part of the Kaidu River Oasis. The area of cultivated land located in the restricted fallow area is 80576.89 hm2, mainly distributed in the central area of the Kongque River Oasis, the northern and southern part of Bosten Lake and the eastern part of the Kaidu River Oasis. The area of cultivated land located in the forbidden fallow area is 107358.03 hm2, mainly distributed in the southern part of Kaidu River and Kongque River Oases and the eastern Bosten Lake. 3) The cultivated land located in the priority fallow area is restricted by cultivated land quality. Those land should be long-term fallowed, which combining with the cultivated land quality improvement. The fallow compensation in the zone be determined by the loss of agricultural income and the cost of land improvement. The cultivated land located in the sub-priority fallow area is in good condition, the fallow can be combined with agricultural water saving to implement seasonally fallow. The fallow compensation should be determined by the loss of agricultural income. The cultivated land in the restricted fallow area is restricted by cultivated land quality and ecological safety. Therefore, the fallow can be combined with cultivated land quality improvement and ecological protection to implement annual fallow, and thus the agricultural income loss, land improvement costs, and ecological protection costs standard should be considered into the fallow compensation.
Abstract: There are several advantages of high initialization performance and accelerating the convergence speed of the model when loading the pre-train model, therefore, almost all the object detection methods used at present need to load the pre-train model. However, there are following problems about loading pre-train model: 1) The network structure cannot be changed and when the device memory resources are limited, it may not be used; 2) There may be great differences between ImageNet dataset and dataset to be trained, hence, the training effect may not be very good. Based on above problems, this research attempts to take SSD model as the basic framework to propose a lightweight object detection method of Lingwu long jujube image, which achieves good results without loading the pre-train model, so as to provide visual technical support for the intelligent harvesting of Lingwu long jujube. Firstly, the Lingwu long jujube dataset was established, including 700 training images and 300 test images. The sorts of Lingwu long jujube images resolution consist of 3 016×4 032, 4 068×3 456 and 2 448×3 264. The models of smartphones used for image acquisition include HUAWEI TRT-AL00A, vivo Y79A and Xiaomi 2014501. In order to meet the input image size requirements of SSD object detection network, the Lingwu long jujube images are uniformly scaled to the resolution of 300×300. Data augmentation methods used in this study include random cropping, random vertical or horizontal flipping, random adjustment of brightness, contrast and saturation. We adopt the format of PASCAL VOC dataset. The labelImg software is used to label the Lingwu long jujube images, and the marked images are stored in the label folder in XML format. Secondly, the Convolutional Block Attention Modules and two dense blocks with convolution groups of 6 and 8 are used in improved DenseNet. Taking the proposed improved DenseNet as the backbone network, replacing the first three additional layers in the SSD model with the Inception module, and combining with the multi-level fusion structure, the improved SSD model is obtained. Then, the results of comparative experiments show the effectiveness of the improved DenseNet and the improved SSD model. The experimental results on Lingwu long jujube dataset show that without loading the pre-train model, the mAP of the improved SSD model is 96.60%, the detection speed is 28.05 frames / s, and the amount of parameters is 1.99×106, which is 2.02% and 0.05% higher than that of SSD model and SSD model (pre-train), respectively. The parameters of improved SSD model are 11.14×106 lower than SSD model, which meets the requirements of lightweight network. The actual working environment of Lingwu long jujube picking robot is complex, which limits the picking speed in a certain sense, and the equipment memory resources may be limited. Therefore, for the visual recognition system of picking root, it is necessary to meet the requirements of lighter network structure and higher detection accuracy at a certain detection speed, The improved SSD model proposed in this study just meets the above requirements. In a word, the improved SSD model can well complete the object detection task of Lingwu long jujube image without loading the pre-train model. Besides, it can also provide new methods and ideas for other object detection tasks with poor effect or unable to load the pre-train model, such as medical images detection tasks, multispectral images detection tasks, and so on.
Abstract: In the production of fish feed, it is necessary to refer to the thermal properties of feed and artificial experience when adjusting the process parameters of the hygrothermal treatment process, including cooling and drying. Specific heat, thermal conductivity, and thermal diffusivity are important thermal properties of fish feed, which have important applications in the adjustment of drying and cooling process parameters and the simulation of hygrothermal transfer of feed. In this study, grass carp (adult fish) extruded feed was taken as the research object. And the inversion algorithm based on the adjoint equation method was established. To obtain the temperature distribution of feed, the self-made heat conduction test device and infrared thermal imager were used. When testing, the feed is quickly spread on the cast aluminum soaking plate, and the feed is closely arranged in a single layer, with a thickness of about 4 mm and a total of about 10 g. The infrared thermal images of the feed layer test surface and the upper surface of the cast aluminum soaking plate were taken by the infrared thermal imager (accuracy±0.1 ℃). The infrared thermal images were processed by SmartView software to obtain the temperature-time data of the feed sample test surface (x=h) and heating surface (x=0). From the T-t data of x=0 and x=h. When calculating with MATLAB software, first solve the adjoint equation to obtain the adjoint variables, then obtain the gradient value, and finally obtain c and k. Using data of temperature distribution, the specific heat, thermal conductivity, and thermal diffusivity of feed can be obtained with the moisture content of 11%~17% and in the temperature range of 20~80 ℃. The results show that the specific heat of grass carp extruded feed is 1.710~1.840 kJ/(kg·℃) in the range of 11%~17% moisture content and 20~80 ℃. Specific heat of feed increases significantly with the increase of temperature (P<0.05). When the moisture content increase from 11% to 17%, the specific heat of feed increase significantly (P<0.05), and shows a linear law. The thermal conductivity of grass carp extruded feed is 0.086~0.148 w/(m·K). When the temperature increase from 20 ℃ to 80 ℃, the thermal conductivity of grass carp extruded feed increase significantly (P<0.05). The effect of water content is also significant (P<0.05). The thermal diffusivity of feed range from 5.701 m2/s to 10.003 m2/s, and is significantly affected by temperature and moisture content (P<0.05). At the same time, the specific heat and thermal conductivity of feed were measured by differential scanning calorimetry (DSC) and thermal characteristic analyzer respectively, and the thermal diffusivity was calculated. They were taken as the measured value. Before the test, the feed particles need to be crushed and passed through the 40 mesh screen. The inversion results are taken as the calculated values. The linear fitting results show that R2 is greater than 0.980, which indicates that the error between the calculated value of specific heat and thermal conductivity and the measured value is small, which proves that the determination method of thermal characteristic parameters of fish extruded feed based on the inversion algorithm is feasible. The above research can provide a new idea for the determination of the thermal properties of fish feed.
Abstract: Moldy core in apple is a common internal disease caused by fungal infection, which can result in quality loss and food safety concerns for the apple fruit and corresponding by-products such as concentrated juice and cider. At present, the slightly infected apples are difficult to be picked out because there are no visible symptoms in the fruit appearance. The traditional inspection method requires cutting apples into halves and visually evaluating the presence or absence of internal defect. Other than being tedious, subjective and time consuming, this manual inspection method destroys the fruit during inspection. Consequently, there is an urgent demand to develop a nondestructive early detection for the apples with moldy core. In this study, a nondestructive vibro-acoustic setup was employed for the detection of the apples with slight moldy-core using two identical piezoelectric transducers. The obtained vibro-acoustic signals were transformed to the images by symmetrized dot pattern (SDP) technique. Then, the SDP images were used to extract the depth feature information through the transfer learning of three convolutional neural networks (CNNs) including AlexNet, VGG16, and ResNet50. Finally, the extracted features were fed to train the support vector machine (SVM) classifier to identify the slightly moldy apple core (moldy-core degree less than 7%). When the time lag coefficient l was 25 and the angular gain factor was 50o, the shape feature difference among the SDP images of the sound and moldy-core apples were largest. Under this condition we applied the obtained SDP images to construct the various SVM classification models based on the different CNN structures and kernel functions. By comparison, the ResNet50-SVM-gaus model had the higher classification performance in the training set with less training time and the number of parameters. To further improve the accuracy of the classification algorithm, it was necessary to optimize the trained ResNet50-SVM-gaus model. Through the super parameter optimization of the network structure, the classification accuracy of the trained ResNet50-SVM-gaus model was improved from 91.38% to 99.63%. By using a imbalanced dataset of the sound apples to diseased apples of 10:1, the total classification accuracy of the ResNet50-SVM-gaus model in test set can reach 96.97%. This indicates that the ResNet50-SVM-gaus model can achieve the accurate classification for the early detection of apples with a slight moldy core. Meanwhile, the stable precision (SP), stable recall (SR), stable F1-score (SF), Kappa coefficient, and Matthews correlation coefficient (MCC) of the ResNet50-SVM-gaus model were 80.19%, 90.36%, 86.21%, 82.54%, and 82.68%, respectively. Therefore, the ResNet50-SVM-gaus model can enhance the classification performance of the minority classes of the moldy-core apples in the early stage. Also, our research finding can provide the theoretical reference for the early detection of internal disease of other fruit.
Abstract: In order to study the change of moisture content in the process of tea hot air drying, this experiment took green tea as an example, through the dynamic hot air drying of rolled tea, designed the experiment to monitor the dynamic change of moisture content of tea with drying time under different feeding amount (800 ~ 1200g), drying temperature (90 ~ 120 ℃) and drum speed (20 ~ 30 r / min), and then analyzed the each significant factor to explore the dynamic changes of water content of tea under different drying conditions. The experimental results show that temperature, rotational speed and feeding rate all have significant effects on the drying effect, and the degree of influence on the drying effect of tea leaves is sorted by temperature, feeding rate and rotating speed from large to small. It is obvious that temperature has the greatest influence on the drying process. For the feeding amount, it is appropriate to cover the drum wall with tea to form a perfect casting curtain, because too much feeding amount will easily cause uneven heating of tea, and then appear dry outside and wet inside, focal point explosion and other phenomena. What’s more, in the whole drying process, the decreasing rate of water content of tea leaves showed a trend of first fast and then slow. The lower the water content, the slower the water loss, and finally the water change tended to be gentle. At the end of drying, the water content of tea leaves is basically stable at 4%~5%, which is also the water content level of tea leaves convenient for transportation and preservation. According to the conclusion of the above significance analysis and the structure parameters of the dryer, this experiment took the drying temperature, drum speed, drying initial water and prediction time as the input, and the water content prediction result of the tea drying process as the output for prediction calculation. In this experiment, BP, Elman and PARTICLE swarm optimization Elman neural network (PSO Elman) neural network algorithms were used to establish the dynamic prediction model of tea moisture content during drying process, and the traditional multiple linear regression fitting model was established to compare and analyze with the above three neural network models. The results of verification and error analysis of the above four water prediction models show that their determination coefficients R2 are 0.9609, 0.9980, 0.9985 and 0.9994, respectively. Compared with the traditional linear regression method, the neural network algorithm can express the linear or nonlinear relationship in the complex system more accurately and show better prediction effect for the tea drying process. Meanwhile, for the three neural network models, PSO-Elman model is more accurate than BP and Elman model, and can better predict the change of water content during the drying process of tea. The research results can provide a theoretical basis for the hot air drying technology and process of tea, and have important significance for guiding tea processing and production, improving processing efficiency and tea quality.
Abstract: In order to solve the problems of slow carving speed and inconsistent petal size of Hami melon, a uniform petal carving algorithm of Hami melon based on point cloud splicing is proposed.The robot carving Hami melon needs to plan the cutting path of the execution terminal (carving knife) in real time according to the three-dimensional coordinates of different processing objects.The image features were extracted and reconstructed sparsely. The feature parameters of melon were obtained by point cloud coordinates; Secondly, based on the sparse points, CMVS / PMVS algorithm is used for dense reconstruction;Finally, the octree algorithm and Poisson surface reconstruction algorithm are used to obtain the accurate 3D spatial coordinates of melon.Different shapes of Hami melon lead to different reconstruction results. In order to achieve the best carving effect, each piece of flesh should have the same volume after carving.Firstly, the cutting height and depth of the melon are determined, and the point cloud of the melon under the height and depth is extracted;Then, according to the point cloud of the outermost circle of Cucumis melo, an arc function is fitted to determine the center of the circle, and 360° is divided by the number of carving petals to determine the pre carving start point, pre carving end point and pre carving path;Then, taking the equal volume of each petal as the objective function, taking the equal cutting depth and cutting angle of each petal as the limiting conditions, the initial triangle is formed by looking for the two closest points from any point in the numerous point clouds as the benchmark, and then expanding the triangle outward with the three sides of the triangle as the baseline, Until all the point clouds are included in the three-dimensional triangle network model, the area of the projected triangle is calculated by Helen formula, and the average value of the Z coordinates of the three projected points is taken as the height, and then the volume of the triangular pyramid is calculated;On the basis of depth first algorithm and particle swarm optimization algorithm, the optimal solution is found in the coordinates of Hami melon point cloud through continuous recursive iteration;Finally, the better cloud coordinates are stored as a new data set, and the point cloud coordinates in the new data set are marked on the outside of the Hami melon, then the manipulator can be controlled to carve the Hami melon evenly.The cutter first adjusts to the appropriate posture angle as posture point 2, then moves along the cutter ridge to a certain depth to posture point 1 and retreats to posture point 3, and then the cutter moves along the outer surface of Hami melon to the next adjacent posture point 2. Repeat the above process to complete the overall carving of Hami melon.In order to verify the accuracy of the algorithm, regular model and irregular model are used to test. The accuracy of the algorithm is verified by comparing the calculated volume of cube, pyramid and irregular body with the real volume.Forty eight Hami melons (16 groups, 3 in each group) were used, the number of carved petals N was 15-30, and the carving depth H was 1.5,2.0 and 2.5 cm.The precision of the group with the number of cut petals N equal to 28 is the lowest.The maximum and minimum petal volumes were measured as 3.40cm3 and 3.25cm3, respectively, and the maximum volume difference was 0.15cm3.The error is less than 5.00%.The results show that the proposed melon petal carving algorithm based on point cloud splicing has high precision, and the research results can provide technical support for robot carving Hami melon.
