Abstract:Plant protection UAV operation has the advantages of safety and efficiency, saving medicine and water volume, strong adaptability, good prevention and control effects, using UAVs to carry out plant protection operations is an important way to effectively prevent pests and diseases. Compared the research on the development and related applications industry, the factors that affected the operation effect and efficiency of the plant protection UAVs were analyzed. Flight control system, single UAV route planning, multimachine operation scheduling scenarios and optimization methods that affected the efficiency and effect of plant protection UAV were described respectively. With the aim of improving the operation effect and operation efficiency of plant protection drones, the status of plant protection UAVs’ flight control, route planning and scheduling were analyzed. In view of the high accuracy requirements of plant protection UAVs, which led to the contradiction of high manufacturing costs of their flight control systems, the lowcost and highprecision attitude measurement devices were developed which can meet the needs of plant protection UAV operations, and corresponding attitude estimation algorithms were developed. For the situation that the plant protection UAVs route planning, optimal scheduling model did not match the actual operation requirements, the optimization scenarios, constraints and optimization methods of single UAV route planning and multimachine scheduling were summarized. Finally, an automatic replenishment platform for plant protection UAVs was developed, an optimized model for job management and scheduling model were built based on multimachine collaboration, and the reliability of plant protection UAVs in complex operation environments was improved. 

Abstract:An apple detection method (Light-YOLOv3) based on lightweight YOLO (You only look once) convolutional neural network was proposed for apple picking robots to detect apples quickly and accurately in the complex background of fruit trees. Firstly, in order to improve the traditional YOLOv3 deep convolutional neural network architecture, a feature extraction network structure containing cascaded homogeneous residual blocks was designed, and the dimensionality of the feature map for object detection was simplified. In this architecture, the conventional convolution was replaced by the depth wise separable convolution, and a multiobjective loss function was defined in terms of the mean square error loss and the cross entropy loss. Secondly, the training data was obtained from the Internet by means of a crawler program, and then labelled. The data augmentation technique was used to expand the training data and normalize it. Thirdly, a multistage learning optimization approach based on stochastic gradient descent (SGD) and adaptive moment estimation (Adam) was proposed to train Light-YOLOv3 network. Finally, an apple detection experiment in the complex background of fruit trees was performed on a computer workstation and an embedded processor, respectively. The experimental results showed that the apple detection method based on Light-YOLOv3 network improved the detection speed and accuracy significantly, i.e., the detection speed on the computer workstation and the embedded processor can reach 116.96f/s, 7.59f/s, F1 value can reach 9457%, and the mean average precision (mAP) can reach 94.69%.

Abstract:In order to settle the security issue in the process of artificial pine cone picking, a hitting pine cone picking robot was designed, which mainly included motor drive module, control module, vision module, clamping module and picking module. The system performed the pine cone identification and location through the vision module, transmitted the result back to the control module, and then controlled the motor drive module to cooperate with the clamping module and the picking module to complete the pine cone picking. Based on the kinematics model, the diameter of the working space of mechanical arm was calculated by Matlab software to be 4.5m. A collision dynamics model based on Lagrange equation and pulse principle was used to solve the torque required to maintain the original law of motion during the collision. The optimized mechanical safety factor was at least 1.5771 and the total deformation was 4.1484mm by the ANSYS Workbench software. Simulation results showed that the structure can satisfy the design requirements in terms of kinematics, dynamics and statics. The pine cone picking test was 〖JP3〗performed in the laboratory environment, and the size of the constructed prototype was 1000mm×1200mm×1100mm. The experimental results verified the rationality and practicability of the structure design of the robot, and its design and analysis provided guidance and theoretical basis for the development of the pine cone picking robot in the future.

Abstract:In order to extract the centerlines of rice seedlings, a new method based on YOLOv3 target detection algorithm was presented, which can extract centerlines of different growth stages of rice seedlings in complex paddy field so as to provide guide lines for autonomous navigation of robot. Firstly, an industrial camera which was 1 m high above the ground with pitch angles of 45° to 60° was used to capture image of rice seedlings, and then the region of interest (ROI) of the crop image was determined in order to find the instructive guide lines. Because of the perspective projection, the rice seedlings rows were labeled in segments. Then, the ROI images dataset was built to train YOLOv3 model. After that, the best YOLOv3 model was used to detect the rice seedling in the ROI and output bounding boxes. Secondly, the bounding boxes of the same rice seedlings row was clustered. Thirdly, image segmentation was applied and the smallest univalue segment assimilating nucleus (SUSAN) feature points was extracted within the bounding box of the same cluster. Finally, the least square method was applied in the algorithm to extract the centerlines of rice seedling. For complex paddy field environment such as windy weather, dark light, rice seedlings shadow and light reflection on water surface, as well as the impacts like duckweed and cyanobacteria, the proposed algorithm successfully and accurately extracted the centerlines of rice seedlings. For 200 test images, the mean average precision of trained network reached 91.47%, the mean average angle errors of the extracted centerlines was 0.97° and the average runtime of one image (resolution: 640 pixels×480 pixels) was 82.6ms. Compared with another method for centerlines extracting, this algorithm had higher robustness, higher accuracy and faster runtime. The result showed that the method was real time and had application values.

Abstract:The automatic steering system of agricultural machinery equipment includes electric hydraulic automatic steering system and electric steering wheel automatic steering system. However, the electric hydraulic steering system has the disadvantages of high production cost and complex structure, and the electric steering wheel steering system has the problem of small control moment and free travel. In order to solve those problems, an automatic steering mechanism and its electronic control system were designed based on the direct connection between DC motor and full hydraulic steering gear. The automatic steering system mainly consisted of automatic steering actuator, automatic steering controller, hydraulic steering mechanism and wheel angle sensor. Automatic steering actuator and the original car hydraulic steering mechanism was coupled to achieve automatic steering function. In order to improve the accuracy of steering control of the wheels，an automatic steering controller was designed which considered Ackerman angle. An electromagnetic clutch and a steering column torque sensor were installed on the output shaft of the steering drive motor to realize automatic switching between manual driving and automatic driving. The automatic steering system designed was processed and applied to tractor, harvester and plant protection machine, which can meet the needs of use. The test results showed that the average deviation value of wheel response angle was less than 0.1°, the maximum deviation value was 0.158°, the response time of ±20° step signal can reach 1.2s and the overshoot was less than 1%. Moreover, the step response was nonoscillatory, which was faster, accurate and stable than the traditional steering control system. The automatic steering system designed not only met the performance index of automatic steering control, but also reduced the production cost, which provided support for the development of agricultural navigation technology.

Abstract:Seed flow during sowing will affect the quality of sowing, which will seriously affect yield when blockage occurs. In order to realize the fast and accurate detection of the seeding quality of the airflow conveying seeder, an arc array seeding flow sensor based on piezoelectric ceramics was designed. Based on the analysis of the seed movement characteristics of the airflow distributor outlet, the sensing unit layout and the overall structure of the sensor were optimally designed; the seed collision experiments under different conditions were used to determine the structural size and material of the sensing unit; a signal conditioning circuit and a pulse counting circuit were designed to realize the online measurement of seeds and realtime transmission through CAN communication. The effect of airflow pressure and metering quantity on the detection accuracy of the sensor was analyzed using the airflow seeding test bench. In the normal working pressure range, the detection error and air pressure approximately met the linear relationship. Based on this, a calibration model for sensor detection was further proposed and bench verification was performed. The test results showed that the maximum detection error of the sensor was within 5% when the air pressure was 166Pa and the seeding rate was less than 170 seeds/s under the recommended operating parameters, and the accuracy rate of the sensors alarm for blockage failure can reach 100%. The system can effectively monitor the seeding performance of the airflow conveying seeder, which can help to improve the quality of seeding operations.

