Abstract:The protective utilization and cultivation technology system for Northeast China’s black soil region primarily encompasses conservation tillage and soil fertility cultivation practices. While developing black soil agricultural production and ensuring national food security, this technology can solidify soil and improve soil properties, maintain ecosystem health and stability. It is the core technical means to promote the protection and utilization of black soil. The application coverage, technical frameworks, and implementation impacts of protective utilization and cultivation technology system for Northeast China’s black soil region were systematically reviewed. It specifically elucidated the operational mechanisms and technical characteristics of core technologies, including no/minimum tillage seeding, subsoil, straw mulching, and organic fertilizer application, while critically analyzing the developmental trajectories of existing technical paradigms and associated machinery systems. Building upon advancements and demands in black soil conservation and utilization, the key challenges in current technological and mechanization development were identified. Finally, it proposed future directions from multiple dimensions: strengthening fundamental theoretical research, overcoming critical technical bottlenecks, advancing intelligent conservation-oriented systems, enhancing agronomic-mechanization integration, and establishing regionally adaptive protective utilization and cultivation technology system frameworks. These insights aimed to inform the optimization of protective utilization and cultivation technology system for Northeast China’s black soil region.

Abstract:With increasing global environmental and economic pressures on agriculture, traditional chemical and physical weed control methods face significant challenges, such as environmental pollution and inefficiency in operations. Intelligent mechanical weeding technology has emerged as a sustainable alternative, effectively addressing these challenges. This review examined the research progress on intelligent mechanical weeding machines designed specifically for dryland environments, focusing on their working principles, key technologies, practical applications, and development status both domestically and internationally. Intelligent weeding machines increasingly utilized high-precision image recognition and advanced deep learning algorithms to achieve accurate weed identification and precise positioning. These systems used mechanical arms or other units to perform efficient and targeted weeding operations, enhancing crop yield and reducing reliance on chemical herbicides while providing substantial environmental and economic benefits. However, challenges such as variable field conditions, high equipment costs, and technical limitations hindered widespread adoption. This review also explored essential technologies in dryland intelligent mechanical weeding, including crop row detection, seedling-avoidance control mechanisms, and multi-sensor integration, emphasizing the importance of improving real-time processing and precision in weeding operations. Future directions included multi-sensor fusion, modular design, and adaptations for various crop environments to enhance the practicality and adoption of intelligent weeding technologies in agriculture.

Abstract:Inter-row weeding during the maize seedling stage is essential for ensuring healthy crop growth. The precision of this process directly affects both weed control effectiveness and crop protection. To improve the efficiency and accuracy of inter-row weeding, a two-stage row guidance device was designed, with its structure and key parameters optimized. The device combined a primary guidance system and a secondary row-spacing adjustment mechanism. The primary guidance system used parallel cantilevers and double-acting hydraulic cylinders to achieve precise alignment, while the secondary adjustment mechanism employed a servo motor and sliding rail to adapt to different row spacings. Theoretical analysis determined that the hydraulic cylinder for the primary guidance system required a minimum thrust of 7536.37N, and the rated thrust for the servo cylinder in the secondary mechanism was 1409N, ensuring stable performance. Indoor tests verified that the servo motor’s efficiency was 82.3%, with a response time of 21ms, indicating good load adaptability and control precision. Field trials showed that at speeds of 0.5m/s and 1.0m/s, the device demonstrated high stability in both alignment and row-spacing adjustment. However, performance was decreased at 1.5m/s, suggesting the need for algorithm optimization at high speeds. The results showed that the device met the operational requirements for inter-row guidance in maize seedling weeding, providing valuable support for the development of weeding machinery.

Abstract:Aiming to address the issues of moisture absorption, low efficiency in topdressing operations, and poor uniformity in fertilizer distribution in the fertilizer top-dressing process for the large ridge double row planting mode of maize, a spiral conveyor fertilization device, multi row collection and airflow fertilization device suitable for this planting mode was designed based on the characteristics of fertilization operation. Theoretical calculations were conducted for the parameters of the spiral conveyor fertilizer discharging device and pneumatic conveying structure. The blade structure of the spiral conveyor was designed and the power of the spiral conveyor drive motor was determined according to the required fertilizer discharge rate. The structural dimensions of the main pneumatic fertilizer conveying pipeline and the pneumatic fertilizer distribution pipelines were determined. By merging the pneumatic fertilizer distribution pipelines using tee pipes, the fertilizer application rate in the middle of the double seedling rows was increased compared to the sides. Fertilizer discharging tests were conducted on this device, and the results showed that the spiral conveyor fertilizer discharging device provided stable fertilizer discharge, with the discharge rate linearly related to the rotational speed. A two-factor, three-level experiment was designed to investigate the effects of wind speed and fertilizer discharge rotational speed on fertilizer distribution uniformity. The rotational speed of fertilizer discharge, wind speed, and their interaction all had extremely significant effects on the coefficient of variation for uniformity in fertilizer discharge among rows. This coefficient was increased as both the rotational speed and wind speed increased. After merging the pneumatic fertilizer conveying pipes, the coefficient of variation for uniformity in fertilizer discharge among rows was slightly increased. The coefficient of variation for uniformity among rows without merged outlets ranged from 6.5% to 7.1%, while the coefficient with merged outlets ranged from 3.8% to 5.8%. The fertilizer discharge rate with merged outlets was approximately 1.7 times of that of the discharge rate without merged outlets. The fertilizer discharging performance met the design objectives and could effectively satisfy the mechanical operation standards for maize top-dressing.

Abstract:Focused on the problems of low function integration, incomplete detection parameters and poor synchronicity and flexibility of corn electric drive precision seeder detection system, the sensors required for the detection parameters were selected, the sensor-detection parameter model was constructed, the signal synchronization acquisition, processing and interaction procedures were developed, and the detection system of the operating condition parameters of corn electric drive precision seeder based on cDAQ controller was created. The system was based on the principle of high-frequency, real-time, synchronous sampling, the hardware adopted cDAQ equipment as the data acquisition controller, and configured separate sampling channels for the signals of each parameter; the software design combined the LabVIEW platform to design the signal processing program and human-computer interactive interface, set up uniform software triggers for all the signal acquisition loops and configure the network ports, and provided the clock for the system by the host computer. The upper computer provided the clock signal for the system to realize the real-time high precision acquisition of a variety of working condition parameters, such as operating speed, seeder meter plate rotation speed, seeding rate, seeding depth, downforce, wind pressure, vibration and so on, in the process of seeding operation. In order to verify the reliability of the detection system, the bench test for seed meter plate rotational speed and seeding rate detection was carried out, together with a field test for operating speed, sowing depth detection, and downforce. The results of the bench test showed that the average absolute error of seed meter plate rotational speed detection was no more than 0.44r/min, and the average relative error was no more than 3.56%; the accuracy of seeding rate detection was no less than 98.50%; the results of the field test showed that in the operating speed range of 0~15km/h, the average relative error of operating speed detection was 4.42%; above 6km/h three rows of monomer seeding depth detection average, standard deviation, coefficient of variation were 2.70%~7.53%, 4.03~7.72mm and 13.99%~17.42%, respectively; downforce static detection test showed that the average difference between the two groups of monomer downforce was close to the actual value of the difference, the relative error was no more than 5.93%, at the low speed of 3~6km/h and 12~15km/h high speed operation, the maximum relative error between the average difference of the two groups of monobloc lower pressure and the actual value detected by the system was 14.91% and 19.30%, respectively.

Abstract:In response to the practical issues of compaction pressure poor stability and uneven compaction strength in corn no-till seeder, a precise control system for compaction pressure was developed based on PID control. The system consisted of a compaction pressure detection unit, hydraulic regulation device, controller, terminal, and mechanical actuator. By utilizing measurement data from tension sensor and angle sensor, the relationship model between the compaction pressure and the measurement data of the two sensors was established by Origin software. The system employed the PID control algorithm to calculate control variables and adjust hydraulic cylinder extension and retraction in real-time, thereby achieving precise control of compaction pressure. Step response experiments revealed that the system’s mean adjustment time was 1.13s, with the mean steady-state error of 2.7N and the mean overshoot of 3.23%. Field experiments demonstrated that the relative error of compaction pressure under hydraulic control mode was 3.08% to 5.38%, with root mean square error of 6.63N to 10.09N，when the target compaction pressures were set at 159N and 182N, and the seeder’s operating speed ranged from 5km/h to 9km/h. In contrast, the relative error of compaction pressure under mechanical adjustment was from 5.05% to 11.48%, and the root mean square error was from 11.67N to 22.49N. The performance metrics of the seeder based on hydraulic control significantly outperformed those based on mechanical control, enhancing the stability of compaction pressure and providing technical and equipment to ensure the quality of notill sowing of corn.

Abstract:Aiming at the problems such as single evaluation index and significant deviation of horizontal comparison of subsoiling operation quality, by loading intelligent terminal equipment on agricultural machinery, collecting GNSS, operation depth and other information of agricultural machinery operation, analyzing the spatial trajectory data of agricultural machinery, calculating the feature vectors of agricultural machinery deep loosening operation, such as operation area, operation efficiency, operation coverage, operation depth compliance rate, operation time utilization rate and so on, based on the minimum-maximum normalization method, the characteristic vectors were normalized, and the weight of each feature vector was determined by the expert scoring method. The agricultural machinery deep loosening operation quality index (AMQI) was further calculated to evaluate the comprehensive quality of agricultural machinery deep loosening operation. In order to verify the quality index of agricultural machinery subsoiling operation, from January 1st, 2022 to December 31st, 2022, the agricultural machinery experiment was carried out in Hongxing Farm of Heilongjiang Province. The vehicle-mounted intelligent terminal was installed on 33 tractors on the farm, and the subsoiling operation data was continuously collected to calculate the quality index of agricultural machinery subsoiling operation. The results showed that the normalized feature vector eliminated the dimensional influence between different features and reflected the size distribution of agricultural machinery in features. The value of AMQI also reflected the comprehensive quality of deep loosening operation of agricultural machinery, compared with the standard area evaluation method, the rating dimension was more, and the evaluation was more comprehensive and scientific, which can provide data support for horizontal and vertical evaluation of agricultural machinery operation.