Abstract: Freshly fruits and vegetables have high water content, which are easily affected by a variety microorganisms and lead to decay, resulting in a shortened shelf life. Penicillium disease caused by Penicillium (P. steckii) is the most harmful and frequent disease in postharvest storage of fruits and vegetables, such as mango and citrus, which are easily infected by moldy pathogens. Nano-TiO2 has been widely used in the preservation of fruits and vegetables because of its high chemical stability and antibacterial properties. On the one hand, under ultraviolet (UV) irradiation, the ethylene (C2H4) gas in the fruits and vegetables packaging has been decomposed into carbon dioxide (CO2) and water (H2O), which makes the concentration of CO2 increase and the concentration of C2H4 decrease. The respiration rate of fruits and vegetables has been effectively delayed by this gas change, therefore, the ripening speed of fruits and vegetables has been also delayed, and the water loss has been controlled. On the other hand, microorganisms such as bacteria and fungi are composed of organic compounds. Reactive oxygen species (ROS) has been produced by nano-TiO2 under light conditions, and its strong oxidation denatures the protein, thus inhibiting the growth of microorganisms or even killing them. In recent years, with the increasing demand for renewable materials and non-toxic chemicals, the biosynthesis of nanomaterials have attracted more attention. The biosynthesis of TiO2 nanoparticles is a bottom-up approach. The main reaction is reduction/oxidation, and no toxic chemicals are used in the synthesis process, resulting in non-toxic materials that can be used in pharmacy, biomedicine and food. In this paper, nano-sized TiO2 particles were prepared by biosynthesis using mango leaf extract as reducing agent and metatitanic acid (TiO(OH)2) as titanium source. The effects of different extraction times on the reduction ability of mango leaf extracts were investigated. Based on the single factor experiments, the response surface methodology (RSM) was used to optimize the biosynthesis process of nano-TiO2. The nano-TiO2 particles were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM), and their antimicrobial properties against P. steckii were studied. During the extraction process of mango leaves, the yield of nano-TiO2 increased with the extension of the extraction time. However, the yield of nano-TiO2 was 86.74% when the extraction time was 30 min, which was not significantly different from 87.62% and 87.93% when the extraction time was 40 and 50 min (P＞0.05). The optimal synthesis process was: TiO(OH)2 addition 0.65 g, reaction time 10.2 h, calcination time 2 h, calcination temperature 786 °C. The photoinduced degradation rate of nano-TiO2 was 96.24%, and the standard deviation from the theoretical value was 0.6%. XRD results showed that the biosynthetic nano-TiO2 was anatase type. SEM analysis results showed that the TiO2 nanoparticles obtained by biosynthesis were quasi-spherical, with a particle size distribution in the range of 20-40 nm and less aggregates, but the modified nano-TiO2 had a smaller particle size and fewer aggregates , the dispersion was better. Under the induction of ultraviolet (UV) light, the biosynthesized TiO2 nanoparticles exhibited a certain inhibitory effect on P. steckii, but the modified nano-TiO2 had better antimicrobial effect. The modified nano-TiO2 used in composite coating had obvious inhibitory effect on P. steckii. These results indicated that the biosynthesized nano-TiO2 can be used in the preservation of fruits and vegetables to maintain the quality and prolong the storage life. This preparation process provides a theoretical reference for the synthesis of nano-TiO2 with better photoinduced antibacterial properties.
Abstract: Due to the climate warming and the aggravation of human activities, the agricultural drought in China is becoming more and more severe. In the last 20 years, the average annual agricultural disaster area accounts for more than 50% of China's natural disasters, which seriously threatens China's food security and social and economic sustainable development. Therefore, it is of great important to study the agricultural drought evolution characteristics and driving mechanisms for scientific drought prevention. The Yellow River Basin (YRB), as the Mother River of China, provides water supply for about 140 million people in the region, and for agricultural irrigation for about 15% of the total irrigated land in the country. However, the YRB has historically been frequently experiencing serious droughts. For example, the disaster area caused by agricultural drought after 2000 is nearly six times than that before 2000, which has posed a serious threat to the national economic and social stability. Therefore, the YRB was selected as a study area and divided into six sub-basins based on climatic and topographic characteristics. The main objective of this study is to comprehensively analyze and study the temporal and spatial evolution characteristics and driving mechanisms of agricultural drought in the Yellow River Basin (YRB). The standard soil moisture index (SSMI) and threshold method are used to identify the duration, intensity and drought events of agricultural drought under different drought levels, and the agricultural drought characteristics and drought event frequencies in different zones of the YRB on the annual and seasonal scales are analyzed. Then the impacts of climate and land use land cover (LULC) change on agricultural drought in the YRB are quantified by driving agricultural drought simulation schemes in the SWAT model. Results show that 1) the longer the cumulative time scale, the less the number of agricultural drought with longer duration occurred. The agricultural drought duration characterized by SSMI-1, SSMI -6 and SSMI-18 were about 1-8 months, 1-12 months and 1-22 months, respectively. The beginning and end time of agricultural drought mainly concentrated in spring and summer. 2) Generally speaking, the agricultural drought in the YRB was very serious in the 1990s, while that in most zones of the YRB was greatly alleviated in the 2000s. Spatially, zone C was most vulnerable to severe and extreme agricultural drought in the 1990s, while zone A in the 2000s was most vulnerable to severe and extreme agricultural drought. 3)Climate change was the main factor that caused the agricultural drought in the YRB with contribution rate about 50% - 90%, while the impact of LULC change was relatively weak with contribution rate about 10% - 50%. In terms of specific agricultural drought characteristic values, climate change had the greatest driving impact on the frequency of agricultural drought in the YRB, which was about 60% - 90%. While the land use change had the greatest driving impact on the intensity of agricultural drought in the YRB, which was about 10% - 50%. The findings are helpful to provide more accurate information for actual agricultural drought management and disaster prevention.
Abstract: Jujube is one of the China's unique fruits, rich in vitamin C, amino acids and minerals, it is a medicinal and food product. Jujube crisp is a kind of snack which is made from sliced and dried jujube. It gradually wins the favor of consumers for their crispy taste and rich VC content. Several common single drying methods for jujube crisps, such as hot air drying, vacuum freeze drying and other drying techniques, have problems such as long drying time, serious loss of nutrients, and poor appearance and taste. In order to improve the drying quality and efficiency of jujube crisps and meet the demand of consumers, a new combined drying method for jujube crisps must be developed. In order to find a reasonable combination of the drying process for jujube crisps,four kind of drying method,freeze-drying (cold trap temperature -40℃, heating plate temperature 65℃, drying chamber pressure 12Pa), infrared drying (infrared temperature 65℃, power 6.75W?g-1), hot air drying (temperature 65℃, wind Speed 2.2m/s), microwave vacuum drying (control temperature 65℃, power 6.75W?g-1), were compared. The influence on drying time and quality (color, hardness/brittleness, microstructure) were studied. The drying method combining freezing and infrared drying was selected by comparison and selected for the drying of jujube slices. The conversion moisture, infrared temperature, and slice thickness were selected as influencing factors, drying time and VC retention rate were used as evaluation indicators, and the response surface was adopted. The experiment optimizes the freezing-infrared combined drying process parameters of jujube slices and compares them with single infrared drying (infrared temperature 64℃, radiation power 6.75w?g-1, wind speed 1.5m?s-1) and vacuum freeze drying (cold trap temperature -40℃, drying chamber pressure 12Pa, heating plate temperature 64℃). Results showed that: 1) The drying time of freezing and hot air drying is longer than other two methods, 8.5 h and 5.75 h respectively, the shortest is 0.83 h for microwave vacuum drying, and the second shortest is 2.5 h for infrared drying. 2) Freeze-dried products have better quality but with average crispness, while infrared-dried products are better than hot air and microwave vacuum-dried products in terms of color, texture (hardness/crispness) and microstructure, and have the best crispness. 3) Conversion moisture content, infrared temperature and slice thickness have significant effects on the combined freeze-infrared drying process of jujube crisps, with the main order of effects on drying time are conversion moisture content, infrared temperature and slice thickness, and the main order of effects on VC retention are infrared temperature, conversion moisture content and slice thickness. 4) The response surface method was used to determine the optimal process parameters: conversion moisture content of 34 %, infrared temperature of 64 °C, and slice thickness of 5 mm, at which point the drying time was 3.6 h and the VC retention rate was 68.9 %. 5) The quality of freeze-infrared combination drying products was better than that of infrared drying, and the drying time was 57.6 % shorter than that of freeze-drying, and the VC retention rate was 34.6 % higher than that of infrared drying. This paper shows that the combined freeze-infrared drying shortens the drying time and ensures the drying quality at the same time, which can provide a new combined drying technology and theoretical basis for the drying and processing of jujube crisps.
Abstract: Paddy rice is the world"s second-largest food crop, rich in water at harvest, drying it to safe water to long-term storage. Traditional hot air drying has many disadvantages, such as low drying efficiency, serious rice burst after drying, low eating quality, and nutritional quality. Therefore, in recent years, the tempering process is often added to the actual drying production of paddy rice. Tempering drying is a periodic drying technology. In the process of tempering, the drying chamber stopped heating continuously, and the moisture of paddy rice was redistributed, which promoted the internal moisture diffusion to the grain surface, thus increasing the moisture diffusion rate and surface evaporation rate. The drying process parameters of tempering mainly include the process parameters of the drying section and tempering section and the matching between them. However, most scholars have explored the changes of macroscopic indexes of rice according to the process parameters of the drying section and tempering section, and there is still a lack of in-depth analysis on the matching relationship between the drying section and tempering section and different parameters on the nutritional quality of rice. Aiming at the problem of insufficient research on the correlation between drying technology and quality indicators, this paper is based on previous research results, this paper explored the effects of different drying parameters on the drying quality of paddy rice. First of all, through the single factor experiment, combined with the analysis of variance and correlation analysis of SPSS software, the relationship and interaction between tempering drying process parameters and drying quality of paddy rice were determined. Secondly, the main factors affecting the drying quality of paddy rice and their corresponding levels were determined by the comprehensive evaluation method of the membership function model. Finally, taking the tempering temperature, initial moisture content, and tempering time as test factors, and the additional crack percentage, protein content, fatty acid value, and gel consistency as response indexes, the Central-Composite central composite test was used to establish regression model, response surface and contour map to analyze the relationship between the test factors and quality indexes and explain the causes of the results. The results showed that the optimal combination of parameters was tempering temperature 49 °C, tempering time 1.61 h, tempering initial moisture content 21 %. Under this parameter combination, the additional crack percentage of paddy rice after drying was 6.95 %, the protein content was 5.32 %, the fatty acid value was 11.55 %, and the gel consistency was 79.88 mm. The verification test was carried out with the optimized parameters, and the additional crack percentage was 6.86 %, the protein content was 5.35 %, the fatty acid value was 11.14 %, and the gel consistency was 82.49 mm. The average error between the test value and the software optimization parameter value was 2.18 %, which was consistent basically. The results showed that the optimized tempering drying process significantly improved the drying quality of paddy rice, which could provide the theoretical basis for production practice and in-depth exploration of the mechanism of paddy rice quality change.
