Low productivity and high electricity consumption are considered problems of the hammer mill, which is widely used in current feed production. In this paper, a folded V-shaped hammer was designed to improve the performance of the hammer mill. To determine the optimal design parameters of the new hammer, the single-factor test and orthogonal tests were carried out with the inclination angle of hammer, the angle of hammer head, and the distance of hammer head as the influencing factors, and the productivity and output per kWh as evaluation indexes. The order of the influence on the productivity and output per kWh were the inclination angle of hammer>the angle of hammer head> the distance of hammer head. The parameters were optimized based on the orthogonal tests with the following results: the angle of hammer head was 160°, inclination angle of hammer was 110°, and the inclination distance of hammer head was 24 mm. The static analysis and modal analysis were carried out on the optimized hammer by using ANSYS software. The results showed that the new hammer satisfies the strength and stiffness requirements during working, does not resonate, and has good dynamic characteristics. The new hammer can effectively improve the performance of the hammer mill, and the research results can provide theoretical basis for the optimization design of the hammer mill.

In this study, the mechanical properties of three varieties of cerasus humilis at different temperatures were systematically investigated by whole fruit puncture test, exocarp uniaxial tensile test and mesocarp uniaxial compression test.It was found that puncture test could not only reflect the shear mechanics of the exocarp in vivo at the tissue level, but also characterize the resistance level of fruit to puncture damage at the macro level.The environmental temperature had significant negative and positive effects on puncture failure stress and puncture failure deformation of cerasus humilis (p<0.05).The stress and elastic modulus of exocarp tension and mesocarp compression were significantly affected by ambient temperature (p<0.05).This study combined with temperature change to study the mechanical properties of cerasus humilis provides a necessary theoretical basis for the prediction of fruit damage and the development of postharvest treatment equipment.

In this study, the parameters of tiger nut were calibrated based on discrete element method, and significant influencing factors and optimal levels were selected by Plackett-Burman test, steepest climb test and center compound test, and verified by electromagnetic vibration hopper bench test. The results show that the relative error between the simulated resting angle and the actual resting angle is only 0.381%. The fitting degree of the model is 96.32% and 94.57% respectively, which can provide theoretical basis for the study of the parameters and discrete element simulation of tiger nut.

To address the issues of poor timeliness and delayed feedback in traditional wheat milling processes for manual particle size detection, a wheat milling online particle size detection device has been designed. This paper focuses on the design optimization of the key feeding component in the device, which affects the accuracy of particle size detection. The feeding component adopts shaftless screw blades. Through theoretical analysis, the main parameter ranges affecting the throughput capacity of the shaftless screw conveyor are determined. A Box-Behnken experiment is designed to obtain the optimal parameter combination for each factor: outer diameter of screw blades 23.8 mm, inner diameter of screw blades 6.4 mm, pitch 11.2 mm, and blade rotation speed 288.9 r/min. Simulation and test stand experiments are conducted using the above parameter combination. The simulation results show that the average throughput capacity of the feeding component is 2.85 kg/h, while the average throughput capacity of the test stand experiment is 2.84 kg/h, with a coefficient of variation of uniformity of 1.33%. These results indicate that the above parameter combination meets the design requirements for the feeding component in the device.

In order to solve the problem of poor mixing effect of inclined spiral conveyor, this paper designed an inclined spiral and ribbon blade combination conveying device. The mechanics and kinematics analysis of the movement process of the material unit in each mechanism was carried out, on which key devices and components were designed based. Effects of the speed of main shaft (X1), the full coefficient (X2) and the angle of inclination (X3) on the mixing uniformity (Y1) and the residual rate of material (Y2) were explored. Three-dimensional quadratic regression orthogonal rotation central combination experiment method combined with response surface method was used to conduct experiments and explore the interaction effects of influence factors on indicators. A regression model of influence factors and evaluation indicators was established through the analysis of variance. The significant factors affecting Y1 were ordered of X3, X2, X1, and the significant factors affecting Y2 were ordered of X2, X1, and X3. In the interaction of factors, X1X2 had a significant impact on Y1 and Y2; X1X3 had an extremely significant impact on Y1; X2X3 had an extremely significant effect on Y1 and a significant impact on Y2. The optimal structure and working parameters combination were determined to be 50 rpm for the speed of main shaft, 60% for the full coefficient, and 19° for the angle of inclination, while the verification experiments demonstrated that the mixing uniformity and residual rate of material corresponding to the verification test were 90.37% and 5.31%, respectively. The inclined device with combined spiral and ribbon blade developed in this study meets the design requirements for the misprocess of the fertilizer utilization of agricultural organic wastes.

This study developed a hybrid solar greenhouse dryer (lean-to) incorporated with a solar collector and photovoltaic (PV) system for smallholder processors of tomatoes and evaluated the thermal performance of forced convection mixed-mode solar dryer with two pretreatments of fresh tomatoes (halves and slices) with salt and sugar. Tomatoes dipped in a 40% sucrose solution for 72 hours before drying exhibited a greater initial drying rate than those treated with salt. The hourly average incident solar radiation without a reflector was 673.8 (±214.2) W/m2 outside and 754.6 (±284.5) W/m2 inside the lean-to solar dehydrator during operation. The incident solar radiation in the collector ranged from 390.3 to 1156.0 W/m2, indicating higher levels at the tilt angle. The hourly average air temperatures outside and inside the solar dehydrator and solar collector during the experiment, respectively, were 30.7 (±2.3), 52.7 (±10.1), and 30.7 (±2.3), 79.7 (±26.9)°C for the salt treatment and 31.0 (±2.0), 55.1 (±15.3), and 31.0 (±2.0), 84.8 (±28.0)°C for the sugar treatment. Thus, the solar dehydrator and the solar collector raised the dehydrating air temperatures over the outside for the salt and sugar treatment by an average of 22.0, 49.0, 24.1, and 53.8ºC, respectively. The average hourly air-relative humidity inside the solar dehydrator was 33.5%, while outside was 47.2%. The pretreated tomatoes had an initial moisture content of 93.1% (w.b). The solar dehydrators thermal efficiency was 72.21%, and its drying efficiency was 56.48%. Consequently, solar energy contributed 84.28 and 71.18% of the generated heating power. The solar dehydrator lost 15.72 and 28.82% of its remaining solar energy due to exhausted air. The solar dehydrator had a daily average energy of 59.375 kWh, and the heating power was 47.473 kWh during the experimental period (29 h).

Aiming at the high crushing rate and impurity rate of corn kernel machine harvesting in the Huanghuaihai region, a longitudinal flow conical variable pitch threshing device is designed, which adopts the combined threshing element of "plate teeth + ribs" and the combined threshing concave plate of "leftward round tube type + vertical round tube type". The cob model was established, and the force analysis of the cob threshing process was carried out, and the type of threshing drum and the installation angle of the threshing concave plate round tube were determined as the main influencing factors, and the collision force on the corn cob was taken as the test index. Using EDEM discrete element simulation software, simulation tests were carried out on different types of threshing drums and threshing concave plates with different installation angles of round tubes with corn cobs, and the better threshing method was finally determined: a conical threshing drum at a drum speed of 450 r/min, and a combination of left-facing round-tube-type+vertical round-tube-type threshing concave plates with an installation angle of 10° (front-sparse and back-dense type) were used. Compared with the vertical circular tube type threshing concave plate, the corn cob contact force decreased from 313.5N to 247.3N, which was optimal for threshing in the range allowed by the corn kernel destructive force.

The intelligent detection of young apple fruits based on deep learning faced various challenges such as varying scale sizes and colors similar to the background, which increased the risk of misdetection or missed detection. To effectively address these issues, a method for young apple fruit detection based on improved YOLOv5 was proposed in this paper. Firstly, a young apple fruits dataset was established. Subsequently, a prediction layer was added to the detection head of the model, and four layers of CA attention mechanism were integrated into the detection neck (Neck). Additionally, the GIOU function was introduced as the models loss function to enhance its overall detection performance. The accuracy on the validation dataset reached 94.6%, with an average precision of 82.2%. Compared with YOLOv3, YOLOv4, and the original YOLOv5 detection methods, the accuracy increased by 0.4%, 1.3%, and 4.6% respectively, while the average precision increased by 0.9%, 1.6%, and 1.2% respectively. The experiments demonstrated that the algorithm effectively recognized young apple fruits in complex scenes while meeting real-time detection requirements, providing support for intelligent apple orchard management.

A small-scale paddy rice transplanter for hilly and mountainous areas faces issues such as few suitable machines, poor transplanting results, and low adaptability and efficiency of large transplanters in small fields. To address these problems, a four-row small-scale paddy rice transplanter was designed, driven by an engine with chain transmission. The machine structure mainly consists of a frame, engine, paddy field wheels, seedling tray, transplanting mechanism, reversing gearbox, and electromagnetic clutch, with a total weight of only 50 kg, facilitating transportation and operation. MATLAB was used for kinematic simulation and analysis of the transplanting mechanism, plotting displacement diagrams of the seedling needles and motion characteristic curves of the transplanting mechanism. ANSYS software was employed for finite element analysis of key components to ensure they meet operational requirements. Experimental studies were conducted with transplanting speed as the experimental factor, using floating rate and missing insertion rate as test indicators. Results showed that under specified transplanting conditions, the floating rate stabilized at around 2.9% and the missing insertion rate at approximately 4.8%. These findings indicate that the designed small-scale transplanter can effectively meet the requirements for rice transplanting operations in hilly areas.