Abstract:Aiming at the lack of online soil moisture detection system for existing corn sowing equipment and the problems of low detection accuracy and poor environmental adaptation of the existing online soil moisture detection system, a method of soil moisture measurement was presented based on capacitance method and depth compensation, and a set of airborne corn sowing soil moisture online detection system was developed. In terms of electrode plate optimization, the system conducted simulation experiments on capacitor structure optimization parameters with electrode plate spacing, electrode plate thickness, and relative area as experimental factors. The optimal capacitor electrode plate parameters were determined to be as follows: electrode plate spacing of 75.8mm, electrode plate thickness of 0.7mm, electrode plate relative area of 5.073mm2, length of 100mm, width of 50.73mm. The hardware part of the system mainly included FDC2214 capacitive sensor, F4046 pressure sensor, and STM32F103 microcontroller. The capacitive sensor was used to obtain the capacitance value of the soil to be tested, and the pressure sensor was used to obtain the pressure value of the soil to be tested, indirectly inferring the soil depth in the tested area. The system software was developed by using Matlab platform for real-time acquisition, calculation, display, and storage of soil capacitance signals and pressure signals. Based on this system, the influencing factors of soil moisture detection models were explored, and a soil moisture detection model based on BP neural network was constructed. The modeling experiment results showed that when the soil moisture was in the range of 7.23% to 21.14%, the model’s predictive performance indicators R2, RMSE, and RPD were 0.927, 0.008, and 3.70, respectively, with good predictive performance. Finally, the constructed model was integrated into the online soil moisture detection system and bench and field validation experiments were conducted. The results of bench test showed that the fitting coefficient R2 of soil moisture content was 0.852~0.927. The absolute error range of soil moisture prediction results was from -2.89% to 2.57%, and the average absolute error was 1.01%. The field test results showed that the coefficient of determination R2 of the fitting curve between the soil moisture monitoring value and the actual value was 0.842, and the absolute error range of soil moisture monitoring was from -0.96% to 0.45%, with an average absolute error of 0.39%. This indicated that the performance of the detection system developed met the needs of soil moisture monitoring during field operations of corn seeders.

Abstract:In order to solve the problem of soil disturbance caused by straw returning interval deep sowing combined operation machine in conservation tillage, an interval subsoiler with direct injection deep sowing shovel was designed. The discrete element simulation and field experiment method were used to study the different shovel body width affect the behavior of soil disturbance. Taking tillage specific resistance, soil swelling degree and soil disturbance coefficient as experimental indexes, the soil movement state and micro-movement in all directions under different shovel width conditions were compared, and the soil disturbance effect of direct injection deep loose shovel was analyzed. The results showed that tillage resistance was the minimum when the width of shovel was 350mm, and tillage specific resistance was the minimum when the width of shovel was 450mm. Soil disturbance was increased with the increase of shovel width, and the shovel width mainly affected soil lateral disturbance, soil retreat and ridge height. Reducing the width appropriately was beneficial to reduce soil lateral disturbance, increase soil retreat and reduce ridge height. The width of the shovel had an important effect on soil fluffiness and soil disturbance coefficient. When the width of the shovel was 350mm, the soil fluffiness was relatively small and the soil disturbance coefficient was relatively large. Different shovel width had certain influence on tillage resistance and disturbed area, and the influence degree of shovel width on disturbed area was greater than that of tillage resistance. Within the design parameters of shovel width, the average errors of test and simulation results of soil bulk degree and disturbance coefficient were 6.36% and 6.84%, respectively. The average errors of test and simulation values of tillage resistance and specific resistance were 9.02% and 12.41%, respectively. The effect of interval subsoiling machine on reducing soil disturbance was obvious, which can provide reference for the optimal design of subsoiling machine.

Abstract:Aiming at the problem of notill seeding under conservation tillage conditions affected by the root-soil complex formed by corn stubble and soil, a corn stubble treatment mode of “row digging-extrusion crushing-vibration soil removal” was proposed, and a soil cleaning machine for corn stubble with row-digging was designed. It mainly consisted of double disc digging shovels, stubble conveying mechanism, concave plate-roller type root soil separation mechanism, shake type rod conveyor mechanism, etc. It can complete the digging, picking, root and soil separation of corn root-soil complex in one go. The structural design and kinematic analysis of its key components were conducted. The force and motion of the double disc digging shovel were analyzed, leading to the determination of its main structural and working parameters. The transportation and force conditions of the root-soil complex in each stage of root soil separation were analyzed, leading to the determination of main structural parameters and motion parameters of the stubble conveying mechanism, concave plate-roller type root soil separation mechanism and shake type rod conveyor mechanism. This ensured that the root-soil complex can gradually achieve the goal of root and soil separation. The field test results of the double disc digging shovel showed that the digging rate of the corn root-soil complex can reach 100%. The soil bin test results of the whole machine showed that the root and soil separation rate was 97.4%, and the root and soil separation rate was relatively high. The designed corn stubble digging and soil cleaning machine had effective stubble digging and root and soil separation capabilities.

Abstract:In order to solve the problem that it is difficult for the passive anti-blocking device to take into account the cutting effect and the operation power consumption during no-tillage sowing of corn in Northeast China, a passive disc antiblocking device was designed based on the principle of dynamic sliding cutting characteristics of the sawtooth disc, which could effectively improve the straw cutting effect while fully applying the sliding cutting effect. According to the dynamic sliding cutting characteristics of the sawtooth disc, a dynamic sliding cutting and structure conversion model was constructed, and the sliding cutting characteristics of the sawtooth of corn straw under support cutting were carried out. The conclusion that the optimal dynamic sliding cutting angle under the sawtooth structure was 15°~30°, and the hypothesis of the influence of the sawtooth rake angle on the two types of cutting process was put forward for the two special cutting processes and load curves generated under the sawtooth structure, and it was verified by combining the soil groove test and the discrete element simulation experiments. The quadratic regression rotational orthogonal experiment was carried out to determine the optimal operating parameters of the sawtooth: the forward speed was 2.0m/s, the sawtooth rake angle was 21.3°, and the tooth height was 6.0mm. According to the simulation results, the disc processing was completed and the field experiment was carried out. The results showed that when the straw covering amount was 1.97kg/m2, the sawtooth disc straw cutting rate was 76.2%, the vertical peak downforce was 875.7N, and the average downforce was 544.1N, the sawtooth structure design of the planar disc was increased by 34.7 percentage points, and the peak downforce and average downforce were reduced by 5.7% and 7.9%. The disc operation performance was ideal, and it met the no-tillage sowing requirements in Northeast China, and can provide a theoretical reference for the research of cut-off anti-blocking device for no-tillage seeder.

Abstract:A corn plant core localization algorithm was developed based on high-fit oriented bounding boxes for complex natural environment corn canopy data, and a labeling strategy was proposed that can effectively reduce the lack of edge precision. To address the issues of insufficient labeling accuracy and weak multi-scale feature extraction in traditional object detection networks, a novel high-precision labeling strategy for YOLO v7OBB was proposed and an innovative learning convergent asymptotic feature pyramid network (LC-AFPN) was developed. Additionally, a color space filtering algorithm was used for canopy segmentation, and a gap-filling algorithm improved image quality. Spatial moments were utilized to accurately calculate the coordinates of the plant core, leading to the learning convergent asymptotic YOLO v7OBB network (LCA-YOLO v7OBB) for corn canopy targets detection. Validation on a complex corn field dataset revealed that LCA-YOLO v7OBB offered strong anti-interference capability and high plant core localization accuracy, with an average accuracy of 85.19% and precision and recall rates of 91.83% and 83.04%, respectively. Compared with 12 other rotating object detection networks, this model demonstrated the best overall performance. Moreover, validation on custom cucumber and eggplant datasets further confirmed its robust generalization ability. This model provided a theoretical basis and technical support for applications such as precision fertilization and agricultural machinery visual navigation.

Abstract:In order to improve the sand collection efficiency of the wind erosion instrument and accurately grasp the sand movement law, the influence of structural parameters of the wind sand separator inside wind erosion instrument on the sand collection efficiency was analyzed by using computational fluid dynamics (CFD) simulation method and combined with the wind tunnel test. The wind-sand separator model was established in Fluent platform, numerical analysis was carried out based on RNG k-εmodel, and the discrete phase model (DPM) method was used to calculate the sand collection efficiency and complete the simulation of the related particle dynamics inside the wind erosion instrument. The wind erosion meter was improved from wedge shape to cylindrical shape, which optimized the structure of the wind erosion meter and improved the sand collection efficiency. The effects of the inlet wind speed of inlet pipe, the particle size of sand particles and structural parameters of wind-sand separator (length of the inlet pipe, depth of the exhaust pipe insertion, cone angle of the conical deflector plate, and the length of the cylinder) on the sand-collecting efficiency were investigated. The simulation results showed that when the wind speed was 13.8m/s, the particle size less than 0.01mm was the main particle that affected the sand collection efficiency. The structural parameters of the wind-sand separator were subjected to a single-factor test, the level range of the test factors was preferred, and the Box-Behnken test was carried out to optimize the values of the parameters to obtain the optimal parameter combinations: the length of the inlet pipe was 12mm, the depth of the exhaust pipe insertion was 70mm, the cone angle of the conical deflector plate was 40°, the length of the cylinder was 160mm, and the sand-collecting efficiency was 77.05%. According to the optimal parameter combination, the wind erosion instrument model was processed and wind tunnel test was carried out, and the sand collection efficiency was 74.38%, and the error with the simulation results was 3.47%, which was better than the common wedge-shaped wind sand separator with better sand collection effect.

Abstract:Aiming at the problems of high resistance, high power consumption, low stubblebreaking rate, and poor ridge shape after the operation of subsoil stubble-breaking machine after straw return to the field in northeast ridging area, a stubble-breaking blade with interaction with subsoiler was designed. The mounting distance between the subsoiler and stubblebreaking blade was determined to be 60mm by discrete element simulation. Meanwhile, in order to satisfy the same relative acceleration between the cutting edge of stubble-breaking blade and soil particles at different depths (30mm,60mm,90mm,120mm) during operation, the sliding angle at different depths was obtained by combining the kinetic analysis of the stubble-breaking blade and subsoiler, and the cutting edge curve of the stubble-breaking blade was determined.Taking the blade disk diameter and stubblebreaking blade mounting angle as the test factors, and operating resistance and power consumption as the test indexes, a two-factor, five-level center combination test was carried out.The test results showed that the minimum operating resistance and power consumption were obtained at the blade disk diameter of 312mm and the mounting angle of 73.2° (the operating resistance was 1167N and the power consumption was 14.6kW). In the field test, the depth of stubble-breaking blade entering the soil and the forward speed of machine were taken as the test factors, the working resistance, ridge height/width ratio and stubble-breaking rate were taken as the test indexes. The optimized results showed that when the depth of blade entering the soil was 102mm and the forward speed was 0.65m/s, the working resistance was 1467N, ridge height/width ratio was 0.529, and stubble-breaking rate was 95.4%. Comparative field performance tests were conducted at this optimal operation parameter, and test results showed that compared with the traditional stubble-breaking blade, the serrated stubble-breaking blade operating resistance was reduced by 13%, the height/width ratio of the ridge was increased by 6%, and the stubble-breaking rate was increased by 1 percentage points, which was able to meet the quality of the machine operation and the agronomic requirements.