Abstract: Accurate mapping of soybean planting area is of great significance to yield estimation, crop-damage warning and agricultural policy adjustments. But there are few reports on the application of remote-sensing technology in soybean identification in the areas with the high frequency of cloud cover, diverse summer crop types and complex field planting structure. Anhui Province is one of the main producing areas of soybean in China, this study selected Longshan and Qingtuan towns situated in typical soybean producing areas in North Anhui plain as the study area, and the hierarchical extraction strategy was proposed to obtain the spatial distribution of soybean planting area in the 2019 growing season based on the Sentinel-2 image which was acquired at the early pod-setting stage of soybean (August 18, 2019). Firstly, A set of decision tree filtering rules were established to eliminate non-agricultural cover types, i.e., water, sparse trees, bare soil and artificial objects (buildings, roads) and thus obtain the overall distribution of field vegetation. Then, 19 candidate features containing the reflectance of 10 spectral bands with a resolution of less than or equal to 20 m and 9 vegetation indices were generated based on the Sentinel-2 image to participated in the soybean extraction. With the support of typical ground-feature samples, ReliefF algorithm was used to evaluate the importance of each candidate feature, and three models i.e., ReliefF-RF, ReliefF-BPNN and ReliefF-SVM were established respectively by combining ReliefF with three machine learning algorithms including random forest (RF), backpropagation neural network (BPNN) and support vector machine (SVM) to screen out the most effective features for soybean identification and examine the performance of the three models in soybean mapping. The extraction effect was evaluated by unmanned aerial vehicle (UAV) images covering six ground samples (each was 1 km×1 km in size). Results showed that the ReliefF-RF model with Kappa ranging from 0.72-0.81 performed the best and the overall accuracy was between 85.92% and 91.91%. For each ground sample，the kappa coefficient was higher than the other two models (0.69-0.79 and 0.70-0.78 for Relief-BPNN and Relief-SVM, respectively); near-infrared B8 (842 nm), red-edge Normalized Difference Vegetation Index (NDVIre2) that derived from B8 and B6, short-wave infrared B12 (2190 nm), Red-Edge Position (REP), red-edge B6 (740 nm), green B3 (560 nm) and Enhanced Vegetation Index (EVI) were singled out by the ReliefF-RF, which indicated that these seven optimum features were more advantageous than other commonly used spectral bands and remote-sensing vegetation indices in soybean identification, and the importance of red edge-related variables was particularly highlighted. In addition, the mapping result derived from the optimum features significantly outperformed which generated from the 10 spectral bands. Although the performance of optimum feature-subset was slightly inferior to total 19 features, ReliefF-RF that contained only seven optimum features showed obvious advantages in terms of time and computation cost, as well as data volume. The hierarchical extraction strategy only focused on field vegetation, the optimum features generated by the strategy were more targeted and were not affected by the proportion of other non-agricultural land cover types, it should have better applicability and generalization in theory. The findings of this study would provide a valuable reference for the soybean extraction in areas under complex planting conditions.
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: The parcel-based crop distribution can clearly reflect the detailed information including farmland location, boundary and crop type. It has high significance to demands such as precision agricultural management, payment of planting subsidies and agricultural resource survey. Although the collaboration of multi-source high-spatial and high-temporal resolution satellite images provides an effective way to realize the parcel-based crop mapping, there exists deficiencies in farmland parcel extraction and temporal feature construction. Based on previous studies upon spatiotemporal collaboration, the present study implements parcel-based crop mapping by following steps: 1) extract parcels based on the 0.6m high-spatial-resolution Google Earth images using D-LinkNet deep learning model; 2) construct time series data set for each parcel by using multi-source observations from Landsat8 and Sentinel-2 satellite, and utilize clear data tiles from images with high cloud cover; 3) reconstruct parcel-based NDVI time series through weighted Double-Logistic fitting method, and extract phenological metrics such as time of starting of growth, time of ending of growth, duration of growth cycle, and calculate spectral indexes from Landsat8 and Sentinel-2 multispectral data; 4) select features using mean decrease accuracy (MDA) indicator, train random forest classification model using crop type data collect from ground experiment, and make parcel-based crop mapping of the study area. The study area is Fusui County in Guangxi Zhuang Autonomous Region. The study area is cloudy and rainy, with rainfall days about 130~220 days, Its topography is diverse and complex, with high degree of land fragmentation. Its planting structure is relatively complex. The dominated crops include sugarcane, paddy rice, banana and orange. The results show that the farmland parcels are well extracted by using D-LinkNet deep learning model, with the edge accuracy of 84.54% and the producer accuracy of 83.06%. On the contrary, the normal multi-scale segmentation method segments the whole image and resultant parcels interferes the extraction of crop distribution. The reconstructed NDVI time series of sugarcane, paddy rice, and banana can clearly reflect phenology. NDVI of sugarcane and paddy rice increases and decreases significantly. The growth season of sugarcanes starts from March to the following March. The growth season of paddy rice lasts for about 3~4 months, and its NDVI time series changes the most intensely. The reconstructed NDVI time series of evergreen eucalyptus and orange shows relatively steady throughout the year. The eucalyptus with high vegetation cover shows high NDVI values during the observation period. The MDA indicator is used to estimate the feature importance. It shows that images acquired in summer and autumn are better for crop classification in the study area, Sentinel-2 red-edge features and phenological features are important to crop classification. Combining the phenological and spectral features can reach the best classification performance. In Fusui County, the overall classification accuracy reaches 88%, and the accuracy of sugarcane reaches over 95%. The crop mapping results shows that sugarcane is spatially distributed around the whole study area, including plaining areas and mountainous areas. The planting area of sugarcane accounts for nearly 70% of the farmland areas, orange accounts for 18.6%, and paddy rice accounts for 7.12%. The paddy rice is near the settlement places. The study successfully extracts phenological features by using Landsat8 and Sentinel-2 multi-source observations, and verifies the importance of phenological features in the parcel-based crop distribution extraction. This research theoretically constructs a model to make parcel-based crop classification by collaborating high spatial and high temporal satellite data, and can provide a set of practical technical scheme for acquiring parcel-based crop distribution.
Abstract: Fluorescence has unique luminescence characteristics. The combination of excitation light and emission light can greatly reduce the interference of background signals and greatly improve the sensitivity of the detection system. Many scholars at home and abroad obtain the optimal excitation wavelength and optimal emission wavelength of the analyte based on the principle of photoluminescence of fluorescent substances, and have developed miniaturized, low-cost dedicated instruments. However, the existing portable instruments still focus on detecting pesticide residues in the solution system, and there are fewer instruments for directly detecting pesticide residues on the surface of vegetable leaves, which cannot meet the requirements of on-site rapid detection in modern agricultural production and life. Therefore, in view of the problems that the existing pesticide residue detection instrument can only detect the pesticide residue in the aqueous system and the detection object was relatively single, the pesticide residue of acetamiprid on lettuce leaves were studied in this paper. The feasibility of modeling pesticide residues and fluorescence intensity on the leaf surface was explored, and a portable detection instrument for pesticide residues on the leaf surface was designed by optimizing the light path structure to suppress the interference of stray light on the leaf surface. Firstly, through experiments, the best excitation wavelength and best emission wavelength of acetamiprid pesticide in standard solution and three plant leaves were at 350 and 500 nm, respectively. An LED with a central wavelength of 350nm and a maximum drive current of 100mA was selected as the excitation light source, and a photodiode with a peak response range from 480nm to 580nm was used as the photoelectric detection device. A filter with a center wavelength of 500nm was used to prevent the passage of other interference light, and only the emission wavelength of the acetamiprid pesticide was allowed to pass to reduce the interference of the secondary spectrum. Then, the optimal parameters of the optical path are determined. By fluorescence experiments, it was found that when the light Angle was 45°, the fluorescence intensity excited by acetamiprid pesticide on the leaf surface was the highest. By calculating the optical path size, it was found that when the direct distance from the LED laser source to the blade was 4.89cm and the vertical distance was 3.46cm, the illumination of the blade was the largest. In addition, in view of the diffuse reflection problem of the light source illuminating the surface of the blade, a diffuse reflection device was designed to achieve the maximum absorption of light energy. Moreover, according to the requirement of weak fluorescence signal detection, the corresponding control circuit, driving circuit and detection circuit were designed. A signal detection system was designed with STM32 chip as the main control chip to collect the voltage signal of the detection circuit, and the pesticide residue value was calculated according to the working curve of pesticide residue value. The PWM wave was output to modulate the LED light source and the difference between the frequency of detecting light and the frequency of ambient light can suppress the interference of ambient light to the light source. Then, SPI and I2C communication protocols were used to communicate with AD acquisition chip and OLED display screen to realize real-time detection of pesticide residues and real-time display of pesticide residues. Finally, the calibration equation was established and a portable detector was designed to detect pesticide residues. The measuring instrument was calibrated and tested, and the measuring value relation model of the portable measuring instrument was established. The determination coefficient of the model reached 0.875. The portable fluorescence spectrometer designed in this study can quickly, accurately and non-destructively detect pesticide residues on the surface of leaves, which provided a reference for the development of a more universal portable detection instrument.
Abstract: In order to analyze the energy consumption of the piped spiral flow hydraulic transportation of tube-contained raw material, the setting angle of the guide bar was the main control variable, and the method of combining theoretical analysis and model tests was adopted to study the spiral flow velocity characteristics on cross-sections between the two piped carriages under conditions of different setting angles of the guide bar in this paper. The results show that the axial velocity distribution trend on cross-sections between the two piped carriages is basically the same under the conditions of different the setting angles of the guide bar, and both show the distribution characteristics of spreading inward from the pipe wall and then outward from the pipe axis. The axial flow velocity value on each section between the two piped carriages is overall large, with the maximum value reaching 3m/s. The radial velocity on cross-sections between the two piped carriages under conditions of different setting angles of the guide bar basically fluctuated between ?1.0-1.0 m/s, and the area where the radial velocity value was 0 was relatively large. With the increase of the setting angle of the guide bar, the radial flow velocity on cross-sections between the two piped carriages gradually showed a 120° rotational symmetry distribution. In the directions of 0°, 120°, and 240° polar axes, the radial velocity value was smaller. Compared with the axial and radial velocity, the circumferential velocity was most affected by the setting angle of the guide bar, and the intensity of the circumferential velocity increased with the increase of the setting angle of the guide bar, and its maximum value could reach 1.5m/s. At the same time, with the increasing of the setting angle of the guide bar, the circumferential velocity of the counter clockwise rotation along the circumferential tangent increased. Similar to the radial velocity, with the increase of the setting angle of the guide bar, the circumferential flow velocity on cross-sections between the two piped carriages gradually showed a 120° rotational symmetry distribution, but the circumferential flow velocity was larger in the directions of 0°, 120°, and 240° polar axes. The study can not only improve the theories of pipeline spiral flow, but it can also provide theoretical reference for the popularization and application of the piped hydraulic transportation technique of tube-contained raw material.
Abstract: In respect of pig instance detection, the application of traditional computer vision techniques is constrained by sundries barrier, overlapping, and different perspectives in the pig breeding environment. In recent years, the attention-based methods have achieved remarkable performance. It can increase the weight of regional information that is beneficial to instance detection, and suppress secondary information to improve model effects. We select a total of 45 live pigs aged 20 to 105 days in 8 pens as the research object. We use a head-up angle of view to collect a total of 3834 labeled images and divide it into 2490 as the training set, 480 as the validation set, and 864 as the test set. we introduce two types of attention units into the feature pyramid network (FPN) framework, which encode the semantic interdependencies in the channel (named channel attention unit(CAU)) and spatial (named position attention block (PAU)) dimensions, respectively. By integrating the associated features, the CAU selectively emphasizes the interdependencies among the channels. Meanwhile, the PAU selectively aggregates the features at each position through a weighted sum of the features at all positions. A dual attention unit (DAU) is proposed to integrate CAU features with PAU information flexibly. We select the two backbone networks as ResNet50, ResNet101 and the four major task networks as Mask R-CNN, Cascade Mask R-CNN, MS R-CNN and HTC cross-combination model to detect the performance of group breeding pigs. In comparison with such state-of-art attention modules as convolutional block attention module (CBAM), bottleneck attention module (BAM), and spatial-channel squeeze & excitation (SCSE), embedding DAU can contribute to the most significant performance improvement in different task networks with distinct backbone networks. Especially with HTC-R101-DAU, compared with HTC-R101-CBAM, the performance is increased by 1.7, 1.7, 2.1, and 1.8 percentage points at AP0.5, AP0.75, AP0.5:0.95, AP0.5:0.95-large respectively; Different backbone networks have a certain impact on the pig detection effect of the same task network. In the task network without any attention unit, the detection effect of R50 is better than R101, but after adding any attention unit, the detection AP values of the two backbone networks are relatively close. In order to separately explore the influence of channels and positions attention units on task network detection performance, the CAU and PAU are added for comparative analysis. Experiments show that DAU is comparable to CAU and PAU, it can obtain better AP index values, shows that the simultaneous fusion of two dimensions of attention information can complement each other to improve the accuracy of position detection. In addition, compared with CAU, adding a specific number of PAU units can generally achieve better AP index values; In order to obtain pixel-level dense context information, we explore the number of series PAU units for the impact of the detection results, a position attention module with 1 to 4 PAU units connected in series was constructed. Experiments show that under the same experimental conditions, the predictive results appear a trend of increasing initially and decreasing afterwards after different numbers of PAU are merged; Comprehensive analysis, the HTC-R101-DAU model can more accurately and effectively detect live pigs in different scenes, and it can lay the foundation for the follow-up in-depth study of pigs.