Abstract:In order to achieve the function of uniformly punching holes in the film for smallgrain crops such as rapeseed, a film hole forming device with a flangetype roller and screwtype conical nail was designed to solve the problems existed in traditional holeforming seeding device like large and complicated structure, adhering soil and seeds, and film damage. The ranges of main structural parameters were determined. The kinematics model of film hole forming device was built. The trajectories of key points of conical nail were analyzed. The punching process on film was determined and the film hole size was analyzed based on the trajectory equation. The fourfactor and threelevel virtual orthogonal experimental study of structural and working parameters of film hole forming device were carried out with the aid of ADAMS. The apex angle of conical nails, the diameter of conical nails, the radius of wheel, and the working speed were used as experimental factors. The film hole length and the distance deviation between two membrane holes were used as experimental evaluation. The simulation experimental results showed that the order of factors affecting the film hole length was the radius of wheel, the apex angle of conical nails, the diameter of conical nails, and the working speed. The order of factors affecting the distance deviation between two membrane holes was the radius of wheel, working speed, apex angle of conical nails, and diameter of conical nails. A better parameter combination was obtained: the apex angle of conical nails was 53°, the diameter of conical nails was 16mm, the radius of wheel was 65mm, and the working speed was 4km/h. The field experiments were carried out with the optimal parameter combination. The results showed that the shape of most of film holes was regular and generally roundlike. The length of film holes was more than 18mm, which was consistent with the simulation results. The coefficient of variation of film hole length in each row was 4.98% and the variation coefficient of uniformity of film hole spacing in each row was 3.44%. The experimental results showed that the combination of experimental parameters was reasonable. The film hole forming device satisfied the design requirements. 

Abstract:The agronomic planting technique of garlic with its bulbil facing upward accords with the growth characteristics and it can achieve a significant effect of increasing yield. The garlic planting machinery on the market is generally difficult to meet the agronomic needs of vertically planting. Based on the achievements in transplanting machinery and using a noncircular gear rotary transplanting mechanism as the coreworking component, a vertically transplanting mechanism for garlic based on agronomic requirements was developed. Firstly, the mathematical model of the transplanting mechanism was established by the D-H transformation method, which was commonly used in robotics. With the analysis of the trajectory and posture of artificially planting garlic, a total number of twelve optimization goals required by the transplanting mechanism were determined. Since the optimization goals had characteristics of fuzzy, nonlinear and strong coupling, the parameterguided heuristic optimization method was used in the optimization process, and the GUI humancomputer interaction optimization software was written under the Matlab software platform. After optimization, a set of design parameters meeting the requirements of the goals were calculated. Referring to the obtained optimizing design data, the contour shape of the noncircular gears were generated in KissSoft software. The topdown design method was used to parametrically design the transplanting mechanism by CATIA software, and simulation verification of the transplanting mechanism was carried out by using ADAMS software. Finally, an experimental bench for the garlic vertically transplanting mechanism was designed, and the multifactor combination experiment was carried out with the transplanting depth, the rotation speed of the mechanism, and the matching speed ratio as the experimental factors. The quadratic regression orthogonal rotation combination design method was used to arrange the experiment, and the regression equation of the influence of each experiment factor on the bulbil angle of garlic after planting was obtained. The results showed that when the transplanting depth was 17mm, the transplanting speed was 29.6r/min, and the matching speed ratio was 100%, the average vertical angle of garlic bulbil would be 8.54°. When the transplanting speed was increased, the verification result was also in the desired range of agronomic requirements. The research results can provide a reference for the development of new garlic planting machinery and other transplanting mechanisms with complicated trajectory.

Abstract:In view of the problems of material blockage, accumulation and the sunflower plate can not enter the header due to the reel rewind in the domestic oil sunflower combine harvesters, according to planting model and agronomic requirements of oil sunflower in China, a special header for oil sunflower combined harvesters with low loss was designed. The analysis was carried out on the posture of the sunflower stalks during the dividing process to determine the width and length of the inner divider and the inner divider gap. Selecting different values of reel speed ratio λ to carry out simulation analysis to the reels motion trajectory in order to determine the range of reel speed ratio and get the optimal diameter and speed of reel. In order to reduce the impact of the dial finger on the sunflower disk during the conveying of the auger, and prevent the sunflower stalk getting entangled on the auger, a scraper conveyor auger was designed. The cutting speed of the reciprocating cutter was determined by the knifetomachine speed ratio γ to ensure a good cutting effect. For evaluating the actual harvest effect of oil sunflower harvester, a field experiment was carried out in Henan Zhuangzi Village, Fukang City, Xinjiang Uygur Autonomous Region. The forward speed of the whole machine was 0.8m/s, the feed rate was 3.3kg/s, and the average loss rate of the header was 1.42%. The operation of the whole machine was stable during the harvesting operation, and there was no accumulation and blockage of the inner and outer dividers, conveying auger feeding smoothly and without entanglement, and there was no return of the oil sunflower plant at the reel, which met the design requirements of the oil sunflower combine harvester header.

Abstract:Aiming at the low degree of mechanization of seed potato cutting, and the existing potato cutting machines have problems such as poor seed cutting uniformity, low seed cutting efficiency and low integration of machinery, a seed potato cutting device was designed, and its key components were analyzed and designed. Through the mechanical analysis, kinematic analysis and energy analysis methods of seed potato cutting process, a mathematical model of seed energy was established, and the impact was determined. The main factors of potato cutting effect were the radius of disc knife, vertical center distance between conveying roller and disc knife, rotation speed of disc knife and rotation speed of clamping roller. Using the cutting efficiency as the evaluation index, the fourfactor fourhorizontal orthogonal test was carried out with the radius of disc knife, vertical center distance between conveying roller and disc knife, rotating speed of disc cutter shaft, and rotating speed of clamping roller shaft as test factors. Analysis of variance and range difference showed that when the radius of the disc knife was 180mm, the vertical center distance between conveying roller and disc knife was 190mm, the rotating speed of disc cutter shaft was 115r/min, and the rotating speed of clamping roller shaft was 56r/min, the seed was cut. The efficiency was 74.5kg/min, the qualified rate of seed cutting was 98.8%, and the results of comparison verification test and optimization test were basically the same, which met the seed potato cutting operation requirements.

Abstract:The damage rate of potato seedlings was high when traditional potato cultivators were used in the early stage of potato emergence. The reason was that the potato seedlings in the early stage of potato emergence were vulnerable to damage. The traditional potato cultivator had a large amount of ridging, so the damage rate of potato seedlings was high during potato tillage. In order to solve this problem, a kind of disc potato cultivator was designed, which can not only adapt to the intertillage of potato at the early stage of seedling emergence, but also it was suitable for middle and late potato tillage. The structure and working principle of the cultivator were described, and the monomer of the ridging disc was analyzed theoretically, and the factors affecting the effect of the tillage operation were obtained. The depth of cultivation, locomotive speed and angle were used as the experimental factors, the rate of weeding and seedling injury were used as the experimental index. The test was taken place on June 1, 2019 at the Acheng Experimental and Demonstration Base of Northeast Agricultural University, and the machine was driven by a tractor. The test results showed that when the tillage depth was 0.13m, the forward speed of the locomotive was 4.6km/h, and the adjustment angle was 52°, the rate of weeding and seedling injury were respectively 95.2% and 3.9%. The test determined the optimal structural parameters of the ridging disk and verified the correctness of the theoretical formula. The experiment was carried out according to the agronomic requirements. Compared with the traditional potato cultivator, the ridging amount of disc potato cultivator had a large regulating range, which improved the applicable period of the machine, and it can achieve better tillage operation effect. The problem of too much ridging amount in the early stage of potato seedling emergence was basically solved by the machine. Compared with the traditional potato cultivator, it was more suitable for potato tillage operation. The research result provided an important theoretical and technical reference for the improvement and optimization of the driventype disc potato cultivator. 

Abstract:Aimed at the problem that the research and development of peanut silage coated silage equipment in China is not perfect, and the joint harvest of peanut fruit seedlings can not be achieved, a fixed straw bale film device was developed on the basis of the 4HB-2A peanut combine harvester. A polyethylene stretched film with width of 25cm and thickness of 25μm was taken as object. By analyzing the elongation rate and overlap rate of the envelope, it was determined that the stretch rate and the overlap rate of the stretched film were 50% when the bale was wrapped. The film guide mechanism was designed according to the requirements of the elongation rate of the stretched film. The torsion angle of the torsion spring τ>68° and the film roll angle θ>108° were obtained through the force analysis of the film guide mechanism. Based on the analysis of the bale specifications, the transverse shrinkage of the stretched film, and the overlap of the envelope, it was determined that the rotation speed ratio of the device rotation and the rotation of the bale was 18. Through the transmission cooperation relationship of the coating device and the design of the bearing drum, the rotation speed ratio of the device rotation and the bale rotation reached the expected value. Based on ADAMS, the lift angle of the pneumatic cylinder of envelope device was simulated, and the lift angle of the device was determined to be 66°. The field performance test results showed that the fixed film device had a stretched film elongation rate of 51.4%, and the film efficiency of the twolayer, fourlayer and sixlayer coatings was 10.5s/layer, 8.4s/layer and 7.6s/layer, respectively. The coefficients of variation of uniformity were 12.20%, 7.70% and 4.70%, respectively. All indicators met the qualified standards, and the quality of coating can meet the requirements of peanut seedlings silage.

