Precision soil fertilization is an important aspect of smart precision agriculture development, and the fertilization prescription map is a prerequisite for precision fertilization. Taking grapevine soil information as an example, this study explores the impact of different sampling densities on the accuracy of soil nutrient distribution. Experimental trials were conducted using sampling densities of 1m x 1m, 3m x 3m, 6m x 6m, 9m x 9m, and 12m x 12m, with the optimal sampling density determined to be 6m x 6m. Nutrient distribution maps were created using Bigemap and ArcGIS software, and based on nutrient balance calculations using ArcGIS software, fertilization prescription maps were developed. Furthermore, precise fertilization schemes for nitrogen, phosphorus, and potassium fertilizers were formulated based on the prescription maps. This study provides methodological and data support for research on precision soil fertilization.

This study aims to develop and evaluate a locally manufactured carbonization unit with a screw conveyor. Various carbonization temperatures (350, 400, and 450°C) and feeding rates (50, 75, and 100 kg/h) were examined to determine optimal conditions for producing biochar from rice husk (RH). The results revealed that increasing the pyrolysis temperature from 350 to 450°C decreased RH biochar yield, while increasing the feeding rate from 50 to 100 kg/h increased it. Ash content was 22.4% at 350°C for 100 kg/h, and the maximum value was 31.4% at 450°C and 50 kg/h. The BET surface area of the biochar increased from 105.71 to 312.32 m2/g at 450°C, with slight non-significant changes at a 100 kg/h feed rate. RH biochar showed decreasing H and O values with higher temperatures and lower feed rates. RH biochar at 450°C and 50 kg/h showed increased macro porosity and surface area, rendering it suitable for agricultural application as a soil amendment.

This paper addresses the problem of the lack of intrinsic and contact parameters when applying the discrete element method to simulate and analyze the key aspects of white kidney bean seed sowing, harvesting and clearing. The experiment took white kidney bean seeds as the research object, measured the intrinsic parameters of white kidney bean seeds by using the universal testing machine, and measured the collision recovery coefficient of 0.445, static friction coefficient of 0.452 and rolling friction coefficient of 0.091 between white kidney bean seeds and Q235 steel plate by physical test and EDEM discrete element simulation parameter calibration. The stacking experiment was carried out by the cylinder lifting method, numerical processing was performed with MATLAB, and the actual stacking angle of white kidney bean seeds was 31.28°. The steepest climbing test was designed with the interspecific contact parameters as factors and the relative error between the actual and simulated stacking angles as indicators. The optimal combination of the interspecific contact parameters of white kidney bean was determined by response surface optimization analysis, and the interspecific collision recovery coefficient of white kidney bean was obtained as 0.39, static friction coefficient was 0.53, rolling friction coefficient was 0.092. Using the optimal parameters for the simulation test, the relative error between the actual stacking angle of white kidney bean seeds and the simulated stacking angle was 1.63%, indicating that the calibrated simulated contact parameters were reliable and could provide reference for the discrete element simulation of white kidney bean seeds.

In this study, a double-shaft type sweet potato rice-planting and rice-returning machine was designed. The structure of the whole machine as well as the key components were analyzed, and the influence of each factor on the operation quality was studied. The results of the study showed that the order of the influence of each factor on the length of broken stems and leaves and the rate of checking was as follows: roller speed > toggle clearance > toggle spacing; the order of the influence on the stubble height was as follows: toggle clearance > roller speed > toggle spacing; and the order of the influence on the rate of injury to potatoes was as follows: roller speed = toggle clearance = toggle spacing. The optimal combination of working parameters in the field test was 1944 r/min for roll speed, 132 mm for toggle spacing, and 20 mm for toggle clearance, at which the qualification rate of stem and leaf breaking length was 94.32%, stubble height was 33.61 mm, and potato injury rate was 0.26%. The relative error with the theoretical optimization value is between 0.13% and 7.14%, which meets the operational requirements of sweet potato rice transplanter.

