Abstract:The protection and utilization of black land in Northeast China had great significance to ensure national food and ecological security. Conservation tillage technology with straw mulching and no/minimum tillage corn seeding as the main technical features was the main technical means for the protection and utilization of black soil in Northeast China. The current no/minimum tillage technology model and supporting equipment of corn seeding in the northeast black soil regions of China were summarized, the seedbed treatment machine used before and during no/minimum tillage seeding of corn were listed, comparative analysis of the working principle and technical characteristics of the seedbed treatment machine under the condition of straw mulching was focused, and the techniques of stubble breaking and furrowing, precise sowing, covering and suppressing of seed in no/minimum tillage seeding of corn were briefly introduced. Based on the overview of main problems existing in the no/minimum tillage corn seeding technical modes and supporting equipment, it was expounded that intensive study should focus on the seedbed treatment, high-speed precision seed metering, intelligent electric drive seed metering, intelligent control of seeding depth, no/minimum tillage ridge seeding and integration of agricultural machinery and agronomy, and it was expected to provide equipment and technical support for the research of no/minimum tillage corn seeding technology and machine in black soil regions of Northeast China.

Abstract:The large amount of surface straws in the no-tillage planting process results in dragging and piling and the ground temperature rises slowly after planting under the conditions of conservation tillage and straw returning to the field in the black soil area of Northeast China. Aiming at the problems, a method that the straw was crushed and deep buried in the strip was proposes, that was, the surface straw was picked up and crushed by the picking and crushing mechanism, the soil and straw screening was completed by the sieve holes at the cover, the stalk collecting spiral performed the directional collection and transportation of the straw, and finally the straw was transported and buried deeply by the straw conveying fan. The key parameters such as the structure, arrangement and speed of the crushing knife were designed, and the straw leakage area of the crushing knife shaft was analyzed. Through theoretical analysis and discrete element single factor simulation experiments, the relationship between the speed of the stalk screw and the torque and the speed of the stalk movement was clarified, and the speed range of the stalk screw was preliminarily determined to be 900~1100r/min and the structural parameters of the ditching shovel was designed. And the discrete element full factor simulation test was used to simulate the relationship between the operating speed and ditching depth and the movement of surface soil particles and the force of the ditching shovel, taking the operating speed, ditching depth and stalk collecting spiral speed as factors, the Box-Behnken test was carried out with the qualified rate of straw buried deep as the test index. The field test results showed that when the device’s forward speed was 3km/h, the trenching depth was 290mm, and the spiral speed was 1000r/min, the straw burial pass rate was 64.2%, and its predicted value was about 67.4% under the similar parameters. The error was less than 5%, which met the design requirements of the device. The method results can provide a scheme and technical support for the promotion of conservation tillage in the black soil area of Northeast China.

Abstract:In the rice planting area of Northeast China, the large amount of rice straw with low moisture content is tough to chop during harvest, and straw decomposed slowly under low accumulated temperature. However, the existing machines and tools still cannot better achieve straw return to the field. The suitable chopping state of straw returned to the field was proposed, which was 5~10cm tearing state. Combined with the shape of the chopped straw and the use of the existing machines and tools, a straw chopping device with two stages of agitation, sliding cutting and tearing was designed and assembled with the combine harvester. The key parameters of crushing process were designed by theoretical analysis. The single factor test showed that when the moisture content of straw was decreased from 69.77% to 29.34%, the chopping qualified rate and broken rate of straw were decreased by 6.44 pencentage points and 955 pencentage points respectively due to the change of dry matter content and bending strength, and the spread width was increased first and then decreased. With the increase of harvest speed, the chopping qualified rate and broken rate of straw was decreased significantly, and the width of straw was reduced by 0.22m. With the increase of shaft speed from 2100 r/min to 2850 r/min,the chopping qualified rate and broken rate of straw were significantly increased, and the width of straw was also greatly increased. The interval of the two-stage fixed knife was enlarged, the chopping qualified rate and broken rate of straw were increased slightly, and the change range of the scattering width was less than 0.11m. Orthogonal test showed that the effect law on chopping qualified rate and broken rate of straw caused by harvesting speed and the rotational speed was almost consistent. The chopping qualified rate and broken rate of straw caused by harvest speed and cutter shaft speed were more significant（P＜0.05). The spread width caused by cutter shaft speed and the interval of the two-stage fixed were more significant（P＜0.05). The design of the device was of great significance and application value to the key technical problems of straw returning in the rice planting area of Northeast China.

Abstract:In the Northeastern China, due to unclear change principles of force and energy consumption during maize straw chopping process, the lower maize straw chopping quality is acquired which is not conducive to the decomposition of chopped straw because of the cold weather. This limits the application and promotion of maize straw retention technology. However, the area of the cropland with obstruction factors, such as poor soil, soil acidification is about 13 million hectares, which seriously affects the food security in China. Therefore, in order to solve above problems, the dynamic supporting type maize straw chopping retention device with different rotation speeds of disc blade was designed, The maize straw chopping retention device mainly included the collecting and chopping device, which was used to collect and transfer the maize straw in the filed surface, and the logarithmic spiral supporting disc device, which was used for dynamic support for the chopping of the maize straw combined with collecting and chopping device. In addition, the logarithmic spiral supporting disc blade was designed based on the slidecutting principle and the angle, thickness and length of the cutting edge and bent angle for the collecting and chopping blade were 20°, 3 mm, 45 mm and 40°, respectively. The rotation radius of the collecting and chopping blade and the logarithmic spiral supporting disc blade all were 250 mm. According to the force status of maize stalk in the chopping process, the chopping process was divided into three stages: collecting stage, transformation stage and chopping stage. In each stage, the force equation of maize straw was established, and it was found that the angular velocity of collecting and chopping blade and logarithmic spiral supporting disc blade and slide-cutting angle of the logarithmic spiral supporting disc blade had the obvious effect. Based on the actual operation conditions and theoretical analysis, the rotation speed of collecting and chopping blade, transmission ratio between collecting and chopping blade and the logarithmic spiral supporting disc blade and slidecutting angle of the logarithmic spiral supporting disc blade were selected as the test factors, and the peak straw breaking force, slide-cutting energy consumption and slidecutting momentum were selected as the test indexes. A Box-Behnken test was executed based on the finite element analysis method because the peak straw breaking force and slide-cutting momentum in actual field experiment was impossible to be measured. The results showed that the primary and secondary factors that affected the peak straw breaking force, slidecutting energy consumption and slidecutting momentum was transmission ratio, slidecutting angle of the logarithmic spiral supporting disc blade and rotational speed of the collecting and chopping blade. When the rotational speed of the collecting and chopping blade. slidecutting angle of the logarithmic spiral supporting disc blade and transmission ratio were 1950 r/min, 40°and 0.5, which was the optimal parameter combination, the peak straw breaking force, slidecutting energy consumption and slidecutting momentum were 101.71N, 1049.42W and 0.032N·s, respectively. The field validation experiment results showed that the slide-cutting energy consumption was 1150.43 W, the error with the model predicted value was 9.63% and the maize straw chopping pass ratio was 93.34%, which satisfied with the national standard. The research can provide references for the design and optimization of the maize straw chopping machine.

Abstract:In order to solve the problem that part of the planter could not normally sow in the area with heavy straw mulching in the cold region of Northeast China, based on the principle of 2BMFJ-DL4 no-tillage precision planter in the primary stubble field, combining with the wide and narrow row planting pattern of 1.1m large ridge rotation of corn and soybean, a kind of frontmounted seed bed preparation device for primary stubble field was designed. The front-mounted seed bed preparation device and the active seeder constituted a no-tillage and seeding over straw compound operation machine, which can complete a number of functions such as seed bed preparation, straw moderate crushing, no-tillage and seeding, straw mulching and returning to the field. Through theoretical analysis and computer simulation, the structure and hydraulic system of the device were designed, and the range of the key parameters of operation was determined. The results of hydraulic system analysis showed that the synchronous performance, speed and torque of the actuator of the hydraulic suspension system and the hydraulic drive system all met the technical requirements. Using Design-Expert 8.0.6 software and three-factor and three-level orthogonal test method, the field experiment of parameter combination optimization was carried out, with the operating speed, the rotation speed of the blade shaft of the seed bed conditioning unit group and the penetration depth of the blade of the seed bed conditioning unit group as the test factors, and the straw clearing rate, the overlaying straw uniformity and the rotating power consumption of the blade shaft of each seed bed conditioning unit group as the evaluation indexes. For straw clearing rate, the order of primary and secondary effects was as follows: operating speed, penetration depth of the blade, and rotation speed of the blade shaft of the seed bed conditioning unit group. For overlaying straw uniformity, the order of primary and secondary effects was as follows: rotation speed of the blade shaft of the seed bed conditioning unit group, operating speed, and penetration depth of the blade. For rotating power consumption of the blade shaft of each seed bed conditioning unit group, the order of primary and secondary effects was as follows: operating speed, penetration depth of the blade, and rotation speed of the blade shaft of the seed bed conditioning unit group. When the parameter combination was the operating speed of 7.2km/h, the blade shaft rotation speed of the seed bed unit group was 600r/min, and the penetration depth of the seed bed gear was 30mm, the straw removal rate was 91.03%, the overlying straw uniformity was 92.61%, and the rotation power of the blade shaft of each seed bed unit group was 7.96kW. The performance met the production agronomic technical requirements. The results provided technical support for improving the utilization rate of seeder and the popularization and application of the mechanization technology mode of no-tillage and straw seeding in the original stubble field in the areas where the total amount of corn straw returned to the field.