In order to achieve efficient and accurate detection of common corn leaf diseases such as leaf blight, gray spot disease, and rust, a corn leaf disease detection method based on CA-YOLOv8 was proposed. In this method, the Coordinate Attention(CA) attention mechanism was added after the feature map output from the Neck part to enhance the feature extraction capability of the model. The experimental results showed that the precision,recall and mean average precision(mAP) of the CA-YOLOv8 model on the test set were 94.08%, 90.53% and 97.38%, respectively. Compared with the YOLOv8, YOLOv8+SE and YOLOv8+CBAM models, the mAP was improved by 2.15, 0.86 and 2.35 percentage points, respectively. Compared with Faster R-CNN, YOLOv5s, YOLOv7, and YOLOv8 models, the mAP has increased by 63.53, 29.24, 3.21, and 2.15 percentage points, respectively. The study showed that the CA-YOLOv8 model can provide a technical reference for the development of a portable intelligent corn leaf disease detection system.

In modern agriculture, with the development and widespread use of agricultural mechanization, mechanical compaction of soils has become a growing problem, resulting in soil degradation in the field. Based on the Boussinesq solution, the soil stress formula for the circular load area is derived, and MATLAB is used to simulate the stress-strain relationship of the soil at different depths. The results show that under the same load conditions, as the soil depth increases, the soil stress gradually decreases, with the most significant stress change occurring at 0.2 m depth. Soil compression experiments conducted using a consolidation instrument revealed that the soil void ratio dropped rapidly under loading of 50-200 kPa, and the decline slowed after 400 kPa. When the soil void ratio decreases to 0.2-0.4, the soil stress changes tend to stabilize. Comparison between the theoretical formula and the compression experimental data indicates that the soil stress gradually decreases as the thickness of the soil layer increases and the pressure load increases, verifying the linear relationship predicted by the theoretical formula.

Accurate prediction of environmental changes in Agaricus bisporus cultivation is essential for better managing climatic conditions within mushroom houses, ultimately enhancing the yield and quality of Agaricus bisporus. However, traditional control systems for Agaricus bisporus production environments can only monitor the current conditions and lack the ability to predict environmental changes, leading to issues such as delayed feedback on environmental data and the effectiveness of control measures. In response to these challenges, this study establishes a temperature and humidity prediction model based on the DOA-BP algorithm. Experimental results demonstrate that the DOA optimization algorithm exhibits strong global search capabilities. By rapidly searching for optimal weights and biases, it overcomes the drawback of the BP neural network getting stuck in local minima, accelerates network convergence, and improves the performance of the BP neural network. The MAE values for temperature and humidity prediction inside the mushroom house are 0.021 and 0.013, respectively. The RMSE values are 0.044 and 0.038, respectively, and the R2 values are 0.976 and 0.968, respectively. Through validation, the DOA-BP temperature and humidity prediction model proposed in this study accurately predicts the temperature and humidity inside mushroom houses. This model can enhance environmental control for cultivation, optimize resource utilization, and reduce production costs effectively.

In order to solve the problems of low correlation between variable fertilizer application system and soil nutrient content detection and insufficient real-time performance, a variable fertilizer application system based on real-time soil nutrient content detection was developed. This paper describes the structure, working principle and design of key components of the soil information acquisition and fertilizer application system. It includes the simulation and analysis of fertilizer application using the discrete element method and the selection of curved blade fertilizer application discs. The system uses STM32F429IGT6 microcontroller and ROS higher-level computer for decision making. The device detects soil nutrients in real time, adjusts the fertilizer motor speed accordingly, and runs autonomously along the planned path. The decision coefficient R^2 between the fertilizer application rate and the speed of the fertilizer application wheel is not less than 0.97, and the relative error between the actual fertilizer application rate and the theoretical fertilizer application rate is up to 5.91%, with the maximum value of the coefficient of variation (CV) of 10.18%. The indoor bench test shows that the relative error between the actual fertilizer application rate and the target fertilizer application rate within a single operating grid is up to 6.2%, with the maximum value of CV being 6.64%. The field test in the orchard showed that the maximum relative error between the actual fertilizer application and the target fertilizer application in a single operation grid was 6.3%, and the maximum value of CV was 12.34%, and the fertilizer application was completed in the operation grid, which demonstrated that the device was able to realize real-time and accurate variable fertilizer application according to the soil nutrient information.

When maize is afflicted by pests and diseases, it can lead to a drastic reduction in yield, causing significant economic losses to farmers. Therefore, accurate and efficient detection of maize pest species is crucial for targeted pest control during the management process. To achieve precise detection of maize pest species, this paper proposes a deep learning detection algorithm for maize pests based on an improved YOLOv8n model: Firstly, a maize pest dataset was constructed, comprising 2,756 images of maize pests, according to the types of pests and diseases. Secondly, a deformable attention mechanism (DAttention) was introduced into the backbone network to enhance the models capability to extract features from images of maize pests. Thirdly, spatial and channel recombination convolution (SCConv) was incorporated into the feature fusion network to reduce the miss rate of small-scale pests. Lastly, the improved model was trained and tested using the newly constructed maize pest dataset. Experimental results demonstrate that the improved model achieved a detection average precision (mAP) of 94.8% at a speed of 171 frames per second (FPS), balancing accuracy and efficiency. The enhanced model can be deployed on low-power mobile devices for real-time detection, which is of great significance for the healthy development of maize agriculture.

A multifunctional leveling platform for orchard in hilly and mountainous areas is developed. The platform design optimizes the double circuit hydraulic system and the horizontal and vertical bidirectional leveling structure to realize synchronous adjustment. Based on the attitude sensor, an intelligent detection and control system is developed to realize the automatic leveling and platform stabilization. The test results show that the platform can reach the maximum climbing capacity of 30° and the limit leveling angle of 15°, which can meet the requirements of orchard operation in large slope and complex terrain, and provide theoretical basis for the future design of orchard operation platform in hilly and mountainous areas.

The article presents an experimental stand for laboratory research of a screw conveyor with a bladed working body. Based on the results of experimental studies, the corresponding response surface regression equations were constructed to establish the influence of controllable factors upon the degree of damage to the grain materials. It was established that the main factor affecting the increase in the amount of the grain damage was factor x3(n), the rotation frequency of the bladed working body. The increase in factors x1(D) and x2(?) led to a decrease in the amount of the grain damage. Based on the results of comparative experimental studies to determine the degree of damage to the grain material during its transportation by the screw and blade working bodies, it was established that the bladed working body provided a reduction in the degree of damage to the grain material with a simpler manufacturing technology.

In the process of seed introduction, there is a problem of seed falling disorderly due to the collision between the seed and tube wall, which seriously affects the uniformity of seed spacing in the field. To solve this problem, this paper designed a kind of annular air-blowing auxiliary seed guide device. After a series of simulation experiments, theoretical research, and high-speed camera bench experiments, the optimal parameter selected combination of the critical structure of the seed guide device. The experimental results showed that when the annular air-blowing assisted seed guide tube was used, the positive air pressure was 2 KPa, the airway angle was 150°, the airway outlet width was 12 mm, and the distribution pore diameter was 4 mm. When the forward speed was 6km/h (the rotation speed of the seed metering disc was 25.30 rpm), the seed sowing effect was the best in the seed guide device; the qualified rate was 88.36%, and the coefficient of variation was 12%. This study provides a reference for improving seed spacing uniformity and can be used to optimize seed guide tubes.

This paper explores hydroponic vertical systems as a sustainable solution to modern agricultural challenges, particularly those posed by climate change. Hydroponics, a method of growing plants without soil using nutrient-rich water solutions, offers significant advantages over traditional farming. Vertical systems maximize space efficiency by growing plants in stacked layers, making them ideal for urban environments with limited space. These systems provide a controlled environment that mitigates the impacts of extreme weather, ensuring consistent crop production. The paper reviews various hydroponic techniques, including deep water culture, nutrient film technique, flood and drain, and drip irrigation. It highlights the efficiency of water use in hydroponics, crucial for areas facing water scarcity. Advanced technologies, such as sensors, automated nutrient delivery, and LED lighting, are employed to optimize growing conditions, enhance resource use efficiency, and improve crop yields. LED lights, in particular, offer energy efficiency, customizable spectra, and low heat output. Mathematical models are used to maximize plant development and resource efficiency, providing a framework for understanding plant-environment interactions. Despite high initial setup costs and the need for technical expertise, hydroponic systems present long-term economic and environmental benefits. This paper underscores hydroponic vertical systems potential to revolutionize urban agriculture, ensuring food security and sustainability amidst climate change challenges.

Aiming at the problems of spraying pole-type plant protection machines difficult to get down to the field after row closure of maize in the middle and late stages, uneven droplet distribution of pressure nozzle-type plant protection drone, and difficult to change the droplet particle size, this paper designed a UAV centrifugal spraying system for maize planting protection through the designed centrifugal nozzle combined with a plant protection drone. A single nozzle parameter test was carried out to study the relationship between nozzle speed, flow rate and droplet size. The variable parameter flow rate is set in the range of 300 ml ~ 1000 mL / min, and the nozzle rotation speed is set in the range of 8000 ~ 18000 r / min gradient change. The test results show that the droplet size is related to the liquid supply flow rate and the nozzle rotation speed. According to the theory of optimal biological particle size, the centrifugal nozzle parameter is determined to select the liquid supply flow rate of 1000 mL / min and the nozzle rotation speed of 14000 r / min. The droplet distribution characteristics test under the actual operating conditions was carried out with this parameter, and the important index parameters such as droplet size, droplet density and coverage rate were analyzed to characterize the UAV aerial spraying operation. The experimental results show that the flight speed of the UAV has an important effect on the droplet deposition parameters, which significantly affects the droplet coverage, droplet density and deposition amount of the bottom layer of maize, and the droplet coverage and the droplet deposition amount of each sampling layer tends to decrease with the increase of flight speed, and the coefficient of variation (CV) value of the centrifugal spraying system was the smallest at the flight speed of 1.5m/s, and the effect of droplet deposition was the most uniform. at a flight speed of 1.5m/s. The effect of droplet deposition is the most uniform. This study can provide a reference basis for the optimization of parameters and the correct use of centrifugal plant protection UAV in the middle and late stage plant protection operations of tall crops such as maize.