Abstract:Aiming at the high speed operation of no-tillage seeder in corn stubble land in Northeast China, the clogging of seeding and fertilizer touching parts leads to the reduction of the quality of seeding operation, etc., the design of a lateral stubble clearing knife suitable for high speed no-tillage seeding operation was improved. Through the theoretical analysis of bending curve of tangent blade and operation process, the structure and working parameters of the lateral stubble knife were determined, and a discrete element simulation model of the blade-soil-root stubble was constructed for the stubble clearing and anti-clogging device in the field operation process, and the quadratic regression orthogonal center was carried out with the bending angle of the tangent blade of the stubble clearing knife, the operation speed and the knife shaft rotation speed as the influencing factors, and the stubble removal rate, the soil disturbing rate, and the equivalent power consumption as the evaluating indexes. Rotary combination simulation test was done. According to the simulation results of parameter optimization, the prototype was manufactured and field performance tests were conducted, and the results showed that under the conditions of corn stubble coverage of 1.73kg/m2, average stubble height of 400mm, and soil hardness of 20.8kg/cm2, the performance was optimal when the combination of parameter combinations of the bending angle of the cutting edge of 34.5°, the operating speed of 14.4km/h, and the cutter shaft rotational speed of 380r/min were combined. In this case, the root stubble removal rate was 91.6%, soil disturbance rate was 26.6%, and power consumption was 12.62kW; the stubble removal rate of the stubble removal device with optimized stubble removal knives was increased by 12.67% compared with that of the stubble removal device with lateral stubble removal knife blade.

Abstract:In order to solve the problems of poor operation quality and low working efficiency of passive no-tillage seeding machine in four provinces of Northeast China under the condition of heavy straw mulching, and some large-scale netcrop precision seeding machines can not work on the original stubble ground, the design of a kind of widewidth folding front lateral clearing and anti-clogging device was optimized, which can compose with the existing conventional seeding machine to form a joint operation machine, which can complete all the seeding operations such as seed bed preparation, fertilizer application, seeding, mulching and compression in any state of stubble land without any treatment. Through theoretical analysis to determine the key parameters of the folding mechanism range, in which the hydraulic cylinder stroke was 500mm, through simulation analysis to determine the folding and unfolding process of the folding mechanism of the angular velocity, linear speed changes were in line with the design requirements, the tooth-embedded clutch collision impact force with the active tooth-embedded disk linear speed was nonlinear growth, in the active tooth-embedded disk trajectory linear speed of 150mm/s, folding angular speed of 18(°)/s, and the impact force was 417.N. The synchronization performance, rotational speed and torque of each actuating element of the hydraulic system met the operational technical requirements. Applying the three-factor three-level orthogonal test method, taking the operating speed, knife shaft rotation speed and knife teeth depth into the soil as the test factors, and taking the rate of clearing straw, consistency between rows of clearing straw, equivalent power consumption, and coverage uniformity as the evaluation indexes, the optimization combination test of field parameters was implemented. Under the conditions of 7.2km/h, 600r/min, and 40mm of soil penetration depth, the straw clearing and blocking device could realize the straw clearing rate of 90.02%, straw uniformity of 91.11%, equivalent power consumption of 6.08kW, and consistency of straw clearing between rows of 91.26%. The results can provide technical support for improving the utilization rate of large net-crop precision planters, increasing the convenience of road transportation of large machines, reducing the compaction damage to the soil caused by the machine entering the ground several times, and reducing the production cost.

Abstract:In order to solve the issue of idealized test results caused by not considering seed-to-soil contact displacement during the testing of seed meters, a material-laying seed meter test bench was designed. The differences between the detection mechanism of testing bench and working mechanism of ground wheel-driven planter and formation mechanism of residual speed of seeds discharged by seed meters were demonstrated. The formula for the calculation of residual speed of seed spreader was derived, and the residual speed of peanut stratified fertilizer rotary tilling and ridging seed spreader with operating speed of 2.12km/h was calculated to be about 0.25~0.42m/s. The simulation was carried out by using the EDEM software and the offset distance and falling depth of spherical and non-spherical seeds (taking peanut as example) at 10~20cm casting height, 0~0.42m/s residual speed, and 30 ways of touching the soil showed that the larger the falling depth of the seeds was, the smaller the offset distance was; the lower the casting height was, the smaller the falling depth of seeds would be, but the offset distance would be larger; the larger the casting height was, the smaller the residual speed, the greater the falling depth and the smaller the offset distance would be; the specific combination of angular velocity and residual speed can reduce the offset distance of the seed. Using this testing bench to carry out the central combination test on the seed meter, it was got that this seed meter had the best operation effect when the working speed was 2km/h, the seed casting height was 15cm, and the residual speed was 0.21m/s, and it reached 87% of the operation qualification rate. The results of field test showed that the best operation effect was achieved when the working speed was 2.12km/h and the seeding height was 15cm, and the qualified rate of seed spacing reached 84%, which proved that this testing bench can accurately detect the qualified rate of the seed meters and explore its optimal working parameters.

Abstract:For corn and soybean strip compound planting mechanized sowing process in the field of large amount of straw, substitute equipment sowing quality was poor, low operating efficiency and other issues, the design of a post-harvest stubble land conditions at a time into the ground can be synchronized to complete the “clearing of straw anticlogging seed bed finishing-corn and soybean sowing fertilizer-straw uniform cover” integrated machine. In accordance with the agronomic requirements of corn and soybean strip compound planting, the structure of the integrated machine was designed, and its working principle and corresponding technical parameters were given; according to the agronomic characteristics of corn and soybean strip compound planting, the lateral spacing of the straw clearing assembly in the straw clearing and mulching device was determined through theoretical calculations; by combining orthogonal experiment and discrete element simulation, simulation analysis and parameter combination optimization were carried out on the structure of straw clearing and mulching device, when the operating speed was 9.9km/h, the rotational speed of cutter shaft was 625r/min, the number of helix heads of the straw clearing assembly was 3, and the inclination angle of stubble spreading control plate was 90°, the straw clearing rate was 91.03%, the mulching uniformity was 87.05%, and the equivalent power consumption was 9.79kW; adopting the single-factor experiment method, the whole machine field performance experiment was implemented in the corn stubble land with 1.48kg/m2 residue of crushed straw after machine harvesting, and the results showed that when the operation speed was 7.2km/h (to ensure the normal work of the seed dispenser of the experimental prototype), the grain spacing of soybean was 8cm, the grain spacing of corn was 10cm, the depth of the knife teeth in the soil was 50mm, the machine passed well, the qualified index of grain spacing of soybean and corn were 79.50% and 88.66%, the index of reseeding were 4.03% and 3.66%, the index of leakage of seeding were 16.48% and 7.68%, and the coefficient of variation were 28.49% and 21.31%, respectively, and the qualified rate of sowing depth of soybean and corn were 90%, the qualified rate of fertilizer depth were 80%, and the qualified rate of horizontal spacing of seed and fertilizer were 80%, the uniformity of straw covering was 88.97%, and there was no seed drying phenomenon in the field after sowing. The research results laid the foundation for the development of the integrated machine for precision sowing of corn and soybean strip compound planting and the popularization and application of technology of corn and soybean strip compound planting.

Abstract:Aiming at the problems of uneven surface and excessive size difference of large particle size of the Cyperus esculentus, which led to the instability of filling and carrying of the seeding device, and it is difficult to achieve accurate seeding, a twohole parallel airsuction roller precision seed metering device for Cyperus esculentus was designed in accordance with the agronomic requirements of equidistant planting of two seeds in one hole. Taking Cyperus esculentus as the research object, the structure and basic principles of the seed discharger were elaborated, the key components of the seed discharger were designed, its structural parameters were determined, and the mechanical analysis of the seed filling and seed carrying process was carried out and a seed dynamics model was constructed. Fluent simulation was used to analyze the pressure and velocity distribution of the cross-section flow field at different locations under different distribution combinations of double holes, and the best combination of holes was optimally determined. Combined with the single factor test, the main parameters affecting the seed discharge performance were further analyzed. The rotation speed of the seed discharge disk, the negative pressure of the air chamber and the diameter of the mold hole were selected as the test factors, the three factor and five level quadratic rotation orthogonal combination test was carried out with the qualification index, the missing index and the reseed index as the evaluation indexes of seeding performance. Multiple regression analysis was carried out on the experimental results to determine the primary and secondary factors affecting the performance indicators of the seed discharge device, and the optimal parameter combination was determined through multi-objective optimization: the speed of the seed discharge disk was 34.3r/min, the negative pressure was 19.79kPa, and the diameter of the mold hole was 6.83mm. The results of this parameter combination were verified by bench test, and the qualified index was 92.1%, the missed sowing index was 3.63%, and the reseed index was 4.27%, which met the requirements of precision sowing for Cyperus esculentus and improved the uniformity of seeding.

Abstract:Due to the low mechanization and standardization level of the vegetable seedling and the lack of germinated-seed assisted planting machine in the small and medium-sized seedling factory of China, a simple split-type substrate filling machine for factory vegetable plug-tray seedling was developed. It mainly included five parts: stirring sub-system, discharge subsystem, tray transmission sub-system, screeding sub-system and control sub-system. The test results showed that it can successively finish the pre-wetting stirring, discharging, plug-tray filling and scraping on the plug-tray, and further digitally display the temperature and humidity, pH and EC values of the pre-wetting seedling nursing substrate. When the diameter of the hole in the bottom of the discharge port was 34mm, the rotation speed of the double helical substrate-distributing roller was 80r/min, and the moving speed of the conveyor belt was 0.44m/s, the machine had the best performance in the plug-tray filling, reaching 99.05%. At this time, the filling efficiency was 300 plug trays/h, and the selected sensor can digitally show the temperature, humidity, pH and EC values of the substrate so that large quantities of standardized factory seedlings can be achieved.

