The process of rice straw and soil burial is an important factor affecting the return of straw to the field. In this paper, based on the previously established simulation model of the interaction between the straw return knife roller, soil, and rice straw, the motion state of soil particles was further studied. When the tillage depth was 20cm, the rotation speed of the cutter shaft was 240r/min, and the unit straw amount was 3.5kg/m2, simulation and indoor experiments were carried out with the straw burial rate and returning depth as the test indicators. The results showed a burial rate of 87.5% and 86.7% and a returning depth of 19.16 cm and 18.68cm, respectively, which validated the simulation and met the requirements of national standards. The simulation results showed that when the calibrated particle 152658 was in contact with the knife roller, it initially moved backward and downward. After reaching the lowest point, it was thrown backward and upward due to the rotation of the knife roller. The movement trajectory was approximately parabolic. The particle then fell back to the ground under the influence of gravity. It collided with other particles and generated fluctuations until it finally came to rest. The soil stress was studied by randomly calibrating the particles. The results showed that when the knife blade first contacts the soil particles, the forces in the X, Y, and Z directions of the particles increased linearly, and the maximum values were 15.61N, 37.2N, and 50.37N, respectively. After the soil particle mass was chopped by the knife blade, the force gradually decreased to 0. Similarly, by calibrating straw particle 45681 and analyzing its movement trajectory, the simulation showed that soil particles initially exhibited a dual effect of promoting and inhibiting the straw velocity. As the soil returned to the surface, the straw was mainly affected by soil friction under the soil layer until the straw velocity dropped to 0. The simulation analysis revealed the working principle of the straw return knife blade for straw burial and returning to the field from a microscopic point of view and provided theoretical support for the optimal design of components.

Based on Chinas provincial panel data, this paper calculates the total carbon emission from cultivated land use in China, analyzes its temporal and spatial evolution characteristics, explores the relationship between carbon emission from cultivated land use and grain yield using cointegration analysis and Granger causality test, and reveals the driving factors of carbon emission from cultivated land use using the STIRPAT model and geographic weighted regression model (GWR). The study found that Chinas carbon emissions from cultivated land use generally showed an upward trend but entered a negative growth stage in 2017. The proportions of the four types of carbon emissions were waste treatment carbon emissions (48.165%), production factor input carbon emissions (46.924%), cultivated land planting carbon emissions (3.513%), and natural source carbon emissions (1.416%). At the same time, the spatial correlation test showed that the carbon emission from cultivated land use in China had significant regional aggregation characteristics. The carbon emission structure of cultivated land use in China was dominated by the carbon emission of production factor input and waste, and there were great differences in the types of carbon emission of cultivated land use among provinces. There was a longterm equilibrium relationship between the total carbon emission of cultivated land use and grain yield in China, and there was a oneway causal relationship between the carbon emission of cultivated land use to the growth of grain yield. The total rural population, the disposable income of rural residents, and the level of agricultural machinery all had a positive impact on the carbon emission of cultivated land use, and the influence coefficients are 0.624, 0.163, and 0.337, respectively. The regression coefficients of various influencing factors showed an obvious step distribution in space. The results showed that there were obvious temporal and spatial differences in carbon emissions from cultivated land use in China, and Chinas agricultural production still has the characteristics of high input, high output, and high pollution. Differentiated carbon reduction policies should be implemented according to local conditions based on the actual situation of all provinces (cities).