Optimization and experimental research on the cutting parameters of the cutter were carried out to solve the high re-cutting rate and loss rate under high-speed harvesting of alfalfa disc-type cutter. Kinematics theory was used to analyze the movement trajectory and cutting area of the cutter in the cutting process, and theoretical calculations to carry out an analysis of the factors affecting the re-cutting area of the cutter. A working parameters adjustable cutting test bench was designed and produced, and cutting experiments of alfalfa were conducted using this test bench combined with response surface methodology. The optimized factors combination was solved by quadratic fitting function, and the value of cutterhead diameter, blade twist angle, and cutting inclination angle was 407.04 mm, 4.21°, and 4.51°, respectively. The verification test showed that the average re-cutting rate and loss rate were 1.48% and 3.13%, less than national standard requirements for alfalfa harvesting quality (re-cutting rate <1.5%; loss rate <4%), low-loss cutting of alfalfa was achieved, and the harvesting quality of the disc-type cutter was improved.

The article consideres the issue of dynamic and energy analysis of the rotary tiller with planetary transmission gear and vertical rotation axis designed for orchards and vineyards. In the result of investigations, analytical expressions have been derived, which enable to determine the resistance force factors of the cultivated medium affecting the rotary tiller and to set up their changing patterns during a single rotation of the rotor in conditions of forward movement of the aggregate/working unit. It has been confirmed that in case of binary symmetric blades located at 120 degree, the resistance forces transmitted from the tiller satellites to the rotor shaft mutually balance each other, as a result of which the traction resistance force of the unit receives the possible minimum value. As regard to the resistance moments transmitted from the tiller satellites to the rotor shaft and to their main moments, it should be noted that they change significantly during a single rotation of the rotor. Particularly, the extreme values of the main moment for each tiller satellite are obtained at the finite points of the rotor’s diameter perpendicular to the forward movement of the tillage machine. Based on the driving and resistance force factors of the machine, as well as the differential equation of the motion, the term has been identified by means of the energy research of the rotary tiller, in case of which the angular acceleration of the rotor’s shaft will be equal to zero and the machine will operate without oscillations and vibrations.

The purpose of this research was to determine the character of kefir ice cream enrichment with Saccharomyces cerevisiae ATCC 36858 in various concentration. The study was conducted using a complete randomized design with 4 treatments (T0=0%; T1=0.25%; T2=0.5%; T3=1% S. cerevisiae ATCC 36858 (w/v)) and 4 repetitions. The results of the study were processed using ANOVA and DMRT. The treatment increases acidity, ethanol, viscosity and decreases the pH value, overrun, and melting rate of the product (p<0.05). The micro-nutrients (C, O, K, Ca, P, Cl, S, Na, Mg, Si) and macro nutrients (protein and fat) has changed (p>0.05). The lactic acid bacteria and yeast content has decrease of 10^5 CFU/mL during 28 days of storage. T2 has a good overall acceptance value with flavor and texture favored by panelists.

Orchard robots play a crucial role in agricultural production. Autonomous navigation serves as the foundation for orchard robots and eco-unmanned farms. Accurate sensing and localization are prerequisites for achieving autonomous navigation. However, current vision-based navigation solutions are sensitive to environmental factors, such as light, weather, and background, which can affect positioning accuracy. Therefore, they are unsuitable for outdoor navigation applications. LIDAR provides accurate distance measurements and is suitable for a wide range of environments. Its immunity to interference is not affected by light, colour, weather, or other factors, making it suitable for low objects and complex orchard scenes. Therefore, LiDAR navigation is more suitable for orchard environments. In complex orchard environments, tree branches and foliage can cause Global Positioning System (GNSS) accuracy to degrade, resulting in signal loss. Therefore, the major challenge that needs to be addressed is generating navigation paths and locating the position of orchard robots. In this paper, an improved method for Simultaneous Localization and Mapping (SLAM) and A-star algorithm is proposed. The SLAM and path planning method designed in this study effectively solves the problems of insufficient smoothness and large curvature fluctuation of the path planned in the complex orchard environment, and improves the detection efficiency of the robot. The experimental results indicate that the method can consistently and accurately fulfil the robots detection needs in intricate orchard environments.

This paper proposes a local path planning algorithm method named S-TEB (Smooth Time Elastic Band), aimed at fulfilling the requirement of full coverage for ORLMs (Orchard Robotic Lawn Mowers) during mowing operations. Firstly, by analyzing the tracking control mode of ORLMs in operational scenarios, control points are selected reasonably. Subsequently, utilizing B-spline curves, the path is optimized to generate the optimal trajectory and speed for ORLMs that satisfy multiple objectives and constraints. Finally, multiple simulations and field experiments were conducted in actual operational environments, with a speed of 0.6 m/s. Experimental results show that in scenarios involving obstacle avoidance, the minimum distance between the automatic lawnmower and the outer contour of obstacles is 4 cm. Compared to the traditional TEB planning algorithm, there is a 4.23% increase in mowing coverage area. These findings provide theoretical and technical support for local path planning in the operational scenarios of ORLMs.

This paper proposed a supplemental feeding pusher based on beef cattles auxiliary feeding needs to solve the traditional feeding mode of manual work, labor intensity, and inconsistent manual work standards. Firstly, the conveyed feed particles movement process was established as a motion model and the basis of the design parameters of the screw conveyor was explained. ANSYS static analysis module was used to ensure that the structural parameters of the discharging device were reasonable, ANSYS vibration modal analysis module was used to verify the frame strength and stability. According to the theoretical design of the trial prototype, the control system with STM32F103RE microcontroller as the core was carried out. Finally, the orthogonal test was conducted with the screw shaft speed, sweeping roller brush height, and traveling speed as test factors; different parameters were set to verify the effect of supplemental feeding and pushing, and parameter optimization of the test results was carried out using Design-Expert software. The optional combination of working parameters was determined to be the feeding screw shaft speed 188 r/min, the sweeping roller brush speed 160 r/min, and the work speed 0.26 m/s. The test demonstrated that the residual feed width was 0.73 m, and the transverse coefficient of variation was 14.9%, which could satisfy the needs of auxiliary feeding for beef cattle. This study reduced feed waste and met the cattle feeding needs to the greatest extent, and it could provide a reference for auxiliary feeding machinery.

The aim of this research is to address the issues of low precision in variable spraying within the existing farmland application system, whereby nozzles cannot be controlled independently and low pesticide utilisation is observed. A variable spraying system based on PTO protocol has been designed. The system comprises an STM32 microcontroller as the control core, including the host computer, multi-channel controller, electronic switch, and electromagnetic spray nozzle. The master control unit receives the spray amount set by the user and calculates the duty cycle of the corresponding nozzle, which is then sent to the multiplex controller in real time through CAN communication. The multiplex controller adjusts the on-off frequency and duty cycle of each electromagnetic nozzle in real time according to the duty cycle of the corresponding nozzle it receives, thus enabling the nozzles to be controlled independently. This study offers theoretical and technical support for the independent control of spray nozzles and the optimisation of pesticide utilisation for variable spray systems based on PTO protocols.

The complex vibration field in agricultural equipment during field operations not only predisposes key mechanical components to fatigue failure, but also leads to crop losses. This study introduces the Operating Transfer Path Analysis (OTPA) method to identify the vibration sources in the pickup header of a straw forage harvester. Finite element modal analysis, vibration testing, and operating transfer path analysis were conducted on the header frame. The findings indicate that excitation sources, including the hammer claw device, transmission, and dust box on the pickup header, are prone to resonant coupling with the header frame. The analysis reveals that the right transmission output shaft contributes 18.3% to the vertical vibrations on the right side panel of the frame. Meanwhile, the left transmission output shaft accounts for 29.4% of the horizontal vibrations on the left side panel. Additionally, the transmission input end is responsible for 54.8% of the horizontal vibrations on the front beam, while the dust box end contributes 45% to the forward vibrations on the rear beam. By identifying the primary transmission paths, the most effective strategies for the vibration reduction and optimization design of the pickup header can be developed. Furthermore, this study offers a theoretical foundation and experimental references for the vibration reduction optimization of other agricultural machinery.

During the grain drying process, in order to adjust the temperature, it is necessary to match the proportion of hot and cold air. This is the problem that the two components in the mixed gas cannot fully mix with each other in a short period of time, resulting in the problem that it takes a long time for the gas flow temperature to reach a stable value. Based on the process and technical requirements of the dryer, a self-priming hot air temperature changing device suitable for the dryer was designed. The two gas components used to improve the variable temperature ratio of the dryer are fully mixed with each other in a short time and a short distance, thereby reducing the loss caused by the food not reaching safe moisture. Based on Bernoulli s principle and the basic theory of airflow mixing in fluid dynamics, a mathematical model of airflow mixing in the constriction section of the main pipeline was established. Fluent was used to numerically simulate the distribution of uniform mixing distance and temperature field in the necking section. The results show that the mixing uniformity in the necking section reaches 75%-80%, which effectively improves the mixing efficiency. A self-priming hot air temperature change device test bench developed independently was used, and the quadratic orthogonal rotation combined test method was used for parameter optimization. Design-Expert.V8.0.6.1 was used for analysis and testing, and the regression equation and response surface were obtained to analyze the effects. Interaction between factors to determine the best combination of optimization parameters: when the number of air inlet pipes is 3.16, the incision axial angle is 27.6°, the temperature difference is 43.5°C, and the pipe diameter is 23.8mm, the post-mixing temperature is 50.93°C, and the mixing distance is uniform is 39.33mm. The test results are consistent with the optimization results. The self-priming hot air temperature changing device of the dryer has certain practical application value.