Abstract:Northeast black soil region is an important commercial grain production base in China, which plays an important role in ensuring national food security and promoting national economic development. Protecting the security of arable land resources in the black soil region of Northeast China is of great significance to maintaining the bottom line of the strategy of “basically selfsufficiency in grains and security of rations”. However, the blacksoil cultivated land has begun to degenerate significantly, and soil fertility has been declining year by year. In addition, due to long-term over-cultivation, high-intensity output and lack of protective measures, some serious problems, including black soil layer became thinner, organic matter decreased sharply, and plow bottom thickened were observed. All the aforementioned problems seriously affected the sustainable development of agriculture in the black soil area in Northeast China, since the large-scale reclamation of black soil. Therefore, changing the farming system and transforming conventional reclamation into conservation tillage was the key to solve the degradation of cultivated land quality in the black soil areas of Northeast China. A layered deep fertilization device combining ordinary compound fertilizer and slow-release fertilizer application method was proposed according to the demand of no-tillage or less-tillage sowing and fertilization of corn in the black soil region of Northeast China. Moreover, the problems of single type of fertilizer applied and non-obviously effect of existing layered fertilization devices were resolved under layered deep fertilization approach. The structure and working parameters were obtained through theoretical analysis and parameter’s calculation. Main factors affecting the fertilization performance of the layered deep fertilization device were analyzed and determined. The backward and downward tilt angle of the wing shovel, and forward speed of fertilization were selected as the test factors, and the amount of fertilizer deviation stability coefficient in each layer was taken as the test index. A quadratic-regression orthogonal combination simulation test was carried out by the coupling simulation method of discrete element method (DEM) and computational fluid dynamics (CFD). A regression model between test index and influencing factors was established. Through the fitting and optimization analysis of the results, it was obtained when the backward and downward tilt angle of the wing shovel and the speed of fertilization was 58.11°, 52.84°and 3.38km/h, the corresponding fertilization amount deviation stability coefficient of the upper, middle and lower layers was 8.50%, 6.54% and 9.10%, respectively. The layered deep fertilization device was processed with the optimized parameters and verified in field test. The results showed that field experiment had a similar tendency with the simulation test under the optimized parameters, which can meet the fertilization requirements.

Abstract:The method of deep loosening and full-layer fertilization can prepare a sowing belt suitable for seed growth and development. It is a combination of plowing and no-tillage. It takes both “free” and “tillage” into consideration, which is a superior protection. Full-layer deep loosening fertilization is of great significance to improve fertilizer utilization and reduce environmental pollution. To satisfy the crop nutrient requirements of a different growth period with one-time fertilization, and improve fertilizer utilization, a subsoiling full-layer fertilizing shovel suitable for corn planter was designed. The angle between the subsoiling shovel, fertilizing tube, and fertilizing plate was analyzed theoretically and designed, and the theoretical values of key parameters were obtained. The experiment with quadratic regression rotation combination design was designed, which taking uniform variation coefficient of fertilizer as response index, working speed and working depth as influencing factors, and using EDEM to establish a discrete element simulation model of the subsoiling full-layer fertilization shovel, the working process of the subsoiling full-layer fertilization shovel was simulated and the experimental data was obtained through simulation analysis. Design-Expert was used to perform variance analysis and response surface analysis on the experiment data to obtain the optimal working parameter combination, which were as follows: the working speed was 3.81m/s, and the working depth was 25.22cm. Field experiment results showed that under the optimal working parameters of this design, the coefficient of variation of fertilizer uniformity was 41.05%, 24.11%, 20.31% and 14.63%, and the relative error between the experimental value and the theoretical optimization value was 10.89%, 4.06%, 2.37% and 3.10%.

Abstract:Straw coverage rate is one of the most important indicators for conservation tillage evaluation. It is also important to realize online detection of straw coverage rate for black land conservation evaluation. Aiming at the problems of various forms of cropland straws and the difficulty in accurately identifying the broken straws, an online detection algorithm of straw coverage rate was proposed based on the combination of K-means clustering and zoning optimization method with machine vision technology. Firstly, K-means clustering algorithm was used for maize straw image segmentation from the background image. And then the straw image was segmented into 16 areas, using statistical methods to calculate respectively the median of straw and the average number of gray levels, respectively. After 16 area average straw center gray value and soil background gray value were calculated, both were taken as a new classification center. Subsequently the K-means clustering method was used to segment the image of corn straw again. When the gray value of the center of straw did not change, the iteration was stopped. With the calculated number of pixel points of straw, the coverage rate of corn straw was obtained, finally. In April 2021, the proposed algorithm was verified at 100 sampling points in corn fields in Changchun City, Jilin Province. The correlation coefficients between the proposed algorithm and the artificial rope pulling method and the artificial image labeling method were 0.7161 and 0.9068, respectively. The corn straw coverage detection misjudgment rate was 7%. The average error of Otsu thresholding method and classical K-means clustering method was respectively reduced by 45.6% and 29.2%. The experimental results showed that the proposed method could detect the straw coverage rate under different weather conditions and planting patterns, accurately. It can provide a method for online detection of straw coverage.

Abstract:In order to explore the effects of straw mulching and decomposition rate on soil temperature, humidity, and maize yield in northeast black soil region, comparative experiments were conducted between total straw mulching (experimental group) and leave stubble treatment of about 10cm straw mulching (compared group) in Zhaozhou County of Daqing City in 2019 and 2020. The results showed that the decomposition rate of straw of the experimental group was only 4.3% and 4.5% in April, 17.8% and 16.8% in May, 22.3% and 27.8% in June, and the decomposition of straw was mainly concentrated in July to August. The soil temperature and humidity were significantly affected by residual straw on the ground, and the soil moisture content of the experimental group was 1.2 percentage points and 1.1 percentage points lower than that of the compared group in May. However, with the increase of straw decomposition rate, the average soil moisture content of the experimental group was about 3 percentage points higher than that in the compared group from June to September. From May to August, the soil temperature at 0cm was restrained during diurnal warming phase, and the maximum difference between experimental group and compared group respectively was 4.8℃ and 3.8℃ in the same period. The soil temperature at 10cm and 20cm was evidently affected by the straw mulching in May and June, and was not significant from July to September. Compared with the compared group, the effect of soil temperature at 30cm was significantly affected in June, but it was changed little in other months. During the daily cooling period, the soil temperature at different depths in the experimental group was decreased more gently than that in the compared group, and the effect of soil temperature preservation and soil moisture preservation was obvious. The straw mulching affected the crop emergence, the crop emergence of the experimental group affected by straw mulching was 4d and 3d later than that of the experimental group. At jointing stage, the plant height of the compared group was 7.3cm and 7.4cm higher than that of the experimental group, and the stem diameter was 0.2cm and 0.1cm thicker than that of the experimental group, respectively. However, the plant height and stem diameter of the experimental group were higher than those of the compared group at other stage. The maize yield of the experimental group was 10716.0 kg/hm2 in 2019, which was 193.5kg/hm2 higher than that of the compared group. In conclusion, the straw returned by crushing and mulching had a two-way hindrance effect on soil temperature and humidity, and the degree of straw decomposition had a certain impact on the two-way hindrance effect. The effect of straw mulching on heat preservation and soil moisture preservation promoted the growth and yield of corn.

Abstract:Due to the lack of accurate discrete element simulation model parameters in the design optimization process of key agricultural machinery components under conservation tillage in black soil area, the optimization improvement of the machinery and tools is restricted to a certain extent. In order to obtain the accurate discrete element simulation contact parameters of the corn straw-soil mixture in the black soil area, the discrete element simulation model of the corn straw-soil mixture was constructed. The physical test and the EDEM simulation test were combined and the Hertz-Mindlin with JKR contact model was used for discrete simulation contact parameter calibration. Using the Plackett-Burman test in the DesignExpert software, the parameters that had a significant impact on the repose angle were selected as follows: soil-soil rolling friction coefficient, soil-steel static friction coefficient, straw-soil rolling friction coefficient, soil JKR surface energy; and the optimal value range of the four parameters were further determined through the steepest climbing test. According to the Box-Behnken test principle, the repose angle was used as the response value to establish a quadratic regression model between the repose angle and the significant parameters; the actual repose angle was used as the target, and the software was used to optimize. The function optimized the significant parameters and the optimal parameter combination was obtained as follows: straw-soil rolling friction coefficient was 0.16, soil-soil rolling friction coefficient was 0.24, soil-steel static friction coefficient was 0.75, and soil JKR surface energy was 0.67J/m2. The optimal parameter combination was compared and verified through simulation experiments, and the relative error between the simulated repose angle and the physical test repose angle was 1.64%. The research results showed that the calibrated parameters were true and reliable, which can provide a theoretical reference for the discrete element simulation of the corn straw-soil mixture in the black soil area.