Abstract:In order to remit the effect of high temperature damage on tea and fruit trees, a spray cooling fan with lowpower consumption was designed. According to the structure size of arc plate fan blade, the structure of air duct on the spray cooling fan was modeled by Pro/E software. And the dynamic simulation was applied with Fluent software. The diameter of air outlet, length of air inlet and length of air outlet were selected as experimental factors. The total outlet pressure and wind speed were taken as indicators, which were obtained by dynamic simulation. DesignExpert 8.0.6 software was used to optimize the structure of air duct. Then, two types of nozzles with WJ-7010 and WJ-8010 were determined with flow test. With two nozzles, the optimized air duct was carried out to conduct wind speed test and spray cooling performance test. The optimized results showed that the order of significance was outlet diameter, outlet length and inlet length. The optimized combination was outlet diameter of 1070mm, inlet length of 350mm and outlet length of 270mm. Combined with the length of fan section of 220mm, total length of the duct was 840mm. Based on the outlet diameter of 1070mm and total length of 840mm, the outlet air volume, maximum wind speed and effective air supply distance were 701.30m3/min, 16.00m/s and 55m, respectively. The cooling performance test result showed that the average temperature was decreased by 0.68~11.11℃ and the maximum temperature difference range was 1.80~13.90℃ when WJ-8010 nozzle was used. At a high temperature of 38℃, the cooling range of spray cooling fan within a range of 0~20m was close to 5℃. This machine could relieve the high temperature stress problem of tea and fruit trees.

Abstract:Aiming at the problem that large fluctuation range of the screening performance of the pneumatic cylindrical sieve membrane impurity separator, additional migration device and reset the layout and size of cylindrical screen holes to maintain the uniformity of airflow distribution, improve the trafficability of impurities，and improve the screening performance stability of the pneumatic cylinder sieve film impurity separator. Based on the analysis of the movement of the membrane hybrid mixture in the cylindrical sieve, the rotational speed of cylinder sieve, wind speed of inlet pipe, and inclination of airflow were selected as test factors. The impurity rate in the film and the film content in the impurity were used as evaluation indexes. A threefactor and threelevel test was designed in principle to analyze the influence of each factor on the quality of the membrane impurity separation operation. The test results showed that the order of influence on the impurity content in the film was: air inlet pipe speed, rotational speed of cylinder sieve and air flow angle; the order of influence on impurity content in the film was: cylinder screen speed, air inlet pipe speed and air flow angle. The comprehensive effects of various factors on the response index were analyzed by using DesignExpert software surface response diagram, which showed that the optimal rotating speed of cylinder sieve, wind speed of the inlet pipe and the inclination of the airflow were 23.8r/min, 5.9m/s and 2.7°, respectively, the theoretical minimum impurity rate in the film and the film content in the impurity for the optimal design were 10.60% and 0.133%, respectively. Then the secondary test was performed to verify the obtained optimal values. It was found that the impurity rate in the film and the film content in the impurity for the optimal design were 10.54% and 0.132%, respectively. The results indicated that the optimization scheme of the device was feasible.

Abstract:In order to find the optimal contact parameters combination of alfalfa seed discrete element model, a device and method which can simultaneously measure the repose angle and accumulation angle of materials were provided. The difference between measured value and simulated value of repose angle and accumulation angle were used as indicators to calibrate the parameters of the alfalfa seed model. The Plackett-Burman test was used to screen out the contact parameters that had significant impacts on the index. The second order mathematical models between the significant parameters and the index were established by using response surface methodology (RSM). The nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) was used to obtain the optimal contact parameter combination of alfalfa seed discrete element model, that was, the interspecies collision recovery coefficient was 0.47, the interspecies static friction coefficient was 0.24, and the interspecies rolling friction coefficient was 0.08. Finally, the trough wheel seeder was used for experimental verification. The results showed that the average relative error of the measured and simulated values of alfalfa seed mass flow rate under different seeding wheel speeds was 2.89%, therefore the discrete element model and contact parameters of the alfalfa seed can be used in discrete element simulation experiments, and the multiobjective optimization method based on RSM and NSGA-Ⅱ had certain scientificness and feasibility.

Abstract:The problems of decrease in I/O speed and increase in data packet loss rate were caused by the increase of sampling frequency and concurrency of information data under the working condition of the silage harvester. Therefore, the data communication protocol and long string Codec methods of the vehicle terminals and cloud services were studied, the impact of Netty framework and traditional NIO framework on concurrency was analyzed, and three Codec methods such as Java serialization, Protobuf and Marshalling were compared and analyzed. The technical schemes of data collection, data transmission and Web application were put forward separately, and a remote monitoring system for working condition information of silage harvester was designed by use of CAN technology and Netty custom communication protocol. The simulation test showed that the system had a 08 times increase in concurrency, compared with the traditional data acquisition system, under the sending cycle of 500ms. At 200ms, 100ms, and 50ms transmission frequencies, the I/O speed of using Marshalling code was increased by 0.4 times, 3.9 times and 1.5 times compared with Java serialization, respectively. The 15 days of continuous field trials showed that the system run smoothly with good stability and reliability. The statistical analysis of the working condition data from the main components of the silage harvester showed that the data can be reference to the diagnosis of the working condition, and the system basically met the monitoring requirements of main components of silage harvester. The developed system can increase the I/O speed and ensure stable data access volume at high frequency and high concurrency. It had a great significance to promote the informatization and intelligent development of silage harvester mechanical equipment.

Abstract:As important water source of the Middle Route Project of the SouthtoNorth Water Diversion in China, the protection and construction of ecological environment in water supply area is top priority of sustainable development of ecological environment in China. With the implementation of water diversion project, the land use and cover situation in Danjiang River Basin would be inevitably changed. Based on data source of 16 phases of Landsat TM/OLI and HJ-1A CCD image in 2002—2017 in the study area, the land use change map was extracted, the land use/cover change (LUCC) trajectory analysis method of improved stable mapping method was established, and the relationship between similarity, turnover and diversity (STD) index of stable mapping and the number of time phases was derived; the change track was divided into five first level track processes: stable, gradual, discontinuous gradual, cyclic and fluctuating, and further subdivided into two and three level track processes. On this basis, combined with quantitative models such as land use dynamic degree and landscape index, the overall characteristics and spatiotemporal changes of the study area were analyzed. The results showed that: during 2002—2017, the cultivated land in the study area was decreased significantly, the construction land and water area continued to increase, the forest land and grassland were firstly decreased and then increased, and the bare land was relatively stable; the main flow of land use change in the study area was concentrated in the construction land and water area, which was transformed from cultivated land; at the same time, due to the construction of Danjiangkou reservoir area and the implementation of the Middle Route Project of South to North Water Diversion, the water area was increased from 218.60km2 to 400.31km2 in length. Affected by the natural topography, the woodland in the northern mountainous and hilly areas of the study area was well protected, while the woodland, cultivated land and grassland in the transition zone between hills and plains had significantly transformed each other, accounting for 5.85% of the total area of the study area. The results can provide data support and decisionmaking basis for the sustainable utilization of land resources, protection of ecological environment and protection of water sources. 

Abstract:Northern Tianshan of China is an important development base of agricultural and animal husbandry. The spacetime information of net primary productivity (NPP) was accurately obtained based on remote sensing data, the grassland resources of agricultural and pastoral areas can be rationally allocated. It has important and actual significance to the development of northern Tianshan. Due to the influence of weather and the limitation of time and space resolution of satellite sensors, it is difficult to obtain remote sensing data with medium space resolution and high time resolution series. Based on the middle spatial resolution Landsat 8 OLI data and the high time resolution series MODIS data, the middle spatial resolution and high time resolution series remote sensing data were obtained by using STARFM algorithm for spacetime fusion of remote sensing data. Then, the vegetation NPP in the middle section of the northern Tianshan was simulated through the CASA model. The results showed that the relationship coefficient r of the fused NDVI data and Landsat 8 OLI NDVI data was not more than 0.759, the Bias was between 0.0062 and 0.0094 and RMSE was between 0.074 and 0.135 in eight periods in 2016. There were good space detail information of the NPP simulated of the fusion data and CASA model. The R2 of NPP simulation value and field measurement value was 0.8601. The research results can provide method for the collaborative simulation of NPP by multisource remote sensing image fusion technology and light utilization model. 