During the sowing operation, the consistency and stability of the row dispenses of a seeder are important indicators for evaluating sowing performance. A multi-channel real-time weighing device was designed to study and analyze the consistency of row dispenses in seeder under identical conditions, as well as the stability of dispenses from a seed dispenser. This device utilized two Arduino boards as controllers for data acquisition, processing, and transmission. Based on the Serial Peripheral Interface (SPI), data exchange between multiple Arduinos was achieved in a master-slave configuration, allowing for data acquisition from 14 pressure sensors in a one-master, one-slave setup. Pressure data was collected using pressure sensors, HX711 converter chips, and Arduino. LabVIEW was utilized as the upper computer to read data from the Arduino host serial port and provide real-time display and storage. This paper presents the structural and working principles of the device. Experimental tests on the weighing unit were conducted using a test bench to evaluate measurement errors. The absolute error mean ranged from 0.143 g to 0.262 g. Additionally, the impact of the seed impact force on the error was simulated using EDEM. The device was used to evaluate a six-row wheat seeder under the experimental conditions of the groove wheel having a length of 2.5 cm and a groove wheel speed of 25 r/min. The maximum coefficient of variation for seeding stability (Y1) was 2.38%, the minimum was 0.83%, and the mean was 1.21%. The coefficient of variation for consistency of seeding in rows (Y2) was 1.86%.

In order to investigate the soil reactions influenced by the single plate with the inclination angles from 0° to 75°, an in-house code of 2D DEM has been developed in this study. An iron flat plate penetrated soil by a constant velocity of 1 mm/s in the study. In the penetration test, the maximum vertical force was 753.8 N which was generated by the 0° plate. In addition, it was found that the less the inclination angle, the greater the vertical force. Furthermore, a greater force in the horizontal direction has been generated at 45° of the inclination angle. This research can provide a theoretical reference for optimizing tools that contact soil, for example, patterns/lugs on wheels, earthmoving blades (such as rotary cultivators, bulldozers, weeding machines etc.) and grouser of tracks.

In order to solve the problem that the wind field disturbs the trajectory of falling seeds and causes the seeds to be unable to be arranged in equidistant rows when the UAV is spreading rice, a shot seeding device that can sow five rows of pelleted rice seeds at the same time was designed. The unit is centered on an external grooved wheel seed metering device and a seed acceleration unit for row seeding and hole sowing. The airflow simulation of the rotor wind field of the UAV was carried out by simulation software to explore the changes in the wind field of the UAV during operation. The position where the wind field disturbance is minimized is chosen for the seed guide tube arrangement. The position with the least wind field disturbance is chosen to arrange the seed guide tube and combine it with a seed acceleration device to reduce the influence of the UAV wind field airflow on the direction of seed movement. The operational effectiveness of the seeding device with and without wind was verified by an indoor test and an outdoor flight seeding test, respectively. Simulation results show that: when the mouth of the seed guide pipe is 0.9 m away from the paddle, the wind field has the smallest influence on the sowing results. The results of the bench test show that: when the rotational speed is 30-45 r/min, the coefficient of variation of the discharge rate of each row (CVR) and total seed discharge rate stability (CVT) are less than 1.98% and 0.84%, and the seed breakage rate is less than 0.95%, which all conform to the UAV fly sowing industry standards. The outdoor mud box test shows that: when the baffle angle changes by 26%, 58%, and 71%, each slot wheel hole can store 5-10, 3-5 and 1-3 seeds respectively, and the UAV operates at a speed of 2 m/s-3 m/s, the pass rate of hybrid rice is greater than 86%, which meets the agronomic requirements of rice sowing operation.

Physical property parameter measurements and simulation model parameter calibrations of Pak Choi seeds were conducted to address the lack of accurate parameters for discrete elemental seed discharging simulation tests in the seed-metering device. Firstly, physical tests were utilized to determine the basic physical parameters and contact parameters of Pak Choi seeds. The results of these physical tests served as the basis for determining the range of simulation parameters. The Plackett-Burman test was employed to screen out factors that significantly affected the simulated angle of repose from the test parameters, including static friction coefficient between Pak Choi seeds-Pak Choi seeds and rolling friction coefficient between Pak Choi seeds-Pak Choi seeds. The optimal interval of these two factors was determined using the Steepest Climb Test. Subsequently, the regression equation between the significance parameters and the angle of repose was obtained through the Central Composite Designs test, and the best parameter combinations were obtained with the measured stacking angle of 24.3° as the optimisation target value: Pak Choi seeds-Pak Choi seeds static friction coefficient of 0.486, Pak Choi seeds-Pak Choi seeds rolling friction coefficient of 0.104. Finally, simulation and bench comparison tests were carried out for stacking angle and Pak Choi seed discharger performance evaluation. The relative error of the angle of repose was found to be 0.288%, while average relative errors for qualified sowing rate, replanting rate, and missed sowing rate were all less than 5%. These results demonstrate that calibrated Pak Choi seed simulation parameters are reliable and can serve as a reference for design optimization of Pak Choi seed dischargers in academic research writing standards.

This research aims to develop a mathematical model for estimating the milling degree of milled rice based on fluorescent imaging. The materials used were the Ciherang, IR64 and Mekongga varieties which are widely grown and consumed by Indonesian people. The experiment was conducted by varying the polishing time starting from 0 seconds to 34 seconds with 1 second intervals. Six grains of polished rice were taken to record their images using a camera with 365 nm UV fluorescent ring light. The data collected in this research were milling degree obtained by gravimetric method, milling degree obtained using a milling meter and color values of fluorescent images of milled rice by image processing. The results showed that prediction of milling degree using the RGB color model has the coefficient of determination between 0.8001 – 0.8652, which is considered as potential to be used as a model for estimating the degree of milled rice based on fluorescence images. The RGB color model shows that the image red signal has the highest coefficient of determination compared to green and blue signals. For all of the three varieties in this study, the Ciherang variety has a predictive model equation for the image red signal y = 3.9027x - 429.61, the IR64 variety has a predictive model equation for the image red signal y = 3.7344x - 415.01, and the Mekongga variety has a predictive model equation for the image red signal y = 3.5627x - 388.86.

The article presents results obtained for the thermal characterization of composite materials with clay matrix and inserts from agricultural waste (MCMLIDA). The experiments carried out led to the estimation of the coefficient of thermal conductivity of the bricks made from the MCMLIDA composite material. MCMLIDA composite materials have physical properties dependent on the parameters of the manufacturing process, one of the most important being the concentration of the insert. MCMLIDA materials were tested for eleven insert concentrations and four types of inserts (maize cobs, walnut husks, wheat straw, wool). Only the materials with the first two types of inserts had the necessary cohesion for the experiments over the entire range of concentrations (0-50%). It was found that the values of the conductivity coefficient of those materials were between 0.4 and 0.8 W/(mK), values that placed them in the area of good insulating materials from a thermal point of view. It was also observed that thermal conductivity increased (along with a decrease in insulating capacity) as the amount of insertion in the matrix was increased.

The article describes the achievement and values of the mechanical and thermal characteristics of composite materials with sludge matrix and the insertion of agricultural waste, focusing on the compressive strength and thermal conductivity coefficient. These two characteristics are essential for civil engineering applications. The compressive strength and thermal conductivity coefficient depend significantly on the insertion concentration in the composite material: the compression strength decreases, and the thermal conductivity coefficient increases as the insertion concentration increases. For mud matrix composites and seed husk insert, the compressive strength varies between 0.375 MPa and 2.292 MPa. In the case of sawdust insert, the compressive strength varies between 0.149 MPa and 2.292 MPa. These values indicate that composite materials are at the lower limit of strength of building materials, but have good insulating properties due to the low coefficient of thermal conductivity. These features recommend using them for supporting walls in light, floor-free buildings, and for partitions with good thermal insulation properties.

Using the staged sowing experiment data and rice quality data of the specialized forage rice "Zhongzao 39"(hereinafter referred to as "Z-39") conducted in Nanning, Guangxi, combined with climate and geographic information data, the meteorological factors that play a key role in the formation of rice quality for the specialized forage rice "Z-39" are screened and determined. Based on the actual planting of specialize forage rice in Guangxi and the critical disaster causing indicators of "Z-39" specialize forage rice, the climate quality zoning index of "Z-39" is determined. GIS fine grid spatial simulation analysis method is used for refined spatial simulation analysis on key meteorological factors. The zoning indicator method and path analysis method are fully used for refined level zoning of the climate quality of Guangxi specialized forage rice "Z-39". It includes three levels: optimal, high-quality, and suboptimal. Ultimately, a refined zoning map for the climate quality of "Z-39" is developed, and the results are in line with the actual situation of forage rice cultivation in Guangxi. The aim is to provide a scientific basis for the rational planning and sustainable development of the specialized forage rice "Z-39" in Guangxi.