Abstract:In order to achieve a rapid, convenient and accurate measurement of the soil organic matter (SOM) content, a multi-sensor array based on artificial olfactory technology was designed to detect SOM content. Totally ten different types of oxide semiconductor gas sensors were selected to form the sensor array, and different concentrations of hydrogen sulfide, ammonia and methane standard gases were used to test the response of the sensor array. It can be seen from the response curve that the sensor array responded to different concentrations and types of standard gases, and the response results were not the same. With the increase of the standard gas concentration, the response curve of the sensor array was also increased. The test results showed that the sensor array had high specificity and certain cross-sensitivity. And from the soil gas response curve of each sensor, six features (response area value, maximum value, average differential coefficient, variance, average value and maximum gradient) were extracted to construct an artificial olfactory feature space (AOFS). Then, partial least square regression (PLSR), back propagation neural network (BPNN) and support vector machine regression (SVR) algorithms were used to establish the prediction model of AOFS and SOM content, and the coefficient of determination (R2), root mean square error (RMSE) and absolute average error (MAE) were used to evaluate the performance of the prediction model. The test results showed that the R2 of the PLSR, BPNN, and SVR test sets were 0.80878, 0.87179 and 0.91957, the RMSE were 3.6784g/kg, 3.1614g/kg and 2.4254g/kg, and the MAE were 3.1079g/kg, 2.4154g/kg and 2.1389g/kg, respectively. The model established by the SVR algorithm had the highest R2, the smallest RMSE and MAE. It had higher predictive performance than PLSR and BPNN, and can be used for the measurement of SOM content.

Abstract:Aiming to achieve the development of mechanized and intelligent citrus picking, an underactuated end-effector for citrus picking robot was proposed. Through the fusion control strategy of grip and deflection, the end-effector was able to achieve the stable picking of citrus with different sizes and ovality. According to the needs of picking citrus of different sizes and the analysis of human hands movement patterns, a double-link parallel finger was designed. The double-link parallel finger included two sets of four-link mechanism, which were designed for underactuated finger to enable the end-effector to adapt to different citrus sizes. On the basis of statics analysis, the motors were determined. Besides, a rotatory joint was added to the finger root to fit closely with the citrus. This design can not only protect the orange skin from being scratched by finger edges, but also can increase the contact area and thus increase the friction. In order to ensure the finger rotating correctly, the motor drive control system model was established according to the selected motor characteristics. Laying the establishment of this system model, the servo control strategy based on current feedback was proposed. Finally, the finger movement simulation and the citrus picking experiment using the end-effector were performed. Simulation results showed that the structure can satisfy the design requirements of realizing citrus picking of different sizes and ovality in terms of kinematics. A prototype of the picking end-effector was made and citrus picking experiments were carried out in the experimental environment. The experimental results showed that when the end-effector pinked citrus with diameter ranging from 30mm to 100mm, the average success rate was 98.3% and the average time was 5.3s. It had the advantages of strong adaptability, stable grip, and no damage of the fruit.

Abstract:Aiming at the problems of slow motion planning, low efficiency, and high path cost of multi-degree of freedom picking manipulators. The Cauchy target gravitational bidirectional RRT*(CTB-RRT*) algorithm was proposed. Heuristic sampling was carried out by Cauchy distribution method to reduce the blindness of sampling. Through introducing target gravity, the step length of the random growth direction and the target direction were dynamically adjusted to improve the local search speed. What’s more, a node rejection strategy was introduced to eliminate unnecessary sampling nodes and improve calculation efficiency. Through two-dimensional and three-dimensional algorithm simulation experiments, the 6-DOF manipulator's obstacle avoidance picking simulation experiment verified the effectiveness of the proposed algorithm. The results of research and simulation experiments showed that the path cost of the improved algorithm was reduced by 5.5%, the search time was reduced by 71.8%, and the number of sampling nodes was reduced by 64.2%, comparing with the RRT*-connect algorithm. To verify the feasibility of the algorithm, the 6-DOF manipulator was controlled to perform obstacle avoidance picking movement in the robot operating system (ROS). The success rate of motion was 99%, and the running time was 0.33s. Comparing with the RRT*-connect algorithm, the path cost was reduced by 12.6%, and the running time was reduced by 69.2%. The number of expansion nodes was reduced by 76.3%.

Abstract:The following problems exist in the cooperative navigation control system of traditional large-scale lateral moving sprinkler irrigation machine, such as easy deviation from the navigation path, poor inter-span walking coordination, and low sprinkler irrigation uniformity. In order to solve the above problems, a distributed cascade cooperative navigation control method was proposed. Based on the establishment of the multi-tower kinematic model of the large-scale sprinkler irrigation machine, combined with the state feedback and PID control, the path navigation control algorithm was designed with the main tower as the master and the cascaded synchronous following control algorithm with the node-tower as the slave. And a collaborative navigation control system was designed and developed based on this method. The real-time attitude of each tower car was obtained through the dual-antenna RTK positioning module, and the control of the movement attitude of each tower car was realized through frequency control technology. Based on the above control methods, a cooperative navigation control system was designed and it was deployed on the developed sprinkler irrigation machine. The navigation control system was installed on the sprinkler irrigation machine, and the sprinkler irrigation machine was modified. A coordinated navigation control test was carried out in Xuchang, Henan. The test results showed that at different navigation speeds, the maximum lateral deviation of the main tower vehicle was within ±3.26cm, and the maximum heading deviation was within ±1.65; the maximum synchronization deviation of the sub-tower vehicle was within ±13.07cm, which met the requirements of autonomous field operations.

Abstract:Dynamic weighing method is an ideal method for dynamic detection of application rate of fertilization and seeding, because the application is not limited by the measurement object and can directly obtain dynamic information. But it is difficult to be applied in practice because of its easily being interfered by environmental vibration. An application rate measuring device, where the supporting force from high-pressure nitrogen springs and the pulling force from S-type weighting sensors was combined for detection, was adopted in this research. A functional application rate detection method was proposed based on the complementary characteristics of the measuring device with opposite direction and proportional amplitude between the pressure and tension. In this method, a function with application rate function as a variable was constructed, and the target application rate function was finally determined by calculating the extreme value of the function. Eighteen groups of experiments, with a wheat seedfertilizer drill machine on a slight potholes cement road, were carried out at different target application rates (225kg/hm2, 300kg/hm2 and 375kg/hm2) and at different vehicle speeds (3km/h, 5km/h and 3~7km/h). And the dynamic and cumulative application rate were measured with the functional detection method. The maximum, average and standard deviation of the absolute relative error of cumulative application rate were 5.61%, 2.26% and 1.58%, respectively. After exceeding 0.033 hm2 of operation area, the maximum absolute relative deviation of the dynamic application rate was 9.61% in all tests, and the maximum average absolute relative deviation and maximum standard deviation were 4.73% and 1.97% in one test. The experimental results showed that the functional detection method can effectively obtain the dynamic and cumulative information of application rate, but the construction method of the function needed further research.

Abstract:针对秸秆纤维基地膜覆膜播种时膜孔尺寸大、形状不规则、播种质量差等问题，设计了一种侧开式滑切破膜精量播种单体，通过对其作业过程的理论分析确定了破膜成穴器、强开凸轮和播种单体的结构和作业参数，建立了膜孔长度数学模型，明晰了相关因素与膜孔尺寸互作规律，确定了影响装置工作性能的主要参数及其取值范围。采用四因素五水平二次回归正交旋转中心组合试验方法，以作业速度、压膜弹簧刚度、破膜刀楔角、破膜刀开启相位角为试验因素，膜孔长度合格率、粒距合格指数、播种深度合格率为评价指标实施田间试验，应用Design-Expert 8.0.6.1软件进行试验数据处理，结果表明：各因素对膜孔长度合格率影响由大到小依次为破膜刀楔角、作业速度、破膜刀开启相位角、压膜弹簧刚度；各因素对粒距合格指数影响由大到小依次为作业速度、破膜刀开启相位角、破膜刀楔角、压膜弹簧刚度；各因素对播种深度合格率影响由大到小依次为作业速度、破膜刀开启相位角、破膜刀楔角、压膜弹簧刚度。当作业速度为1.6～3.4km/h，压膜弹簧刚度为2N/mm，破膜刀楔角为30°，破膜刀开启相位角为-2.4°～1.8°时，膜孔长度合格率大于90%，粒距合格指数大于90%，播种深度合格率大于85%。

Abstract:Aiming at the problems of low utilization rate of garlic sowing mechanization and inconvenient adjustment of sowing depth, an electro-hydraulic mixed garlic planter was designed. The system was mainly composed of electronically controlled seeding device, sowing depth adjustment device, parameter detection device and human-computer interaction interface. The single chip microcomputer was used as the core controller, and the speed sensor and rotary encoder were used to realize the match of plant distance and operating speed. The relationship of trench resistance and depth was analyzed to determine the key components of the hydraulic device for depth adjustment. Combined with the use of photoelectric sensors and display screen, the real-time display of operating parameters and alarm function for abnormal seeding were completed. Taking the hybrid garlic as the experiment object, the sowing depth consistency experiment, sowing quantity detection experiment and sowing quality experiment were conducted respectively. The results showed that the average error of sowing depth adjustment was 4.7%, and the coefficient of variation of sowing depth was 5.3%. The qualified rate of sowing was 83.7%, and the missed sowing rate was 6.2%, which met the agronomic requirements of garlic sowing. The average error of sowing rate detection was 4.0%, and compared with the same kind of conditions, the missed sowing rate of garlic planter with gasoline engine as the power source was reduced by 3.1 percentage points. The research results can provide a certain reference for the mechanization and automation of garlic sowing.