Abstract:Aiming at the low efficiency and inconsistent quality in manual pre-cutting of solanaceous crop seedlings before grafting, a whole-tray mechanical pre-cutting method was proposed to expand the operational space for subsequent on-tray grafting and improve work efficiency. A novel whole-tray pre-cutting device for solanaceous seedlings was designed, featuring a tilted tray conveyor system and a height-adjustable cutting mechanism. The designed device can adapt to different rootstock and scion varieties. Establishing tissue structure models of tomato, pepper, and eggplant seedlings based on microscopic imaging, as well as models of different blade angles by ANSYS, and simulate the cutting effects of different blade angles on seedlings. The simulation results showed that a cutter with a 30°blade angle produces the smoothest seedling cross-sections. To further validate the device's performance, entire trays of tomato, pepper, and eggplant seedlings were subjected to a four-factor, three-level response surface analysis experiment by using Design-Expert. The experimental results indicated that the best pre-cutting effect was achieved under the parameters of conveyor speed at 0.3m/s, cutting rate at 0.633m/s (motor speed: 3500r/min), air-blowing angle at 140°, and air pressure at 0.5MPa. The average success rate of pre-cutting is 98.9%, and the processing efficiency is 600 trays per hour (for 72cell trays). This study can provide certain technical and experimental bases for the research and development of the pre-cutting device of the grafting machine.

Abstract:In order to investigate the primary reason of increased lodging rate due to increased operating speed of planting mechanism of rapeseed blanket seedling transplanter, the motion process of seedling transfer, seedling pushing and seedling block contacting the soil was analyzed, and the kinematics model was established. The equations of motion and force of the rapeseed blanket seedling block during the planting process and the equilibrium equations of the seedling standing were derived. The design parameters of the planting trajectory on the landing angle of seedling block, the landed angular velocity of seedling block and seedling standing situation were analyzed. Based on Matlab GUI, a blanket seedling motion process auxiliary analysis software was written to optimize a set of institutional parameters that could satisfy the requirements of rapeseed blanket seedling planting, mainly including the eccentricity of elliptical gear of 1.5, the gear module of 2.3mm, the tooth number of 19, the initial installation angle of planet carrier of 38°, the initial phase angle between the planting arm and the planet carrier of 42°, the length from the center of the planetary gear to the seedling needle tip of 142mm. Trajectory verification and bench testing were carried out. The results showed that when transplanting rapeseed blanket seedlings with seedling age of 35d and seedling height of 80mm, and setting the planting frequency of 220 holes/min, with the increase of forward speed, the lodging rate was increased and the planting qualification rate was decreased. The blanket seedling lodging rate was increased significantly when the forward speed was increased from 600mm/s to 700mm/s, which was basically consistent with the theoretical calculation of critical forward speed result of 670mm/s for seedlings standing. When the forward speed was 600mm/s, the lodging rate of the planting mechanism was 9.67%, which was 68.81% lower than before the optimization, and the qualified rate was 88.67%, which was 31.69% higher than before the optimization. Under this condition, the seedling blocks fell to the ground with upright posture, which achieved the transplanting requirements of rapeseed blanket seedlings. The correctness of the theoretical model and the reasonableness of the optimization of the trajectory parameters were verified by experiments.

Abstract:Potato (Solanum tuberosum L.), the fourth-largest staple crop in China, is widely cultivated in the northwest dryland farming regions. Focusing on the typical operating conditions in northwest terraced fields, where plots are small, irregularly shaped, and roads are narrow, which caused significant difficulties for potato combine harvesters when turning and maneuvering in the field. The predominant planting method in this region involved large ridged double-row planting with black plastic film covering and soil placed on top. Many harvesters in the area faced issues such as low operational efficiency, poor tuber-soil separation performance, high tuber damage rates, and high impurity rates. To address these challenges, a potato combine harvester based on multiple steering modes and anti adhesion soil fragmentation type was designed. This harvester can simultaneously perform multiple operations, including digging, tuber-soil separation, membrane separation, surface soil cleaning, sorting, collection, bagging, and automatic unloading. The overall structure of the machine and its key operational parameters were determined based on the harvesting agronomic requirements and field conditions in the primary potato-producing areas of northwest terraced fields. Initially, relevant design principles from automotive and tractor engineering were applied to determine the structure and key parameters of a multi-mode steering wheeled chassis. Furthermore, inspired by the burrowing principle of the northwest mole’s head, bionic research methods were employed. Using 3D scanning technology and reverse engineering, the geometric parameters of the mole’s head were obtained, and a composite biomimetic wedge-shaped digging shovel device was designed. A dynamics model analysis approach was then used to specifically determine the operational parameters and force analysis for the multi-mode steering wheeled chassis, the composite biomimetic wedge-shaped digging shovel device, the soil-crumbling separation and conveying device, agricultural film and seedling removal device, as well as the manual impurity removal and automatic grading device. Based on these research findings, the entire machine was thoroughly designed by using 3D modeling and 2D drafting, and a prototype was manufactured. Field tests were conducted, and the results showed that the loss rate was 1.98%, the tuber damage rate was 1.59%, the skin-breaking rate was 2.15%, the impurity rate was 1.84%, and the productivity ranged from 0.21hm2/h to 0.36hm2/h. The potato combine harvester based on multiple steering modes and anti-adhesion soil fragmentation type met national and industry standards in all test indicators, providing valuable reference for the mechanization of potato harvesting in northwest dryland areas.

Abstract:Aiming to enable automated apple picking, a single-drive cableless pneumatic apple picker with a simple structure that can be portable and mounted on an automated picking device was proposed. The apple picker was driven directly by a micro-pump with three arc-shaped fingers symmetrically distributed in the center and driven by a single linear pneumatic flexible actuator. The picker fingers were normally closed, and opened when air pressure was applied, and passively retracted to grasp the apple after the pressure was released. Based on the characteristic parameters of apples in the Jilin region, the design and size parameters of key components of the cableless pneumatic apple picker were determined, and an integrated cable-free picking system was designed. Based on the deformations and mechanical properties of the flexible actuator, a kinematic and gripping force model of the apple picker was created to evaluate the functionality of the apple picker. The results showed that the pneumatic apple picker opened and closed quickly with gripping force and opening angle that met the target apple picking requirements. Using an arm-like mobile robot, apple-picking experiments were conducted in the laboratory and in the orchard. Experimental results demonstrated that the pneumatic apple picker was able to safely and steadily grasp apples throughout the picking process with an 84.9% success rate, which was capable of performing apple picking operations in complex orchard environments.

Abstract:Aiming at the problem of low grading precision of traditional automatic grading machine of distinguished and high-quality fresh tea leaves, sorting fresh tea leaves by machine vision is an effective way to improve the quality of tea grading. And a PSO-Fuzzy-PID controller introducing adaptive weights and Circle chaotic mapping was designed; the research on the control and test of conveying speed of fresh tea leaves based on improved Fuzzy-PID was carried out to address the problem of large fluctuations in the conveying speed of fresh tea leaves leading to the image blur. The results showed that the thesis algorithm had better optimization performance and convergence speed; during the operation of the conveying transmitting system of fresh tea leaves, when the conveying speed was set at 78.5mm/s, its speed was recorded every 1ms, the transmission speed fluctuation was controlled at 0.7mm/s; the transmission system response time of the improved Fuzzy-PID was reduced by 81.41% and 61.74% compared with that of the traditional PID and Fuzzy-PID, respectively; the overtone was reduced by 81.24% and 41.82%. The core contribution was to significantly improve the stability of the transport speed of fresh tea leaves, thus effectively reducing the degree of image blur caused by speed fluctuations and making the acquired images closer to the clear state. Therefore, the research result not only ensured that the automatic bud and leaf classification system based on machine vision can be accurately and stably controlled, but also provided a practical technical solution to solve the scientific problem of image blurring caused by the fluctuation of conveying speed.

Abstract:In order to solve the problems of uneven cutting depth and poor adaptability of bark undulation in rubber tapping machinery, a laser ranging and depth control rubber tapping machine was designed, and the trajectory dynamics in rubber tapping operation were analyzed by constructing a mathematical model, and the trajectory analysis equation was obtained. Based on the geometric relationship between the rubber tapping actuator and the rubber tree, the tool distance adjustment calculation method was determined, the influence mechanism of the distance angle of the ranging point on the adjustment error of the rubber tapping knife was clarified, and the trajectory walking and precise control of the tool in the rubber tapping process were realized by using the Arduino control board. The orthogonal test was carried out with the speed of the displacement motor, the skin consumption and the threshold range of cutting depth as the test factors, and the number of adjustment times, pressure variance and cutting depth qualification rate of a single rubber tapping tool were used as evaluation indicators. The test results showed that under the conditions of the speed of the displacement motor was 24r/min, different skin consumption and threshold setting range, the pass rate of cutting thickness can reach more than 87%, which was the best rubber tapping effect when the speed of the displacement motor was 24r/min, the skin consumption was 1.3mm, and the threshold range of tapping depth was -0.1~0.1mm, the pass rate of tapping thickness was 95.74%, the average number of tool adjustments was 22.33 times, the pressure variance was 14.89N2, and the smoothness of the cutting surface was good, which met the requirements of tapping depth control.

Abstract:The tip clearance is unavoidable due to the rotation of the impeller during the operation of the hydraulic machinery. The tip leakage vortex and its cavitating flow due to the tip clearance can easily lead to the reduction of key performance parameters such as the pump head and efficiency, and with the enhancement of adverse phenomena such as vibration and noise, which seriously deteriorated the safe, stable and efficient operation of the axial-flow pump, and even caused damage to the pump device. In order to study the effect of tip clearance on the cavitation in a pump unit, slanted axialflow pumps without tip clearance and with three different tip clearances (δ/R=0.0010, 0.0033 and 0.0067) were numerically studied based on SST-CC model and ZGB cavitation model. The study focused more on the correlation between the cavitation and energy performance of the pump. The results showed that the tip clearance mattered the energy performance of the slanted axialflow pump under both free and cavitation conditions, and the energy loss due to this got larger as the tip clearance was increased. The cavitation flow pattern of the case with narrow tip clearance (δ/R=0.001) had little difference from that of the case without tip clearance, and both of them presented as the blade surface cavitation. However, in the cases with the larger tip clearances (δ/R=0.0033 and 0.0067), the sheet cavitation clearly appeared and merged with the blade surface cavitation to form a wedge-shaped cavitation. The cavitation led the phenomenon that water convergence and flow separation on the suction surface, and the interaction between the flow separation and wake flow from the impeller resulted in the passage vortex. This phenomenon was shown to be more pronounced and higher as the tip clearance appeared and increased. Besides, the cavitation and tip leakage flow regions were highly coexisting, indicating that the sheet cavitation was generated by the cavitation bubbles carried by the tip leakage flow. The energy performance of slanted axialflow pump under the cavitation condition was mainly caused by the passage vortex and the tip leakage vortex, and the intensity, scope and energy loss caused by both vortexes was increased with the increase of tip clearance size.