The DEM (discrete element method) simulation and optimization of the shapes and quantity of spoons of spoon-wheel disc in the spoon-wheel seed-metering device under vibrational conditions are investigated in this paper. EDEM (Engineering-DEM) software was adopted to establish DEM models of ‘Zhongyu No.3’ coated maize seeds and the spoon-wheel seed-metering device first, and four additional spoons of various shapes (labeled as K1~K5, respectively) were designed. The test results indicated that the acceleration of seeds in the Y-direction in spoons (K2~5) was all less fluctuating than those in the original spoon (K1), and the multiple rate was the largest in spoon (K5). The ultimate optimal working speed of the spoon-wheel maize precision planter in southwest China was identified as 3 km/h, with 22 spoons and the ideal spoon shape being K3. The bench validation test was executed under vibrational conditions based on the optimal spoon structure and operation settings. The qualified rate exceeded 94.5% at an operating speed of 3~4 km/h, while the multiple rate was less than 4%, the leakage rate was lower than 1.5%, and the variation coefficient was smaller than 25.5%. The variety adaptability test was launched when the working speed was 3 km/h. The qualified rates of various maize varieties were all more than 96.5%; the multiple and leakage rates were both less than 2%, which satisfied the technical requirements of maize precision sowing in southwest China. The qualified rates of various maize varieties were all more than 96.5%, and the multiple and leakage rates were both less than 2%, which satisfied the technical requirements of maize precision sowing in southwest China.

The study used near-infrared reflectance (NIR) spectroscopy and hybrid calibration methods to predict oil and free fatty acid (FFA) content of Oil Palm Fruitlets (OPF) non-destructively. The reflectance and chemical content of OPF were measured and the calibration between NIR spectra and chemical content was performed using hybrid calibration methods (PLS-ANN, PCA-ANN). The best models to predict oil and FFA content of OPF respectively were the hybrid model of PLS-ANN with 25 Factor Components (FC) (R2 = 0.96; SEP= 2.21%, RPD = 4.79) and 19 FC (R2 = 0.96; SEP= 0.25%, RPD = 4.24) using Savitzky-Golay first derivative spectra pre-treatment.

In order to improve the sowing performance of air-pressure maize dense planting high-speed precision seed-metering device and reduce the occurrence of multiple and missed seeds phenomenon, a seed-cleaning mechanism with progressive seed scraper was designed. The structure and working principle of the seed-metering device and seed-cleaning mechanism are described, the mechanical model before and after the excess seed enters the seed cleaning area is established, and the design parameters of the key components of the seed-cleaning mechanism are determined through the method of theoretical analysis. The experiments of single-factor and multi-factor are conducted with seed clearing angle, operating speed, positive pressure value of blower as influencing factors, and with qualified index, miss index, multiple index as the experimental indexes. The results show that the optimal seed-clearing performance parameter combination of the seed-cleaning mechanism is seed-clearing angle of 0.024°, operating speed of 10 km/h, positive pressure value of 6.0 kPa, verification test of the parameter combination of the qualified index of 98.11%, multiple index of 1.44%, miss index of 0.45%. In the comparative experiment, the qualified index of the device with seed-cleaning mechanism increased by about 2.3% compared to the device without seed-cleaning mechanism, and the multiple index decreased by about 2.2%. The seed-cleaning mechanism is reasonably designed to meet the seed clearing operation requirements of air-pressure maize dense planting high-speed precision seed-metering device.

Black heart disease is one of the screening indicators of seed potatoes, which has a serious impact on the quality and yield of potato, and at present there are fewer non-destructive testing methods for internal defects of seed potatoes. This paper aims to utilize non-destructive testing technology to quickly identify qualified and black hearted seed potatoes, and then to protect yield and food security. In this paper, transmission spectroscopy system was utilized to collect the spectral data of 104 qualified seed potatoes and 104 black hearted seed potatoes in 450~940 nm band. Subsequently, four algorithms, namely Savitzky-Golay (SG), Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC) and First-order Derivative (FD), were utilized to pre-process the seed potatoes spectral data to improve the data noise ratio. Feature wavelength extraction was made using Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA) to enhance the sample data characteristics and improve the model interpretability. The construction of classification models for qualified and black hearted seed potatoes relied on two deep learning techniques, Convolutional Neural Networks (CNN) and Recurrent Neural Network (RNN), which were trained and tested for the feature bands respectively. The experimental results showed that SG-CARS-CNN was the optimal combination of classification algorithms, and the classification accuracies of both the training set and the test set reached 100%, which improved the accuracy of the test set by 3.85% compared with that of the traditional machine learning algorithms, and provided an accurate method for the rapid screening of qualified seed potatoes.

The accuracy of curved path-tracking for headland turning of transplanters is crucial to maintaining the row spacing precision required for rice planting. To address this issue, a method based on H-infinity state feedback control is proposed. In this method, the requirement of robustness is transformed into linear matrix inequalities (LMIs) to optimize the gain coefficients of the control law. The simulation test show that this method outperforms the Linear Quadratic Regulator (LQR) when facing uncertain parameters (longitudinal speed and cornering stiffness) and path curvature disturbance. In addition, the field test results show that when the transplanter tracks a 1/4 circular arc path with a radius of 2 meters, the mean value of the absolute lateral error and the absolute heading angle error using this controller are 0.029 m and 3.69°, respectively. The maximum absolute lateral error is 0.072 m, and 64% of the absolute lateral error are less than 0.04 m, meeting practical requirements. Compared with the LQR controller with feed forward control, the mean value of the absolute lateral error is reduced by 36%. This method meets the accuracy and robustness requirements for unmanned rice transplanter turning at the headland.

In this paper, a screening machine was designed to remove the impurities in the tuber harvest, which integrates the functions of vibration screening, air separation, and flexible polishing. Discrete element simulation analysis was carried out to investigate the movement of tuber harvest and soil in the machine and the effect of polishing and removing impurities, the rationality of the structure, and the size were verified. Orthogonal tests were designed and carried out, with the rate of impurity, loss, and crushing as indicators and crank speed, impeller speed, and polishing roller speed as factors. The optimum working parameters were obtained: crank speed 280.12 r/min, impeller speed 1056.27 r/min, polishing roller speed 405.02 r/min, the impurity content was 0.29%, the loss rate was 1.01%, and the breakage rate was 0.11%. Through experimental verification, the actual value and theoretical value are basically the same, which verifies the rationality.

In response to the poor fertilization performance of the deep application mechanism of the deep application liquid fertilizer applicator under multiple parameters, the fertilization variation of the crank rocker deep application mechanism under multiple working parameters is explored. To obtain the fertilization variation of the crank rocker deep application mechanism, a fertilization performance test bench for the crank rocker deep application mechanism is developed. On this test bench, the crank speed, liquid pump pressure, and spray hole diameter are used as experimental factors, and fertilizer application rate is used as experimental indicators. A composite design scheme of rotation center is adopted to establish a relationship model and response surface diagram between experimental influencing factors and influencing indicators. Design Expert 8.0.10 software is used to analyze and optimize the experimental data. The optimal results are a crank speed of 145.80 r/min, a liquid pump pressure of 0.25 MPa, a spray hole diameter of 3.02 mm, a fertilizer application rate of 28.6 mL, and a fertilizer loss rate of 1.9%. At this time, the fertilization performance of the mechanism is optimal. This parameter combination is applied for testing and verification to verify its rationality. The results can ensure that the crank rocker deep application mechanism has good working performance when working under multiple parameters, providing theoretical reference for designing deep application liquid fertilizer machines with simple structure and optimal fertilization performance.

In the layout of modern agricultural warehouse logistics handling industry, it is an inevitable way to realize industrial upgrading by replacing people with mobile robots. Aiming at the problems that the existing obstacle avoidance control algorithm of agricultural handling robot is easy to fall into local optimal solution, and the operation process of agricultural warehouse logistics handling robot is prone to collision, the obstacle avoidance control of agricultural warehouse logistics handling robot is studied, and a control algorithm based on improved potential field ant colony is proposed. The moving trajectory of the agricultural warehouse logistics handling robot during the handling process is studied, and the spatial kinematics equation of the robot is given. The ant colony algorithm is used to optimize the classical artificial potential field algorithm to improve the global optimization ability and balance the interaction between gravity and repulsion. In the aspect of local area obstacle avoidance of agricultural storage and handling robots, the artificial potential field is optimized twice based on the strategy gradient algorithm. By analyzing the probability of the next action command, the randomness of the travel path selection when multiple robots work at the same time is improved. After testing, the path of the proposed control algorithm is the shortest, and under the condition of complex path planning, the number of collisions between robots is also significantly less than that of the traditional obstacle avoidance control algorithm. The practical application can meet the needs of improving the efficiency of warehouse logistics management.

Lycium barbarum L. (L. barbarum) is an economic crop with high added value and profit. Vibration harvesting is a suitable mechanized harvesting method for L. barbarum. It bruises easily during harvesting due to the softness and vulnerability of fresh ripe fruit, resulting in economic losses. This study analyzed the fruit drop and collision during vibration harvesting. High-speed photography was used to obtain the impact speed and angle of the falling fruit, and a kinematic analysis of the collision with the collection surface was conducted. The majority of the fruit had an impact speed of 2-6 m/s and an impact angle of 30-90° with the collection surface. A drop test was conducted to assess fruit bruising, and the impact speed was converted to the drop height. A orthogonal rotation experiment was conducted, and mathematical model was established between the drop height, impact angle, and impact material, and the fruit bruise rate, maximum impact force, recovery coefficient, and impact time. The effects of the factors on the fruit bruise rate, maximum impact force, recovery coefficient, and impact time were analyzed. The test results show that a vibration harvesting device for L. barbarum should be designed to reduce the height between the fruit and the collection surface and utilize a tilted collection surface and high cushioning materials to reduce the fruit bruising. This study provides guidance for subsequent research on the bruising of L. barbarum during vibration harvesting and harvester design.