Abstract:针对现有油菜联合收获机收获作业时油菜籽粒细小不易分离导致收获后籽粒含杂率高、人工复清劳动强度大、缺乏晾晒前机械化复清装备的生产实际问题，设计了一种适于油菜联合收获机作业后含杂油菜籽的复清机。通过运动学和动力学分析确定了螺旋输送装置、离心振动式筛分装置和侧向风选装置的结构及其运行参数，解析了离心振动式筛分装置离心过程和振动过程，基于CFD分析了清选罩壳内部气流场状态。以振动频率、垂直振幅和离心风机出风口风速为影响因素，以油菜联合收获后含杂油菜籽复清机籽粒含杂率和筛分效率为评价指标，开展了单因素试验与正交试验，确定了较优运行参数组合。单因素试验结果表明：振动频率在12.08~14.61Hz，垂直振幅在3.59~3.64mm，离心风机出风口风速在5~7m/s范围内时，清选性能较优；正交试验结果表明：影响含杂率因素主次为离心风机出风口风速、振动频率、垂直振幅，影响筛分效率因素主次为振动频率、垂直振幅、离心风机出风口风速，确定较优参数组合：振动频率为14.61Hz、垂直振幅为3.61mm、离心风机出风口风速为7m/s，在此参数组合下，油菜联合收获后含杂油菜籽复清机的籽粒含杂率平均值为0.53%，筛分效率平均值为98.39%，符合油菜籽粒后续存储标准（含杂率小于3%）。

Abstract:In order to improve the working efficiency of mobile straw granulator and solve the problem of mismatch between operating speed and feeding quantity in the process of corn straw harvesting, an automatic monitoring system for operating speed was designed to realize automatic monitoring and control of operating speed of the mobile straw granulator. The system was composed of a fuzzy controller with adaptive variable universe of feeding quantity and a hydraulic motor speed control system. The operating speed of the straw granulator was controlled by the hydraulic system. The actual feeding quantity was obtained by the power of the screw conveyor, and the prediction model of the feeding quantity was established according to the grey theory, with the prediction value as the input of the variable universe fuzzy controller. The output of the variable universe controller was the input of the hydraulic motor speed regulation system. The operating speed PID controller drived the hydraulic control system to adjust the running mechanism of the pellet machine to change the running speed, so as to match the running speed and the feed quantity to achieve the optimum feed quantity and achieve the purpose of advance adjustment. Three tests were designed, which were used to obtain the model parameters, the stability test under the condition of uniform straw, and the tracking performance test under the condition of non-uniform straw. The experimental results showed that under the condition of uniform straw, the operating speed can reach the best operating speed within 3m and the overshoot less than 5%, and then kept a good stable running state, so that the granulator can work with the best feeding quantity. Under the condition of non-uniform straw, the operating speed can track the change of the feeding quantity with an overshoot not more than 5%. The tests showed that the system can detect and match the operating speed and feeding quantity in real time, and can effectively improve the working efficiency of the mobile straw granulator.

Abstract:Aiming to obtain the optimal molding parameters of the straw multi-stage roll forming machine when compressing corn stalks with lower moisture content, and explore the influence of molding parameters on molding results, based on the Design-Expert Box-Behnken Design (BBD) experimental design method and principle. Taking the moisture content, crushing length and the final roller speed of the forming machine as experimental factors, and the rebound rate, density and the molding energy consumption as the test indicators, using the three-factor and three-level response surface analysis method, the mathematical models between each factor and the rebound rate, density and the molding energy consumption were established respectively. The influence of the significant interaction of various factors on the test indicators was analyzed. The results showed that when the forming machine compressed corn stalks, the contribution rate of each test factor to the rebound rate from large to small was: the final roller speed, the crushing length, and the moisture content; the contribution rate of each test factor to the density from large to small was: the crushing length, the final roller speed, and the moisture content; the contribution rate of each test factor to the molding energy consumption from large to small was: the final roller speed, the crushing length, and the moisture content. When the final roller speed was 1.07r/min, the moisture content was 21.5%~25.0%, and the crushing length was 64~108mm, the rebound rate was less than 7.0%, the density was greater than 350kg/m3, and the molding energy consumption was less than 16.0kW·h/t; the optimal molding parameters obtained by parameter optimization were: the moisture content was 24.26%, the crushing length was 73.25mm, the final roller speed was 1.07r/min, at this time, the rebound rate was 6.32%, and the density was 375.6kg/m3, the molding energy consumption was 15.89kW·h/t. This research can provide a theoretical basis and technical support for multi-stage continuous cold roll forming of straw.

Abstract:Aiming at the problem of reducing damage rate of flower bud in mechanical picking of Camellia fruit,a layered harvesting device for Camellia fruit was designed.The principle of interaction between layered picking device and fruit branch was analyzed. The model between layered mechanism and fruit branch, layered picking mechanism and fruit branch was established, and the stress between the layered mechanism and fruit branch, layered picking mechanism and fruit branch was simulated by means of ANSYS Workbench. The results showed that the bending degree of fruit branch was increased with the increasing distance of layered rubber roller, and the normal stress and shear stress of fruit branch cross section were increased, the normal stress and shear stress of fruit branch cross section were increased with the decreasing gap of picking rubber roller clearance.The feasibility of layer picking was verified by experiments.Taking the layer thickness,layer depth,rubber roller clearance and rubber roller speed as the influencing factors,and the leakage rate of Camellia fruit and the damage rate of flower bud as the evaluation indexes,the experiment was carried out with Ganwu No.1 Camellia fruit.The results showed that the successive factors affecting the leakage rate of Camellia fruit were rubber roller gap,layer depth,layer thickness and rubber roller speed,the successive factors affecting the flower bud damage rate were layer thickness,layer depth,rubber roller speed and rubber roller gap.The best combination of parameters for Camellia of Ganwu No.1 were obtained by comprehensive scoring method when the layer thickness was 360mm, and the layer depth was 290mm,the rubber roller gap was 18mm, and the rubber roller speed was 65r/min.Under this work condition,the leakage rate of Camellia fruit was 13.33%, and the damage rate of flower bud was 6.33%.Compared with the picking device without layered mechanism,the average damage rate of flower bud of layered picking device was reduced by 6.22 percentage points.

Abstract:Sweet potato seedling recycling machine can realize sweet potato seedling recycling for feeding, avoid the waste of resources. Throwing device is an important component of sweet potato seedling recycling machine. However, throwing sweet potato seedlings has high power consumption. The dynamic analysis of sweet potato seedling in the throwing device shows that the fan blade backward tilt is more conducive to throwing than forward tilt. The power consumption analysis of the throwing device shows that when the structural parameters of the fan are fixed, the specific power consumption is high as the speed is increased. The gas-solid coupling method was applied to simulate the conveying process of the throwing device. It was found that as the speed increased, the average flow velocity in the recovery machine was gradually increased. The blade number and blade inclination had a great influence on the performance of the throwing device. Then the fan speed, blade number and blade inclination angle were taken as the experiment factors, and the specific power consumption, recovery rate and throwing speed were taken as the experiment indexes, the center combination experiment with three factors and three levels was carried out．The results showed that the influence of factors on the specific power consumption from large to small were fan speed, blade inclination, blade number; the influence of factors on the recovery from large to small were fan speed, blade number and blade inclination; the influence of factors on the throwing speed from large to small were fan speed, blade number and blade inclination; when fan speed was 880r/min, blade number was 3 and blade inclination angle was 7°, the specific power consumption of throwing device was 718m2/s2, and sweet potato seedling recovery rate was 92.79%, the throwing speed was 5.96m/s. Comparative experiments showed that after the optimization and improvement of the throwing device, the specific power consumption was reduced by 15.83%, the recovery rate of sweet potato seedlings was increased by 1.75% and the throwing speed was increased by 5.49%.