Abstract: The water level of coastal wetlands is of great significance to the development of coastal economy and the growth of mangroves. At present, the mainstream method of obtaining water level still relies on hydrological stations to monitor regularly and at fixed points. This method has high monitoring costs and does not meet the requirements for timeliness. The rapid development of satellite altimetry technology allows it to be used as a supplement to ground monitoring. This study takes the coastal wetland of the Beibu Gulf in Guangxi as the research object, uses the daily Jason-3 and Sentinel-3A altimetry data from 2016 to 2020 as the data source, and calculates the initial coastal wetland water level value through the basic radar altimetry toolbox The principle of triple-middle error is used to eliminate outliers to obtain the initial coastal wetland water level. Because the impact of land will pollute the nearshore waveforms, thereby reducing the measurement accuracy, in order to further improve the reliability of the measurement, first import the obtained initial coastal wetland water level points into the Omap, and remove the water level data falling on the land and vegetation coverage areas. Then, four re-tracking algorithms of gravity center shift method, threshold value method, improved gravity center shift method and improved threshold value method are used to re-calibrate the height measurement water level to obtain the corrected water level of the coastal wetland. The coefficient of determination, RMSE and MAE are selected to quantitatively evaluate the accuracy difference of the two altimetry satellites using different algorithms to extract the water level of the coastal wetland. High-precision altimetry satellites are selected to explore the intra-year and inter-annual dynamic changes of the coastal wetland water level, using the intra-year water level variation, monthly average water level, seasonal average water level, and annual average water level for analysis. The research results show that the four re-tracking algorithms can extract the water level of coastal wetlands, and the improved threshold method has the best re-setting effect. The maximum coefficient of determination obtained by Jason-3 is 0.78, the minimum RMSE is 0.35m, and the minimum MAE is 0.28m; the maximum coefficient of determination obtained by Sentinel-3A is 0.87, the minimum RMSE is 0.24m, and the minimum MAE is 0.18m. The results show that the monitoring accuracy of Sentinel-3A is high. The water level change of the Beibu Gulf coastal wetland in Guangxi from 2016 to 2020 shows obvious seasonality. The average water level change during the year is 3.37m, and the water level changes more drastically, showing a downward trend as a whole, with an average annual change rate of 0.005 m/a. The spaceborne radar altimeter provides a powerful method for monitoring the water level of coastal wetlands on a large scale, which is of great significance to the study of coastal wetland changes and ecological environment protection.
Abstract: Ecological security pattern (ESP) is considered to be one of the important spatial approaches to alleviate the contradiction between ecological protection and economic development, and is also the basic premise to ensure regional ecological security and maintain social sustainable access to ecosystem services. In recent years, coupling multiple ecosystem services has gradually become a new research direction of ESP. Generally speaking, previous studies have assumed that different ecological processes do not interfere with each other and that there is no trade-off relationship between ecosystem services. In the process of ecological node identification, it is often ignored to identify the ecological obstacle points that hinder the movement or communication between organisms and the ecological pinch points that are more likely or very frequent in the process of biological migration. The Yellow River Basin is not only the main birthplace of Chinese civilization, but also an important ecological barrier in China. It is of great practical significance to identify the patches and corridors that have an important impact on regional ecological security, optimize the ecological space, and improve the ecosystem service function for the realization of high-quality development of the basin. Based on the five typical ecosystem services of food supply, carbon sequestration, oxygen release, water production and soil conservation in Gansu section of the Yellow River Basin in 2019, this paper simulated the ecosystem service priority protection areas of the study area in 2019 as the ecological source areas using multi-scenario ordered weighted averaging (OWA) model. The minimum cumulative resistance model is used to construct the basic resistance surface, and the circuit theory model is used to extract the ecological corridor and identify the ecological pinch points, so as to construct the ESP of Gansu section of the Yellow River basin with the ecological source as the core, the ecological protection priority areas with different gradients as the benchmark framework, and the ecological corridor pinch points as the axis, and optimize the ecological space. The results show that: there are 169 ecological source patches in the study area, with an area of 27460.56 km2, accounting for 19.2% of the total area of the study area. The five ecosystem services in the study area show a collaborative relationship from an overall perspective. The three natural boundary regions of Gannan Plateau, Longzhong Plateau and Longdong Loess Plateau are affected by topographic climate, vegetation cover and human activities, and the differences and similarities of ecosystem services in different regions will occur. Through the different combination of rank weight, seven kinds of ecosystem service protection schemes are provided, which make the extracted priority reserve have the core and comprehensiveness of ecological sources, so as to achieve the goal of high efficiency and balanced allocation of ecosystem service protection. Considering the trade-off degree (0.935), the priority conservation areas under scenario 4 were selected as the ecological source of the study areas. The minimum cumulative resistance model is used to identify the ecological corridor, and the circuit model is introduced to identify the spatial scope of the ecological corridor. A total of 441 ecological corridors with a length of 6774.9 km were identified in the study area. By calculating the current density of the ecological corridor, 49 ecological pinch points were identified. It is proposed to construct the optimization system of ecological safety space layout in Gansu section of the Yellow River Basin with "four axes, six regions and multiple centers", and to form a functional and networked regional ecological space optimization structure. The results can provide decision support for sustainable management and ecological management optimization of the upstream ecosystem of the Yellow River Basin.
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 the GPM (global precipitation measurement) era, IMERG (integrated multi satellite retrievals for GPM) with high spatiotemporal resolution (i.e., spatial resolution of 0.1° and maximum temporal resolution of 0.5 h), is one of the most mainstream satellite precipitation products. This study primarily evaluated the application ability of the latest satellite remote sensing and the retrospective IMERG Final Run precipitation product in the monitoring drought. First, the in-situ gird CPAP (China gauge-based monthly precipitation analysis product) data was selected as the reference data. Then, two dimensionless and commonly used meteorological drought indices, i.e., the SPI (standardized precipitation index) and SPEI (standardized precipitation evapotranspiration index) were calculated based on the IMERG and CPAP data at conventional scale, respectively. On the basis of the two points above, we verified the potential performance of IMERG product for the drought monitoring application over mainland China in the period of 2000-2017. The research results showed that: 1) the IMERG product could better capture the spatial pattern of monthly mean precipitation in mainland China (spatial correlation coefficient of 0.96 and relative bias of 0.02), and had higher consistency with respect to CPAP data in parts of mainland China. The field of region with correlation coefficient over 0.9 was occupied 73.7% of the continental area. However, there were relatively high spatial heterogeneity in the Xinjiang and Qinghai Tibet Plateau regions. 2) The two drought indices (SPI index and SPEI index) calculated based on the IMERG product featured high reliability and good consistency with respect to those of CPAP data at multiple time scales (1, 3, 6, and 12 months), and the regional mean correlation coefficient was more than 0.8 in most sub regions. But the SPEI index had better applicability than the SPI index, and they featuring best performance at the 12-month scale. 3) In southwestern China region, the IMERG product could satisfactorily reflect the variational process of drought (drought intensity and drought area) with time (temporal correlation coefficient over 0.96 for the SPEI), and finding out that it precisely captured the spatial characteristics of typical drought disasters on the specific month (March 2010) as well, especially for the SPEI index. The two drought indices were calculated based on the retrospective IMERG product possess high accuracy over mainland China, and they are suitable for drought monitoring in most regions. In addition, if the precipitation factor was considered only, the SPI index calculated based on the IMERG product could be applied to identify and evaluate meteorological drought at large scale. However, under the background of global warming, it is suggested that the SPEI index should be considered preferentially to utilize.
Abstract: Semantic segmentation of an image has become a key interdisciplinary application in the image processing, computer vision, pattern recognition, and artificial intelligence. In deep learning architectures, the convolutional neural network for interferometric semantic segmentation (CNN-ISS) is widely used in digital image processing and machine vision. The CNN-ISS can be utilized to effectively extract further features, such as texture and geometric features, indicating stronger transfer learning and generalization, compared with traditional image classifications of remote sensing. As such, the CNN-ISS is suitable for the interpretation of high-resolution remote sensing image, identification of complicated features, and crop mapping. In classification, large remote sensing images need to be segmented into specific tiled images, thereby to serve as the object of convolutional neural network (CNN) processing. However, an artificial image tiling can generate fragments on the edge of a tile, leading to the low classification accuracy of pixels near the edge of the tile. Here, the phenomenon was defined as the edge effect of tiled images, where the classification accuracy of pixels near the edge of the tile was lower than that of the central area. In this work, two indicators was designed, including the error rate with a distance to tile edges (ERD), and the error rate of the whole image (ERW), to quantify the edge effect of CNN-ISS processed tiled images. Meanwhile, the offset positions (i, k) were set for the starting point of the shift window to ensure that any pixel on the whole image must be in the central area of the tile generated under a certain offset setting. Then, five technical solutions were obtained to test the minimized edge effect of tiled images using the scores in multiple groups of categories. Taking the Tangshan as the segmented typical rural surface, a DeepLab V3 was selected as the core model of CNN-ISS to analyze the edge effect of the classification. The results showed that the pixel classification accuracy was positively correlated with the distance from the pixel to the edge of a tiled image. The highest error rate was 6.931 3% occurred along the edge of the tiled image, and the lowest error rate was 3.515 6% in the center of the tile, indicating the accuracy of the central area was higher than that of the edge. It showed an obvious edge effect of tiled images. In edge effect elimination scheme for the tiled images, the total classification accuracy improved significantly, where the Kappa coefficient and Mean Intersection over Union (mIoU) of the entire image increased 0.399 8%, 0.0122 and 1.965 1%, respectively. Taking the Kappa coefficient, one of the classic accuracy indices for the remote sensing image interpretation, as an example, the order of accuracy including the control group was: solution 2 (0.881 0)> solution 5 (0.878 9) > solution 3 (0.878 8) > solution 4 (0.877 7) > solution 1 (0.875 9) > the control group (0.868 8). Besides, the solutions of edge effects depended mainly on the types of features in the tiled images. The general law was that the tile edge effects of linear features and complex isomers (pit ponds, rural residential areas) were more obviously improved the accuracy, as the solutions were more significantly accurate, compared with that of the base land, or other agricultural land. Compared with the control group, the improvement order of IoU in the solution 2 was: roads (4.134 3%) > pit ponds (2.974 6%) > rivers and ditches (1.607 4%) > rural residential areas (0.647 5%) > other agricultural land (0.461 8%). Without changing the core model of CNN semantic segmentation, the elimination scheme for the edge effect of a tile can be used to effectively improve the accuracy of remote sensing image classification, especially for the linear features and complex isomers.
Abstract: In the situation that high-efficiency water-saving irrigation engineering technology is difficult to be applied popularly in field crops, it is a feasible way to optimize the water-saving irrigation schedule to improve the efficiency of irrigation water by integrating and applying the existing research results in water-saving irrigation. In this paper, the research is carried and the method to optimize water-saving irrigation schedule is developed in Xinzheng county, Henan province. The methodological processes are as follows: first, to estimate the water volumes the winter wheat requiring in its full and every growth periods by calculating indirectly using Penman-Monteith Formula recommended by FAO in 1998 with meteorological data. Second, to estimate the total water resource supplied in the full growth period of winter wheat including atmospheric precipitation, soil water content and available water resource for irrigation which can be calculated by using meteorological data, field moisture capacity and wilting coefficient of different types of soil texture, hydro-geological data which can be collected in turn. Third, to optimize and distribute the total supply water, which is few and can not meet the demand of the winter wheat in its full growth periods, to different growth stages of winter wheat, that is to get the by the method of calculating Jensen-model with full use of the existing water sensitivity index of winter wheat in different growth stages with the aim of maximizing the yield of winter wheat. Finally, to calculate the irrigation water quota in different growth stages of winter wheat on the basis of the calculating of the actual evapotranspiration, atmospheric precipitation and soil water content in different growth stages of winter wheat.The results show that: 1) The total water requirement in the full growth period of winter wheat is about 425 mm in Xinzheng, and the total supply water is less than which in normal and dry years in the full growth period, so it is necessary to implement deficit irrigation schedule. 2）Using Jensen-model, irrigating quota on each application in different growth stages of winter wheat cannot be calculated directly, actual evaporation in different growth stages should be calculated firstly, and which has been studied out that the allocation proportion of evaporations in seedling, over- wintering, booting, heading, and filling stages is 0.1564﹕0.0562﹕0.2334﹕0.3507﹕0.2032 in turn, that is their weight coefficient of sensitivity index in different growth stages. 3) The key irrigation periods of winter wheat in Xinzheng city are heading and filling stages. In high flow years, is filling stages, the irrigating quota in which accounts for 74～97% of the total irrigation amount; and in normal flow years and dry years, is heading stages, the irrigating quota accounts for 55%～73%. Under the three scenarios of non-irrigation, average irrigation and insufficient irrigation suggested in this study, the yield under insufficient irrigation estimated using Jensen-model is 26.8%~40.9% higher than non-irrigation or average irrigation in normal flow year, and 28.8%~55.0% higher in dry year. So, irrigation should be given up and insufficient irrigation should be carried out in field crops though the amount of water resources available for irrigation in Xinzheng City is only 640~1225 m3/hm2, which is 28.8%～55.0% of the quota given in Henan Province Local Standard-Agricultural Water.The conclusion can be given that the existing research and the basic data from counties now can meet the needs of formulating a deficit irrigation schedule, and the method proposed can be used for reference in other counties.