Abstract:Aiming to address the challenges of difficult annotation, complex features, and low boundary extraction precision for solid waste in remote sensing imagery, a two-stage method was proposed based on weakly supervised learning: in the first stage, an image-level labeled dataset was utilized to conduct comparative experiments among five network models, ultimately selecting the Swin Transformer as the feature learning model. Subsequently, the gradient-weighted class activation mapping was employed for feature region visualization to obtain heatmaps. These heatmaps were further processed by using a combination of adaptive thresholding and color difference methods to obtain a rough outline of the solid waste. In the second stage, the DeepSnake model was employed for optimization to achieve refined contours. This study utilized unmanned aerial vehicle (UAV) multispectral remote sensing image data to conduct experiments in six typical urbanrural interface areas within the Langfang Development Zone, Hebei Province. The results of the experiments were as follows: in the first stage, testing of the five network models revealed a pronounced advantage for the Swin Transformer in feature extraction quantitative analysis, with a precision of 93.8%, recall of 95.0%, and F1 score of 94.4%. Visualization of attention regions also indicated that it had the best recognition effect. The coarse outline extraction by using the combination method of adaptive thresholding and color difference demonstrated superiority in the binary comparison experiment. In the second stage, quantitative analysis of fine contour extraction evaluated by using the average precision (AP) metric from the COCO dataset, yielded an AP value of 91.3% at IOU 0.5 and 77.5% at IOU 0.75; moreover, qualitative comparison of contour extraction between the first and the second stages highlighted the optimization effect of DeepSnake. The results demonstrated that this study can accurately identify and extract solid waste by using an image-level labeled dataset, offering pronounced accuracy advantages and providing a viable method for the ecological environment management of urban and rural areas in China.

Abstract:To address this challenge and achieve high-quality development, the scientific construction of the ecological security pattern in coastal areas can effectively balance regional development and ecological protection. Taking Dongying City, a coastal resource-based city, as an example, the ecological sensitivity assessment was used to identify ecological sources. Based on the distribution patterns of crucial ecological elements such as land, rivers and beaches, ecological source partitions were delineated. The security pattern of “surface (ecological sources)-line (ecological corridors)-point (ecological pinch points, ecological barrier points)” was then constructed from the perspectives of dispersed ecological sources and ecological source partitions, and key areas for ecological protection and land space restoration were comprehensively identified. The results showed that there were 49 ecological sources in Dongying City, mainly distributed in lowaltitude coastal wetland regions of the north and east, mainly distributed in of which 17 ecological source partitions were identified. The integrated resistance value was up to 98.742, with high resistance predominantly clustered in the built-up area and its vicinity. Totally 84 ecological corridors from ecological sources and 24 from ecological source partitions were established, the overlapping ecological corridors had more ecological significance. Moreover, totally 72 ecological pinch points were identified, particularly emphasizing the need for focused maintenance at the river corridor. Additionally, totally 54 ecological barrier points were mainly concentrated in Dongying District, Kenli District and Lijin County. Tailored protection, maintenance, management, and restoration strategies were proposed for types of critical areas, aiming to coordinate comprehensive ecological protection across “land-river-beach-sea”and provide a reference for constructing and optimizing the ecological security pattern in similar coastal areas.

Abstract:Aiming to solve the problem that it is difficult for spaceborne light laser detection and ranging (LiDAR) global ecosystem dynamics investigation (GEDI) emitted laser pulses to penetrate the forest canopy in dense forest areas to accurately obtain understory terrain information, and the overlap between GEDI stand canopy echo and understory terrain echo will be increased in highslope terrain, and it is difficult to estimate forest canopy height with high accuracy, combined with the characteristics of defoliation in winter broad-leaved forest and the strong penetration advantage of GEDI emitted wave laser pulse, a model of forest canopy overestimation in different seasons was constructed by using the GEDI waveform length parameters. The accuracy of forest canopy height estimation in summer and winter was analyzed by using different percentage waveform length parameters (rh_aN) of GEDI. Subsequently, terrain slope factor DTM data was introduced to correct the forest canopy height estimation model, segmenting forest canopy height estimation based on terrain slope, thereby addressing the problem of low accuracy in forest canopy height estimation caused by the overlap between canopy echoes and terrain echoes due to steep terrain. The research results showed that the coefficient of determination R2 of forest canopy height estimation accuracy in summer was 0.573, with root mean square error (RMSE) of 3.695m; in winter, the R2 was 0.633, with RMSE of 3.671m. After correcting the forest canopy height estimation model with terrain slope, the overall estimation accuracy in winter, with R2 of 0.709 and RMSE of 3.271m, was significantly improved. Accuracy of forest canopy height estimation in winter was markedly better than in summer, and the introduction of terrain slope factors effectively enhanced the accuracy of forest canopy height estimation under different terrain slope conditions.

Abstract:The application of trace amounts of sugar solution additives to tobacco leaves is a critical step in the tobacco processing and cutting technology, significantly impacting the physical and chemical properties of the leaves and enhancing cigarette quality. However, current precision detection methods for sugar solution additives primarily focus on dosage monitoring, lacking an evaluation of the post-application effects.The hyperspectral imaging technology and deep learning methods were utilized to perform non-destructive detection and visualization analysis of trace additives in tobacco leaves after sugar solution application. A prediction system based on a deep learning convolutional neural network (CNN) model was developed, incorporating multiple spectral preprocessing methods and feature band selection techniques to optimize model performance and improve the detection accuracy of additive content in tobacco leaves. Spectral data from tobacco samples with varying proportions of propylene glycol were collected by using a hyperspectral imaging system. The data were preprocessed by using three methods: standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky-Golay filtering, which were employed for data preprocessing respectively. Feature bands were selected through competitive adaptive reweighted sampling (CARS), principal component analysis (PCA), and identification of spectral trough points, resulting in six common consistent key wavelengths at 1146nm, 1614nm,2511nm, 2517nm, 2522nm, and 1941nm. CNN, random forest (RF), and partial least squares regression (PLSR) models were constructed to predict the additive content, with hyperspectral data visualization conducted by using the CNN method. The results showed that the SNV-PCA-CNN model achieved the best predictive performance for both the training set (R2C was 0.9880, RMSE was 0.0020kg/kg) and the test set (R2P was 0.9896, RMSE was 0.0021kg/kg), and the cumulative contribution rate was close to 99% by taking the first-four principal components, demonstrating excellent fitting and generalization capabilities. The predictive ability of the deep learning CNN model significantly outperformed the performance of traditional machine learning methods RF and PLSR, reflecting the CNN model sufficient generalization capabilities for hyperspectral data of tobacco samples with sugar solution additives. The combination of hyperspectral imaging and the CNN model showed great potential for detecting trace additives in tobacco leaves, providing technical support for non-destructive testing and precise control in the tobacco processing industry.

Abstract:In order to achieve high-precision and rapid prediction of carbon and oxygen elements and active groups on the surface of biochar, a data set containing quantitative characterization information of midinfrared spectroscopy and surface carbon and oxygen elements and their occurrence forms was established based on 120 groups of biochar samples accumulated by the research group. Using support vector machine (SVM) and random forest (RF) machine learning intelligent modeling methods, combined with interval partial least squares (IPLS) and principal component analysis (PCA) and other feature selection strategies, four prediction models of IPLS+RF, IPLS+SVM, PCA+RF and PCA+SVM were constructed, and the quantitative and rapid prediction of surface carbon and oxygen content (S_C,S_O) and eight carbon and oxygen occurrence forms, a total of ten prediction targets, was realized. Among them, there were five forms of C=C, C—C, C—O, C=O, O=C—O from the C1s energy spectrum and three forms of C=O, C—O, O=C—O from the O1s energy spectrum. The results showed that the main occurrence forms of carbon on the surface of biochar were C_C=C and O_C—O, and the main occurrence forms of oxygen on the surface of biochar were C_C—O, C_C=O, C_O=C—O and O_C=O; the characteristic bands of 4000~3464cm-1 and 1588~650cm-1 both contained characteristic information highly related to the content and speciation of carbon and oxygen on the surface of biochar, but the information contained in 1588~650cm-1 was more abundant. From the perspective of model prediction accuracy, the four prediction models of IPLS+RF, IPLS+SVM, PCA+RF and PCA+SVM all had good prediction ability, especially IPLS+SVM and PCA+SVM. The coefficient of determination of the optimal model for ten prediction targets was above 0.93; however, from the perspective of model stability and generalization ability, C_C—C, C_O=C—O, O_C=O, O_C—O still needed to be further improved.

Abstract:Aiming to address the challenges of accuracy and efficiency in rice disease detection under natural conditions, a lightweight detection model, YOLO-RD, was presented based on an improved YOLO v5s framework. The model was optimized and successfully deployed on edge computing devices, enabling the creation of a portable device for fast rice disease detection. In the proposed model, GhostNet was integrated to reduce computational complexity and the number of parameters. Finally, the lightweight Shuffle Attention mechanism and the dynamic detection head DyHead were employed to enhance feature extraction and adaptive detection capabilities, particularly for complex disease features. Furthermore, the standard CIoU loss function was replaced by Shape-IoU to improve detection performance in challenging environments by focusing on shapebased regression. Experimental results demonstrated that YOLO-RD achieved a mean Average Precision (mAP) of 94.2%, while significantly reducing computational complexity and parameter size. Specifically, YOLO-RD reduced computation, parameters, and weight by 44.4%, 43.2%, and 41.3%, respectively, compared with the baseline model. In addition, the model outperformed detection models such as YOLO 11n, YOLO v8n, YOLO v5n, and others in terms of accuracy. When deployed on a raspberry Pi 4B edge computing device, YOLO-RD achieved an inference time of 1.97 s per image, meeting the requirements for real-time application. These findings suggested that YOLO-RD offered an efficient and robust solution for intelligent rice disease detection in practical agricultural scenarios.