Abstract:Aiming at solving the problems, such as inadaptation to baled straw, insufficient loading capacity, and easily blocked soil covering device, that happened in the first generation orchard straw mulching machine, a self-unbaling orchard straw mulching machine was developed. The machine consisted of tracked chassis, unbaling-spreading device, bin and soil covering device, etc. The unbalingspreading device was a toothed belt structure and installed at the rear of the bin. To adapt to a variety of straw bales and improve bale breaking ability and mulch uniformity, after analyzing the process of unbaling and spreading, the key parameters such as inclination angle, height and rotating speed of the device were determined. To reduce drag during rope cutting and bale breaking, a triangular knife-tooth was designed, and the distribution of the knife-teeth was planned based on the analysis of straw compression and disturbance area. A double-sided opposite-throwing soil covering device was designed to cover soil on the surface of straw layer synchronously. The test results showed that the straw loading capacity was increased to 3.1 times of the original machine. When the speed of the straw mulching machine was 0.8~1.4 km/h and the rotating speed of the unbaling-spreading device was 180~240 r/min, the thickness of the straw mulching layer was 5.1~18.1 cm with standard deviation not more than 3.4cm, and the thickness of the soil covering layer was 2.3~4.0 cm with no interruption happened during soil-covering, meeting the requirements for straw mulching in orchard. The established straw mulch thickness model, with a determination coefficient of 0.9672, can be used to guide the parameters adjustment in actual production. The machine realized the operation integration of straw unbaling, inter-row mulching and thin soil covering, which laid foundation for improvement of orchard straw mulching mechanization technology and equipment performance.

Abstract:Taking Mengjin County of Henan Province along Yellow River as an example, the morphological characteristics of “non-grain” cultivated land in Mengjin County were systematically identified from the aspects of utilization status and slope distribution, landscape pattern and spatial proximity, cultivation distance and road access, economic gradient and ecological security. The results showed that there was a high overlap between the “non-grain” space and the high-quality agricultural production space, the tendency of non-food utilization of cultivated land was obvious, and the proportion of the adjustment from cultivated land to forest land was too large. Due to the large difference in labor productivity between grain cultivated land and “non-grain” cultivated land, the scale of cultivated land for economic crops is relatively small and scattered, which can not form economies of scale. High-speed transportation shortens farmers-travel time for farming, and the impact of farming distance on the “non-grain” of cultivated land is decreasing. There are a large number of recoverable land near traffic trunk lines, which is closely related to the construction of “corridor landscape project” in recent years. Economic abandoned land accounts for a large proportion in economic gradient areas and farmers in underdeveloped areas have a relatively high degree of dependence on cultivated land. The ecological red line is the rigid bottom line for maintaining regional ecological security. Within the red line, the “rewilding” project should be actively implemented. Combined with the national ecological strategy of the Yellow River, and aiming at building the compound ecological corridor of the Yellow River, the restoration and adjustment schemes of different “non-grain” cultivated land in different locations and types were put forward. The research results can provide reference for the decision-making of land control work in the new period.

Abstract:In order to further study growth trend and yield changes of winter wheat at different time scales, remotely sensed vegetation temperature condition index (VTCI) and leaf area index (LAI) which are closely related to crop water stress and crop growth were selected as two key variables for indicating crop growth condition and estimating crop yields in the Guanzhong Plain, China. Taking Morlet wavelet as a function, wavelet transform and cross wavelet transform were used to analyze the main oscillation period and resonance cycle between VTCI, LAI and time series yield at different time scales. The weights of VTCI and LAI at each growth stage were determined by calculating the wavelet cross-correlation degree, which were used to construct the single-parameter and double-parameter yield estimation models, respectively. The results showed that VTCI, LAI and yield had different main oscillation periods and resonance cycles. The normalized root mean square errors (NRMSE) of the weighted VTCI and weighted LAI yield estimation models constructed by the wavelet transform were 16.88% and 13.58%, respectively, the values of the coefficient of determination (R2) were 0.259 and 0.520, respectively, and the NRMSE and R2 of the double-parameter estimation model were 13.52% and 0.531, respectively. These results indicated that the yield estimation model based on double-parameters had higher accuracy. For the cross wavelet transform, NRMSEs based on weighted VTCI and weighted LAI yield estimation model were 16.83% and 13.56%, R2 were 0.263 and 0.522, respectively. NRMSE based on double-parameter estimation model was 13.40% and R2 was 0.533. Therefore, it can be concluded that the estimation models based on the cross wavelet transform had higher accuracy than those based on the wavelet transform. The double-parameter yield estimation model constructed by resonance cycles was used to estimate the yields in the Guanzhong Plain from 2011 to 2018, and the results showed that the yield was high in the west and low in the east.

Abstract:Affected by the global warming, the frequency and intensity of drought events have shown a significant increase in recent years, which has seriously affected crop yields. Therefore, selecting appropriate monitoring indicators and constructing accurate yield estimation models are of great significance to ensure the country’s food security. The Guanzhong Plain in Shaanxi Province was chosen as the study area, and remotely sensed vegetation temperature condition index (VTCI) and leaf area index (LAI) which are closely related to crop growth were selected as the growth monitoring indicators. The principal component analysis (PCA) combined with Copula function were used to construct univariate (VTCI or LAI) and bivariate (VTCI and LAI) winter wheat yield estimation models at the county scale. The results showed that the liner regression model of comprehensive values of LAI and winter wheat yield constructed based on PCA-Copula had the highest accuracy (R2=0.567, P<0.001). However, when the liner regression model of comprehensive values of VTCI and LAI and winter wheat yield (R2=0.524, P<0.001) was used to estimate the yield of winter wheat in each county (district) in the study area from 2012 to 2017, the distribution of the error between the estimated yield and the actual yield was more concentrated, and the maximum error value was also smaller, which was more reliable than the results of the winter wheat yield estimation model based on a single variable. These results indicated that the bivariate yield estimation model constructed by PCA-Copula was more suitable for largescale winter wheat yield estimation.

Abstract:Aiming at the problem that traditional crop disease recognition methods rely on manual extraction of features, the steps are complex and inefficient, and it is difficult to recognize in the field environment, a crop disease recognition model combining multi-scale convolution structure and attention mechanism was proposed. This research improved on the basis of residual network (ResNet18), introduced the Inception module, and its multi-scale convolution kernel structure was used to extract disease features at different scales, and the richness of features was improved. On the basis of the residual structure, the attention mechanism squeeze-and-excitation networks (SE-Net) was added to enhance the weight of useful features, weaken the influence of useless features such as noise, and further improve the feature extraction ability and enhance the robustness of the model. The experimental results showed that the improved multi-scale attention residual network model (Multi-Scale-SE-ResNet18) had an average recognition accuracy of 95.62% on the eight crop disease data sets collected in a complex field environment, compared with the original accuracy of the ResNet18 model, it was increased by 10.92 percentage points. The model size was only 44.2MB. The improved Multi-Scale-SE-ResNet18 had better feature extraction capabilities, and it can extract more disease feature information, and better balance the recognition accuracy of the model with the model complexity, which can be used for crop diseases identification in the field environment.

Abstract:In order to accurately predict the nitrogen content in different scales of apple leaves at flowering, young fruit and fruit expansion periods, a combined color characteristics based prediction model of apple leaf nitrogen content was proposed. Firstly, the image of apple leaves was obtained and 17 color features, including R,G,B monochromatic components and 14 color combination parameters were extracted, and the key influencing factors of nitrogen content of apple leaves in different periods were extracted by principal component analysis to eliminate the correlation between the original variables and reduce the input vector dimension of the model. Secondly, the PCA-SVM, PCA-BP and PCA-ELM prediction models were established in different periods, the prediction effect and accuracy of apple leaf nitrogen content were compared, and the best prediction model in different periods was obtained. Finally, the best prediction model was used to predict the nitrogen content of apple leaves in different periods, and the parameters of the best prediction model were optimized by adaptive genetic algorithm. The results showed that the prediction accuracy of PCA-SVM model was higher than that of PCA-BP and PCA-ELM model in different growth periods; the mean absolute error of PCA-SVM prediction model in flowering period, young fruit period and fruit expansion period was 0.640 g/kg, 0.558 g/kg and 0.544 g/kg, and mean absolute percentage error was 0.057 g/kg, 0.050 g/kg and 0.064 g/kg, and root mean square error was 0.800g/kg, 0.747 g/kg and 0.737 g/kg, which was better than that of the prediction model before optimization. The model had good prediction performance and generalization ability, which can provide theoretical basis for orchard precision fertilization management, improving fruit quality, avoiding resource waste and environmental pollution.