Abstract:In order to solve the problem that the ability of panicle recognition by each channel or index of digital image color space is not clear, in rice yield estimation based on UAV image, an effective panicle characteristicselecting method was developed. The field experimental data were collected from super rice achievement transformation base of Shenyang Agricultural University in 2017 and 2018, including highresolution digital image collected with UAV and the number of panicles in each sampling square in rice plots. In order to identify the panicle recognition ability of channels or index in the RGB and HSV color space, a triclassification image sample library of rice panicle, leaf and background was firstly constructed, and features extraction was performed by using the best subset selection (BSS) algorithm. The BSS extracted the seven characteristic parameters which were suitable for panicle segmentation of japonica rice in Northeast China, and used as input to panicle segmentation model based on BP neural network. The recognized panicle pixels from segmentation model were clustered by connected component analysis and the number in each sampling square was estimated, which can be compared with field measurement results for quantitively error analyzing. The results showed that the best subset selection based feature extraction performed best when the number of the feature was 7 (features were R,B,H,S,V,GLI and ExG, respectively), and the latitude was 3m. The corresponding minimum MSE of cross validation is 0.0363. The rice panicle segmentation model can effectively achieve the extraction of japonica rice panicle in Northeast China, with the average RMSE and MAPE of rice panicle number extraction in three flight altitude images taken by 3m, 6m and 9m were 9.03 and 10.60%, 11.21 and 14.88%, 13.10 and 17.16%, respectively.

Abstract:Precise prediction of chlorophyll content in different vertical positions of tomato canopy is an important indicator for timely prevention and control of tomato diseases and insect pests, precise fertilization and irrigation. UAV can quickly and efficiently obtain crop canopy spectral information, which facilitates agricultural production. Aiming to predict the soil and plant analysis development (SPAD) values of different vertical positions of tomato canopy by using multispectral remote sensing images of UAV. Firstly, a UAV equipped with a multispectral camera (Sequoia) was used to obtain multispectral images of the tomato blooming and fruit setting stage, fruiting early stage and fruiting late stage. At the same time, SPAD-502Plus chlorophyll meter was used to measure the SPAD values of the upper, middle, lower and the whole canopy of tomato. The SPAD values of the three growth periods of tomato showed that the SPAD values of the upper leaves of tomato canopy were higher than those of the middle and lower leaves in the fruit setting stage, and the SPAD values of the middle leaves of tomato canopy were higher than those of the upper and lower leaves in the fruiting stage. Secondly, RTK was used to record the location of sampling points to establish region of interest (RoI) and extract the reflectivity of each band in RoI. Vegetation index was calculated according to the reflectance data. The correlation and sensitivity between SPAD values and vegetation index of tomato upper, middle, lower and the whole canopy were analyzed. Finally, the best vegetation index was selected and the prediction model of SPAD value was established. The study results were as follows: the correlation degree and linear sensitivity of SPAD values and vegetation index of the upper canopy leaves were better than those of the middle and lower canopy leaves. In the same prediction model, R2 value of the upper and the whole canopy prediction model was higher than that of the middle and the lower canopy, so it was difficult to accurately predict the chlorophyll content of the lower canopy only by using the canopy spectrum. The R2 value of support vector machine (SVR) model in the upper, middle and lower layers of canopy and the whole canopy was higher than that of partial least squares (PLS) and BP neural network model. The research result provided a method basis for UAV to accurately predict tomato canopy chlorophyll.

Abstract:Artificial evaluation of plastic film residue is high labor intensity and low efficiency. A method of combining with color features extraction, impulse coupled neural network segmentation and image morphology algorithm to recognize residual plastic film was proposed in the field by using UAV images. The research area was Pingba County of Anshun City, Guizhou Province, and 1500 images were taken in the research area as experimental data. The UAV was flying at a height of about 40m, and the image data were collected under clear and windfree conditions. These UAV images were conducted geometric correction, 3×3 median filter and histogram equalization processing. Two color space transformation models (RGB, HSV) were compared and analyzed. In order to find out the influence of light intensity on the recognition accuracy, the direct sunlight area and the shadow area of foreground (residual plastic film) and background (soil) were separated to analyze their gray value difference with two color model. It was found that the gray value of shadow area foreground was between the direct sunlight area background and the shadow area background in term of B component while the direct sunlight foreground and shadow area foreground was lower than the background in the term of S component. The manual threshold method, the iterative threshold method, the maximum interclass variance method, the maximum entropy method, the Kmeans clustering method and the impulse coupled neural network were used to segment the residual plastic film from background for both of the B and S components respectively. It was found that the B component was able to recognize sunlight area foreground but not able to recognize shadow area foreground from background. The S component was able to recognize direct sunlight and shadow area foreground from the background. Moreover, the impulse coupled neural network method based on S component had better segmentation effect, and the maximum interclass variance and the iterative threshold method was the second. According to the sunlight direction and different crop growth periods, recognition algorithms for identifying residual film in the field were established. The identification rates were 96.99%, 69.47%, 93.55% and 88.95%, respectively, at sixleaf stage of tobacco growth, after tobacco leaves were harvested, after tobacco rods were pulled out and during the winter idle period. The average overall recognition accuracy of the test area was 87.49%. This method demonstrated fast speed and high recognition accuracy, which can provide a reference for the evaluation and precision collection of residual film. 

Abstract:With the rapid development of Internet of Things and artificial intelligence, the detection and treatment of crop diseases are gradually developing towards intelligence. Using computer vision methods to identify crop diseases accurately and efficiently was of great significance to ensure the normal growth of crops. In order to extract the highlevel semantic features of images and solve the problem of different image sizes of various plant diseases and insect pests, a multilevel extremely efficient spatial pyramid (EESP) model based on deep learning was proposed. Firstly, the image was preprocessed, and then the proposed model was constructed. In order to extract characteristic information of different scales, the cavity ratio was different in each layer. By integrating the information of each layer, different characteristics of various crop pest images were obtained. Finally, crop pests and diseases were identified through image classification method. The data set included 61 pests and disease categories of 10 crops. After 300 epochs training, the experiments showed that the Top1 accuracy of the proposed model reached 88.4%, which was effectively improved by about 3 percentage points compared with that of traditional methods, and it was found that using the threelayer EESP model can obtain the best effect. It had certain practical value and can be applied in actual scenarios.

Abstract:The skeleton extraction of cows is based on the prediction of key points of cows, which can provide important reference for detection of claudication, analysis of estrus behavior, and estimation of motion of cows through point and line reconstruction of skeleton structure of cows. Based on the partial affinity field, taking the video taken by the monitoring camera of the farm as the original data, totally 1600 images were used to train the cow skeleton extraction model, and the prediction of the key point information and partial affinity field information of the cow in the standing and walking states was realized, and the accurate extraction of the cow skeleton structure through the optimal matching connection was realized. In order to verify the performance of the model, totally 100 images of single cow and 100 images of double cows were tested. The experimental results showed that the model had a 78.90% confidence in the attitude of single target walking cows, and a 10.96 percentage points decrease in the confidence of double target walking cows compared with single target walking cows. In order to test the overall accuracy of the model, the accuracy of the model under different key points similarity OKS was calculated, and the accuracy rate was 93.40% when strict standard OKS was 0.75. Furthermore, the experimental results showed that the method can extract the cow skeleton in the video, which had high confidence and low missing rate when there was no occlusion, and the confidence was decreased when there was serious occlusion. For single target and multitarget detection, the frame processing speed of the model was 3.30f/s and 3.20f/s, respectively, and the speed was basically the same, which can lay the foundation for multitarget cow skeleton extraction. The results showed that the model can extract the skeleton information of dairy cattle accurately and could be used for the research of lameness and calculation of motion behaviors.

Abstract:In order to evaluate the change of crop water footprint in Heilongjiang Province in recent years, the water footprint of 11 regions in Heilongjiang Province were calculated from 2008 to 2018 based on water footprint theory, meanwhile its spatial and temporal distributions and its influential factors were analyzed. The results showed that the blue and green crop water footprints varied geographically in an enormous way, the distribution trend was high in south and north regions and low in east and west regions. According to the Spelman’s analysis of correlation coefficient, it could be acknowledged that the eastwest horizontal regions had high population density, which caused small consumption of water resources used for crop irrigation and it rendered low trend in water footprint in the eastwest horizontal regions. The northsouth regions were devoted to agricultural production and it had high consumption of agricultural water and relatively high in blue water footprint. The northsouth regions in Heilongjiang Province had good storage capacity of rainfall, so northsouth regions presented high trend in green water footprint. In eastwest regions, their terrains were flat with less coverage of vegetation, which made it low in green water footprint. According temporal series model to predict the regular pattern of crop water footprint in Heilongjiang Province, the total crop water footprint in Heilongjiang Province in 2021 to 2025 was forecasted as 2050m3/t steadily. The research result would be important in arranging the use of agricultural water resources in recent years. 