Abstract:Robotic automated harvesting proves to be an efficient solution for greenhouse tomato cluster harvesting operations. The ripeness of tomato clusters stands as a vital criterion influencing the decision-making process for the harvesting robot. Aiming to employ Deep White-Balance and Zero-DCE deep neural networks for color cast correction and shadow detail enhancement in tomato images to enhance image quality by addressing color cast issues and improving local illumination in both fill light and night environments, the concept of the deep residual shrinkage network was introduced, incorporating the RSBottleneck-CW module into YOLO v5s. This module conducted soft threshold processing on the feature map to effectively suppress noise interference in the image. Experimental results demonstrated that in the night environment, after enhancing the image solely with the Zero-DCE algorithm, the recall of the detection model reached 0.924, capturing more tomato fruits and trusses. In a supplementary light environment, the image underwent joint processing with Deep White-Balance and Zero-DCE to restore authentic colors and enhance texture details. This resulted in the detection model achieving an mAP of 0.849, reflecting a 0.038 increase compared with that of the before processing. The YOLO v5s integrated with the RSBottleneck-CW module exhibited robust adaptability to feature map noise. Irrespective of whether the image underwent depth enhancement, its mAP and F1-Score consistently surpassed those of the original YOLO v5s. In the nighttime environment, the highest recorded mAP and F1-Score values were 0.902 and 0.844, respectively. Similarly, in the supplementary light environment, the peak mAP and F1-Score values reached 0.868 and 0.817, respectively. After the detection model detected the fruits and trusses, the final ripeness level of the tomato clusters were determined by using the bounding boxes aligning algorithm. In the ripeness stage of tomato clusters ranged from 90% to 100%, the average absolute errors in ripeness recognition under nighttime and supplementary light conditions were 1.837% and 1.067%, respectively. These findings can serve as decision-making criteria for night automated harvesting operations of tomato-picking robots.

Abstract:Under practical Panax notoginseng cultivation scenarios, due to the visual similarities between diseases such as gray mold and plague, as well as small individual targets with complex and variable shapes of diseases such as anthracnose under natural conditions, current methods face a difficult problem of P.notoginseng leaf disease segmentation. A modified Transformer-DCNv2-BlendMask model for P. notoginseng leaf multicategory diseases image segmentation was proposed. To deal with the visual similarity problem and variable shape targets appeared on P. notoginseng leaf disease, a Transformer encoder to capture long-distance dependencies for multiple disease categories was introduced. And the deformable convolution networks v2 (DCNv2) showed a better adaptability of convolutional networks by enabling free-form deformation of the convolution to segment disease with various shape. The model and other instance segmentation models such as BoxInst, ConInst, SOLOv2, Mask R-CNN and YOLO v8-seg on the P. notoginseng leaf disease dataset, which contains multi-category diseases were compared. The results demonstrated the competitive performance of our model, achieving a average precision (AP) of 86.14%, outperforming the baseline BlendMask model by 3.17 percentage points and the previously best-performing Mask R-CNN by 4.37 percentage points. It also exceeded the baseline by 0.16 percentage points, 4.32 percentage points and 4.46 percentage points for the gray mold, plague and anthracnose categories, respectively. Thus, our method provides a robust solution for segmenting shape-variable and visually similar diseases in complex environments, helping to achieve accurate quantification of diseases.

Abstract:In order to solve the problems of traditional ant colony algorithm in agricultural machinery path planning, such as initial blind searches, deadlock, slow convergence rate, and low-quality converged path, a path planning method based on jump point optimized ant colony algorithm (JPOACO) was proposed. Initially, the jump point search optimization algorithm was employed to preprocess the map, thereby obtaining simplified jump points. These simplified jump points were utilized for pheromone initializing on the grid map, to enhance the guiding capability of simplified jump points and reduce blind search in the early stages. Secondly, a punish mechanism for dead ant was designed to lower the pheromone levels on paths traversed by ants which fell into deadlock, and to decrease the occurrence of deadlocks. Furthermore, the heuristic information function was redesigned and a hierarchical pheromone factor was introduced to enhance convergence speed and shorten the converged path length. Finally, a path optimization strategy was applied to eliminate unnecessary path nodes, further reduce converged path length and improve smoothness, ultimately improve the converged path quality. Simulation results showed that in simple environments, the JPOACO algorithm reduced path length by about 22.6% and 2% in comparison with traditional ant colony algorithm and other optimized ant colony algorithms, respectively. It also decreased convergence number and convergence time by about 77.0%, 77.5% and 49.3%, 87.8%, respectively. The zero-death number and zero-death time were reduced by about 19.5% and 80.5% in comparison with the latter. In complex pineapple planting environments, JPOACO achieved a path length reduction of 16.6% and 4.7%, decreased convergence number and convergence time by about 77.1%, 17.4% and 73.7%, 47.4%, respectively. The zerodeath number and zerodeath time were reduced by about 34.3% and 58.2% in comparison with the latter. These results indicated that the JPOACO algorithm was highly feasible and applicable.

Abstract:With the transformation of pig breeding industry to largescale and intensive, non-intrusive individual identification technology is very important for traceback, food safety, disease control and scientific breeding. Pig facial landmark detection serves as a fundamental requirement for achieving non-invasive pig identification. A pig facial landmark detection model named FCM-SimCC was introduced, building upon the SimCC landmark detection algorithm. The model replaced CSPDarkNet with FasterNet for feature extraction and incorporated the CA attention mechanism within FasterNet to enhance the capture of long-distance features. Supervision of the model was achieved through the MLT adaptive weight multi-task loss function combined with KL divergence loss and Wing Loss. Test on a dataset of 4861 images was done, representing a variety of pig breeds and facial poses, the FCM-SimCC model attained mean average precision, 50% average precision, and 75% average precision of 76.12%, 93.44%, and 83.25%, respectively. These results indicated improvements of 3.14, 1.77, and 4.47 percentage points over the original model, with a reduced computational demand to 2.79×109 and a parameter count of 1.38×107, marking a 38.68% decrease in floating-point operations and a 20.16% reduction in parameters. When compared with mainstream landmark detection methodologies such as DeepPose, HRNet, and YOLO X-Pose, the FCM-SimCC model showcased its ability to provide rapid and precise pig facial landmark detection with lower computational resources and fewer parameters, offering valuable insights for similar tasks in pig facial landmark detection and individual pig identification.

Abstract:Aiming to enhance the accuracy and interpretability of current heat stress prediction models for dairy cows, the extreme gradient boosting algorithm (XGBoost) was employed by using infrared body surface temperature and potential influencing factors. A Shapley value-based method, SHAP, was introduced to interpret the prediction outcomes. The maximum temperature (IRTmax) and average temperature (IRTave) from the trunk, fore udder (UD), face, and eyes were selected as body surface temperature variables, and environmental parameters and cow-specific variables were integrated to create a feature subset. The findings revealed that under heat stress conditions, the IRTmax and IRTave of the four body parts were significantly higher than that under non-heat stress conditions （p<0.01). Among the ensemble models compared, i.e., random forest, adaptive boosting, and gradient boosting decision trees, the XGBoost model, optimized through grid search and using fore udder infrared temperature (IRTave_UD) as a key feature, demonstrated the highest accuracy in predicting heat stress, achieving 80.8% accuracy, an F1 score of 79.2%, and an area under the ROC curve (AUC) of 0.873. SHAP analysis indicated that the average infrared temperature of the fore udder (IRTave_UD) positively correlated with heat stress likelihood, while lactation days showed a negative correlation. These two indicators were crucial for identifying heat stress in cows. The research findings can provide valuable technical support for precise cooling management in dairy barns during the summer season.

Abstract:Traditional manual measurement of poultry comb and wattle areas poses contact-induced stress risks, zoonotic disease transmission hazards, and substantial measurement errors. A non-contact measurement system integrating YOLO v7 with an improved U-Net architecture was proposed. Three key innovations were presented: a dual-stage detection framework utilizing YOLO v7 for head pose screening and ROI extraction, effectively eliminating offangle image interference; a novel CoT-UNet model incorporating Contextual Transformer blocks into U-Net’s encoder for dynamic-static context fusion, combined with DyC-UP module employing dynamically adjustable convolution kernels to enhance irregular edge detection; a pixelarea conversion algorithm achieving precise spatial mapping through calibration coefficients. Experimental results demonstrated significant improvements: the enhanced CoT-UNet outperformed baseline models by 4.77 percentage points (comb) and 8.75 percentage points (wattle) in IoU, along with 5.31 percentage points and 5.06 percentage points precision gains respectively. Absolute measurement errors for comb (0.62~3.50cm2) and wattle (0.10~2.93cm2) showed marked superiority over manual methods (3.58~7.27cm2). Multi-scenario validation revealed stable relative errors of 2.41%~13.62% for combs and 1.00%~29.21% for wattles across varied postures (three types), angles (two positions), and distances (two levels). This automated system enabled stress-free poultry biometric measurement, providing reliable technical support for intelligent breeding selection.

Abstract:In order to achieve accurate classification of caged laying hens-sounds and intelligent, non-contact detection of laying hens-health, emotion, production status and other information, a caged laying hens-sound classification and recognition method based on improved MobileNetV3 was proposed. The heat stress sound, fright sound, egg-laying sound and singing sound produced by laying hens under cage conditions were collected from Xinhua No.2 laying hens as research object, the one-dimensional sound signals were transformed into three-dimensional Mel-spectrograms after sound pre-processing, and the laying hens’sound data set consisting of 8541 Mel-spectrograms was established. The accuracy of sound classification for caged laying hens was improved by introducing the efficient channel attention (ECA) module in MobileNetV3. The experimental results showed that the MobileNetV3-ECA model achieved 95.25%, 95.16%, 95.02% and 95.08% of accuracy, recall, precision and F1 score, representing an enhancement of 1.99, 2.08, 2.00 and 2.04 percentage points, respectively, in comparison with the original model. Comparing the models with the introduction of coordinate attention (CA) and convolutional block attention module (CBAM) respectively, the accuracy of the model was improved by 2.11 and 2.03 percentage points with the introduction of the ECA module. Significant improvements were also seen in other metrics. The accuracy of MobileNetV3-ECA was improved by 1.99, 2.03 and 2.50 percentage points compared with that of ShuffleNetV2, DesNet121 and EfficientNetV2. The MobileNetV3-ECA based sound classification and recognition method for laying hens proposed provided algorithmic support for automated and intelligent sound detection in the large-scale breeding of laying hens, and also provided a reference for the function optimization of poultry house inspection robots, and opened up a way of thinking for heat stress early warning of large-scale caged laying hens.