In IoT hydroponics, the integration of Internet of Things (IoT) and Machine Learning (ML) has opened up great opportunities to increase the productivity and smart system’s management. With the collected data from sensors in the environment, the machine learning model would analyze and predict the trend of the environmental factors, this combination not only improves the outcome quality but also helps saving the resources. Integrating machine learning into an IoT hydroponics system could not only create a smart, autonomous and adaptable system to changing conditions of environment in real-time but also optimize resources for a cost-effective and productive hydroponic system. In this study, a novel method was presented for predicting environmental factors using Machine Learning algorithm for smart IoT hydroponic systems. By applying this method, an IoT hydroponic system can predict the trends of environmental factors which affects the plants such as temperature, moisture, pH levels…. The experiment results show that the accuracy of the predicted data is reliable, it reached 94.2% for a day and 92.6% for a week. These results could help users take proactive measures to improve the cultivation quality.

The current field of pneumatic subventing prediction focuses on a single task and neglects the possible interrelationships between different outputs. In order to improve the prediction accuracy and reduce the number of algorithm model establishment, this study conducted field experiments on soil in autumn and winter. Neural network algorithms RBF (radial basis neural network), BP (backward propagation neural network), DNN (Deep learning network) and CNN (Convolutional neural network) were used to make multi-output regression prediction for changing the traction resistance and disturbance area affected by different levels of subsooning velocity, depth and pressure value in the process of pneumatic subsooning. The evaluation indexes RMSE, MAE and R2 were compared with the single output regression model, and the accuracy of the four models with the highest accuracy was compared with that of its own single output model to prove the correlation between traction resistance and disturbance area. The results showed that the R2 of the four model test sets of RBF, BP, DNN and CNN were 0.9999, 0.9966, 0.9986 and 0.9762, respectively. The R2 of the disturbance area are 0.9997, 0.9924, 0.9968 and 0.9715, respectively. RBF has the highest R2 and the lowest RMSE and MAE, indicating that the RBF model has the best prediction effect. Compared with the single output regression model of RBF model, the prediction accuracy of both outputs is higher, so it can be used to predict the subsoiling drag resistance and disturbance area.

To promote the application of solar energy-heat pump combined drying technology in forage processing and enhance the drying efficiency of alfalfa, an experimental study was conducted. The research utilized a solar energy-heat pump drying system and a mesh belt dynamic drying device to investigate the drying characteristics of alfalfa. Drying characteristic curves were obtained, and the drying model and parameters were determined through model comparison. The study also analysed the impact of factors such as hot air velocity, temperature, alfalfa stacking thickness, turning angle of the spinner rack, and conveyor belt speed on the drying characteristic curves and parameters of alfalfa. A predictive model for alfalfa moisture content was developed, and the effective moisture diffusivity and activation energy were calculated. The findings revealed that alfalfa does not exhibit a constant speed drying stage, and its drying primarily occurs during the deceleration drying stage. The Logarithmic model was found to accurately describe the moisture change pattern during the dynamic drying process of alfalfa, with a model fitting coefficient R^2 exceeding 0.994, with an effective moisture diffusivity ranging from 2.776×10-10 m2/s to 4.7324×10-9 m2/s, and an activation energy of 37.02 kJ/mol. The study suggests that increasing the hot air velocity and temperature, reducing the conveyor belt speed, and adjusting the alfalfa stacking thickness can further enhance the drying rate and reduce the drying time.

Studying the effect of variable fertilization during the jointing stage on winter wheat production in the rice-wheat rotation area is critical for evaluating the application effect and economic benefits of variable fertilization technology. The variable fertilization experiment of wheat was carried out in Jiangsu province by using the self-developed fertilizer applicator. Three fertilization methods were used to conduct a comparative analysis of the fertilization amount, population structure, and yield of winter wheat during the jointing stage. On this basis, the economic feasibility of variable fertilization during the jointing stage was evaluated. The experimental results showed that the control accuracy of variable-rate fertilization with fertilization equipment was greater than 95%. After variable fertilization, the coefficient of variation of NDVI values in the winter wheat canopy spectral data remained between 0.076 and 0.125, and the Christensen uniformity coefficient remained between 0.901 and 0.940. Compared with the traditional empirical balance method for quantitative fertilization of plots, the real-time variable fertilization plot used 13.6 kg/hm2 less fertilizer during the jointing stage. The findings validate that implementing variable fertilization can help reduce nitrogen fertilizer input, improve nitrogen fertilizer utilization efficiency, reduce environmental pollution, and enhance the sustainability of agricultural production.

In order to accurately and quickly achieve wheat grain detection and counting, and to efficiently evaluate wheat quality and yield, a lightweight YOLOv8 algorithm is proposed to automatically count wheat grains in different scenarios. Firstly, wheat grain images are collected under three scenarios: no adhesion, slight adhesion, and severe adhesion, to create a dataset. Then, the neck network of YOLOv8 is modified to a bidirectional weighted fusion BiFPN to establish the wheat grain detection model. Finally, the results of wheat grain counting are statistically analyzed. Experimental results show that after lightweight improvement of YOLOv8 with BiFPN, the mAP (mean Average Precision) value of wheat grain detection is 94.7%, with a reduction of 12.3% in GFLOPs. The improved YOLOv8 model now requires only 9.34ms for inference and occupies just 4.0MB of memory. Compared with other models, the proposed model in this paper performs the best in terms detection accuracy and speed comprehensively, better meeting the real-time counting requirements of wheat grains.

The protein content of alfalfa leaves surpasses that of stems significantly, rendering harvested alfalfa following stems-leaves separation a valuable resource for livestock feed, thus ensuring the provision of high-quality raw materials for production. This study introduces a novel process for stems-leaves separation, alongside the establishment of a suspension velocity experiment rig aimed at investigating and determining the suspension velocity of alfalfa leaves, stems, and plants across various moisture levels. The relationship among various factors including different alfalfa components, the length of lateral branches, stem lengths, Moisture Content (MC), and suspension velocity was empirically derived through experimentation. In this study, the chopping and blowing method was proposed, where the alfalfa was cut into pieces according to a certain length, and then the alfalfa was blown apart by generating airflow through a fan. To comprehensively analyze the impact of airflow velocity and cutting length on the Separation Evaluation Index, a response surface mathematical model was developed. The empirical findings indicate optimal stems and leaves separation of alfalfa when the airflow velocity reaches 4.29556 m/s, paired with a cutting length of 33.7956 mm. Conclusively, this experiment validates the efficacy of the chopping and blowing separation method for alfalfa stems and leaves segregation, thereby offering valuable insights into alfalfa stems and leaves separation practices. The outcomes of this study hold significant reference value for the broader alfalfa agricultural domain.

To solve the problem of poor steering performance of existing self-driving tractors based on electro-hydraulic coupled steering systems (E-HCSS) under multiple influencing factors, the research on electro-hydraulic coupled steering characteristics of self-driving tractors was carried out in this paper. Taking the electro-hydraulic coupled steering system as the research object, the E-HCSS test bench of the tractor was built, and the influencing factors affecting the responsiveness of the steering process were obtained through theoretical analysis: hydraulic fluid temperature, oil supply pressure and driving speed. The hydraulic fluid temperature, oil supply pressure and driving speed were taken as the test factors, and the steering system response time and response error were taken as the performance indexes for the single-factor steering test and orthogonal test. By establishing the regression mathematical model between the influencing factors and the indexes, the interactive influence of the factors on the indexes was analyzed, the optimal parameter combination was obtained, and the optimization results were verified. The test results indicated that the tractor electro-hydraulic coupling steering system could achieve good steering performance under the optimal parameter combination, and the optimal parameter combination was: hydraulic oil temperature 60°C, hydraulic oil pressure 15 MPa and driving speed 8 km/h. The studys results were as follows: hydraulic oil temperature 60°C, hydraulic oil pressure 15 MPa and driving speed 8 km/h. The studys results could provide a reference for the steering control of the self-driving tractor, the design of the self-driving steering system and the optimization of the parameters.

Simultaneous localization and mapping (SLAM) is one of the key technologies for agricultural robots to build maps and localize in complex orchard environments and realize unmanned autonomous operations. Due to the complexity of the orchard environment, the single canopy feature and the diffuse reflection of light caused by the leaves, etc., the map construction process of the orchard environment leads to mismatch and increases the cumulative error of the map construction. Aiming at the above problems, this paper propose a navigation map construction method for orchard environment based on the fusion of Scan Context and NDT-ICP. The method firstly searches the Ring key quickly to get the candidate frames, and scores the similarity between the candidate frames and the current frame, and effectively detects the loopbacks by two-stage searching algorithm to reduce the false matches in the map of orchard environment. Meanwhile, a point cloud alignment method based on the fusion of normal distribution transform coarse alignment and iterative nearest point exact alignment is used to reduce the cumulative error of the orchard environment map. The results show that the improved algorithm compensates the drift of the point cloud map with higher mapping accuracy, better real-time performance, lower resource utilization, higher overlap between the trajectory estimation and the real trajectory, smoother loops, and a 4% reduction in CPU occupancy. In the complex orchard environment, the root mean square error and standard deviation of the trajectories of this papers algorithm are 0.57 m and 0.19 m, which are 68% and 83% higher than those of the loop detection algorithms in the Lightweight Ground Optimized Lidar Trajectory Measurement and Multivariate Terrain Mapping (LeGO-LOAM), respectively. Accurate map construction and low drift pose estimation can be performed.The research algorithm effectively reduces the influence of mis-matching and large cumulative error in the process of map construction in the orchard environment, meets the demand for high-precision environmental mapping in the orchard environment, and provides technical support for promoting unmanned operation in the orchard environment.