Abstract:Based on the daily meteorological data of 28 meteorological stations in Heilongjiang Province from 1966 to 2015 and the observation data of 20 agricultural meteorological stations during the growth period from 1991 to 2008, the effective precipitation, water requirement and water surplus deficit index and their climate trend rate in different growth stages of soybean were calculated. The drought rank and the drought frequency and intensity of each growth stage were determined according to the water surplus deficit index. Then the corresponding distribution map was drawn by using ArcMap spatial analysis, which revealed the water supply and demand and drought situation of soybean in each growth stage in Heilongjiang Province. The results showed that the annual average effective precipitation of soybean in Heilongjiang Province was 253~370mm, the average value was 321mm, in addition to the initial all the other growth stages showed the distribution trend of high in the middle part and low in the east and west, the climatic trend rate of effective rainfall during the growth period of soybean was -6.16~9.09mm/(10a), and the average value was 241mm/(10a), the effective precipitation in the initial stage was on the whole increasing, but in the late season stage was on the whole decreasing. The average annual water demand of soybean was 336~465mm, and the average value was 388mm. In each growth stage, the water demand was low in the middle and high in the east and west areas. The climate trend rate of water requirement during the growth period of soybean was -16.01~2.42mm/(10a), the average value was -5. 17mm/(10a), and the trend of water requirement in each growth stage was generally decreasing. It was increased firstly and then decreased from west to east areas when the average annual surplus deficit index was -44.5%~8.9% and the average value was -15% in the growth period of soybean, and an overall upward trend when the climate trend rate of water surplus deficit index was -1.89~4.92%/(10a). The drought frequency distribution and water requirement spatial distribution of soybean in different growth stages were roughly the same, among which the drought frequency in early growth and rapid growth stage was higher than that in middle growth and late growth stage, and the drought was easy to occur in spring and summer. The research result can provide a theoretical basis and reference for reasonable irrigation and drought prevention of soybean in Heilongjiang Province. 

Abstract:Based on coKriging interpolation, the normalized vegetation index (NDVI), precipitation and river network density were used as covariates, and the groundwater depth of the Wengniute Banner in four phases of 2005—2017 was taken as the main variable. Then the groundwater depth in the study area was calculated. Using the improved hydrological response unit mode, the interpolated groundwater depth was spatially converted into vector data. And the traditional simple interpolation result analysis method was improved by using coKriging and minimum response unit to make it more suitable for actual groundwater convergence, and 551 minimum response units were obtained. Based on this, spatial and local autocorrelation analysis was performed. It can be observed that the depth of groundwater was obviously different spatially. The groundwater level was high in the west and low in the east, which was gradually affected by precipitation and rivers. The average depth of groundwater in time series did not change much, but it gradually showed a tendency of aggregation. 

Abstract:In order to explore the influence of different time scales data source on groundwater depth prediction and increase the accuracy of depth of groundwater prediction in the freezing and thawing irrigation area, the multivariate time series (CAR) model with monthly, quarterly and annual data were studied, and the differences, including different time scale data source and different input variables were analyzed to decrease the effects of groundwater hysteresis and nonlinear in Yongji irrigation field, Hetao Irrigation Area. The results showed that the CAR model with quarterly data source was obviously better than that with monthly and annual CAR model. The determination coefficient (R2), the Nash-Sutcliffe coefficient (Ens) and the rootmeansquare error (RMSE) of the CAR model with quarterly scale data were 0.936, 0.934 and 0.046m, respectively. Compared with the CAR model with monthly scale data, the R2 and Ens were increased by 1130% and 11.86% and RMSE was decreased by 32.35%. Compared with the CAR model which only considered the freezing and thawing temperature, R2 and Ens of the CAR model considering the whole year temperature and CAR model without temperature were decreased by 0.53%, 0.64% and 2.98%, 3.09%, RMSE was increased by 4.55% and 11.36%. The CAR model with quarterly scale data and only the temperature in freezing and thawing period source was the optimal groundwater predictive model in the region, and R2 was 0.941, Ens was 0.940, and RMSE was 0.044m, with high simulation accuracy, which can provide reference for groundwater depth prediction in freezing-thawing irrigation area. 

Abstract:With the decrease of irrigation water in Hetao Irrigation District year by year, the salt input into the irrigation district can not be effectively drained. As a result, the salt can only be redistributed in the irrigation district. Based on field measurement and laboratory experiment, the temporal and spatial variation characteristics of the soil profile，different soil layer and groundwater solute were analyzed by using geostatistics and solute dynamics methods in the cultivated land-wasteland-lake system. The soil salinity was estimated in different periods and the effect of groundwater depth on soil salinity were revealed. The results showed that a large amount of salt in the cultivated land was transported into wasteland with the groundwater during the irrigation period. Before autumn irrigation, the accumulated salinity of the wasteland was two times of that of cultivated land. After autumn irrigation, the desalination amount of wasteland was three times of that of cultivated land. In the whole growth period, the salt in soil of 1m cultivated land still accumulated 56%. The salt was not completely discharged after autumn irrigation, and the desalination rate was 44%. There was slight salt accumulation in deep soil layer. The accumulated salt was 63% in 1m wasteland soil and the desalination rate was 62% after autumn irrigation. The accumulated salt in soil of 1m wasteland was 377705kg/hm2. The salt content of 20~100cm wasteland recharged by groundwater was 17985kg/hm2, accounting for 5% of all the accumulated salt. The salt content of 0~20cm soil was increased by 202395kg/hm2, accounting for 54% of all the accumulated salt. The salt content of the deep soil layer transferred by groundwater from cultivated land to wasteland was 114015kg/hm2, accounting for 30% of the accumulated salt. the salt content from horizontal infiltration of cultivated land to wasteland was 43305kg/hm2, accounting for 11% of the accumulated salt. The spatialtemporal distribution of groundwater and lake salt was strip and patch, which had greatly spatial similarity. Lake became a salt storage area. Measures should be taken to decrease the depth of groundwater by 0.2m. The groundwater depth in the study area should be controlled between 1.7m and 2.3m. The results can provide theoretical basis for water and salt transport in irrigation area.

Abstract:Aiming to realize the reasonable allocation of water resources in irrigation district, the composition of big data resources of irrigation district was analyzed, and the corresponding data mining algorithms were proposed. The cosine correlation coefficient was introduced, and the fuzzy hierarchical cluster analysis was used to realize the case classification and characteristic analysis of department water distribution based on the data of regional water resources, economy, population and industrial water consumption. A variable step length exhaustive method was used to calculate the dynamic weight of relevant parameters of water distribution in irrigation district. Fuzzy distance was used to match the most similar irrigation district. Weighted influence factors and exponential smoothing method were used to estimate the water demand of irrigation area based on casebased reasoning. The proposed methodology demonstrated the effectiveness in the analysis of department water distribution characteristics and water demand prediction of mediumsized irrigation districts in 11 cities and administrative regions of Zhejiang Province in 2018. The results showed that water distribution among different regions in Zhejiang Province was divided into four categories, showing different characteristics of water distribution among different departments; the relative error of water demand prediction in irrigation area was not more than 9.39%. The established theoretical method could provide decision support for making reasonable regional inter industry water distribution scheme and estimating irrigation water requirement.

Abstract:Activation technologies such as magnetization and deelectronation can significantly improve the salt leaching efficiency of irrigation water. In order to clarify the influence mechanism of magnetization intensity on the soil water and salt transport of magnetizationdeelectronic activation water, the effect of magnetization intensity on the soil water and salt transport of magnetizationdeelectronic activation water was studied by a onedimensional vertical soil column infiltration test, which was carried out at different magnetization intensities (0, 0.1T, 0.2T, 0.4T and 0.8T) magnetizationdeelectronic activation water. The results showed that the magnetizationdeelectronic activation water infiltration could improve the soil water infiltration capacity and salt leaching efficiency, and it was closely related to the magnetization intensity, the soil water infiltration capacity and salt leaching efficiency showed a quadratic function relationship which was increased first and then decreased with the increase of magnetization intensity. Meanwhile, the moisture absorption rate S and the magnetization intensity H also showed a good quadratic function relationship. Through the analysis of test data and the infiltration model parameters, it was found that when the magnetization intensity was about 0.4T, the cumulative infiltration corresponding to the magnetizationdeelectronic activation water infiltration was the largest, the infiltration time was the shortest, the soil water content was the largest, the salt content was the smallest, and the desalination effect was the best. Therefore, 0.4T can be used as the optimal magnetization intensity of magnetizationdeelectronic activation water.