Abstract:The identification of vegetable seedlings offers many useful applications in precision agriculture，such as automated weeding, variable rate fertilization and precise spraying of diseased plants. Aiming to recognize vegetable seedlings accurately and rapidly in natural environment, multiple kinds of vegetable seedlings were taken as study object, and a two-stage based lightweight detection model was proposed. In order to improve the speed and efficiency of image feature extraction, a mixed depth wise convolution that naturally mixed up multiple kernel sizes in a single convolution was applied as backbone network to process input images. Moreover, the feature pyramid networks (FPN) was introduced to integrate different feature maps of backbone network with the aim of improving the identification accuracy of deep learning detection model for multi-scale targets. By minimizing network channel dimensions and decreasing the number of full connection layers in detection head，the two-stage based detection model parameters and computational complexity were greatly reduced. In addition, a distance-IoU (DIoU) loss was proposed for bounding box regression to make the predicted box match with the target box perfectly. Experimental results showed that the mean average precision and recognition speed of multiple kinds of vegetable seedlings based on the proposed model were 97.47% and 19.07 f/s, respectively, and model size was 60 MB. The average accuracy of detection model can obtain 88.55%，when a crop size was less than 32 pixels×32 pixels or leaves occlusion occurred. It was demonstrated that the two-stage based lightweight detection model havd good generalization and robustness performance compared with that by other models，such as Faster R-CNN and R-FCN. The approach presented obtained high accurate rate and fast inference speed in the recognition of vegetable seedlings, which opened a new journey for the research of vegetable detection in precision agriculture.

Abstract:The traditional detection methods of stress response of mutton sheep focus on the static blood test method, which cannot achieve real-time and continuous detection in the process of animal farming and transportation. A set of devices for dynamic detection of wearable biological and environmental signals in the process of mutton sheep transportation was designed. The heart rate and body temperature of mutton sheep during transportation were obtained by pulse wave sensor and infrared temperature sensor. The time domain analysis method was used to extract five typical characteristic parameters of transport stress characteristic parameters of mutton sheep, and their characteristics were analyzed in detail. The characteristic parameters MR, SDNN, RMSSD, pNN50 and CV tended to increase with the extension of transportation time, and were random due to changes in roads, which proved the changes in transportation stress. The average prediction accuracy of the stress state prediction model based on expert experience and supervised machine learning method was more than 89.81%. The results showed that through the development of wearable biosensing devices the pulse wave and body temperature can be monitored and the characteristic parameters of transport stress of mutton sheep can be extracted. The three states of transport stress can be effectively identified, the classification prediction management mechanism of transport stress of mutton sheep can be realized, and the problems such as low efficiency of transport supervision and quality control of mutton sheep can be solved.

Abstract:Animal behavior is closely related to animal welfare and health. It is an important means to evaluate animal welfare and health status through the identification and detection of animal behavior. In order to achieve the recognition and detection of layer behavior in the stackedcage system, a knowledge distillation layer behavior recognition model based on ensemble of multi-teacher model was constructed, and the student network training was guided by multiple teacher model. The knowledge distillation method was applied to the feature extraction network of layer behavior recognition model based on Faster R-CNN framework. Taking ResNeXt, Res2Net and HRNet networks as teacher networks and ResNet 34 networks as student networks, the layer behavior recognition model was trained through knowledge distillation method. The experimental results showed that the performance of layer behavior recognition model was significantly improved. Compared with the recognition model without knowledge distillation, the accuracy, average precision and recall of the model were improved from 93.6%, 78.7% and 86.2% to 96.6%, 89.9% and 94.6%, respectively. After knowledge distillation, the student model basically reached the performance level of the teacher model, while the number of parameters and computation were reduced 32% and 33% than the teacher model, and the inference time of the model was reduced by 66%. The knowledge distillation model proposed obtained a highprecision recognition model through a relatively simple network structure, which provided the possibility for the deployment of layer behavior recognition model in edge embedded devices.

Abstract:Inner Mongolia is rich in grassland resources, and sheep industry is the main animal husbandry in the autonomous region. The intelligent identification of sheep grazing behaviors combined with GPS monitoring of grazing path can provide theoretical basis for estimating of feed intake distribution in grazing area, grazing planning and grassland livestock balance. Threeaxis acceleration sensors were used to design a wireless data acquisition system for grazing behaviors of herding sheep, and the system can automatically collect the three-axis acceleration data of grazing behaviors. BP neural network model, full connection deep neural network model and convolution neural network model were established to realize the classification and recognition of feeding, chewing and ruminating behaviors of herding sheep respectively. The experiments were carried out in a semi-desertification grassland in Inner Mongolia, and the natural grazing Mongolian sheep were selected as test objects. The results showed that the average recognition rates of BP neural network model, full connection deep neural network model and convolution neural network model were 83.1%, 89.4% and 93.8%, respectively, and the convolution neural network model had the highest recognition accuracy, and the adaptability and stability of the network model was strong, which can meet the requirements of classification and recognition of sheep grazing behavior. The feeding path of sheep can be monitored by GPS. The research result can provide theoretical basis for ranch managers to formulate grazing system and improve grazing level.

Abstract:Soil desiccation cracks result in a decrease in irrigation efficiency and nutrients loss during irrigation events, and the prediction of crack preferential flow would provide theoretical basis for soil water management during crop planting. A dual-permeability model was proposed for crack preferential flow, based on the principle of water volume balance in which the sum of surface infiltration rate, laminar flow flux and lateral flow rate through crack walls equaled the surface irrigation intensity. The dual-permeability model was validated with help of dye tracer experiments of preferential flow. Furthermore, this preferential flow model was applied to practical use with rotation-combination design of initial/boundary conditions, i.e. antecedent water content and irrigation intensity. The results showed that the preferential flow patterns could be markedly classified into matrix flow (soil depth was 0~10cm) and preferential flow (soil depth was greater than 10cm). The variations of dye coverage were rapidly decreased when the soil depth exceeded 10cm. A comparison of the measured and simulated data showed that the dual-permeability preferential flow model was remarkably valid in predicting the characteristics of the surface infiltration rate, matrix flow depth and the dye coverage variations with depth. The Pearson correlation coefficient between the measured and the simulated data showed a significant level (P<0.01, R2 was 0.981). The propagation of crack preferential flow process could be divided into supply dominated phase, surface infiltration capacity/crack wall laminar flow dominated phase and surface/crack wall infiltration capacity dominated phase. Based on this model, a rotationcombination numerical simulation containing four levels of antecedent water content (θi was 0.20cm3/cm3, 0.25cm3/cm3, 0.30cm3/cm3 and 0.35cm3/cm3) and six levels of irrigation intensity (R0 was 0.10cm/min, 0.08cm/min, 0.06cm/min, 0.04cm/min, 0.03cm/min and 0.02cm/min) was conducted. The simulated preferential flow patterns were analyzed under 24 treatments. The results showed an increase in preferential flow fraction and a decrease in irrigation uniformity when the irrigation intensity was increased. As the antecedent water content was increased, the strength of preferential flow was decreased and the matrix flow depth became larger. In general, the proposed model was valid in predicting the propagating wetting fronts of crack preferential flow by adopting the water volume balance principle, which eliminated the disadvantages of the traditional dual-permeability preferential flow model that the roughness of the crack walls and the thickness of the laminar flow can not be accurately quantified. The proposed model provides a novel perspective into crack preferential flow prediction, and the simulation results would provide theoretical basis for the farmland water management and percolation loss.

Abstract:In order to explore the nitrogen rate and water management, the multivariate regression analysis was applied to explore how levels of available soil water storage at planting (WB), supplemental water during the growing period (R) and nitrogen rate (N) affected yields of winter wheat (Triticum aestivum L.) and water use efficiency (WUE) in a mobile rain-proof shed between 2013 and 2015. The results showed that effects of all factors on yields of winter wheat followed the sequence of WB, N and R. Likewise, effects of all factors on WUE followed the sequence of WB, R and N. The coupling of all factors on yield and WUE had significant negative and positive effects, respectively; in adequate WB, nitrogen rate could fully exploit the role of WB on yield increasing, and improve WUE. Acceptable yield and WUE were defined as greater than or equal to 0.95 of the maximum predicted response within the range of the treatments. Overlap of acceptable zones of grain yields and WUE were respectively 90~100mm and 104.5~224.5kg/hm2 (WB=450mm),94.3~100mm and 105.8~186.4kg/hm2 (WB=350mm). At WB=650mm, overlap of acceptable zone of the maximum grain yield and the high WUE was 71~100mm and 141.2~264.8kg/hm2.