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: Soil erosion modulus from laboratory modeling is often used to predict soil and water loss for a specific area in the field. Therefore, this study aims to investigate the erosion difference between laboratory and field simulation under various intensities of rainfall and areas on a loessal slope in western Shanxi, China. An emphasis was placed on the laboratory modeling and in-situ simulated rainfall events in the field. A systematic analysis was made on runoff modulus, erosion modulus, sediment discharge of unit width and rill development between laboratory and field. The intensities of simulated rainfall were set as 50, 60, 70, 80, 90, 100, 110, 120 mm/h, combined with natural rainfall events in the study region. A coefficient of uniformity above 85% was, considered in the simulated rainfall, similar to the raindrop distribution and size in the natural rainfall. Calibration of rainfall intensities was conducted at the beginning of each experiment. In the field, the runoff/erosion catchment plots were established in the size of 2, 3, 4, 5 m (length) and 2 m (width) in Wangjiagou small watershed in western Shanxi, while in the laboratory, that in the size of 2, 3, 4, 5 m (length) and 0.5 m (width) in the Taiyuan University of Technology. The soil surface was bare, where the soil type was loessal, and the slope gradient was 20°. Initial water content of soil was determined all the same in simulated experiments. Each rainfall event was repeated two times. The period from the rainfall beginning to runoff occurrence was recorded as “runoff occurrence time” during each rainfall event, where the duration of each rainfall simulation was 30 min from the appearance of runoff. All samples of runoff and sediment were collected in the polyethylene bottles with the volume of 1 L at the bottom end of the plot at 2 min intervals, as the final runoff volume and sediment yield. The erosion modulus and runoff modulus were analyzed with the rainfall intensity and area, in the field and laboratory, indicating significant correlation between rainfall intensity (slope length) and sediment yield. Rill morphology and sediment discharge of unit width were further measured to explore difference between field and laboratory. The results showed that laboratory measurements were greater than those of field in-situ simulation. When the slope area of field was 4 times that of the laboratory, the runoff and sediment yield were not 4 times, where the larger the area was, the smaller the ratio of erosion was, indicating that the amount of soil erosion in the field cannot be predicted simply by the laboratory measurements. The rainfall intensity had also greater impact on the runoff erosion than the area. Under the same rainfall condition, the rill was more likely to occur on the laboratory slope surface, and more developed than on the field, which was more inclined to cut rill deep to enhance the runoff erosion force of laboratory slope. Under certain rainfall intensity and slope length conditions, the mass flux tended to be stable after the first peak at the 10~14 min in the field, while the peak appeared at 4 min in the laboratory, where the value was 1.58~10.40 times of that in the field. It showed that the sediment discharge of unit width and its fluctuation in laboratory were higher than that in the field, and the response time was shorter.
Abstract: Using hydraulic structures (especially gates) to measure flow is currently the most widely used method for water measurement in irrigation districts of China. The main advantages of this method are lower investment and being able to control while measuring. However, its accuracy for field applications is very limited while use traditional way, in some cased the maximum error may reach 30%. So, improving the accuracy of the water measurement with gates is an urgent matter for irrigation water management. Lots of effort has been made in recent years on flow rate measurement under sluice gate, and various flow rating models were presented in literature. However, these methods almost focus only on one certain flow condition and mostly does not specially concern the application of field calibration. In addition, the empirical coefficients (as flow coefficient and submergence coefficient) of those formulas have remarkable uncertainty, and most semi-empirical formulas were based on theoretical derivation and laboratory experiments which are quite different from the actual field application. All of those made it hard to get precise measurement of flow in the field. The main goal of this paper is to propose a flow calculation model with simple form and can be applied to multiple gate flow regimes. This paper established a 3D hydrodynamic model of the actual sluice gate to study the hydraulic characteristics of the sluice under different flow conditions and verified that the selected grid size has no influence on the results, and then combined 3D numerical simulation, indoor model experiment verification with field prototype observation data to propose a flow calculation model applied to multiple flow regimes. The research method of this paper is first verified the validity and accuracy of the calibration model based on the measured data proposed. Then analyzed the calibration effect of the model applied to the gate in different flow modes, and check whether it can be used for free and submerged orifice flow. Furthermore, validate the field data of the proposed model method and analyze the source of error. This paper used one portion of the field data to calibration the model, and used another portion to verify the accuracy of the model. Finally, this paper analyzed the accuracy of the model based on an example of a gate in the middle route of South-to-North Water Transfer project. This paper used measured data in September were used for calibration, and then the data in August, October and November were used for verification. Results show that 1. The model can be used to determine the flow rate with relatively high accuracy, and 90.63% of the data has less than 5% error; 2. The model can be sued for both free and submerged orifice flow rate and the proportion within 5% error dropped to 86.67%. Using a gate of the South-to-North Water Diversion Middle Line in August, October, and November, the accuracy of the model can be verified to achieve 77.64% of the data error within 5%, and 95% of the data error within 10%; The proposed model is simple, smooth and continuous. In field application, it is promising for improving the accuracy of gate flow measurement with more rating data.
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: In the global scope, the application of vegetable grafting seedling technology is very extensive, and the seedling enterprises completely rely on professional grafting technical workers, which leads to the aging of employees and the shortage of employment and other problems. Grafting machine can effectively overcome the shortcomings of low efficiency of manual grafting, improve the quality of grafting seedlings and standardized operation. For the existing grafting machines, most of them need artificial feeding seedling, and the production efficiency of machines is greatly limited, which affects the popularization and application of grafting machines. In order to solve the problems of rootstock cotyledon damage and petiole splitting in the process of artificial feeding seedling of grafting machine, a rootstock seedling positioning mechanism was designed based on the principles of positive pressure air pressing seedling and negative pressure adsorption positioning. Firstly, the external geometric parameters of cucurbita moschata seedlings and the breakpoint pressure of cotyledon were measured to provide basis for the design of adsorption block structure and working parameters. Then, the trajectory equation of cotyledon back development curve is extracted by point fitting method, which is used for the profile design of adsorption block working face. By establishing the finite element analysis model of the mechanism, under the given boundary constraint conditions, the dynamic simulation of the airflow field inside the adsorption block is carried out by using CFD software, so as to obtain the distribution of the flow field in the gas chamber and the influence of various factors on the adsorption force of rootstock cotyledon. The optimal structural parameters of the adsorbent block were determined by simulation orthogonal test. The order of the influence of various factors on the average suction is outlet negative pressure > diameter > depth. When the negative pressure at the outlet of adsorption block is 3 kPa, the pore diameter is 1 mm and the depth of suction hole is 4 mm, the pressure of 21 suction holes is less than the rupture point pressure of cucurbita moschata cotyledon, and the adsorption block has good adsorption and localization ability for cotyledon. According to the results of feeding seedling test, the adsorption success rate of cucurbita moschata cotyledon was 96.67%, the success rate of pressing seedling was 99.33%, the comprehensive feeding success rate of seedling was 96.03%, and the seedling injury rate was only 0.67%. The operation performance of the mechanism could meet the requirements of automatic feeding seedling of grafting machine. The reasons for the failure of cotyledon adsorption were the inaccurate control of cotyledon direction and feeding seedling height, and the petiole splitting caused by too small cotyledon angle. The simulation test of adsorption block working face profile and structural parameters is of great significance to improve the flexibility and safety of rootstock. It can greatly shorten the design cycle of adsorption block. The research results provide theoretical basis and design reference for solving the problem of automatic feeding seedling of grafting machine.
Abstract: In the high temperature season, the surface temperature of the soil is very high, and the internal water content of the soil is rare. Sudden rainfall has a great influence on the dynamic change of soil temperature and the water-heat exchange and migration. At present, there are few research achievements on the hydrothermal interaction of soil in the process of rainfall unsaturated infiltration, which cannot truly reveal the influence mechanism of rainfall unsaturated infiltration on soil temperature change and heat transfer. Therefore, it is very important to study the influence of the water movement caused by rainfall infiltration on the soil temperature change and the law of heat transfer. In order to reveal the soil moisture movement in unsaturated rainfall infiltration process of high temperature and the influence of soil heat transport mechanism, this paper established an soil heat transport in the process of rainfall infiltration mathematical model and finite element numerical calculation program is compiled, in view of the typical silty soil layers in nanjing, was carried out by unsaturated rainfall infiltration to the influence of soil heat transport, numerical calculation and analysis. The results showed that in the absence of rainfall, soil temperature change and heat transfer were mainly caused by heat exchange between the surface soil and the environment, and the depth of heat transfer was about 0.2m. Under the effect of constant rainfall intensity, the soil matric suction and volumetric water content in the silt layer change gradually with the duration of rainfall due to the unsaturated infiltration process of rainfall. When the soil moisture front reaches different depths, the volumetric water content increases rapidly, and the soil volumetric water content after the moist front gradually approaches the saturated volume water content. Under the influence of rainfall unsaturated infiltration, heat exchange occurs between low-temperature rainfall in soil pores and soil particles, which changes the distribution law of the original soil temperature field. Moreover, with the continuous increase of rainfall infiltration depth, the influence of rainfall infiltration process on soil heat transfer gradually weakens. By comparing and analyzing the field monitoring data and numerical calculation results, the change rules of soil rainfall infiltration and heat transfer were revealed, and the rationality of the numerical calculation program of soil heat transfer was verified. The research results can provide important reference for agricultural water conservancy engineering and soil and water conservation, distribution and utilization of soil hydrology and water resources, urban water resources control and ecological environment protection.
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: Biocrusts are fundamental components and surface landscape in arid regions, while affect biogeochemical processes. Actually, biocrusts stoichiometry is largely unknown in the desertified region of Northern China. Especially, how precipitation influences biocrusts stoichiometry in desert steppe is still uncertain. A manipulative experiment with additions of precipitation and drought treatment by using rain shelters and sprinkler irrigation system to control precipitation input, which was conducted to test their effects on the biocrusts in desert steppe with contrasting natural precipitation. Then the carbon (C), nitrogen (N) and phosphorus (P) contents of biocrusts were measured to explore the C: N: P stoichiometry and its driving factors. After one-year precipitation control experiments, we found that drought treatment increased C: N, C: P, and N: P ratios in the crust layer, and the ratios in the underlying soil increased after increasing precipitation. Second, drought treatment increased the difference in C between the crust layer and the underlying surface, while reducing the difference of the N and P content. Increase precipitation exacerbates the difference in N and P content between the crust and the underlying surface. But drought treatment was conducive to the accumulation of C in the crust layer. The effectiveness of soil P in the crust was reduced after Increase precipitation. Changes in C: N: P stoichiometry may be caused by changes in soil properties, especially C and soil water content (SW). Of course, soil microbial biomass carbon (SMBC) and nitrogen (SMBN) were also important in shaping C: N: P stoichiometry. Overall, these results demonstrated that the C: N: P stoichiometry of the crust layer and the underlying surface has different responses to precipitation in the desertified region of Northern China.
Abstract: Territorial spatial planning is the important measure of regional resources utilization and ecological protection, promote modernization of space governance system, service for ecological civilization construction and national modernization strategy, the territorial ecological restoration is the activities and processes of territorial space comprehensive improvement and ecological restoration, to direct at imbalance of regional spatial pattern, and inefficiency of resource utilization, and the damaged of the ecological function. It is the main content of establishment and implementation of the territorial spatial planning. Ecological restoration partition is the important premise of reasonable formulation of territorial spatial ecological restoration planning and scientific and efficient to carry out ecological restoration. Since the 1950s, in the regional-dominated functional zoning, China has carried out such regionalization work as agricultural regionalization, economic regionalization, land use regionalization, urban function regionalization, ecological function regionalization and land main function regionalization. The functional zoning of territorial space with different emphasis has different methods and basis, such as factors and indicators of evaluation, space types of zoning and grading of zoning due to the different goals and functional positioning of zoning. New era, the territorial spatial ecological restoration have been given a new responsibility and mission. It is the urgent needs and important guarantees to accelerate territorial spatial ecological restoration, and promote territorial spatial bearing capacity, and construction the pattern of ecological security in territorial space, and it has important theoretical and realistic significance to promote the harmonious coexistence between man and nature, and promoting the construction of ecological civilization and beautiful China. Through the analysis the zoning positioning and connotation characteristics of regional land, ecology, economy and other dominant functions, based on the basic theory of "life community", "Production - life - ecology" coordination and "Suitability management"，and other theory about territorial spatial planning and ecological civilization construction, and based on the combination of "top-down" and "bottom-up", the idea and method of ecological restoration zoning of territorial space was proposed based on dominant functional zoning: First, to understand the background of natural resources, and finish the first level ecological function foundation partition; Second, to evaluate the status of regional ecological functions, and complete the secondary ecological restoration pattern zoning; Third, to define key areas of ecological restoration, and complete three-level ecological restoration mode zoning. This method takes the rule of territorial differentiation, dominant ecological functions and major ecological problems as the basis for zoning, and integrates ecological, economic, social and other factors. The partitioning method has the following characteristics: First, it highlights the dominant function; Second, follow the ecological law; Third, adaptation of the spatial scale; Fourth, strengthen up and down connection. In the design of this method, the goal orientation, function orientation, problem orientation, task orientation and other aspects are comprehensively considered, so as to obtain scientific and feasible zoning results as far as possible, which is conducive to the ecological restoration and comprehensive improvement of territorial space. However, it still needs to improve constantly in practice, to analyze the development trend of ecological restoration zoning: First, it is to emphasize differences; Second, to emphasize simplicity; Third, to emphasis on operability; Fourth, to emphasis on evaluation. The research is of positive significance to the compilation, implementation and ecological control of territorial space ecological restoration planning, and can provide scientific and technological support for the overall protection, systematic restoration, comprehensive improvement and to promote the development of a beautiful China.