Taking the large storage tank as the cleaning object, a cleaning robot integrating shoveling, crushing, sweeping and dust-absorbing was developed, and its dust-absorbing system was analyzed and optimized. Firstly, Fluent-EDEM gas-solid coupling was utilized to simulate the dust-absorbing system. By analyzing the fluid distribution and particle trajectory, the internal structure of the dust collection box was optimized to reduce the dust particles entering the fan box. Then, by analyzing the structural parameters of the suction nozzle, the influence of the nozzle shoulder angle, nozzle length, and shoulder height on the dust-absorbing effect was explored, and the parameters were determined, so as to reduce the energy loss and increase the flow rate on both sides of the nozzle. Finally, through the dust suction test, different models of nozzles were tested for dust suction, and the wind speed at the nozzle was measured, and the leakage of dust particles on both sides of the nozzle was significantly reduced after optimization, which verified the reliability of the simulation results and provided a theoretical basis for the design of the sweeping robot.

Vegetable precision planting agronomy is suitable for my countrys current vegetable planting system, and the air-suction vegetable precision planter is currently the most important work tool in my country. This paper designs a kind of air-absorbing vegetable precision sower for the problems of small vegetable seeds with small grains, poor mobility and high difficulty in achieving uniform sowing of small seeds. First, Fluent software is used to simulate and analyze the flow field of the air chamber in the seed metering device, and the pressure and velocity of the fluid in the air chamber are analyzed. Through the comparison of the pressure distribution cloud chart and the velocity distribution cloud chart, the influence of different apertures, holes, vacuum degree, and gas chamber depth on the flow field of the gas chamber is analyzed. The air suction seed discharger test bench was set up and orthogonal test was carried out, and the test results showed that the optimal parameter combination was 3.5 kPa vacuum degree of the air chamber, 2.4 mm diameter of the type hole, and 18 r/min rotational speed of the seed discharging disk. The high-speed photographic test was carried out under the optimal parameter combination, and the results showed that leakage of suction, adsorption of 1 seed, and adsorption of multiple seeds appeared in the process of suction, and it is important for the development of the air suction precision machine for small seeded vegetables with better performance. The results showed that the phenomenon of leakage, adsorption of 1 seed and adsorption of multiple seeds occurred in the process of seed suction, which provided a reference basis for the development of a better performance of the air-absorption precision planter for small seeds.

The farmland in the southwestern mountainous areas of China is mostly hilly terrain with multiple obstacles, and traditional manual spraying operations are time-consuming and laborious. The use of agricultural plant protection unmanned aerial vehicle (UAV) can reduce the problem of high manual operation costs. To solve the problem of optimizing the spraying operation path of plant protection UAVs, this study focused on the complex agricultural environment in the southwestern mountainous areas of China. First, a 2D agricultural map model with multiple obstacles was constructed using MATLAB. Second, the optimization requirements for job paths were analyzed, and a path optimization model based on the grid graph method was studied, aiming to shorten the total flight distance and reduce the number of paths. By applying the genetic algorithm, efficient optimization of the spraying path of plant protection UAV was carried out. Simulation verification showed that the optimized path significantly shortened the flight distance, accelerated convergence speed, and effectively avoided local repeated paths, thereby greatly improving the spraying efficiency of plant protection UAV.

In order to make the tractor better meet the needs of users under the premise of satisfying the use of functions, the Kano - AHP model is used to design the appearance of the tractor. Firstly, the emotional needs of users are collected, and the tractor modeling is designed according to the requirements combined with the Kano model. The design scheme is displayed through Rhino in the form of three-dimensional modeling. According to the design requirement index summarized by Kano model, the tractor modeling hierarchical structure model was established by using analytic hierarchy process, the weights of each index were obtained, and the best design scheme was selected according to the weights. Finally, the selected best scheme was imported into Jack ergonomics simulation software for stress analysis and comfort analysis of the lower back, and the analysis results were used to check whether the scheme met the man-machine physiological standards.

The present work investigates the dependences between weather conditions and the specific characteristics of nine wheat varieties and the reflection of light spectra. The obtained images captured with an unmanned aerial vehicle UAV model DJI Mavic 2 Pro and RGN camera reflect the state of vegetation of wheat varieties depending on environmental factors and the specific morphological features of each variety. The differences are analyzed and presented by varieties, the relationship between the factors through reflected light and the condition of the investigated winter wheat varieties. The study provides valuable information for future research on the influence of meteorological conditions on the accuracy of the results obtained with UAV imaging.

This article presents the results of experimental research on the extraction of polyphenols from nettle, lavender, and sage using the percolation method. This technique is recognized for its efficiency in extracting bioactive compounds from plants. Polyphenols are a group of natural chemical compounds characterized by the presence of multiple phenolic groups in their molecular structure. They are predominantly found in plants and are recognized in various industries, including agriculture, for their antioxidant, antimicrobial, and antifungal properties. The antioxidant capacity of the extracts from nettle, lavender, and sage refers to the ability of these extracts to neutralize free radicals. The concentrations of polyphenols in the obtained extracts were measured using the Folin-Ciocalteu spectrophotometric method. The impact of pressure on total polyphenol content varied by plant species. Sage showed increased polyphenol content at higher pressures, indicating more efficient extraction with the proposed technology.

In order to solve the difficulties in logistics distribution in remote rural areas, a systematic planning of agricultural logistics distribution for UAV distribution is carried out. Considering the limit of cruising range, from the perspective of green routing, a multi-package distribution path planning model of UAV agricultural logistics considering the limitation of cruising range of UAV is established with the goal of minimizing total energy consumption. According to the actual number of UAVs, the task allocation is carried out, and a mixed integer nonlinear programming model of task allocation is established. The improved ant colony algorithm is used to solve the problem. The core idea is to exchange the pheromones of each ant subgroup, and then use the insertion-based heuristic method and crossover and inversion operations to optimize the path. For the case of remote areas in western China, the agricultural UAV distribution path planning considering the mileage limit is conducive to saving resources and obtaining the lowest energy consumption distribution path ; for the problem of agricultural logistics distribution path planning considering the mileage limit of UAV, the improved ant colony algorithm designed in this study has higher solution accuracy than the traditional ant colony algorithm.

With the rapid advancement of agricultural mechanization, intelligent header technology has emerged as a pivotal element in optimizing the efficiency and quality of grain combine harvesters. This paper offers a comprehensive analysis of the current state of intelligent header technology, with a particular emphasis on the structure, working principles, contour-following mechanisms, and height control technologies. By integrating cutting-edge sensor technologies, advanced control algorithms, and optimized mechanical designs, intelligent headers can achieve precise control over height and posture, thereby significantly reducing crop losses and enhancing both harvesting efficiency and quality. Despite substantial progress, challenges remain in areas such as response speed, real-time performance, height measurement accuracy, and control algorithm effectiveness. Future research will likely concentrate on improving control system performance, refining component and system designs, and incorporating emerging technologies to better accommodate diverse crops and complex terrains. This paper also provides a critical evaluation of current limitations in intelligent header research and projects future trends, offering valuable theoretical and practical insights for optimizing header structures, minimizing losses, and enhancing intelligent functionalities. The ultimate aim is to drive continuous innovation and advancement in header technology for grain combine harvesters.

Water jet technology, as a non-contact cutting and crushing technique, is commonly used in industries such as cleaning, rust removal, cutting, drilling, and mining. It enables a green and environmentally friendly production process by avoiding environmental pollution, heat generation, blade replacement, and sharpening issues. Cutting, cleaning, and crushing techniques are widely applied in various stages of agricultural production, but mostly through contact-based methods. The application of non-contact water jet technology in the agricultural field is still in its infancy. This paper summarized the current application status and research progress of water jet technology in different operational stages of agriculture, including sowing, management, field harvesting, and post-harvest processing. The specific requirements of key parameters for different operational objects and stages were analysed. Furthermore, the challenges encountered in the application of water jet technology in agriculture and provides prospects for future research directions were discussed. The review is intended to provide references for the promotion and green sustainable development of water jet technology in the agricultural field.

In order to address the high impurity and loss rates in the cleaning process of existing peanut combine harvesters, the design basis of the cleaning sieve was explored. Tests were conducted to determine the composition of the peanut picking fruit and the characteristics of the material suspension mixture. Additionally, the mechanical relationship between the fruit and miscellaneous mixtures and the cleaning sieve was investigated. The wind speed ranged from 8 m/s to 10 m/s, the vibration frequency ranged from 6 Hz to 8 Hz, and the inclination angle of the sieve ranged from 5° to 9°. The scavenger sieve platform was constructed and tested using Box-Behnkens central combination test method. The optimal combination of fan wind speed (9 m/s), sieve surface inclination angle (8°), and sieve vibration frequency (7 Hz) resulted in a pod impurity rate of 1.16% and a loss rate of 1.4%. The device significantly reduces impurity content and loss rate during peanut harvesting. The studys results can serve as a reference for improving the design of the peanut combine harvester cleaning mechanism and optimizing operating parameters.

When designing appropriate machinery systems, equipment, and infrastructures for interacting with, cultivating, gathering, and agriculture-related processing, it is required to have an understanding of the engineering characteristics of agricultural products. This unpredictability makes it difficult to design or develop machines that can efficiently and effectively manage a wide range of product characteristics. Experimental analysis was used to accomplish the study s objective, which was to investigate the implications of variation on the physical characteristics and frictional parameters of common beans (Phaseolus vulgaris L.) concerning the design of the threshing machine. One hundred bean seeds from each variety were randomly selected and their three primary dimensions were measured with a digital vernier caliper (least count 0.01 mm) and a micro-screw gauge in order to determine the dimensional parameters. The remaining parameters (elongation at the width, thickness, and vertical orientation, geometrical mean diameter, arithmetic mean diameter, square mean diameter, equivalent mean diameter, roundness, sphericity, flakiness ratio, aspect ratio, cross-sectional area, projected area, transverse surface area, and the seed volume) were calculated using mathematical models. Gravimetric characteristics true density and seed volumes were calculated using the toluene displacement method. The data were subjected to analysis of variance (ANOVA), and the Duncan multiple range test was used to separate the means. Significance was accepted at 95% confidence interval (p< 0.05).The results data are required for predicting loads in agricultural storage structures, and to establish useful sources for the development of machinery for handling, cleaning, storing, transporting and drying, among other things.