Abstract:In order to explore the scientific and reasonable irrigation and fertilization system for apple trees in semi-arid region, the effects of water and fertilizer coupling effect on the growth and physiological characteristics of young apple trees in northern semi-arid region under drip irrigation were studied. Four irrigation levels and three fertilization levels were set, among which irrigation treatment was 75%~90% (W1), 65%~80% (W2), 55%~70% (W3) and 45%~60% (W4) of field water holding capacity. The mass ratios of N, P2O5, K2O to airdried soil were 0.9g/kg, 0.3g/kg, 0.3g/kg (F1), 0.6g/kg, 0.3g/kg, 0.3g/kg (F2) and 0.3g/kg, 0.3g/kg, 0.3g/kg (F3), respectively. The results showed that: under different water and fertilizer coupling treatments, the maximum value of plant growth, leaf area and dry matter weight of young apple trees at each growth stage appeared in F1W2 treatment, and the minimum value appeared in F3W4 treatment. Compared with F1W1 treatment, plant growth and leaf area were increased by 6.9%, 6.2%, 11.0%, 2.7% and 9.3%, 5.8%, 5.0% and 3.3%, respectively, at germination and flowering stage, shoot growth stage, fruit setting and maturity stage. The growth index could reflect the physiological characteristics of crops to some extent. With the growth of the trees, different water and fertilizer coupling treatments had more and more influence on the SPAD value of apple trees-leaves. Water consumption of apple trees during the whole growth period was increased with the increase of irrigation amount and fertilizer amount. Water productivity of apple trees under F1W2 treatment reached the maximum of 2.43kg/m3, and increased by 14.6% compared with that of F1W1 treatment and water consumption was decreased by 12.2%. The maximum value of net photosynthetic rate, transpiration rate and stomatal conductance of young apple trees appeared in F1W1 treatment, and that of F1W2 treatment were decreased by 4.2%, 9.7% and 4.2%, respectively, but water use efficiency was increased by 5.9%, and the maximum value also appeared in F1W2 treatment. In conclusion, F1W2 water and fertilizer treatment reached the best water and fertilizer coupling mode and was the best irrigation and fertilization system.

Abstract:Understanding how different sowing dates and irrigation scheduling affect wheat dry matter accumulation was very helpful to improve grain yield and resource utilization efficiency. Field experiments with six-levels sowing dates and four-levels irrigation for winter wheat over two years were conducted during 2017—2019 in North China Plain in Hebei Province, China. Based on the two-year experiment, combined with the literature data of coupling irrigation with sowing dates of Wuqiao Experimental Station from 2011 to 2017. The development index of “wheat clock” model was used to quantitatively express the development phase of winter wheat. The effects of different sowing date and irrigation treatment on the dynamic characteristics of biomass accumulation were analyzed by Logistic mathematical model and establishment of biomass prediction model of winter wheat. Furthermore, winter wheat yield prediction model was established based on the biomass prediction model. The results showed that sowing date affected biomass accumulation by affecting rapid growth period of biomass accumulation. With the delay of sowing date, the rapid growth period was shortened, which made the biomass decreased. The difference of the maximum aboveground biomass caused by different irrigation treatment was mainly determined by the maximum growth rate of biomass, and the increase of irrigation amount helped to increase the maximum growth rate. The characteristics of biomass accumulation of winter wheat were different under different sowing date and irrigation treatments. According to the biomass and yield prediction model of winter wheat based on accumulated temperature before wintering and water supply amount in the growing season, the root mean square error (RMSE) and normalized root mean square error (NRMSE) of measured and simulated above-ground biomass of winter wheat were 1980.2kg/hm2 and 15.7%, respectively, and the RMSE and NRMSE of measured and simulated yield were 839.7kg/hm2 and 10.6%, respectively. Logistic model based on development index can well simulate the biomass accumulation of winter wheat, and had a good simulation accuracy on yield under different sowing dates and irrigation conditions. Under adequate soil moisture conditions before sowing, the appropriate accumulated temperature before wintering was ranged from 200℃·d to 600℃·d, and the appropriate water supply amount in winter wheat growing season was between 200mm and 450mm. The research result can provide scientific basis for the reasonable control of sowing date and irrigation measures in North China, and provide ideas for the prediction of winter wheat yield under different sowing dates and irrigation conditions.

Abstract:In order to explore the influence of different irrigation methods on growth and physiological characteristics of dry direct seeding rice in the black soil region of Northeast China, according to different irrigation methods, three test treatments were set: drip irrigation dry direct seeding (DH), flood irrigation dry direct seeding (MH) and basin irrigation dry direct seeding (HS), with conventional basin irrigation (CK) as control. The dynamic changes of dry matter accumulation process and photosynthetic characteristics of rice at different growth stages were quantitatively analyzed by fitting curves. Results showed that dry matter accumulation of rice under different treatments presented a slow-fast-slow S-curve change rule along with growth time, but dry matter accumulation, start-stop time of rapid growth, growth rate and growth period varied with irrigation methods. The dry matter accumulation of rice in descending order was HS, MH, DH and CK. The rapid growth period of rice treated with CK started in the middle tillering stage, and the rapid growth period of rice in other treatments started at the transitional stage from the middle tillering stage to the end tillering stage. The rapid dry matter growth period of the different treatments all ended in the milk maturity stage. After heading and flowering period, chlorophyll SPAD value in dry direct seeding treatment was decreased faster than that in CK; except late tillering stage, net photosynthetic rate (Pn), transpiration rate (Tr) and stomatal conductance (Gs) in dry direct seeding treatment were lower than that in CK, and stomatal limit value (Ls) was higher than that in CK. The correlation analysis showed that the dry matter accumulation of dry direct seeding rice was positively correlated with chlorophyll SPAD value, Pn, Tr and Gs（P<0.01）. The analysis of photosynthetic characteristics parameters and dry matter accumulation showed that dry direct seeding DH, MH and HS had lower photosynthetic characteristics than that in CK, while dry matter accumulation was better than that in CK; HS had better photosynthetic characteristics and dry matter accumulation than DH and MH. The research results can provide theoretical basis for selecting rice planting mode in black soil region of Northeast China.

Abstract:Crop transpiration is one of the key parameters to guide crop irrigation. It is an effective way to save water to obtain crop transpiration in real time and realize irrigation on demand. However, the microclimate effect in greenhouse is significant, the relationship between crop transpiration and environmental factors is complex, and each environmental factor is interrelated and presents nonlinear change. Taking tomato as the research object, the weighing method was used to measure the real-time transpiration of crop. Greenhouse microclimate data could be obtained in real time through the installation of sensors, including air temperature (AT), relative humidity (RH) and light intensity (LI) as the microclimate environment input of the model, and canopy relative leaf area index (RLAI) as the crop growth input of the model. On this basis, a prediction model of tomato transpiration by long short term memory (LSTM) network was proposed. The model was used to predict the transpiration of tomato, and compared with the nonlinear autoregressive with exgeneous inputs (NARX) neural network, Elman neural network and recurrent neural network (RNN). The results showed that the determination coefficient (R2) and mean absolute error (MAE) of the LSTM prediction model were 0.9925 and 4.53g,respectively. Compared with NARX, Elman neural network and RNN, their R2 were increased by 8.97%, 1.18% and 0.82%, respectively, and their MAE were decreased by 8.16g, 6.23g and 0.52g, respectively. The prediction model proposed had high prediction accuracy and generalization performance, and the research results could provide reference for the study on the regularity and water demand of greenhouse crops.

Abstract:Continuous, accurate, and quantitative non-destructive testing of bitter pit, as well as research on the phenotype of new varieties of apples by breeding experts, require the support of accurate bitter pit identification technology. The presence of bruise will interfere with the recognition of bitter pit and reduce the recognition accuracy. Therefore, it is necessary to carry out research on the recognition of bitter pit and bruise. Based on the CT images of apples, a method for identifying apple bitter pit and bruise was proposed. The method such as maximum between-class variance, region labeling and median filtering were used to segment 337 apple CT images and locate the injured area. Following this step, a total of 18 features of the shape, texture and location of the injured area were extracted. Additionally, the feature information was selected using two methods of multiple stepwise regression and class distance separability criterion. The common features selected by the two methods were used as the selected feature information. Finally, the support vector machine optimized by genetic algorithm and the support vector machine with default parameters were used to identify apple bitter pit and bruise. The recognition results showed that the overall recognition accuracy of the support vector machine optimized by the genetic algorithm was higher than 93%, and the overall recognition accuracy of the support vector machine algorithm with default parameters was higher than 84%. The recognition accuracy of the support vector machine optimized by the genetic algorithm was obviously better than that of the support vector machine with default parameters. The research results can be used to cultivate the phenotype analysis of apple bitter pit and bruise.

Abstract:Quick and accurate assessment of fish freshness is of great significance for intelligent quality monitoring and ensuring the safety of consumers. In the current fish freshness evaluation method based on visual images, the study of fish gills needs to remove the gill cover, which is invasive to the fish body, and the analysis of other parts has a low evaluation accuracy. To solve the above problems, a fish freshness classification method based on color histogram & grey-level co-occurrence matrix-linear discriminant analysis (CHG-LDA) was proposed. Firstly, preprocessing operations such as labeling, image zooming and color space conversion were performed on the collected fish images. Secondly, the extracted color histogram features and grey-level co-occurrence matrix (GLCM) features were fused to constitute the features, and the feature dimension was reduced by LDA. Finally, K-nearest neighbor (KNN) algorithm was used to classify fish freshness. The CHG-LDA method proposed solved the problem of poor classification performance caused by the low quality of the extracted fish image features. The experiment was carried out on a real crucian data set, and the index values of precision, recall, F1-score and accuracy were all 1. Compared with color histogram features, color moment, GLCM features, etc., this method improved the performance of each evaluation index on KNN, RF, ANN, and LightGBM classifiers. Among them, the evaluation time of KNN was the best, which was 0.01s. Experimental results showed that this method can achieve accurate and non-destructive evaluation of fish freshness, and it was feasible for actual production monitoring.