Abstract: Efficient nutrient utilization is an important part of agriculture green development. As a typical representative of agricultural mechanization and modern production, Heilongjiang Land Reclamation Area (HLRA) was one of China's major grain-producing regions and had produced 410 million tons of grain since 1949. And the total grain output in 2018 was 2.296 million tons, accounting for 3.47% of the total national output. So evaluation and analysis of the nutrient balance of farmland soil during the period were critical. And HLRA was chosen as the research object in this paper. The nutrient balance method was developed to analyze and evaluate the input and output of N, P, and K of farmland soil from 2000 to 2018. The results showed: From 2000 to 2018, N, P, and K input of farmland soil in HLRA showed a steady-growth-decline trend. The N, P and K input in 2000 was only 4.41×108 kg, 6.79×107 kg and 2.09×108 kg. The nutrient input of farmland soil increased rapidly from 2003 to 2012, and the highest value was 8.43×108 kg, 1.35×108 kg and 5.61×108 kg. The N, P and K input in 2018 was 6.56×108 kg, 1.27×108 kg and 5.29×108 kg. The main ways of N input were chemical fertilizer, organic fertilizer and biological nitrogen fixation; the main ways of P input and K input are chemical fertilizer and straw returning to field respectively. From 2000 to 2018, N, P, and K output of farmland soil in HLRA showed a steady-growth-decline trend. The N, P and K output in 2000 was only 3.16×108 kg, 3.23×107 kg and 2.06×108 kg. The nutrient output of farmland soil increased rapidly from 2003 to 2012, and the highest value was 6.64×108 kg, 7.62×107 kg and 5.06×108 kg. The N, P and K input in 2018 was 6.12×108 kg, 7.34×107 kg and 4.88×108 kg. The main ways of N output and P output were grain and straw; the main way of K output was straw. Also, the N output from ammonia volatilization should be paid attention to. N, P, and K input per area of farmland soil in HLRA showed a steady-growth-steady trend from 2000 to 2018. The N, P, and K input per area in 2000 was 228.80 kg/hm2, 35.23 kg/hm2 and 108.46 kg/hm2. The value in 2018 was 228.08 kg/hm2, 44.32 kg/hm2 and 183.98 kg/hm2. N, P, and K input per value of farmland soil in HLRA showed a decline trend from 2000 to 2018. The N, P, and K input per value in 2000 was 0.03621 kg/yuan, 0.00558 kg/yuan and 0.01717 kg/yuan. The value in 2018 was 0.00949 kg/yuan, 0.00184 kg/yuan and 0.00765 kg/yuan. N and P utilization efficiency of farmland soil in HLRA showed a growth trend from 2000 to 2018, but K showed a decline trend. The N, P and K utilization efficiency was 51.03%, 27.98% and 10.04% in 2018.N profit and loss of farmland soil in HLRA showed a growth trend, P profit and loss of farmland soil in HLRA showed a steady trend, and K profit and loss of farmland soil in HLRA showed a decline trend. Compared with Australia, Canada, France, Germany, Japan, UK, and the USA, N profit and loss in 2018 was 15.08 kg/hm2, which was at an excellent level. But P profit and loss in 2018 was 18.78 kg/hm2, which was at a poor level. And K profit and loss in 2018 was 14.16 kg/hm2. N and K were in a nutrient balance state, but P was in a nutrient surplus state, which was related to the fact that P input to the farmland was easily fixed by soil. At the current stage, the fertilizer input in HLRA was mainly relying on chemical fertilizer, and the amount of organic fertilizer was relatively low, which was not conducive to fertilizing soil and slowing down the trend of black soil degradation. So HLRA was suggested to develop various methods, such as subsidies and demonstration, to gradually promote the application of organic fertilizers. Besides, Long-term monitoring of nutrient balance of farmland soil was required in the future, which was beneficial to scientific adjustment and optimization of soil nutrient management measures and strategies, improving nutrient utilization efficiency, guaranteeing food security and boosting agriculture green development.
Abstract: Water vapor movement is one of the important components of total water flux in the vadose zone of drylands. Generally, though the amount of these non-rainfall water is usually quite small in comparison to rainfall, the vapor sorption and condensation are vital water sources for plants, insects, and small animals when soil water content is very low. In arid and semiarid drylands, biocrusts have been regarded as a critical upper layer which greatly changes surface soil water movement and even surface soil energy balance, however, their influences on water vapor sorption and condensation have not yet been fully understood. Therefore, it is necessary to investigate the characteristics of water vapor sorption and condensation in biocrusts and their influential factors for quantifying vapor water supplement from biocrusts and better-understanding biocrust effects on vapor movement in drylands. Due to this reason, we investigated the characteristics of vapor sorption and condensation in typical cyanobacteria crusts (cyano-crusts), cyanobacteria and moss mixed crusts (mixed crusts), moss crusts (more than 30 a), and bare sand (aeolian sand) on the Chinese Loess Plateau. In this study, through analyzing the vapor sorption (adsorption and desorption directions) of biocrusts and bare sand in laboratory and measuring their vapor condensation (condensation process and daily vapor condensation amount) in field. Our results showed that the soil water content increased with the water activity (aw), and the biocrusts significantly increased vapor sorption amount as compared with bare sand. Specifically, the water vapor adsorption of biocrusts was averagely 66.7% higher than that of bare sand. Especially for moss crusts, which was 1.0-2.2 times higher than that of bare sand. Furthermore, the water vapor sorption amount was also varied between different types of biocrusts, and the water vapor adsorption of cyano-crusts, mixed crusts, and moss crusts were obviously different, which was 0.011, 0.020, and 0.015 g/g, respectively. The simulation results implied that the GAB (Guggenheim-Anderson-de Boer) model was capable of descripting vapor sorption isotherms of biocrusts, with R2>0.99, RMSE<0.001 2 g/g, and E (mean relative percentage deviation modulus) <16.0%. We also observed significant hysteresis effects according to the hysteresis index in WSIs, in decreasing order of moss crusts, mixed crusts, cyano-crusts, and bare soil. The hysteresis index of biocrusts was 2.0-3.0 times than that of the bare sand. Moreover, the results of vapor condensation showed that the water vapor mostly condensed from sunset to sunrise for all the treatments in our study, then it gradually evaporated and reached the minimum value at ~15:00. In comparison to the bare sand, the rates of water vapor condensation and evaporation in the biocrusts were much faster. Especially in September, the vapor condensation amount of biocrusts was averagely 1.5 times higher than that in the bare sand. Overall, the vapor condensation was deeply influenced by the meteorological factors (i.e. air temperature and relative humidity). Furthermore, as compared with bare sand, the daily condensation amount of the biocrusts was averagely 1.6-1.8 times higher than that of bare sand. Particularly, the condensation amount of different types of biocrusts was varied, and the condensation amount of moss crusts the highest and was still 81.8%, 11.1%, and 5.3% higher than that of the bare sand, cyano-crusts, and mixed crusts, respectively. In conclusion, vapor sorption and condensation of biocrusts played an important role in soil vapor movement, because i) biocrusts covered soil surface and enhanced vapor sorption amount due to the high clay and organic matter contents, and ii) biocrusts increased vapor condensation amount by improved soil properties and moss mulching effects. Therefore, biocrusts should be intensively considered in water transport studies in drylands.
Abstract: Since 2000s, the agricultural structure of Sanjiang Plain had been greatly adjusted with large amount of dry land crops changed into rice, which resulted in a set of problems in the utilization of water resources. Based on the background above, it was necessary to study the main crops’ water profit and loss situation, so as to put forward regional irrigation strategies and serve the national food security. To reveal the water surplus & deficit situation of the middle crop、spring wheat and spring wheat in Naoli River Basin, which was located in the hinterland of Sanjiang Plain, the Priestley Taylor formula and Crop Water Surplus & Deficit Index were used in this article. The MODIS image data, the long-term sequenced meteorological data and the DEM data were used as its fundamental data resources in all the above analysis. Results showed that the Potential Evapotranspiration (ET0) increased from 910.25 mm in 2000 to 964.04 mm in 2015 in this river basin. The water demand of main crops, including middle crop, spring wheat and spring maize, were also increased at different ranges as a whole; The natural precipitations could not meet the middle rice’ irrigation demand, which was characterized by Crop Water Surplus & Deficit Index decreasing trends from 2000 to 2015 in Naoli River Basin, and its absolute value was increasing from northeast to southwest in the spatial distribution. The spring wheat’s Crop Water Surplus & Deficit Index was larger than the middle rice, and it showed similar characteristics in the whole spatial distribution for each years. The spring maize’s Crop Water Surplus & Deficit Index showed this spatial characteristics of northwest slightly lower than that in the southeast, which was both in mild water shortage status in Naoli River Basin; Drought classification was evaluated on the basis of Crop Water Surplus & Deficit Index, so as to study on the drought characteristics in Naoli River Basin. Results showed that the middle crop, which area proportion growth rate reached 143.46%, was basically in mild drought state in this basin. Despite at the state of water shortage, spring wheat had not reached the drought standard as a whole. The spring maize area in mild drought state in Naoli River Basin had decreased by 79.90%. Agricultural structure of this basin had been greatly adjusted with large amount of spring wheat and spring maize changed into middle rice, which resulted in a rapid increasing for the middle rice since 2000, and this phenomenon led to water shortage severely. It was remarkable that the spring wheat and spring maize owned extremely rare negative impact on the water surplus and deficit situation in this basin. These research results provide the references and consultancies for the farmland irrigation schemes and agricultural structure adjustment in Naoli River Basin.
Abstract: The remote sensing images used in agricultural production are often affected by clouds during the acquisition process. As a result, the sharpness of the acquired image will be reduced low sharpness of the acquired image. The interpretation of terrain information in such unclear remote sensing images can be very difficult and the subsequent applications will be greatly affected, such as crop growth detection, crop classification and yield prediction. In order to solve this problem, a method for cloud removal of remote sensing images based on improved conditional generative adversarial net-work was proposed in this paper. This method provides a common network architecture for the removal of thin and thick clouds in remote sensing images. In addition, the generator of network is improved to solve the problem of image generation caused by the single feature extraction method of the network. Firstly, use a series of convolutions to extract the feature information of the input image. Then, multi-scale feature maps are obtained from the feature information through the spatial pyramid pooling operation. Finally, restore these different size feature maps to the original size and mix them together. In this way, the scale of the feature extraction by the generator can be increased. The resulting effect will also increase accordingly. In order to evaluate the cloud removal method, experiments were performed using remote sensing image data sets and the results of this method were compared with traditional conditional generative adversarial net-work method and the pix2pix method. At the same time, two objective indicators were introduced for evaluation. They are the peak signal-to-noise ratio (PSNR) and the structural similarity(SSIM). The experimental results show that 1)The method can The optical remote sensing images used in agricultural production are often affected by clouds during the acquisition process. As a result, the sharpness of the acquired image will be reduced. Decreased image clarity will make it difficult to interpret feature information. Subsequent applications in agricultural production will also be affected, such as crop growth detection, crop classification and yield prediction. In order to solve this problem, a method for cloud removal based on improved conditional generative adversarial net-work was proposed. This method generates the mapping relationship between pixels of the cloud and cloudless data through training conditional generative adversarial net-work. And it complete the transformation from cloud remote sensing image to cloudless remote sensing image on this basis. Eventually, it can effectively realize the removal of the cloud component in the optical remote sensing images. And at the same time, it can realize the restoration of details of optical remote sensing images. In this way, it provides a common network architecture for the removal of thin and thick clouds in optical remote sensing images. However, the single feature extraction of the conditional generative adversarial net-work leads to poor quality of the generated results. Therefore, the generator of network is improved to solve the problem. Firstly, a series of convolutions are used to extract the feature information of the input image. Then, multi-scale feature maps are obtained from the feature information through the spatial pyramid pooling operation. Finally, these different size feature maps are restored to the original size and are mixed together to generate the final cloudless optical remote sensing images. By this means, the scale of the feature extraction by the generator can be increased. The resulting effect will also increase accordingly. In order to evaluate the cloud removal method, experiments were performed using optical remote sensing image data sets. In the experiments, the results of the improved method were compared with three types of methods. They are original CGAN method, traditional cloud removal method and the pix2pix method in deep learning. For better evaluation, two objective indicators were introduced to make a quantitative assessment of experimental results. They are the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM). The experimental results show that1) The method can be applied to the cloud removal of thin cloud and thick cloud in optical remote sensing images. And it achieved good results in both types of cloud removal; 2) Compared with the original CGAN, the generated cloudless remote sensing image is closer to the real cloudless remote sensing image. Remove the thin cloud using the improved model, the PSNR value increased by 1.64db. And the SSIM value increased by 0.03. Remove the thin cloud using the improved model, the PSNR value increased by 1.05db. And the SSIM value increased by 0.04; 3) Compared with the traditional cloud removal method, improved model removes cloud layer in optical remote sensing image more thoroughly. At the same time, the color of the features in the optical remote sensing image is better and more realistic. Compared with the pix2pix method, details of the ground in the generated cloudless optical remote sensing images are better recovered. The value of the PSNR indicator for remote sensing images increased by 1.24db after the removal of the thin cloud. The value of the PSNR indicator for remote sensing images increased by 0.89 after the removal of the thick cloud. The value of the SSIM index of remote sensing images has also been increased accordingly. The results verify the feasibility of removing cloud from remote sensing images based on improved conditional generation of adversarial network. Furthermore, it can provide a new idea and method for agricultural remote sensing image processing.