Abstract:The objective was to reveal the spatial and temporal distribution of apple tree fine roots under different water and fertilizer integration modes, explore the regulatory effect of different drip irrigation fertilization strategies on the growth of apple tree fine roots, and provide a theoretical basis for regulating the growth of apple tree fine roots by drip irrigation fertilization mode. In 2019—2021, a two-factor two-level complete combination design field experiment was carried out, the capillary laying method was set up with one row-one tube and one row-two tubes, the fertilization cycle was set for 15d and 30d, and the growth and death of fine roots during the active growth period of apple trees were continuously observed by microroot tube in situ monitoring technology, and the response dynamics of fine root growth and turnover of apple trees to capillary laying mode and fertilization cycle were analyzed. The existing length density and growth of fine roots changed dynamically with the seasons to a unidial curve, and the amount of fine root death was a bimodal curve. The fertilization cycle of 15d significantly increased the existing length density, growth and death of fine roots in time and space distribution compared with the 30d of fertilization cycle. The effect of capillary arrangement on the existing length density and death of fine roots in apple trees did not reach a significant level in time, and the effect on fine root growth changed with seasonal changes. In terms of spatial distribution, the existing length density, growth and death of fine roots in one row-two tubes were significantly greater than those of one row-one tube in the 19~38cm soil layer, and the law was reversed in the soil layer of 57~76cm. The capillary laying mode and fertilization cycle and its interaction had a significant impact on the root turnover rate, the one row-one tube fertilization cycle of 15d can accelerate the turnover of fine roots compared with other treatments. The fertilization cycle had a more obvious regulatory effect on the growth and death of fine roots in apple trees, and the capillary laying method can adjust the spatial distribution of fine roots, and the 15d treatment of one row-one tube fertilization cycle was more conducive to improving the existing length density and growth of fine roots, accelerating the turnover of fine roots, and optimizing the spatial distribution of fine roots.

Abstract:The Inner Mongolia Autonomous Region is an important ecological security barrier in northern China. It is of great significance to study the mechanism of vegetation change and hydrothermal factors in the Inner Mongolia Autonomous Region. Based on normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2020 in Inner Mongolia, a path analysis method was used to analyze the direct and indirect effects of temperature and precipitation on vegetation cover change in Inner Mongolia. The Copula function was used to establish the probability distribution function to describe the dependence of precipitation-NDVI and temperature-NDVI under different values, which provided scientific basis for ecological construction in this region. The result showed that from 1982 to 2020, the precipitation in Inner Mongolia decreased at a rate of 0.357mm/(10a) (P=0.276), the temperature increased at a rate of 0.243℃/(10a) (P<0.001), and the NDVI increased at a rate of 0.009/(10a) (P=0.228), and the improvement area was much larger than the degradation area. Precipitation and temperature inhibited vegetation growth through each other. The comprehensive path coefficient of precipitation on vegetation NDVI was positive (0.927), while the comprehensive path coefficient of temperature on vegetation NDVI was negative (-0.809), and the direct effect of precipitation on vegetation growth was much greater than the indirect effect of temperature. When the precipitation was 7mm (west), 15mm (middle), 20mm (east) and 10mm (whole area) above the threshold, NDVI was greater than 0.16, 0.3, 0.5 and 0.3, respectively, and the vegetation index was increased with the increase of precipitation and joint probability. NDVI was increased with the decrease of temperature from west to east, and the temperature range conducive to vegetation development expanded to the low temperature area, showing a stepped distribution.

Abstract:Soil salinity affects a range of physiological processes in the cotton fields and is key factor controlling cotton productivity and yield. Two-year experiments (2020 and 2021) were conducted to evaluate the effects of different leaching regimes on soil salinity, aboveground dry matter of cotton, and yield of seed cotton in Southern Xinjiang. There were four leaching amounts (W1: 75mm, W2: 150mm,W3: 225mm and W4: 300mm) and three leaching periods (T1: once at seedling period, T2: twice at seedling and budding periods and T3: thrice at seedling, budding and pollen setting periods) in addition to non-leaching treatment (CK: 85% crop evapotranspiration). During the experiment, soil salinity, aboveground dry matter accumulation, yield seed cotton and economic coefficient (ratio of yield to the total of dry matter accumulation and yield) were measured. The results showed that the leaching could leach the salinity in salinized cotton fields. Compared with the CK treatment, soil salinity in 0~100cm was decreased by 13.17% and 26.57% and the yield was increased by 104.13% and 59.36% in 2020 W4 and 2021 W3, respectively. The results of the Logistic equation to fit the dry matter accumulation were satisfactory (R2≥0.9654, P<0.05) for each treatment. Aboveground dry matter accumulation and seed cotton yield were positively correlated with leaching amount, and there was a difference between the economic coefficient and leaching amount under the same leaching period. The principal component analysis, technique for order preference by similarity to an ideal solution model (TOPSIS), gray correlation analysis and membership function analysis were well correlated with each other, and the correlation coefficients among the models were ranged from 0.92 to 0.99. Based on the overall difference combination evaluation model, the W4T2 treatment achieved the optimum. Further comprehensive analysis, considering the drought and low rainfall in the region, the results suggested that when leaching amount was 225mm and leaching periods at the seedling and budding stages during the reproductive period, the evaluations of comprehensive index (1.3765) was suitable for salinized cotton fields in the drip irrigation. The research result can provide valuable information for improving management of salinized cotton fields in Southern Xinjiang.

Abstract:Setting up an indoor freeze-thaw cycle experiment, with different initial soil water contents (15%, 20%, 25%), different salt contents (original soil, 0.2% NaHCO3), different biochar particle sizes (0~0.5mm, S treatment; 0.5~2mm, L treatment) and the untreated group (CK). The effects of soil pore structure changes on soil permeability and water and salt redistribution under different regulatory measures during freeze-thaw cycle were analyzed. The results showed that freeze-thaw induced soil pore expansion, aggregate fragmentation, soil saturated water conductivity (ks) increased, frozen soil saturated water conductivity (kfs) decreased. In addition, the increase of initial soil water and salt content would increase the damage of soil structure by freeze-thaw action, increase the expansion of soil pores and the change amplitude of ks and kfs after the freeze-thaw cycle, and aggravate the proportion of soil water and salt upward migration during freeze-thaw period. The application of biochar can reduce the expansion of soil pores and improve the stability of soil aggregates during freeze-thaw period. Compared with CK, the ks was decreased by 48.35% and 37.69% on average under S and L treatment, respectively, and the kfs was decreased by 55.44% and 78.55% on average under S and L treatment, respectively. At the same time, biochar treatment can reduce the moisture content of the upper soil (10cm) and increase electric conductivity value. The proportion of large pores and small pores in soil were the key driving factors of ks and kfs, respectively. It was showed that the application of 0.5~2mm biochar had the best effect on soil permeability and water and salt redistribution under freeze-thaw conditions. The research results can provide theoretical basis and technical support for the theoretical research system of water and salt transport in freeze-thaw soil.

Abstract:Currently, China’s livestock breeding industry is rapidly scaling towards intensification, making environmental control in livestock houses crucial. In cold northeastern winters, insulation used to prevent heat loss leads to high humidity levels, which harms livestock. Therefore, an efficient dehumidification system is essential to reduce heat loss and improve conditions. An internal air circulation dehumidification system was designed based on condensation and moisture separation, utilizing natural cold resources for effective dehumidification and energy savings. However, the system’s performance was influenced by several control factors, including the temperature difference between inside and outside, dehumidification airflow rate, and refrigerant flow rate, which affected multiple objectives such as indoor temperature decrease, dehumidification rate, and energy consumption. Thus, the system required a multi-objective control strategy. An improved non-dominated sorting genetic algorithm-Ⅱ (INSGA-Ⅱ) was proposed to optimize the balance between insulation,dehumidification, and energy preservation strategies, avoiding local convergence. Verified through the Zitzler-Deb-Thiele (ZDT) test functions, INSGA-Ⅱoutperformed the traditional NSGA-Ⅱ in both inverted generational distance (IGD) and generational distance (GD), reflecting a closer approximation to true solutions. In optimizing the dehumidification system, the INSGA-Ⅱ algorithm reduced the spacing (SP) value from 0.1118 in NSGA-Ⅱ to 0.0202,significantly expanding the optimal solution domain and preventing local optima. The operational efficiency was increased by 106.42%, and the solution speed was improved. In terms of temperature regulation, the average temperature drop using INSGA-Ⅱ was 1.43℃ lower than that of NSGA-Ⅱ, achieving a 23.06% reduction, which helped to reduce temperature fluctuations and energy consumption 〖JP3〗during dehumidification. Thus, the INSGA-Ⅱ algorithm effectively enhanced the multiobjective optimization and control performance of the internal circulation dehumidification system in livestock houses.

Abstract:Ultrasound is a physical food processing technology with promising industrial application prospects. To develop an ultrasound device suitable for food processing, the COMSOL multiphysics simulation software was used to numerically simulate and calculate the sound field distribution of a slit-type continuous ultrasound device under single-frequency (28kHz and 40kHz) and dual-frequency (28/40kHz) modes. The accuracy of the simulation model calculation was verified through an aluminum foil corrosion test. The simulation results showed that the single-frequency ultrasound sound field generated a negative-phase sound pressure directly below the transducer, and a positive-phase sound pressure with stable vibration was formed in the radiation intersection area around the transducer. The results of the aluminum foil corrosion test confirmed that the surface of the aluminum foil showed an irregular wavy deformation in the negative-phase sound pressure area and a granular pitting corrosion in the positive-phase sound pressure area. By calculating the relative standard deviation of the absolute total sound pressure of the ultrasound sound field directly below the transducer and in the radiation area around the transducer from the simulation data, it was obtained that the lowest relative standard deviation of 28kHz was 0.764, the lowest relative standard deviation of 40kHz was 0.960, and the lowest relative standard deviation of 28/40kHz was 0.658. The lowest relative standard deviation of the 28/40kHz dual-frequency ultrasound was 86.1% of that of the 28kHz single-frequency ultrasound sound field and 68.5% of that of the 40kHz single-frequency ultrasound sound field. The research result showed that the distribution of the dual-frequency ultrasound sound field was more uniform, which can provide a basis for the research and development of efficient food ultrasound processing equipment and offer guidance for the application of slit continuous ultrasound in food processing.