Abstract:In order to find out the effects of biochar on saltaffected soil physical-chemical properties and alfalfa growth in the Yellow River Delta, a pot experiment was conducted. Soil nutrients, soil structure, soil salinity, alfalfa yield and quality were analyzed under different biochar application levels (0, 0.5%, 1%, 2%, 5% and 10%). Based on grey correlation method, the biochar application effect was evaluated. The results showed that after biochar additions, soil organic matter and total nitrogen content were increased by 16.27%~246.65% and 6.38%~58.51%, respectively, but the changes of total phosphorus, available phosphorus and total potassium contents were relatively small. Meanwhile, soil bulk density was decreased significantly, while aggregates more than 0.25mm and soil aggregates stability enhanced under lower biochar rate. Compared with CK, biochar addition treatment reduced soil watersoluble salt contents by 38.90%~46.17%, and the contents of Mg2+, Cl-, and SO2-4 had significant reductions. The alfalfa yield was increased by 8.19%~43.00%, however, there was no significant difference in quality. With the increase of biochar application, soil fertility appeared a increasing trend, while aggregate stability showed an opposite character. Soil salt content and alfalfa yield were decreased first and then increased. Overall, biochar application improved the saltaffected soil physical-chemical properties and alfalfa growth. And 0.5% biochar addition rate had the best application effect.

Abstract:The agricultural use of composted sludge is an effective way to solve the problem of sludge recycling. Because sludge is rich in organic matter, agricultural use of sludge will affect the quality of soil carbon pool. In order to clarify the effects of sludge application on carbon components of two kinds of soils with different pH values, the effect of sludgeapplication on soil organic, inorganic carbon components and soil acidity were determined, and the relationship between soil inorganic carbon and organic carbon and soil pH value was explored. Under the wheatmaize rotation mode, two consecutive years 〖JP3〗experiment was carried out, four sludge addition amounts were 3.75t/hm2, 7.5t/hm2, 37.5t/hm2and 75t/hm2, respectively, and one blank control was provided, which were marked as H1, H2, H3, H4 and CK, respectively. The main conclusions were as follows: the organic carbon components content such as soil organic carbon (SOC), readily oxidizable carbon (ROC), dissolved organic carbon (DOC) and humus carbon (HSC) were increased with the increase of sludge addition. Compared with CK, the SOC, ROC, DOC and HSC of acidic sandy soil were increased by 82.39%, 25.62%, 158.33% and 30.77%, respectively, when the sludge addition was 75t/hm2 （P<0.05); the corresponding values were 84.36%, 49.26%, 340.00% and 354.90% in alkaline loam （P<0.05), and there was a very significant positive correlation among the organic carbon components in two kinds of soils （P<0.01). The application of sludge reduced the ROC distribution ratio (except when the amount of sludge was 3.75t/hm2), but increased the distribution ratio of DOC and HSC. However, the proportion of ROC and HSC was decreased, but the proportion of DOC was increased in acidic sandy soil. In addition, the content of soil inorganic carbon (SIC), active inorganic carbon (AIC) and pH value in alkaline loam were reduced due to application of sludge, and the pH value of soil was also reduced; however, AIC and pH value were increased in acidic sandy soil. There was a significant positive correlation between SIC and pH value of two kinds of soils （P<0.01). It can be concluded that application of composted sludge can produce different carbon effects on different acidbase soils. Therefore, sludge can be used in production practice to cultivate fertilizer or regulate the change of carbon pool quality in soil, and the acidification phenomenon of acid soil can be changed by adding composted sludge. 

Abstract:Using metagenome sequencing technology and fixed carbon and nitrogen metabolism in KEGG database as a research tool, taking wheat continuous cropping grain longterm positioning of three methods for fertilizing soil in Shaanxi Weihe Hanyuan as the research object, the influence of microbes in the farmland ecosystem in the region of fixed carbon and nitrogen metabolism pathway of main microbial species and functional genes were analyzed, and the results were as follows: PcoA analysis of metabolic pathways of soil microorganisms at KEGG database Level 3 at three fertilization levels showed that the abundance of functional genes in soil under conventional fertilization was closely related to the balanced fertilization treatment, but it was far from that under low fertilization. Fertilization significantly changed the functional gene abundance of carbon fixation and nitrogen metabolism, and the main functional genes of conventional fertilization and balanced fertilization were larger than that of lowdose fertilization. In the carbon fixation pathway, the abundance of main functional genes in the conventional fertilization was greater than that in the balanced fertilization, and in the nitrogen metabolism pathway, the abundance of the main functional genes in the balanced fertilization was greater than that in the conventional fertilization. Sorangium, Spiribacter, Lentzea, Rhodovibrio, Pseudomonas, Flavihumibacter, Streptomyces, Nitrososphaera, Rubrobacter, Dyadobacter, Novosphingobium, Pedosphaera, Thermogemmatispora were population of soil carbon fixation pathway marker microorganisms in this region. E4212A.fumA.fumB, E2319.atoB, mdh, ACSS.acs, korB.oorB.oforB, pps.ppsA, ppdK, sdhA.frdA, K18594, K18604, E4212 B.fumC, folD, ppc and accA produced significant responses to carbon fixation function genes for fertilization level. Sphingopyxis, Alcanivorax, Nitrosospira, Aeromicrobium, Roseiflexus, Devosia, Altererythrobacter were major species of nitrogen metabolism. nirB, nasA, nasB, nrt.nak.nrtP.nasA and GDH2 were the main functional genes of nitrogen metabolism in this region. Balanced fertilization was more beneficial to fertilizer saving and emission reduction and sustainable use of soil, which was the fertilization level suitable for continuous wheat field in this region.

Abstract:As the sow building environment is a complex, nonlinear and timevarying system, consisting of multiple coupling factors, it is difficult to predict the environment comfort reasonably. Therefore, a prediction model was built to determine the variation trend of environment comfortable degree. The assessment index system was constructed, and the parameter optimization of the least squares support vector regression (LSSVR) with mixed kernels was presented based on mutative scale chaos cuckoo search (MSCCS) algorithm to find optimal parameters γ and σ. The model was exploited to predict the sow house environmental comfort. Three models of particle swarm optimization (PSO-LSSVR), genetic algorithm (GA-LSSVR) and traditional LSSVR were compared with the proposed prediction model. The experimental results showed that MSCCS-LSSVR had a higher accuracy and more reliable performance than the other three models, the mean absolute error (MAE) were 0.0611, 0.0972, 0.1306 and 0.1681, respectively. To facilitate the use of prediction model for farmers, a comfort assessment and prediction system graphical user interface (GUI) based on Matlab was developed. Farmers could download the historical data from a webserver and then exploit them as training and testing data, the assessment and prediction results at different time calculated and displayed on the GUI. A prediction model was exploited in Zhenjiang, Jiangsu Province, China, and it performed well. It can reflect the air quality reasonably and also provide decision support for precise regulation of a swine house environment. It can help farmers decrease the risk of livestock breeding. 