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: A new kind of clay modified by cetyltrimethyl ammonium chloride(CTAC) was prepared to solve the problem of sand fixation in desert highway construction and maintenance. H1, H2, H3, H4, H4, H5 and H5 were assigned to the treatments of CTAC and clay with mass ratios of 2:4, 3:4, 4:4, 5:4 and 6:4, respectively. In addition, unmodified clay was prepared as the blank control group H. The water retention performance was tested in an artificial climate box to simulate the desert climate. And the changes of mass and compressive strength were tested before and after ageing to test its anti-aging property. The grass planting experiment was conducted to analysis the effect of materials on germination rates. At last, the mechanism of sand fixation and water retention was analyzed by X-ray diffractometer, infrared spectrum analyzer and scanning electron microscope. The results showed that the moisture content of the original clay decreased to 0 at the 3rd day. And the water retention property was obviously improved with the increase of CTAC content. The highest and lowest moisture content were H5 and H1, respectively. And the moisture content on the 7th day was 27% and 7%, respectively. The moisture content of H4 was also higher, 23% on the 7th day. This indicated that the water retention performances of modified clay samples were significantly improved. With the increase of CTAC content, the water retention performance was gradually enhanced. In the compressive strength test, the universal testing machine failed to measure the data due to the low strength (less than 0.1 MPa) of the unmodified clay group H. The strengths of the modified clay samples were significantly improved, and the strengths of the modified clay samples all met the standard requirements (no less than 1 MPa). Moreover, the strength of the modified clay increased with the increase of the content of CTAC, with the highest strength of H5 (2.2 MPa), the lowest strength of H1 (1.7 MPa), and the higher strength of H4 (2.1 MPa). This indicated that CTAC could bond dispersed clay particles together to form a consolidation layer, and its strength could meet the requirements of mechanical construction. In the anti-aging performance test, after aging for 500h, no obvious cracks were found on the surface of the samples, and the water retention performance decreased by less than 5%. The strength loss rate and mass loss rate of all the groups increased with aging time, and the higher the CTAC content was, the higher the strength loss rate and mass loss rate were. The strength loss rates of H4 and H5 were respectively 7.3% and 10.4% (after 500 h of aging). The mass loss rates of H4 and H5 were respectively 2.6% and 3.2% (after 500 h of aging). The germination rate of the H group(unmodified clay) was 7%, and the germination rate of the modified H1 group was 33%. With the increase of CTAC content, the germination rate of grass seeds gradually increased. And the germination rate of H4 group was up to 47%. With the increase of CTAC, the germination rate began to decline, and the germination rate of H5 group was 41%. This was mainly because CTAC could bond the loose clay particles together, thus significantly reducing the gap between clay particles and improving the water retention capacity of clay layer. It could provide necessary soil moisture for grass seed germination, so the germination rate of grass seed greatly increased. However, excessive CTAC would overfill the space of clay particles and reduce the permeability of the consolidated layer, so the germination rate of H5 began to decrease. The X-ray diffractometer analysis showed that the lamellar space of clay before and after modification changed from 1.2535 nm to about 1.4850 nm. It indicated that CTAC entered into the clay lamellae, which made the lamellae spacing become larger. Infrared spectrum analysis showed that the characteristic peaks of 2930 cm-1 and 2850 cm-1 were respectively asymmetric stretching vibration peak and symmetric stretching vibration peak ofv-CH2in CTAC, which were newly emerging in modified clay. Combined with X-ray diffractometer analysis, it could be seen that CTAC entered into the clay lamellae. The microscopic analysis showed that CTAC could bond the loose clay particles together through intercalating effect. The clay gaps were turned into hydrophobicity, which resulted in the increase of the water transport resistance. So the modified clay had better sand-fixation and water-retention performance. However too much CTAC blocked the space of clay particles, the permeability of clay decreased, so the germination rate of H5 decreased. Although the compressive strength and water retention performance of H5 is slightly better than H4, as a kind of sand fixation material, the most important performance is the survival rate of seedlings. Therefore, under the premise that all other performances meet the standard requirements, H4 with the highest germination rate is selected as the best treatment scheme. The results could provide reference for the application of the new sand-fixing materials.
Abstract: The development of intelligent agricultural pest monitoring technology is developing rapidly, and the bird monitoring technology is still in its infancy. In recent years, due to ecological improvement, the number of pheasant breeding has increased sharply. Its fondness for seeds and seedlings of wheat, corn, sweet potatoes and other crops has caused certain harm to agriculture. however, the traditional bird repellent methods have deficiencies in terms of efficiency and danger. An efficiency pheasant monitoring method combined with artificial intelligence is needed to provide early warning and expulsion of pheasants. Pheasant activities are mostly in the early morning and dusk under complex environment with protective color or habit of hiding. A pheasant monitoring method suitable for the deployment of embedded system is proposed in this paper. According to the behavior of pheasant, specific conditions required to monitor pheasants, the study proposed a pheasant monitoring method suitable for the deployment of embedded computing platforms which combine the enhanced Tiny-YOLOV3 target detection network to monitor pheasants. Due to the deployment on a mobile platform in the field environment, a lightweight network is required, while ensuring the accuracy and real-time monitoring. Therefore, according to the basic structure of the Tiny-YOLOV3 lightweight target detection network, a real-time monitoring network ET-YOLO for the emergence of pheasants in a complex field environment is proposed. The feature extraction net part deepens the net depth of Tiny-YOLOV3 feature extraction, increases the detection scale to improve the original net target detection accuracy. The net detection layer uses the detection method based on CenterNet structure to further improve the detection Measurement accuracy and speed. Using the field collection of pheasant images in various environments as dataset which including 6000 high resolution images of pheasant in different distances、angles and environments, through dataset augmentation, the pheasant monitoring dataset is produced. The experimental evaluation indicators are mainly tested and evaluated in terms of accuracy, real-time performance, and model size. The average detection accuracy, average detection speed, and detection model size of the pheasant are used for evaluation, the experimental results show that the average detection accuracy of ET-YOLO in the complex field environment is 86.5% and the average detection speed is 62 frames / s which is 15 percentage points higher than the average detection accuracy of Tiny-YOLOV3 before the improvement and the average detection speed is 2 frames/s higher than that of Tiny-YOLOV3 before the improvement. Compared with other state of the art target detection algorithms. The average detection accuracy is higher than YOLOV3, Faster-RCNN and SSD_MobileNetV2 by 1.5, 1.1 and 18 percentage points respectively. The average detection speed was 38, 47and 1 frame/s higher than YOLOV3, Faster-RCNN and SSD_MobileNetV2 respectively, the detection model size is 56 MB. Compared with other state of the art target detection algorithms, this method is suitable for deployment on embedded system equipped with agricultural robots and intelligent agricultural machines in terms of monitoring accuracy, real-time performance, and model size, which can efficiently monitor pheasants in complex environments.
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: Vegetation coverage has a direct impact on the quality of regional ecological environment. Dynamic monitoring of regional vegetation coverage changes and analysis of its influencing factors are of great significance for effectively carrying out ecological engineering construction and achieving sustainable development of ecological environment. Danjiangkou Reservoir is the core water source area of the Middle Route of South-to-North Water Transfer Project. Its ecological environment directly affects the water quality and water quantity of the water source area. At present, there are some problems in the study of NDVI dynamic change in this area, such as short research time and inadequate quantitative evaluation of human activities. Based on EOT algorithm, taking Danjiangkou water source area as the research area, a 1 km resolution NDVI data set from 1982 to 2018 was constructed using GIMMS NDVI and MODIS NDVI data. On this basis, the characteristics of NDVI changes in the study area from 1982 to 2018, climate factors and human activities factors were analyzed, respectively. The results show that: NDVI fluctuated upward from 1982 to 2018, and the trend was 0.0029 year-1 (P < 0.05). Spatially, 89.93% of the annual average NDVI showed an increasing trend. 10.06% of the annual average NDVI showed a decreasing trend. In terms of influencing factors, climatic factors are the main factors affecting NDVI change in the whole region, and the influence of temperature on NDVI of vegetation is greater than that of precipitation. Temperature and precipitation have significant spatial heterogeneity on NDVI. Spatially, temperature is mainly positivel correlated with the areas around Hanzhong Basin in the west, Ankang City in the middle, Shangzhou City in the north and Zhuxi County in the south, while other regions have low correlation.Precipitation is negatively correlated with Danjiangkou Reservoir and Shiyan City, while the correlation is low in other regions. The residual method was used to separate the effects of climate and human factors on regional NDVI. It was found that the comprehensive contribution of climate factors and human activities factors was 92.14% and 7.86% at the whole regional scale during the study period. However, in the regions with significant changes in NDVI, the comprehensive contribution of climate factors and human activities factors was comparable. In recent years, human activities in the region have been increasing, while the influence of climate factors is gradually declining. Human activities have dual effects on regional NDVI. 67.74% of the regional human activities in the study area have positive effects on NDVI. The positive effects are reflected in a series of ecological protection and construction engineering measures to restore the ecological environment. 32.26% of the regional human activities in the study area have negative effects, and the negative effects are reflected in the development of society. A series of unreasonable production activities carried out at the economic level.
Abstract: Grain reserves is an important material foundation for ensuring food security, and food security is a major prerequisite for national security. The fatty acid content is a sensitive indicator of the changes of grain quality. Therefore, in order to achieve safe and green grain storage, real-time understanding of the fatty acid content of stored grain is significant for the safety of grain during storage. In this paper, 4 prediction models such as multiple linear regression(MLR), artificial neural network (ANN), support vector regression (SVR) and least square support vector regression(LSSVR) were applied to predict the fatty acid content of stored rice, and the predictive performances of these 4 prediction models were compared based on coefficient of determination(R2), mean absolute error (MAE), mean absolute percentage error and root mean square error (RMSE), which were measured by the difference between the observed and the corresponding predicted values in the test set. First of all, totally 201 rice storage data were collected from 35 granaries in 5 grain depots in the three northeastern provinces of China. In these storage data, each data contained 10 characteristics, which were warehousing month, initial moisture, initial fatty acid value, detected moisture, stored effective accumulated temperature, storage time, detected grain temperature, detected granary temperature, detected month and detected fatty acid value, respectively. Then, we analyzed the correlation between these predictive factors based on the Pearson correlation coefficient. However, we found that there were strong correlations between some predictive factors. In order to eliminate redundant information, we reduced the dimension of predictive factors by principal components analysis (PCA), and 4 key predictive factors which were initial moisture, initial fatty acid value, stored effective accumulated temperature, detected grain temperature were obtained after PCA dimension reduction. Finally, the key predictive factors were normalized and randomly segmented 80% used for training, 20% for testing, and the PSO algorithm were adopted to optimize the parameters of SVR and LSSVR before simulation experiment, the optimal parameters for the SVR model were found based on C value of 569.3, ε of 0.05 and γ of 2.7, and the optimal parameters for the LSSVR model were found based on C’ value of 1000.0 and γ’ of 0.003, respectively. For testing the data set, the experimental results showed that the predictive performance of LSSVR of which the coefficient of determination values of 0.911, MAE values of 0.275(KOH)/(mg/100g), MAPE values of 1.604% and RMSE values of 0.348(KOH)/(mg/100g) was significantly better than SVR and ANN, and was slightly better than MLR. The various indicators revealed that the LSSVR and MLR had better predictive effect on fatty acid content of stored rice, and SVR was the worst among all models. It concluded that the LSSVR and MLR had high forecast accuracy and strong reliability in prediction of fatty acid content of rice, they all can be used as a method for predicting fatty acid content during rice storage. This study realizes the prediction of fatty acid content of stored rice and provides a reference for scientific and safe green storage in the future.
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: Accurate and rapid acquisition of crop and weed category information is an important prerequisite for automated weeding operations. In order to solve the problem of efficient and accurate identification of weeds in crop fields in complex environments, this research proposes a weed recognition model based on improved DenseNet. Based on the DenseNet-121 network, this model introduces an ECA attention mechanism after each convolutional layer to strengthen the weed features and suppress the extraction of background features, thereby improving the accuracy of weed recognition. In addition, add DropBlock regularization after each DenseBlock block to ensure the generalization ability of the model and realize efficient and accurate identification of weeds in complex environments. Under the same experimental conditions, using corn seedlings and six types of associated weeds as samples, the average recognition accuracy of the model in this article can reach 98.63%, which is higher than the VGG-16, ResNet-50 and unimproved DenseNet-121 models. , Which proves that the model can well deal with the identification of crops and weeds in complex environments, and can lay a solid foundation for the development of an intelligent grass-recognition system for weeding robots.