Abstract:Crushing of raw materials is an important process step in feed processing, and hammermill screen breakage is a common failure. Aiming at problems such as the lack of effective contact parameters of crushed particles and inaccurate numerical simulation in the discrete element simulation of the particle screening process in the screen breakage identification device, maize was used as test material to obtain the impact characteristics of the hammermill screen, and on the basis of the particle size distribution characteristics of crushed maize particles, the characteristic particle diameter of crushed maize particles was selected to make test samples. The collision ramptest and funnel test were combined with discrete element simulation. The polyhedral particle model was used to represent the crushed maize particles. The crushed maize particles contact parameters were calibrated.Results showed that the sum of average impact strength of the upper and lower parts of the screen was great and the impact frequency was high, making it easier to break. The coefficients of restitution between crushed maize particles and between crushed maize particles and carbon steel were 0.14 and 0.44, respectively, simulation verification test indicated that the relative errors were 0.56% and 1.95%. The kinetic friction coefficients between crushed maize particles and between crushed maize particles and carbon steel were 0.77 and 0.85, respectively. The relative errors of the simulation verification test were 3.04% and 3.56%.The research result can provide basic data and theoretical basis for analyzing the impact characteristics of the hammermill screen and optimizing the screen breakage identification device.

Abstract:A portable real-time fluorescence detection system was proposed for real-time detection of fresh pork freshness. The system consisted of two main parts, i.e., the research of nitrogen-doped graphene quantum dots (N-GQDs) fluorescent nanomaterials and the creation of portable fluorescence detection device. The morphology, structure and surface functional groups of N-GQDs were analyzed by transmission electron microscopy, Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy, and it was confirmed that N-GQDs was successfully synthesized. The optical properties of N-GQDs were discussed, and it was proved that N-GQDs had excellent sensitivity and selectivity to amines. The response mechanism analysis showed that there was a static quenching effect between N-GQDs and NH3. The portable fluorescence sensor detection device included hardware design and software design, which mainly included five modules, namely light source excitation module, fluorescence detection module, temperature and humidity detection module, wireless communication module and threshold alarm module. Through the wireless communication module, the detection data was transmitted to the mobile phone APP and the host computer in real time, and the data was visualized and stored. A portable real-time fluorescence pork freshness detection system was developed by combining N-GQDs fluorescent nanomaterials with portable fluorescence detection device, and its performance was verified by experiments in fresh pork. The precise detection of TVB-N in pork at cold storage (4℃) and room temperature (25℃) showed excellent linear relationships (R225℃=0.97, R24℃=0.92).

Abstract:The detection of quality deterioration in fresh agricultural products was recognized as being of great significance for industries such as logistics, transportation, and storage. Fresh agricultural products are highly susceptible to quality deterioration, with ammonia serving as a critical indicator of such changes. To overcome the challenges of complex circuit design and limited lifespan in traditional chip-based ammonia sensors, a chipless radio frequency identification (RFID) ammonia sensor for detecting volatile ammonia in fresh produce was proposed. The sensor design utilized the high frequency structure simulator (HFSS) to develop a microstrip patch antenna, optimizing its electromagnetic properties, return loss, and polarization characteristics. Structural enhancements were achieved by incorporating metal shortcircuits and parasitic elements into the antenna. A sensor tag was fabricated using laser engraving, and ZnO/TiO2 nanocomposite material, known for its excellent ammonia selectivity at room temperature, was applied to the radiating elements of the antenna. A chipless RFID-based testing system was then established to detect volatile ammonia in fresh agricultural products. The sensor’s crosssensitivity to interfering gases and its stability under low-temperature, high-humidity conditions was further evaluated. Principal component analysis (PCA) and Pearson correlation analysis were used to analyze the sensor’s performance in practical applications. Experimental results showed that the chipless RFID ammonia sensor operated with a central resonance frequency of 2.25GHz, achieving a gain improvement of 0.13dB after adding metal short-circuits. In a controlled environment with ammonia concentrations ranging from 0mg/L to 100mg/L, the sensor demonstrated a sensitivity of 0.11dB·L/mg. During practical testing, the sensor exhibited a higher response to chicken (9.0dB) compared with shrimp (4.5dB). Additionally, the sensor displayed strong resistance to interference gases such as H2S, CO2, CH4, and C2H5OH, with absolute correlation coefficients below 0.5. The ammonia detection response was stable under low-temperature, high-humidity conditions and exhibited a monotonic relationship with temperature and humidity. These findings underscored the potential of the chipless RFID ammonia sensor as a robust, cost-effective solution for monitoring volatile ammonia in fresh agricultural products, providing significant theoretical and practical contributions to food quality assurance.

Abstract:Aiming at the problems of the transient jerk and low operational stability during the mode switching of electric tractors which are powered by a dual motors drive system (DMDS), a engagement/release drive mode switching control method was proposed based on the transient characteristics of DMDS. The friction torque model of the wet multi-disc electromagnetic clutch and the dynamics model of the dual motors drive system were established in the transient process of mode switching, and the model predictive control (MPC) strategy which was used in the engagement process and torque transfer control (TRC) strategy which was used in the release process were proposed to realize the coordinated control of traction motor (TM), PTO motor (PM) output torque and the friction torque of wet multidisc electromagnetic clutch. With jerk and operating speed deviation as evaluation indexes in the mode switching process of the electric tractor, DMDS mode switching bench tests were carried out. The results showed that the maximum jerk of MPC engagement strategy was 15.86m/s3, and the absolute maximum operating speed deviation was 0.17km/h, which was 56.24% and 51.42% lower than that of traditional PID control strategy, respectively. The maximum jerk of TRC release strategy was 9.06m/s3, and the absolute maximum operating speed deviation was 0.07km/h, which was 74.92% and 76.66% lower than that of traditional PID control, respectively. The proposed method took into account the action characteristics of the key components in the dual motors drive system and load time-varying characteristics in the field working environment, improved the mode switching smoothness and operation stability of DMDS, and met the requirements of tractor traction operation, which can provide a reference for the research of multi-source drive control of electric tractors.

Abstract:In order to solve the problem that the tractor driving index constraints cannot be obtained at the beginning of the design for the fuel cell tractor due to the unknown using mass, a parameter adaptive optimization method was proposed with the dual-axle drive fuel cell tractor as the research object. A mass closure algorithm was adopted to solve the problem that the power system was unable to accurately obtain the driving index constraints due to the unknown using mass. With the goal of improving the operating efficiency, a traversal search algorithm was used to optimize the front/rear reduction gear ratios. The mass closure algorithm, the traversal search algorithm and the genetic algorithm were integrated to form a parameter adaptive optimization method of a two-axle-driven fuel cell tractor with unknown using mass. The method can simultaneously optimize the using mass, dynamic parameters and front/rear reduction gear ratios of the fuel cell tractor. To verify the reasonableness of the method, a rule design method was developed as the comparison method, and the two methods were simulated under plowing conditions. The results showed that the using mass and equivalent hydrogen consumption of the dual-axle drive fuel cell tractor obtained by the parameter adaptive method were reduced by 14.44% and 8.41%, respectively, compared with the rule design method. The operating efficiency of the power source motor was increased by 3.28 percentage points and 5.29 percentage points, and the output power of the energy source fuel cell and power battery was reduced by 6.81% and 38.59%, respectively. The method provided a theoretical basis for the parameters design of fuel cell tractors with unknown using mass.

Abstract:As an approximate straight-line mechanism, the ladder-shaped four-bar straight-line linkage (ladder-shaped linkage) was named for its special configuration, which connecting-rod paralleled to the frame. Due to the complexity of existing path synthesis theories of ladder-shaped linkages, a graphical synthesis method was presented. Firstly, the research improved the previous research based on analytical computations of the Ball-Burmester point (Ball point) theory, and proved that under certain conditions, the special configuration and the degeneration of circle point curve on the linkage were necessary and sufficient conditions for each other. Secondly, based on this proposition, the geometric feature characteristic-circle was discovered, leading to the possibility of graphical synthesis. A synthesis method was developed. Given the position of Ball point and the direction of linear motion, the position of each hinge and the dimension of each connecting rod can be determined by planimetric plotting. Moreover, two ladder-shaped linkages in different dimensions can be synthesized at once by the same initial condition. The plotting steps were given, and some special cases in the plotting process were discussed. Matlab programs were compiled to verify the synthesis method in three different initial conditions, proving that the mechanism obtained the ability of drawing approximate straight line. Finally, The parameter line-ratio was proposed to measure the length of liner motion time. The line-ratio of linkages under three different initial conditions was listed. By genetic algorithm, the linkage with maximum line-ratio was explored, given a ladder-shaped linkage with a line-ratio of 0.665, which can be applied in quadruped and hexapod robots.

Abstract:The volume efficiency of the high-power external gear pump is insufficient at high speeds, rendering it inadequate for meeting the demands of high-speed electric construction machinery. Firstly, the 3D model of the traditional pump was established, and the mathematical model of the oil suction flow-pressure of the tooth cavity was derived based on the obtained structural parameters. Furthermore, an optimization scheme of oil suction runner based on “π” groove design was proposed to improve the volume efficiency by analyzing the mathematical model of oil suction flowpressure in the tooth cavity. Then the structural parameters of the full factor orthogonal design were simulated by using Pumplinx, and a prediction model for optimizing pump volume efficiency was established. Finally, the performance of the optimized pump was verified by experiments. The results showed that when the radial oil suction was small, the instantaneous pressure required by the tooth cavity to fill the oil was large, and the filling time of the tooth cavity was shortened when the pump was running at high speed, which was the main reason for the decrease of the volume efficiency of the pump at high speed. Through the combined radial and axial oil suction method, the minimum volume ratio required for radial oil suction (Δp≥0.1MPa) was reduced by 42.62 percentage points at 3000r/min, resulting in a high liquid filling rate of the tooth cavity. The influence degree of the optimized structural parameters on the volume efficiency was d2, Rm, d1 in order from large to small, and the prediction model for volume efficiency, with an R2 value of 0.9971, demonstrating high reliability. The volume efficiency of the traditional pump was decreased rapidly when the operating speed exceeded 2700r/min, and dropped to 81.87% at 3000r/min. However, the optimized pump exhibited a gradual decline in volume efficiency beyond 2700r/min. However, the volume efficiency of the optimized pump experienced a slow decrease. In comparison with traditional pump, there was an increase in volume efficiency by 1.8 percentage points, 6.79 percentage points, and 11.64 percentage points, respectively at speeds of 2800r/min, 2900r/min, and 3000r/min.