Abstract:In order to further explore the influence of hydrochloric acid pretreatment on the pyrolysis characteristics of biomass, the thermogravimetric method was used to compare and analyze the pyrolysis characteristics of corn straw and poplar before and after pickling under low heating rates (10℃/min, 20℃/min, 30℃/min, 40℃/min and 50℃/min). The kinetic parameters and corresponding thermodynamic parameters of pyrolysis process were calculated by distributed activation energy model (DAEM), and Fourier transform infrared spectrometer (FTIR) was used to analyze the change of chemical structure of biomass before and after pickling. The results showed that the pyrolysis process of biomass experienced four stages：water loss (room temperature~120℃), glass transition (120~210℃), main pyrolysis (210~400℃) and carbonization (400~700℃). Pickling pretreatment increased the maximum weightlessness rate and the final weight loss rate of biomass pyrolysis, and reduced the generation of coke. Under the conversion rate of 20%~70%, it was calculated that the pyrolysis activation energy of corn straw and poplar before and after pickling were 218.27~340.08kJ/mol,  225.17~291.73kJ/mol, 227.35~254.76kJ/mol and 197.39~235.52kJ/mol，respectively. At the same time, the ΔH of corn straw and poplar before and after pickling were 29109~291.28kJ/mol, 249.68~249.82kJ/mol, 228.68~228.86kJ/mol and 221.78~221.93kJ/mol, respectively. The ΔG were 119.23~122.92kJ/mol, 118.57~125.09kJ/mol, 123.78~128.22kJ/mol and 121.97~129.29kJ/mol, respectively. The ΔS were 26654~271.42J/(mol·K), 198.01~206.29J/(mol·K), 156.53~159.14J/(mol·K) and 144.02~153.81J/(mol·K), respectively, indicating that hydrochloric acid pickling pretreatment on the whole reduced the activation energy, enthalpy change and entropy change in the process of biomass pyrolysis, increased the Gibbs free energy (ΔG), promoted the pyrolysis reaction. The infrared spectrogram of the corn straw and poplar were similar before and after pickling, but there was a significant intensity change at the same absorption peak, indicating that the pickling pretreatment had different influence on the organic functional groups of different biomass. The research result can provide theoretical basis for the efficient utilization of biomass and the design of pyrolysis process parameters.

Abstract:Aiming to address the issue of rice supply chains susceptibility to private data leakage in data sharing during the use of block chain technology for traceability，the block chain technologys distributed shared global ledger and nontampering features were utilized, the block chainbased modeling and system implementation of rice supply chain traceability information protection was studied. Firstly, the supply chain traceability privacy data was symmetrically encrypted by using the ciper block chaining (CBC) model before it was uploaded to the block chain network, while the key was encrypted by using elliptic curve cryptography (ECC) and written to the block chain network, the block chain network stored the encrypted ciphertext of the privacy data and authorized the node to view the block chain traceable privacy data using its own private key to achieve the sharing of privacy data in the block chain network. On this basis, the security performance of the method was analyzed and the cipher diffusion of the encryption algorithm reached 0838. Finally, the whole supply chain information traceability system of rice was designed and implemented based on the Hyperledger Fabric platform, and validated and analyzed through specific application cases. The results showed that the nodal authorization method proposed differentiated between nodes for the privacy data that needed to be protected, striking a balance between the need for encryption protection of privacy data and the need for public regulation of supply chain traceability data, the problem of data sharing between multiple nodes of rice supply chain production, processing and circulation was solved, which provided reference for the research on the traceability of rice supply chain.

Abstract:The label texts on food package include some information like production date, nutrition facts and production corporation etc. The information provides important foundation for consumers to buy food. It also can help the food supervision and inspection administrations to discover the potential problems of food safety. Food label detection is the groundwork of food label recognition. It can help to decrease the heavy workload of manual inputting and advance efficiency of data processing. The dataset of food label was constructed firstly, and then a semantic segmentation based distance field model (DFM) was proposed. In DFM two tasks were included: pixel classification and distance field regression. The pixel classification task was used to segment the text from background regions, and the distance field regression task was used to predict the normalized distance from the pixel located in the text region to the boundary of text region. For effectively using the correlation of two tasks, an attention module was added into DFM to optimize the model structure. In addition, the loss function was improved to resolve the loss value of the distance field regression as it was too small to train smoothly. The results of ablation experiment showed that the accuracy of the proposed model was increased by 4.39 percentage points and 3.80 percentage points respectively according to the improvement of attention module and loss function. The comparative experiments of different model methods showed that DFM had good performance in detecting the text of food labels, and the recall rate and precision were 87.61% and 76.50%, respectively.

Abstract:Feicheng peach is prone to spoilage due to its surface color changing rapidly after harvest, which will degrade its quality. Hyperspectral imaging technology was used to detect the soluble solid content (SSC), firmness and maturity of Feicheng peach for improving its quality and price. There were 80 maturity 70% and 90% Feicheng peach were used for hyperspectral images (400~1000nm), SSC and firmness collection, respectively. These samples were split into calibration set and validation set with a ratio of 2∶1 by samples set partitioning based on joint X-Y distances method after the outliers were eliminated by using Monte Carlopartial least squares method. MLR detection models were established using feature wavelengths selected by competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA), respectively. The more effective detection results was emerged by CARS-MLR model, with a determination coefficient of calibration set (R2c) of 0.8191, a determination coefficient of validation set (R2v) of 08439 and a residual prediction deviation (RPD) of 20 for SSC assessment, R2c of 0.9518, R2v of 0.8772 and RPD of 2.1 for firmness assessment. Visualization maps for SSC and firmness were generated by calculating the spectral response of each pixel on peach samples. Furthermore, the artificial neural network model was provided to predict the maturity of Feicheng peach using feature wavelengths selected by the sequential forward selection algorithm, with total recognition accuracy of 98.3%. It can be concluded that hyperspectral imaging technology can be applied to determine the SSC, firmness and maturity of Feicheng peach, laying a foundation for the online nondestructive quality monitoring and timely harvest of Feicheng peach. 

Abstract:The binding degree of soy protein isolate (SPI) to dextrans (D) was changed by increasing the concentration of polyethylene glycol (PEG) by using PEG to bind the SPI and D through Maillard in a crowded liquid system. By increasing the concentration of PEG to change the degree of solute crowding in the solution, the effects of crowding at different degrees on the SPI-D Maillard response were investigated, and the changes in the structure of the SPI-D complexes were studied. Macromolecular crowding effect as a new concept in life science was introduced to the present study. In recent years scientists strongly suggested that much like pH value, ionic strength, or solution composition, the degree of molecular crowding should be considered as an important factor for describing the environmental conditions in a solution. The free amino group content and sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) were used to study the binding of SPI-D complex under different PEG concentrations. The infrared spectrum was used to indicate the hydrophobicity, free sulfhydryl content and turbidity analysis. And structureactivity relationship analysis of different saccharification degrees structural changes and functional properties of the expression of SPI emulsifying properties. The results showed that with the increase of PEG concentration, the degree of complexation of the complexes was increased, the structure of the protein was changed, the structure of αhelix was decreased, the irregular curl was increased, the hydrophobicity was decreased, and the emulsification performance continued to be improved. When the PEG concentration was 0.06g/mL or more, the saccharification growth rate of the SPI-D complex was slowed down. 

Abstract:More and more attention has been paid to the doubleprotein food, which is beneficial to human health by mixing animal and plant proteins. Therefore, it is vital to understand the structure and properties of soybean-whey mixed protein, and its impact on mixed food texture and sensory quality. The effects of ultrasound treatment on the emulsifying activity and structural properties of soybean-whey (SPI-WPI) mixed protein were studied. The effect of ultrasound treated time on the structural and emulsifying property of SPI-WPI was studied by SDS-PAGE, Fourier infrared spectrum, UV absorption spectra and ANS fluorescence probe emission spectra. The results showed that ultrasound treatment had no significant influence on primary structure of SPI-WPI mixed protein. However, it had a significant effect on secondary structure and tertiary structure. The content of αhelix and βsheet were decreased, the content of βturn was increased, and the content of unordered was also increased slightly with the increase of ultrasound treatment. The results of surface hydrophobicity and UVvisible spectrum showed that the conformation of the mixed protein system was changed because of ultrasound, the polypeptide chains were partially expanded, hydrophobic groups were exposed, and the protein structure became more stretched. The turbidity of the treated samples was significantly lower than that of the untreated samples, indicated that the ultrasound treatment produced a cavitation effect that made the protein molecules more dispersed, and the resulting protein had a higher emulsification activity. The emulsification activity and emulsion stability of the mixed protein system were increased first and then decreased, reaching a maximum at 30min. The results showed that the emulsification of SPI-WPI mixed system could be significantly improved by different treated time.

Abstract:Whey protein concentrate and soy protein isolate were used to partially substitute milk protein. The effect of processing patterns and protein compositions on the fat globules destabilization at low temperatures and textural formation of ice creams was studied by pasteurization at 65℃ for 30minutes prior or after homogenization. Their formulations with milk proteins, milkwhey proteins and milksoy proteins were made. Parameters such as fat particle size distribution, protein surface coverage, rheological property of mixes, ice cream overrun, melting rate, hardness, air bubble distribution and sensory property of ice cream were analyzed. The results indicated that the fat destabilization index, rheological property and texture properties of ice cream with milk proteins were not affected by processing patterns. However, for mixed proteins with milkwhey proteins or milksoy proteins ice cream emulsions, two kinds of processing patterns led to the increase in fat particle size, protein surface coverage and consistency index. Pasteurization treatment after homogenization resulted in higher displaced rate of adsorbed protein by sucrose fatty acid ester when compared with pasteurization prior homogenization, which favored the destabilization of fat droplets and texture formation of ice cream. The partial coalescence degree for milkwhey protein and milksoy protein ice cream was 282.19% and 252.70%, respectively. Moreover, ice cream showed high overrun values, and good melting resistance ability and bubble distribution uniformity. 