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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: By analyzing the problems of traditional methods for estimating the weight of pigs, the authors discuss a new method which applies computer vision technology to pig production. The projected image area of pigs when viewed directly from above was computed. The pig weights were estimated by the linear regression of the pig real areas. The results show that a strong relationship exists between pig weight and the projected area of the pig after removing the sections of head and tail in images. The correlation coefficient is 0.94. By comparing with the measured weights, the relative error is less than 2.8%. The experiment indicates that this hands-off method has great significance in scientific management of the pigs, which does not require large labor and material resources, and also avoid the loss in production resulted from stress.
Abstract: Owing to the fact that there were geometric nonlinearities, physical nonlinearities and contact nonlinearities during the working of vehicle air spring, it is difficult to estimate its mechanical property accurately using empirical formula. In recent years, with the development of nonlinear finite element theory and computer techniques, it is possible to estimate the mechanical property of air spring using nonlinear finite element method. Based on the study of an air spring used on a certain kind of vehicle suspension system, its three-dimensional finite element model was developed. In the model, the cord reinforced rubber bellow was simulated by both Mooney-Rivlin constitutive model and Rebar model, and the listrium and piston were simulated by rigid-body model. The nonlinear finite element analysis software ABAQUS was applied for computing the mechanical property of vehicle air spring. To further validate the reliability of the calculated results, the static characteristic test for measuring the mechanical property of air spring was carried out on electro-hydraulic servo experiment rig system of Instron 8800 air spring. The analysis indicates that these calculated results are in good agreement with the experimental results. Hence, nonlinear finite element method is an economical and practical approach to estimate mechanical property of vehicle air spring.
Abstract: Abstract: In the northern and especially northeastern areas of China, it is so quite pleasantly cool and dry in the autumn that farmers used to cure peanuts in the field for some days after digging in order to decrease the mass of the peanut plants, and more easily transport and pick up the crop. It indicated that the two-stage harvest might be more suitable to peanut production in the north and northeast areas of China. Based on the viewpoint and theory of combining machinery with agronomy, the main peanut varieties in the western of Liaoning were selected as test materials, the variances of moisture content, and mechanical properties of peanut stems and pegs accompanying the change of curing days were studied by means of an infrared moisture meter and a universal bio-material testing machine. During the test, the curing days of peanut plants in the field after digging was selected as the basic variable, and more than seven days as the time span. The moisture contents of peanut stem and peg, and the tensile strength of the peg and its nodes were measured. The change rules of moisture content of peanut plants during the curing process in the field were obtained, which showed that the change rules of three kinds of peanuts were very similar i.e. the moisture content of the peanut stem and peg dropped rapidly with the extension of curing time in the early drying time (previous two days), and then the moisture content decreased slowly. The change rules of moisture content of peanut plants change tended to be an asymptote from the third curing day, when the moisture contents of the peanut stem and peg were almost no longer dropping, and finally settled around 9%. The moisture content of the peanut peg and its two nodes ranged from 8.48% to 65.68%, and the changes of tensile strength and moisture content in the three kinds of peanuts were quite similar. In the whole curing process, the tensile strength of the peanut peg was always highest, the tensile strength of the peanut-peg node was lowest, and the tensile strength of the stem-peg node was in the middle. The tensile strength of the three key positions of the peg all changed with the moisture content. And the tensile strength of the fresh peanut plants with high moisture content were highest, the tensile strength of peanut peg and its two nodes decreased rapidly in the early curing time, and then dropped slowed until it gradually tended to a constant value. The regression equation of the tensile strength and the moisture content of the peg and its two nodes as obtained by the method of SPSS software were that the fitting coefficient of stem-peg node tensile strength was 0.9891, the fitting coefficient of peanut-peg node tensile strength was 0.9974, and the fitting coefficient of peanut peg tensile strength was 0.9966. And under the experimental condition, the optimal curing days before picking up was preliminarily determined to be 3~5d, and the corresponding moisture content of the peanut peg ranged from 10% to 20%, the tensile strength of peanut peg and stem-peg node ranged from 10N to15N, and the corresponding tensile strength of peanut-peg node ranged from 7N to 9N. The above study results could be used as important references to design a picker and thresher of peanuts and to determine the optimal picking time, as well as deeply research the mechanisms of picking up and threshing with less loss of dropping and damage.
Abstract: Abstract: Studies of Erhai Basin indicate that Land use change by human activities in the watershed is the leading cause of regional climate, hydrology, water quality and ecological changes. Therefore, it is necessary to study the relationships between human activities and land use/cover change (LUCC), which is beneficial to offer the scientific decision support for reasonable land planning and land use. Combined with GIS technologies of spatial analysis and using the artificial intelligence algorithm Ant Colony Optimization(ACO) for optimizing, in this paper, we applied the method of Agent-based modeling to establish the spatiotemporal process model of LUCC in order to simulating the dynamic change of land use in whole watershed. Firstly, we made a choice and evaluation for impact factors of land use changes, as well as constructions of the cost of land use change equations in order to construct more reasonable decision rules of land use choice. Then, we have extracted three agents composed by microcosmic and macrocosmic systems which were farm agent, resident agent and government agent. Also, microcosmic rules of decision and behavior were created according to ACO. On the other hand, we have established macrocosmic decision rules according to a resistance coefficient system from the land use planning, as well as a comprehensive decision rule. And then, based on Java language and Repast platform of modeling, the program design, implementation and simulation of model were given in detail. Finally, the validation, calibration and verification of model and analysis of the simulated results were also conducted. Our conclusions from the experiment were three: 1) Ant colony algorithm was more effective in promoting the significant moving and decision of agents, and the simulated results gained better accuracies in both mathematics (up 5.6%) and geometry (up 3.4%) than using a random algorithm. However, the merit of ACO was not suitable for its use in all of land-use types. For an instance, there were no any improvements and sometimes even reduction in accuracy for those land-use types which were less affected by human activities, such as forest, grassland and wetland uses. Thereby, we suggested that ACO was more sensitive to interaction between human and land-use changes, and it was suitable for optimizing human behaviors and decisions of land-use transfer. 2) If the policy on land use was kept unchanged, the major contradiction between human and land in the future ten years should be the persistent reduction of agricultural land (127.64 hm2 cultivated lands and 11.20 hm2 garden lands) and the continuous increase of urbanized land (95.80 hm2). This indicated a big cost of urbanization in Erhai Lake Basin, which also gave a warning of increasing impervious surfaces (IS) produced in future rapid urbanization, and the IS may raise risks of urban non-point source pollution in the future. 3) The fast increasing of wetlands (growth rate of 50.07% was the fastest in the change of all land use types) indicated that the governmental land use policies to ecosystem protection have played a better role in macro control of land resources allocation. From this research, we suggested that the local government should maintain the existing strategies of ecological environment protection to reduce the risk of water pollution in Erhai Lake Basin. The competition in the market economy model of land-resources-commercial should be encouraged to balance the next major conflicts between human activities and land resources.
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: By taking Agricultural High-tech Industrial Park of Chinese Academy of Agricultural Sciences (Wan Zhuang) and its peripheral regions with a total area of 4.2 × 3.1 km as the study area, this paper carried out an aerial photogrammetry experiment by using the RICOH GXR A12 camera carried on an unmanned aerial vehicle (UAV), and the experiment mainly tested the precisions of planar positioning under a POS (positioning and orientation system) supported bundle block adjustment method and of area measurement, as well as the precision of the crop area identification of an UAV orthophoto map obtained from an aerial triangulation correction. We use an unmanned aerial vehicle (UAV) to obtain 690 images which covered the whole study area. After a series of processes such as image screen, POS-supported aerial triangulation correction, digital elevation model making, image fusion, and digital differential rectification, we have obtained the ortho-photo map of the whole study area. Since the deployment of high precision ground control point wastes time and energy, POS-supported aerial triangulation employs a non-control point model. Therefore, its absolute positioning precision may be affected by the error of the GPS carried on an UAV. In order to eliminate this error, the project team used a high precision wordview image to rectify the ortho-photo map. In this way, we could improve the image positioning precision, and meanwhile unify the study sample areas with the overall larger scope image coordinate system, so as to provide high precision samples for large-scale agriculture remote sensing statistics and monitoring. The result shows that, under the condition of no control point and after direct POS data bundle block adjustment, the mean square error of plane positioning precision of the X axis direction is 2.29 m, Y direction is 2.78 m, and overall plane error is 3.61 m. If a three order general polynomial model is adopted to conduct a geometric precision correction, then the mean square error of the X axis direction is 1.59 m, the Y direction is 1.8965 m, and the mean square error of the overall plane is 2.32 m. The above figures conform to the 1:10 000 ground plane precision requirements specified in the 'Standard for Aerotriangulation of Digital Aerophotogrammetry' and can meet the positioning precision requirements of a crop area survey in remote sensing monitoring. After obtaining the ortho-photo map, the four ground objects in the area evaluation areas of spring corn, summer corn, alfalfa, and bare soil were classified by employing two methods of supervised classification and object-oriented classification. By taking the differential GPS survey results as the evaluation criteria, the overall precisions of the four crops reached 88.2% (supervised classification) and 92.0% (object-oriented classification) respectively. The separate classification precisions of the two classification methods of the four ground objects were 88.9%, 86.7%, 93.0%, 86.6%, and 90.35%, as well as 90.35%, 92.61%, 94.93%, and 93.30% respectively. The result showed that remote sensing images of unmanned aerial vehicle (UAV), by acquiring small scale and quadrat sampled crop images, have a prospect of wide application. After promotion, it can meet the demands of nationwide crop ground sampling on high spatial resolution images, and can partially replace the operation model of GPS measurement.
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: 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: 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: 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: 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: 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: 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: 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: 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: 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: The study on the driving forces of rural residential land can instruct the consolidation of rural residential area, which is an important part of the study of inner law of rural residential area evolvement. Taking the Beijing mountainous area as study area, the driving forces of rural residential area change was analyzed based on GIS and SPSS using the logistic regression model by view of spatial coherence. The result indicate that the change of rural residential area is controlled by its former distribution and droved by the exterior driving forces under the interior driving forces context such as natural factors and location comprehensively. The change of rural residential area is a process that selecting the preferable location integrating the influence of the nature, local accessiblity and social-economy. The developing orientation of its driving forces is made to probe into the suitable consolidation modes in different localities, which will help to strengthen the management of rural residential area during the construction of new socialist countryside.
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: Field experiments were conducted at Luancheng Station, Chinese Academy of Sciences in different precipitation years. The impacts of water supplied conditions on root distribution, yield and water utilization efficiency(WUE) of winter wheat under different irrigation treatments were analyzed in order to supply a basis for optimum irrigation mode which could increase the yield and improve water utilization efficiency. The results indicated that most roots were concentrated in the upper 80 cm soil layer, and the density of roots declined exponentially downward with the increase of the soil layer depth. Considering water consumption in different soil layers, and the relationships among yield, water utilization efficiency and total water consumption, the optimal irrigation mode in North China plain was put forward, i.e., no irrigation in rain-full years, one time irrigation at jointing stage in normal years and two times at jointing stage and booting stage in dry years with the suitable water quota of 60 to 75 mm each time, which not only increased the winter wheat yield, but also benefited to using the deep soil water and improving the water utilization efficiency.
Abstract: Crop Regulated Deficit Irrigation (RDI)，based on the crop-water relations，is an irrigation technique with high yield and water use efficiency. The beneficial effect of moderate water deficit was analyzed using the data of field experiments in Shaanxi，Gansu and Xinjiang. It showed that RDI should be applied at the early growth stage. The degree of water deficit can reach 45%～50% of field capacity，which has no bad effect on crop yield and can increase crop water use efficiency obviously. And some problems of RDI were also disscussed.
Abstract: The importance of and the need to secure food safety and facilitate international trade through establishing a traceability system for domestic animals and livestock products were discussed, and the essential components and characteristics of domestic animal traceability system were also introduced in this paper. Several animal identification technologies including information and network technology were compared and summarized. The history of implementation and evolution of legislative regulation of traceability systems in developed countries were reviewed; the main issues which hamper the implementation of traceability system were discussed. A pilot project of a Chinese traceability system, in which new technologies were developed, was also proposed. The trends and direction for the development of traceability system was highlighted, and findings of this paper could provide a basis for establishing a national traceability system for domestic animals and livestock products which is feasible to the situation of China.
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.
Abstract: The advances of the greenhouse control system modes were discussed, and several typical greenhouse control system modes were introduced in this paper. The main problems restricting the application of the greenhouse control systems are their high cost and low intelligence due to the hardware topology frameworks of greenhouse control systems. The idea of distributed structure of greenhouse control mode based on CAN bus could decrease cost and also provide a valid way to solve its intelligent problem. At the same time, the development status in the future was given including internet-based control and management, fieldbus-based monitoring sensors and control actuators, and the standardization of control systems in greenhouse production.