Aiming at the problems such as excessive redundant information, small proportion of target area and randomness of target location in the collected corn grain images, a new corn grain image slicing method based on color space (HSV) threshold segmentation was proposed in this paper, which improved the recognition accuracy of damaged and mildewed corn   grain. Firstly, the segmentation threshold was determined, the corn grain contour was extracted, and the cropping  coordinates were determined and the image was clipped according to the vertex coordinates of the minimum external rectangle frame of the contour. Secondly, the weight of GoogLeNet model without image slicing processing and with image slicing processing were obtained. After the first, second and third convolution layer and inception5b module of GoogLeNet, the Grad-CAM visualization method was used to visualize the features extracted from different convolutional layers. Finally, based on the accuracy of verification set, the ability of the two models to extract intact, damaged and mildewed corn grain features was evaluated. The results showed that the method proposed in this paper could improve the verification set accuracy to 93.74%, which was 7.99% higher than that of the data set without image slicing processing on GoogLeNet. The models concerned areas were displayed by the Grad-CAM visualization method, and the features extracted from the network were interpreted visually, which verified the effectiveness of this method and provided a new idea for the pretreatment and identification of corn kernel image.

In order to increase the economic return of maize cultivation and expand the promotion degree of maize threshing machinery, this paper aims to improve the threshing and netting rate of maize and reduce the breakage rate of threshing process, and designs an adjustable maize threshing device by studying the structural characteristics of maize threshing device. Through theoretical analysis, the diameter of the threshing device drum was determined to be 600 mm, the length of the grain rod was 1 400 mm, and the length of the adjusting rod was 150 mm. Through mechanical and kinematic analysis of the threshing process, the variable gap of the concave plate screen was derived to be 0-25 mm, and then the threshing gap was derived to be 20-45 mm. According to the design of the threshing drum, the operating parameters were determined, the speed of the threshing drum was 200-300 r/min and the material feed is less than 2.1kg/s. A physical prototype of the adjustable corn threshing device was tested with the adjustment gap, threshing drum speed, and material feed as the test factors, and the threshing rate and breakage rate as the indexes, and the parameters were optimized based on the test results. The results showed that the significance of the factors influencing the corn cleaning rate and kernel breakage rate was as follows: adjustment gap > threshing drum speed > material feed. The results of the validation tests showed that the optimal combination of parameters was 30 mm adjustment gap, 300 r/min threshing drum speed, and 1.5 kg/s material feed rate, and the optimal combination of parameters resulted in 99.07% and 2.23% of corn cleaning rate and kernel breakage rate, respectively, meeting the agronomic requirements of the grain threshing process. This study also provides a reference for the design and optimization of corn threshing equipment.

The straw can be used as a new energysaving and environmentfriendly raw material after microgrinding to achieve fine and highvalue utilization. By reading literature on the topic, the research status of the utilization technology of straw powder and the research situation of the method, theory, and equipment of straw microgrinding were summarized. This paper identified the existing problems and prospects for future development. Straw has diverse applications, including its use in composite materials, and the market demand continues to grow. According to the characteristics of straw, the most suitable grinding method is mechanical grinding, while many problems exist, such as high energy consumption and dust pollution. At present, most straw microgrinding equipment draws inspiration from the microgrinding technology and equipment of ore materials, which has poor adaptability to different raw materials and fails to meet the requirements of fine powder particle size and high productivity. Additionally, research on grinding theory mainly focuses on factors influencing the grinding effect, energy consumption, and yield, while limited research is done on the grinding mechanism based on the physical properties of straws. In the future, the application scenario of highvalue straw powder should be expanded, the straw composite microcrushing method more suitable for largescale production should be explored, and the automation, specialization, simplification, and lightweight nature of straw microcrushing equipment should be improved.

 Aiming to address issues such as low mechanization, poor peeling quality, and lack of evaluation standards for water chestnut peeling in China, this paper provides a comprehensive analysis of the physical characteristics of water chestnut and thoroughly explains three peeling technology evaluation indexes: the peeling rate, peeling loss, and peeling efficiency, as well as their calculation methods. This paper also systematically summarized the common water chestnut peeling technology and emerging peeling technologies both domestically and internationally in recent years. The main peeling technologies, such as chemical peeling, steam peeling, mechanical peeling, ultrasonic peeling, and infrared heating peeling, were emphasized. The advantages and disadvantages of various peeling technologies were analyzed, and the technical difficulties in the peeling process of water chestnuts, such as ripening, browning, and high peeling loss rate, were pointed out. In addition, future developments of water chestnut peeling technology, including combining multiple peeling technologies and extending the operation process, were proposed. These insights aim to provide a reference for the research of water chestnut peeling technology and inspire innovative designs of peeling machinery in China.