The detection of pesticide residues in white tea fresh leaves is an important step to ensure the quality safety of white tea finished products. Traditional detection methods are costly and inefficient to realize the demand for fast, low-cost, and accurate detection of pesticide residues in white tea fresh leaves. In this study, five types of white tea fresh leaf pesticide residue sample data were obtained using hyperspectral imaging technology for the high-frequency detected pesticides Glyphosate and Bifenthrin, and the SVM and 1D-CNN models were established to detect the samples after noise reduction processing and feature band screening methods. The study shows that the 1D-CNN model has better feature extraction ability, in which the SG-CARS-1D-CNN model has the highest detection accuracy, which is 94.62%, 95.12%, 94.35%, 94.95%, and 95.27% for the five type of species samples, respectively. This study provides pesticide residue detection for white tea fresh leaves based on the combination of hyperspectral data and an artificial intelligence model, which provides an intelligent, nondestructive, efficient, and high-precision pesticide residue detection model for white tea fresh leaves.

As the feeding mass of harvester continues to be increased, the accumulation of the maize mixture on the screen more serious, leading to a decrease in screening efficiency of the cleaning screen. The maize mixture on the screen was quickly transported backward through a bionic screen based on the motion characteristics of earthworms to reduce accumulation. However, the impact of the main operating parameters of this bionic screen on the cleaning performance was not yet clear. Therefore, the main operating parameters that affect the loss percentage and impurity percentage of maize grain in the cleaning device of bionic screen were simulated using CFD-DEM. Analysis of variance, regression and response surface were carried out on the test data, and the optimal parameter combination was obtained through parameter optimization: the concave depth of the screen surface was 25 mm, the installation angle of the screen surface was –5.5°, and the airflow velocity at the inlet of the cleaning device was 12.3 m/s. At this time, the lost percentage of maize grain was 1.56%, and the impurity percentage of maize grain was 1.85%, which met the requirements of national standards. The experiment provides reference and basis for the follow-up exploration of the screening mechanism of bionic screen.

Aiming at the problems of low harvesting level of Chinese cabbage, high cost of manual operation and lack of special harvesting machinery, a double-row wheeled self-propelled Chinese cabbage harvester was designed on the basis of measuring the physical parameters of Zaofeng 01Chinese cabbage varieties and combining with the main local planting patterns. It can complete the root cutting, pulling, clamping and conveying, packing and collecting of double-row Chinese cabbage at one time. Through the design and selection of the key working parts of the double-row wheel self-propelled Chinese cabbage harvester prototype, the key working parameters of the profiling device, the root cutting-pulling device and the clamping conveying device were determined. The kinematics analysis of the harvester in the profiling, cutting, pulling, clamping and conveying links was carried out, and the field operation performance test of the prototype was completed. The results showed that: when the rotation speed of the cutter was 280 r/min, the rotation speed of the clamping conveyor belt was 240 r/min, and the forward speed of the machine was 1.44 km/h, the maximum qualified rate of harvesting was 95.08 %, the minimum value was 90.65 %, and the average value was 93.79 %. At this time, the working performance of the working machine is stable, the harvesting effect is good, and all performance indicators meet the relevant design requirements and standards. The research results can provide reference for the development and structural improvement of Chinese cabbage low-loss harvesting equipment.

In this study, saline soil parameters were calibrated based on EDEM discrete element method, soil density, soil elastic modulus, soil shear modulus, soil particle size distribution and Poisson s ratio were determined. The Hertz-Mindlin with Johnson-Kendall-Roberts(JKR) model was used to simulate the characteristics of soil stress and strain of particles under external forces. The JKR contact parameter between saline soil particles was used as a test factor, and the soil accumulation angle was used as a test index to carry out the saline soil contact parameter calibration test. It was finally determined that an elastic recovery coefficient of 0.262, a static friction coefficient of 0.263, a dynamic friction coefficient of 0.234, and a JRK surface energy of 10.084 were the optimal combinations of contact parameters for saline soils.

This study is based on the discrete element method to calibrate the physical parameters of astragalus membranaceus. Plackett Burman test, steepest climb test, and Box Behnken test were used to screen for significant influencing factors and optimal levels, and a quadratic regression model was obtained for the relative error between the simulated and physical experiment resting angles. The results showed that the relative error between the simulated and physical test angles of repose was only 0.392%, which can provide a theoretical basis for the discrete element simulation test of the working process of the astragalus membranaceus picking machine.

To meet the economy requirement of the horticultural machinery, a two-speed transmission system was proposed based on the characteristics of the driving cycle of the horticultural machinery. Firstly, the test cycle of the horticultural machinery was established based on the data collector that fixed on the machinery. Secondly, the two-speed driveline system was designed. To reduce the energy consumption in the horticultural machinery working cycle, the gear ratio of the two-speed gear box was optimized with the goal of minimum energy consumption by the Genetic Algorithm. The optimized gear ratio were 11.6 and 9.62. The comparison of energy consumption between single gear ratio and two-speed gear ratio was made. The comparison result showed that the energy consumption can reduce 0.25% under one transportation test condition, the energy consumption can reduce 0.41% under one ploughing test condition, and the energy consumption can reduce 0.41% under one rotary test condition.

Aiming at issues such as low instantaneous grasping ability, unsatisfactory cutting quality, and proneness to damage of the blades for existing harvesters, by observing the physiological structure and movement characteristics of the ant s mandible and by bionic design theory, a bionic blade was designed to optimize its performance. In this paper, Camponotus was selected as the research object to observe the movement of the right mandibular teeth. It was concluded that the movement of the ants mandibular teeth was a cutting-sawing motion. A comparative analysis was carried out using the flat blade and the mandibular teeth blade, uncovering that the mandibular teeth movement formed a sliding cut with a variable sliding cutting angle. The mandibular teeth were beneficial for clamping the target and boosting the instantaneous grasping force. The fourth tooth of the mandible was selected as the bionic prototype. from which the contour curve was extracted and analyzed, followed by the design of the bionic blade. Through the finite element method, the influence laws of parameters such as the tooth pitch, structural angle, and blade inclination angle on the stress field and deformation of the bionic blade were analyzed under two force application circumstances: along the inclination direction of the tooth edge and the blade face direction. The results showed that when the applied force was along the tooth edge inclination, the total deformation of the bionic blade initially decreased and then increased with the tooth pitch increase. The maximum equivalent stress of the bionic blade rose gradually with the tooth pitch increase, and the total deformation decreased with the increase of the inclination angle of the tooth. The equivalent stress diminished with the rise in the inclination angle. With the increase of the structural edge angle, the total deformation of the bionic blade rose gradually. When the force was applied along the blade face direction, the deformation and stress values of the blade were significantly lower than those when the force was along the tooth edge inclination. The research findings can offer theoretical references for the design of bionic blades for harvesters.

Strong wind and sand activities will seriously damage the ecological restoration and agricultural safety production on the edge of desert areas, resulting in irreversible economic losses. In order to prevent and protect the agro-ecological environment in the wind-blown sand area, this paper constructs a combination of double-row vertical nylon net sand barrier and grass grid sand barrier. Through numerical simulation and wind tunnel experiment, the protection benefits of double-row vertical nylon net sand barrier and grass grid under different spacing conditions are analyzed, and the layout conditions with optimal spacing are obtained. The results show that when the spacing between double-row vertical sand barrier and grass grid is 5H-10H, the airflow velocity behind the double-row vertical sand barrier cannot be fully developed, the increase of airflow velocity is small, and the average wind prevention efficiency is above 85%. The effective protection distance com-pletely covers the entire combined sand barrier area, and a large number of sand particles near the surface are fixed to the grass grid, so the sand resistance rate is over 77%. The combined sand barrier has a good cooperative protection effect and achieves efficient wind prevention and sand fixation. The wind tunnel experiment verifies the reliability of the results. It also realizes efficient wind prevention and sand fixation under extreme wind and sand weather, and avoids sand burial on farmland and ecological restoration areas caused by extreme wind and sand weather.

To achieve the process of automatic film cutting for cotton and improve the efficiency of cotton precision film hole seeding machine operation, this paper proposes a wireless handle button control method and designs a automatic film and tape cutting system for cotton precision film-laying hole seeder. The system includes electromagnetic integrated valve group, hole opener lifting hydraulic cylinder, membrane pressing hydraulic cylinder, multifunctional hydraulic cylinder for cutting film, strapping support hydraulic cylinder, hydraulic limit sensor, arc-shaped film cutting shovel reset sensor, wireless control handle for film cutting and film cutting controller. The system is based on the VisualTFT platform, equipped with a multi-functional touch screen. By integrating functions such as obtaining the forward distance of the machine, hydraulic control principles, and wireless control models for film cutting and burying, it achieves automatic cutting and burying of ground film and drip tape processes. The experiment verified the working performance of the automatic film cutting and feeding system of the cotton seed precision film mulching hole seeder and the results showed that the average monitoring accuracy of the machines forward distance was 98.16%; the response time for controlling the film cutting belt and burying film belt was =0.78s, and the execution time was =2.68s; the success rate of cutting film strips was 100.00% and the success rate of burying film strips was above 98.33%, which met the operational requirements of automatic film strip cutting for precise cotton seeding film hole planting machines.