Abstract:Aiming at the problems of insufficient field test data of tractors and inaccurate realtime evaluation and prediction of unit performance and agronomy, a vehicleborne test terminal covering multiparameters and multiworking conditions was built, and a data platform for tractor operation load was established to obtain field operation load data of key parts of tractors. Based on this platform, the field operation load data of key parts and key parts of tractors were obtained. On this basis, the intelligent algorithm for reliable realtime prediction and evaluation of tractor traction performance was studied, which provided comprehensive basic data and effective prediction algorithm for product development, performance prediction and operation evaluation. Firstly, the operation parameters and structure system of the vehicle test terminal were introduced. Then, the tractor operation load data platform based on the field operation test nationwide was designed and built. Finally, based on the large agricultural data, the BP neural network and genetic algorithm were combined to classify and mine the basic working load of the data platform. The traction performance of tractor rotary tillage was predicted and evaluated. The results showed that the prediction accuracy of the neural network based on genetic algorithm was as high as 96.77%, and the root mean square error (RMSE) was less than 0.01, which showed that the prediction accuracy of the neural network based on genetic algorithm was as high as 96.77%. Neural network algorithm based on genetic algorithm can accurately and reliably evaluate and predict traction performance of tractor rotary tillage operation. 

Abstract:Aiming at the problem of positioning errors caused by terrain tilt, uneven soil hardness, and continuous turning during tractor operation in the field, a multisensor data fusion navigation positioning system based on GA-BP neural network training was designed. The integrated navigation system was mainly composed of RTK-GPS and IMU, and integrated GA-BP Kalman algorithm and error analysis. Based on multisensor navigation parameters, the positioning error of the tractor was corrected to make the tractors trajectory more stable. According to the established navigation and positioning system test platform based on the MK904 tractor, the original navigation and positioning information was obtained at the Luoyang Mengjin Yituo Product Test Base, and the algorithm was verified in Matlab. The test results showed that the accuracy of the roll angle of integrated navigation and positioning system was improved by 0.01rad when the tractor was driving straight; during continuous turning, the accuracy of the roll angle was increased by 0.02rad during the left turn, and the accuracy of the roll angle was increased by 0.04rad during the right turn. According to the error analysis and the digital characteristics of the positioning information, it can be obtained that the GA-BP Kalman algorithm can correct the GPS positioning error caused by field fluctuations, uneven soil hardness, and continuous turning to a certain extent, so that the tractors driving trajectory was more stable. It provided a reference for the followup research of tractor path tracking control. 

Abstract:A novel magnetorheological damper (MRD) integrated with controllable damping, displacement selfinduced and vibration energy harvesting ability was proposed to solve the problems of simple function integration and low efficiency of vibration energy harvesting in conventional MRD systems. The working principle of the proposed MRD was analyzed, especially the principle of vibration energy harvesting device with a single induction coil and a double induction coil, and winding frame with a nonmagnetic and a lowmagnetic material were explained in detail. Then, the vibration energy harvesting device with the single induction coil and double induction coil was simulated by ANSYS software. The prototype of the proposed MRD was manufactured, and the experimental test system was also set up. Afterwards, the energy harvesting performance of the developed MRD with the single induction coil and double induction coil was experimentally tested, respectively. The experimental results showed that the induced voltage with the double induction coil was 2512V and the energy harvest power with the double induction coil was 1.5W under the sinusoidal displacement excitation with 7.5mm amplitude and 4Hz frequency, and the energy harvesting efficiency was about twice of that with the single induction coil. In addition, the energy harvesting efficiency with the nonmagnetic and lowmagnetic winding frame of the proposed MRD was almost the same.

Abstract:In order to improve the safety of robothuman interaction, a new type of intelligent material named electroactive polymer (EAP) was chosen as the sensitive material of the sensor array unit, and a flexible pressure sensor array and its signal acquisition system were designed. The mathematical model of the input and output of the pressure sensor was presented and a method of increasing the force sensory information by using bicubic interpolation method was proposed. Furthermore, a prototype of the sensor based on VHB4910 was fabricated. Finally, the feasibility, accuracy and practicality of the sensor array were validated by calibration experiments and application experiments. The experimental results showed that the difference between the theoretical value and the measured value of the developed sensor capacitance was about 0.01pF, the experimental results agreed well with the theoretical one. The maximum sensitivity was 0.1343pF/N and in the range of 0~6N, and the repeatability index was 28.3%. This tactile sensing display was flexible prone to stretch and had other excellent performance such as simple structure, good flexibility, easy to carry, and abrasion resistance. The tactile display had great application potential in case of safety of robot interaction, which can be used to test the surface contact force when the robot grasped some vulnerable objects such as eggs and strawberries. 

Abstract:Aiming at the demand of intelligent agricultural robots for a wider range of machine vision, a solution of parallel vision table for agricultural robot was introduced. Based on the input and output characteristics of the double rocker mechanism, a new design method of kinematic chain was presented, which can be used to design a decoupled 2DOF parallel mechanism with a fully spherical workspace. Two feasible kinematic chains were derived, i.e. P5R and PRR. Two decoupled 2DOF parallel vision table with a fully spherical workspace were designed based on the above kinematic chains, i.e. RR&P5R and RR&PRR. The displacement relationship of the two mechanisms were established respectively through kinematics analysis. The optimal length ratio of the members of the two mechanisms were obtained respectively through the size optimization. After comparison, the RR&P5R parallel vision table had the better input and output performance. Through statics analysis, the restraining force at each hinge was obtained. Through finite element simulation, the influence of load on the motion accuracy of RR&P5R parallel vision table was analyzed. The result showed that the strength of RR&P5R mechanism met the requirements. However, the displacement deviation of revolute joints of RR&P5R mechanism was large, which was caused by the cumulative elastic deformation of members. 

Abstract:It is difficult to establish the accurate mapping relationship between thermal error and temperature of machine tools. Aimed at the problems of adaptability and robustness of the thermal error model based on the traditional shallow network, a method of thermal error prediction and compensation based on parallel deep learning network was proposed. A deep learning prediction model based on three sub depth belief networks in parallel was established. Each sub depth belief network had the same network structure and different weight parameters. And the restricted Boltzmann machine of the input layer was shared to each sub depth belief network. A construction method of the parallel depth network structure based on prediction error was designed to determine the number of neurons in each RBM hidden layer. A parallel depth network training method based on initial weight sharing was proposed. One of the depth belief networks of the model was pretrained based on the unsupervised learning method with logarithmic divergence. Other depth belief networks shared the initial weight. And the backpropagation algorithm was used to further adjust the optimal weights of each sub depth belief network. The experimental results showed that the root mean square error of thermal error model based on parallel deep learning network was 2.2μm. This method improved the adaptability and robustness of thermal error compensation greatly while improving the accuracy of prediction.

Abstract:For an agricultural robot, camera vision implements the function of detecting ripeness, shape, size of crops and locating the stems precisely in order to harvest with no damage. A common calibration model with adjustable accuracy was needed to achieve higher precision in cooperative works of certain manipulator and CCD cameras. Creatively, a variable order NURBS surface model for camera calibration was presented. Firstly, seven images were acquired by a slide way and a calibration board of A0 size. The data was extracted afterward. Based on the thought of NPBS method, four double NURBS surface calibration models with order of 3, 4, 5 and 6 were setup respectively using data of five images (index:1, 3, 4, 5 and 7). Other two images (index: 2 and 6) were used to evaluate the calibration error. According to the requiring preciseness and the calculating time, the models of order 3 and 4 were chosen to accomplish model switching (higher order models can be chosen according to higher precision requirement). Secondly, camera image plane was subdivided evenly with respect to parameter (u, v). In each subdivision, an arithmetic average deviation of calibration was calculated by using the model with lower order. Then a threshold was determined, and the diagram of model switching was formed. That meant using a higher order NURBS surface model in the higher distortion region, vice versa. Thus, orders of the NURBS surface model can be chosen according to subdivision of the image plane based on preevaluation of the calibration error. In experiments，it was proved that the average calibration error was under 0.89mm. It was accurate enough for our agricultural robot prototype.