In order to solve the problem of timeconsuming, inefficiency and low accuracy of manual sorting of Pleurotus eryngii, this paper proposes an intelligent sorting method and robot intelligent sorting system for Pleurotus eryngii, which is dualmodel parallel method of grading detection and grasp detection based on deep learning. The depth camera is used to collect the images of Pleurotus eryngii, and the robot is used as the sorting actuator. The intelligent sorting control software is designed based on ROS (Robot Operating System), python and C++ language, and the monitoring and management system is designed based on PyQt. The test results show that the sorting system can automatically realize the grading detection of Pleurotus eryngii and the robot sorting and grasping. The sorting detection of single Pleurotus eryngii takes 18ms, and the average accuracy of grading detection is 88.35%, the success rate of robot grasping is 98.33%, and the success rate of intelligent sorting is 88.35%, which confirms the feasibility and effectiveness of the system as a whole. It provides a new solution for the whole realization of intelligent sorting system of other agricultural products.

In order to clarify the influence of impact load on damage and fracture characteristics of walnut during primary processing, in this paper, based on the continuum damage theory, the existence of damage was first proved by uniaxial compression test. Then, the damage and fracture models of walnut were established by single impact and repeated impact loading tests using the drop hammer impact test bench. Finally, the influence of walnut size between 30mm and 44mm on model characteristic parameters was discussed. The results showed that the damage accumulation coefficient was the minimum value 3.89 when the walnut size was 35mm, when the walnut size was 30mm, the threshold energy required for cracking was 4.74J/kg. The walnut fracture was caused by the damage of walnut. The energy threshold is the judgment standard for walnut crack generation, and the damage accumulation coefficient quantifies the damage resistance ability of walnut. The threshold energy is linearly with the increase in the walnut size. The relationship between the walnut size and damage accumulation coefficient conforms to polynomial function. The results are helpful to control walnut fracture during primary processing.

In order to solve the problem of inaccurate judgment of fresh tobacco maturity based on subjective experience, image processing and feature extraction were carried out on fresh tobacco leaf with different maturity, and a fresh tobacco leaf maturity judgment model was established to realize intelligent judgment of fresh tobacco maturity. By collecting 10 color features and texture features of upper leaf images of Yunyan 87 varieties with different maturity, variable cluster analysis and correlation analysis were carried out respectively, and the one feature with the strongest correlation between each type of feature and maturity was selected to form a feature subset. In this paper, support vector machine based on genetic algorithm (GA-SVM), Back propagation neural network based on particle swarm algorithm (PSO-BP) and Extreme learning Machine (ELM) were used to identify the maturity of fresh tobacco. The results showed that the optimal five tobacco leaf image features were used as model inputs, the discrimination accuracy of the established GA-SVM、PSO-BP、ELM model was 92.00%、90.00%、84.00%. It is proved that it is feasible to discriminate the maturity of fresh tobacco by using machine vision technology, which provides theoretical basis and technical support for intelligent tobacco leaf harvesting.