Abstract:The feasibility of applying synchronous fluorescence technology was studied to quickly detect the residues of sarafloxacin hydrochloride (SARH) and doxycycline hydrochloride (DCH) in chicken. Firstly, the three-dimensional synchronous fluorescence spectra of SARH standard solution, DCH standard solution, chicken extract without antibiotics and chicken extract containing SARH and DCH were analyzed, and the wavelength difference Δλ of both SARH and DCH were determined as 110nm, and the fluorescence excitation peaks of SARH and DCH were respectively determined as 320nm and 381nm for the detection of SARH and DCH residues in chicken. Secondly, the effects of the concentrations of magnesium sulfate solution and SDS solution, as well as time, on the fluorescence intensities through the single factor test were analyzed. The best detection conditions of SARH and DCH residues in chicken were as follows: the concentration of magnesium sulfate solution of 0.375mol/L, the concentration of SDS solution of 0.300 mol/L and time of 12min. Thirdly, the prediction models of SARH and DCH residues in chicken were established through the algorithms of multiple linear regression (MLR), partial least squares regression (PLSR), and support vector regression (SVR), respectively. The experimental results showed that the comprehensive evaluation of the prediction model based on the PLSR algorithm was the best among these algorithms. For the prediction model of SARH residues based on the PLSR algorithm, the R2P, RMSEP, and RPD were 0.8465, 0.3441mg/kg, and 2.5882, respectively. For the prediction model of DCH prediction based on the PLSR algorithm, the R2P, RMSEP, and RPD were 0.9141, 5.8909mg/kg, and 3.2435, respectively. The results showed that the detection of SARH and DCH residues in chicken was feasible through synchronous fluorescence technique, the implemented method was straightforward and fast, and could provide a reference for the rapid detection of SARH and DCH residues in chicken.

Abstract:Gellan gum is commonly used as a food ingredient because of its gelling and thickening properties. Application of high intensity ultrasound (HIUS) in food industry is currently attracting much attention because it can be used to alter food physical or chemical properties with a low impact on the environment. Gellan gum solution was subjected to high intensity ultrasound at 55℃ (above the sol-gel transition temperature) before acdification to determine the effectes of HIUS on glucono-δ-lactone (GDL) induced gelation properties of low acyl gellan gels (LA). The results showed that with the increase of gellan concentration, fracture stress, initial Youngs modulus, the opacity index and water holding capacity were increased, but fracture strain was decreased. With the increase of ultrasonic time and ultrasonic power, the fracture stress and initial Youngs modulus were decreased, while the fracture strain was increased. The fracture stress and initial Youngs modulus were firstly increased and then decreased with the increase of GDL/LA weight ratio. The optimum GDL/LA weight ratio to the gel strength for the acid gels was about 1. As the GDL/LA weight ratio was increased, fracture strain and the water holding capacity were decreased while the opacity index was increased. The reduction in gel strength was attributed to the reduced chain length of the gellan polymer molecules and the gel network may include dangling chains which did not contribute to elasticity. The higher the gellan concentration was, the more dense microstructures were. The results indicated that high intensity ultrasound could be used for modifying gellan gum to improve its gelling properties.

Abstract:In order to improve the emulsification property of soybean whey protein (SWP) and improve the utilization value of soybean byproducts, the complex was prepared from soybean whey protein and dextran sulfate (DS), and its formation mechanism and emulsification characteristics were studied. The ζ-potential, turbidity and spectral methods were used to analyze the structural changes and the interaction mechanism of the protein-polysaccharide complex system. The average particle size and observation of microstructure were used to characterize the distribution and aggregation state of the composite, and the emulsifying characteristics of the composite system were analyzed. The results showed that the pH value and protein/polysaccharide ratio significantly affected the interaction between SWP and DS. SWP and DS could form more stable electrostatic complex through electrostatic interaction at pH value 3.5. Fluorescence spectra and Fourier transform infrared spectra showed that the addition of DS changed the microenvironment and secondary structure of SWP, and the relative content of α-helix in the complex was increased significantly. Hydrogen bond and hydrophobic interaction also affected the formation of the complex. With the increase of DS concentration, the particle size of the complex was increased first and then decreased. When the ratio of SWP/DS was 4, the agglomeration degree of the composite was the highest, and the average particle size was (3667.25±95.32)nm. Under this condition, the composite formed significantly improved the emulsification properties of SWP. The emulsifying activity index and emulsifying stability index were increased by 31.03% and 14.71%, respectively.

Abstract:Pickering high internal phase emulsion was prepared by using soybean globulin (11S) and soy β-conglycinin (7S) under acidic conditions. The stability of the emulsion was studied by particle size, potential, Fourier transform infrared spectroscopy（FITR）, freeze scanning electron microscopy, optical microscopy and rheology, and its digestion characteristics were also discussed. The results showed that when pH value was 2.0, the emulsion formed by 7S and 11S had higher emulsifying activity and emulsifying stability, and 11S had higher hydrophobicity and emulsifying property than 7S. When the protein concentration was 0.015g/mL and the volume fraction of oil phase was 78%~82%, stable high internal phase emulsion can be formed. By increasing the volume fraction of the internal phase, the emulsion system with stable 7S and 11S protein particles distributed more evenly and was not easy to aggregate, which enhanced the formation of gel network. Compared with 7S stabilized Pickering high internal phase emulsion, 11S formed a stronger gel network structure with stronger gel strength and more stable emulsion system. Simulated in vitro digestion experiments showed that under acidic conditions, the particle size and potential value of the emulsion were lower, and the fat release was less. The high internal phase emulsion formed by the protein could delay the release of lipid to varying degrees. The research result clearly identified the structural characteristics of 7S and 11S under acidic conditions and the digestive behavior of stable high internal phase emulsions in gastrointestinal tract, and provided theoretical support for the research and development of food functional ingredient delivery system.

Abstract:The tractor traction performance is closely related to the distribution of the tractor's total weight on the front and rear axles. For the rear wheel drive tractor, it is one of the effective ways to improve the tire-soil adhesion state so as to promote the traction performance of the tractor by reasonably selecting the ballast weight for the drive axle and optimizing the axle load distribution between the front and rear axles. A position-adapted battery ballast frame structure was proposed to improve the ballast effect so as to improve the traction performance of the electric tractor. Based on the equations for traction performance prediction, an optimization model of battery ballast parameters was established with the goal of comprehensive optimization of driving efficiency, slip ratio and safety ballast of front axle. The simulation model of electric tractor under the horizontal traction condition with the load range of 1~5kN was built on the Matlab/Simulink platform, and the traction performances before and after the ballast optimization were simulated and analyzed. Referring to the position-adapted battery ballast frame structure, the experimental prototype of electric tractor was designed, and the ballast parameter optimization model was verified by ploughing in the soil tank in the indoor environment. The results showed that under the premise of ensuring the safety ballast of the front axle, the battery layout optimization can improve the traction speed and energy utilization rate by 4.16% and 5.66%, respectively, which effectively improved the traction performance of electric tractor.

Abstract:The double drive closedloop mechanism has the advantages of simple and compact structure, better flexibility and bigger workspace, so it can be used to design parallel mechanisms. Based on the theory of position and orientation characteristics (POC) equations, a systemic approach of type synthesis for spatial parallel mechanisms containing planar closed-loop structures within limbs was proposed, consequently numerous novel parallel mechanisms consisting of fewer limbs were synthesized by using this technique. Firstly, the topological compositions and equivalent outputs of seven kinds of dual drive loops were presented and analyzed. Then, the 3T1R, 3T2R and 3T3R chains with dual drive five-bar loop were generated. Based on the complex chains synthesized, three kinds of three-chain and two kinds of two-chain 3T1R parallel mechanisms, two kinds of four-chain and four kinds of three-chain 3T2R parallel mechanisms, as well as two kinds of four-chain and two kinds of three-chain 3T3R parallel mechanisms were constructed. Furthermore, the topological characteristics of these fifteen kinds of mechanisms were analyzed, including the number of the independent loops, number of over-constraints and coupling degree. The results showed that the mechanisms with fewer limbs had not only the characteristics of simple, compact and symmetrical structure, but also had the low coupling degree to facilitate the kinematic and dynamic analysis, which made these mechanisms promising prospect in the application of industry. This work contributed to enriching and improving the structural synthesis theory of the parallel mechanisms with fewer limbs.