Citri Grandi Exocarpiums drying is a very important step in production and processing, this paper investigates the development status of Citri Grandis Exocarpium drying, reasonably analyzes the scientific and technical problems in this field, and provides references and countermeasures for the rational development of Citri Grandis Exocarpium industry. According to the characteristics of Citri Grandis Exocarpium, the current status of related technologies and equipments used in this field are scientifically investigated. By combining the traditional drying process of Citri Grandis Exocarpium and existing drying methods for Chinese Medicinal Herb, the effects of different drying equipments are compared and studied on the following considerations: the effective components and quality of Citri Grandis Exocarpium, the adaptability and economy of drying machines. Then, the technical deficiencies of drying methods and equipments are discussed, and the key technologies and development trends are analyzed. In the current drying industry of Citri Grandis Exocarpium, the traditional drying room, sunlight drying and shade drying have the lowest cost, microwave drying and hot air drying have the highest efficiency, and vacuum freeze drying and variable temperature pressure differential puffing drying retain the most active ingredients of Citri Grandis Exocarpium. However, each drying method has its disadvantages through comprehensive analysis of all aspects, therefore it is necessary to explore and master the traditional drying process and characteristic parameter changes of Citri Grandis Exocarpium, and to establish the quality grade standards and the technical drying standards for Citri Grandis Exocarpium, in addition, it is a potentially feasible way to use combined drying technologies for maximizing the advantages of each drying method.

In order to change the low efficiency mode of manual bag removal and mechanical crushing of waste bacteria rods, a small crushing separator integrating bag removal and crushing was designed. The debag device and the crushing device were designed, and the force of the auger on the waste bacteria rod during the crushing process was analyzed, based on the discrete element software EDEM, the binding model of the waste rod was established, and the grinding process was simulated. Through the design of orthogonal test, the influence of the parameters of the auger on the grinding degree of the waste rods was obtained and the prediction model was established. Through response surface analysis and prediction model, the parameters affecting the grinding degree of waste bacteria rods were optimized. The best working parameters were obtained as follows: the rotating speed of the grinding shaft was 323.4r/min, the outer diameter of the auger was 261.185mm, and the thickness of the blade was 6mm. The model predicted that the grinding degree of waste bacteria rods was 81.739%. The best working parameters were substituted into the simulation test, and the relative error between the predicted value of the model and the simulated value was 1.79%, which verified the availability of the prediction model. The prototype was manufactured with the outer diameter of the auger of 260mm and the thickness of the blade of 6mm, and the crushing test was carried out. The results showed that when the rotation speed of the auger was 320r/min, the working performance of the whole machine was stable, the feed of the waste bacteria rod was smooth, the crushing qualification rate was 92%, and the bacteria bag removal rate was 93%, which met the design requirements of the waste bacteria rod crushing separator.

Research work on maize is always limited by the short harvesting period and the high labor intensity of harvesting. The pressure feed wheels in the maize peeling device are made of rubber and can deform greatly in practice, making it difficult for ANSYS and EDEM software to build a flexible working simulation model for them. In order to address the above problems, a flexible simulation model of the maize peeling device is established in this paper by coupling EDEM and RecurDyn. The simulation is based on three operating conditions with peeling roll and press wheel speed as test factors. The results show that when the speed of peeling roller is 480 r/min, the speed of pressure feed wheel is 96 r/min, and the feeding speed is 500 kg/h, the average force of corn cob is 15.65 N, the variance of the force is 7.80, and the rotation speed of cob around its own axis is 58.86 r/min, which is the most stable force and fast rotation speed of corn under the working condition. With the cob peeling rate, seed drop rate and kernel breakage rate as the test index for bench test to verify the simulation, when the peeling roller speed of 480 r/min, the pressure feed wheel speed of 96 r/min, feeding speed of 500 kg/h, the cob peeling rate of 90.22%, the seed drop rate and kernel breakage rate of 0.97% and 1.07%, peeling rate at the same time, the drop rate and kernel breakage rate of lowest. Breakage rate were the lowest, and the experimental and simulation results coincided with each other. This study shows that the use of EDEMRecurDyn coupling to establish a discrete simulation model of the corn peeling device can provide preliminary guidance for the subsequent test work of the corn peeling device, with compressing the test time and reducing the labor burden.

Visionbased detection of agricultural pests is an important technology for achieving automated and realtime monitoring of pest conditions. Firstly, this paper introduces the application of traditional machine learning techniques in the visionbased detection of pests in China and internationally. Then, this paper summarizes the research progress of the new generation of visionbased detection methods for pests, which are based on deep learning techniques such as R-CNN, Fast R-CNN, Faster R-CNN, SSD, and YOLO. Next, this paper analyzes the problems that exist in the research and practical applications of visionbased detection methods for agricultural pests. The traditional machine learningbased methods have problems such as low feature capture ability, detection accuracy, and robustness, as well as high resource consumption. The deep learningbased methods have higher detection performance than the traditional machine learningbased methods but have problems such as poor performance on small and differently distributed targets, low detection accuracy, and slow speed. Finally, this paper discusses possible research directions in the future for the visionbased detection of agricultural pests based on deep learning techniques, including the development of public resources for agricultural pest image data, robust handling for data distribution shifts, deep feature learning, and multiscene applications.

Aiming at the problem of low screening rate (high soil content) of FUM， triaxial mean size and critical damage pressure of FUM and soil were measured, by means of FUM and soil aggregate Statistical analysis of triaxial dimensions and mechanical properties test. The results showed that the triaxial size of FUM and the soil aggregates on the screen was not significant, and the critical extrusion force value of FUM and the soil aggregates on the screen was significant. Based on this conclusion, the efficient separation scheme of FUM and soil aggregates by screening and kneading method was proposed. The efficient separation test device for FUM was constructed. The optimum range for calculating the kneading force of screening and kneading device was 20-40N, and the value range of the kneading monomer thickness was 0.2-0.4cm. The quadratic regression orthogonal rotation test scheme was designed, the results showed that the influence of the feeding amount, the square term of the feeding amount and the square term of the conveying screening speed on the screening rate was very significant, and the kneading force , the interaction between feeding amount and the speed of the conveyor screening had a significant impact on screening rate. Feeding amount and the square term of the speed of the conveyor screening had significant effects on damage. Kneading force, interaction between feeding amount and conveyor screen speed, interaction between feeding amount and kneading force, and the square term of feeding amount had significant effects on damage. By DesignExpert.V8.0.6 software, the optimal parameter combination was obtained: feeding amount of 0.68kg/s, conveyor screen speed of 0.38m/s, kneading force 36N, screening rate of 80.5%, damage rate of 12.6%, respectively. Field tests showed that the average screening rate of the separator was 79.18%, and the average damage rate was 13.34%, which could meet the agronomic requirements of mechanized harvesting of FUM.

“Huxiang F2” Shiitake spawn sticks during the color change period upon debagging were taken as the test object, and their physical and mechanical properties were investigated. The density of Shiitake spawn sticks was measured using the sand discharge method, yielding a value of 0.64g/cm3. The dynamic friction coefficients between spawn sticks and spawn bags, as well as between spawn sticks and 65Mn spring steel, were determined to be 0.485 and 0.584, respectively, employing the slope method. The attachment strength and strain tearoff force averaged at 1.01kPa and 25.69N, respectively. A radial compression test was performed on the Shiitake spawn sticks using an electronic universal testing machine. Combining the experimental results with theoretical calculations, when the loading speed of the spawn sticks was 10mm/min, the average radial compressive strength of the rods was found to be 44.86kPa, with corresponding average values of elastic modulus and Poissons ratio of 0.48MPa and 0.17, respectively. These research findings establish a fundamental theoretical foundation for the design of key components and the determination of operating parameters for Shiitake spawn stick debagging equipment.

The physical parameters of chili seeds are important inputs in the discrete element simulation. In order to improve the reliability and accuracy of the numerical simulation, the physical property parameters of capsicum seeds were measured experimentally, including triaxial size, density, Poissons ratio, friction coefficient, recovery coefficient, et al. Combined with the “Hertz Mindlin with JKR” viscosity model in EDEM, surface energy parameters were introduced to conduct the angle of repose test. The three most significant influencing parameters (chili seedseed rolling friction coefficient, chili seed surface energy, and chili seedsteel plate rolling friction coefficient) were selected among the influencing factors by PlackettBurman test, and the regression model of the three significant influencing parameters and the angle of repose was established to study the influence of the significant factors on the angle of repose under the interaction effect. The interval of significant parameters was divided into 5 levels by gradient average for climbing test to get the optimal range of values, and finally the response surface method (BoxBehnken) was applied to analyze the variance of the quadratic polynomial of the regression model in terms of the angle of repose, the relative error and the three important parameters, and the model was optimized with the minimum value of relative error to get the optimal combination: rolling friction coefficient between chili seeds was 0.75, JKR surface energy was 0.31J/m2, and rolling friction coefficient between chili seeds and steel plate was 0.60. The optimal combination of parameters obtained from the calibration test was used to conduct the simulated stacking test, and the average angle of repose was 26.71°, and the relative error was 4.61%.

The physical properties of Pueraria are quite different from other potatoes, such as large shape, high fiber content and surface grooves with sandiness. The mechanized processing of Pueraria starch cannot copy potatoes model, and the key equipment has its unique features. Most Pueraria starch enterprises are small and use potato processing equipment and technology, with few special equipment, unreasonable structure and low production efficiency, which is not conducive to the technological progress and development of Pueraria starch industry. The application scenarios of Pueraria starch processing technology and equipment are summarized based on the analysis of the domestic literature on potato starch processing and the application status of processing equipment. Taking the 500kg/h Pueraria starch processing process as an example, the structure and principle of key equipment and the problems of lack of advanced technology, high energy consumption and serious pollution in production are summarized. Suggestions were put forward to strengthen research on advanced technologies for Pueraria processing and planting, establish relevant standards and regulations, and improve comprehensive development and utilization, so as to provide reference for promoting industrial technology progress and largescale development.

In order to explore the best process parameters of microwave vacuum drying of seed gourd, taking Gansu Baiyin “seed gourd No.1” as the test material, the homemade microwave vacuum equipment for drying seed gourd solids test was used to explore the drying temperature, vacuum degree and specific power on the drying characteristics and physicochemical quality of dry products. The results showed that with the increase of drying temperature and vacuum degree, the decrease of specific power, the decrease rate of material moisture ratio increased and the drying efficiency improved. The effective moisture diffusion coefficient of seed melon solids ranged from 0.70074×10-9~4.56579×10-9m2/s and increased with the increase of drying temperature, vacuum degree and specific power. The highest contents of polysaccharide (105.44mg/g), VC (1.21mg/g) and dietary fiber (80.69%) with high rehydration ratio (4.23) and bright color were obtained at the drying temperature of 50 ℃, vacuum degree of -0.070MPa and specific power of 20W/g in the samples. Taken together, microwave vacuum drying can better guarantee the comprehensive quality of seed melon solid and improve the added value of products. This study can provide a theoretical reference for the development of the potential value and industrial processing of seed melon solid.

Early diagnosis and treatment of tomato diseases can help to improve the yield of tomatoes. The combination of artificial intelligence and agricultural production can achieve realtime nondestructive detection of tomato diseases. In this study, a research method for tomato leaf disease classification and recognition based on deep learning is proposed. Five kinds of common diseases of tomato leaves are selected for experimentation. Improvements are made to the MobileNetV3 model, and the effects of different learning methods, activation functions, and optimization algorithms on the accuracy of the model are analyzed. The model is compared with MobileNetV3, VGG16, ResNet50, and InceptionV3, and the robustness of the model is evaluated by tenfold crossvalidation. The research shows that the model has good classification performance, achieving an average recognition accuracy of 97.29% for common tomato leaf disease images. The model is superior to other models in terms of model size, running time, and classification accuracy, providing a reference for the recognition of common tomato leaf diseases.