In this paper, a new horizontal-shaft roller-type cotton stalk puller was designed to address the problems of weak research on cotton stalk pulling and harvesting machines, poor agronomic adaptability, and insufficient research. First, the physical and mechanical properties of cotton stalk were experimentally studied, and the cotton stalk pulling force test was conducted. and it was positively correlated with the cotton stalk diameter. Then, the moisture content and the bending characteristics of cotton stalk were evaluated. The test results showed the bending characteristics were positively correlated with the moisture content but were not evidently influenced by the diameter. Second, with the missed pulling rate and pull-off rate as the evaluation indexes and three independent variables, namely, forward speed, linear speed of stalk pulling rod, and rotation speed of stalk pulling roller, as the influencing factors, a 3D response surface model was established. On this basis, the lack-of-fit term P (p = 0.3650) > 0.05 of the evaluation index—missed pulling rate P1—was acquired, and the P value of pull-off rate P2 was always smaller than 0.0001. Finally, the results demonstrated that the influence of various factors on the missed pulling rate of cotton stalk is significant and followed the order forward speed > linear speed of stalk pulling rod > rotation speed of stalk pulling roller; the significance level regarding the influence on the pull-off rate followed the order rotation speed of stalk pulling roller > linear speed of stalk pulling rod > forward speed. Through the parameter optimization analysis, the optimal parameter combination was obtained which coincide with the model optimization and prediction result. The proposed method provides a basis and experimental reference for studying cotton stalk harvesting machineries.

The mechanical properties of lavender are the basis for design and study of mechanized equipment for planting and harvesting of lavender. This paper determines and studies the natural width and height of plant and spike length of three kinds of lavender widely planted in the Yili region and obtains the distribution rules of parameters of the basic physical properties of lavender. Meanwhile, the test of the mechanical properties of lavender was done at the moisture content in the harvest period and different moisture contents. The results indicated that the maximum separation force of the flower of three kinds of lavender (111.3N) was much smaller than the minimum breaking force of the stem (201.5N); and the moisture content significantly affected the mechanical properties of lavender, which could provide corresponding design parameters and important theoretical basis for the design of a new lavender harvester based on separation technology.

With the rapid urbanization in China, there has been a gradual increase in the production of kitchen waste, which poses significant environmental challenges. High-temperature aerobic fermentation is an effective method for recycling kitchen waste. This study focuses on utilizing kitchen waste, wood chips, and compound microbial agents as the main raw materials for fermentation. Various parameters such as temperature, moisture content, and amount of compound microbial agent were selected to conduct experiments on the high-temperature stage of the aerobic fermentation process for kitchen waste. Through response surface optimization experiments, it was determined that the optimal conditions for achieving fast high-temperature fermentation of kitchen waste are as follows: temperature at 60?, moisture content at 60%, and amount of compound microbial agent at 10%. The order of influence on the reduction rate of kitchen waste is found to be temperature followed by the amount of compound microbial agent and moisture content. These findings provide valuable insights into resource utilization strategies for managing kitchen waste.

As a bridge connecting agricultural production and consumption, the circulation of agricultural products has the function of connecting supply and demand, guiding production and promoting consumption. However, the development of rural logistics in China is slow, and most logistics centers still rely on experience to plan the pick-up vehicle routings, resulting in long transport time and high cost. In order to improve the efficiency of pick-up and reduce transportation costs, a joint optimization model of cold-chain pick-up vehicle routing and cargo allocation for fresh agricultural products was proposed in this study. Soft time window constraint and three-dimensional loading constraints were considered, and the lowest pick-up cost was used as optimization goals in this model. In addition, adaptive large neighborhood search algorithm (ALNS) and heuristic depth-first search algorithm (HDFS) were combined to solve the model. A case study of Kunming International Flower Auction Center was conducted to compare the schemes of pick-up vehicle routing before and after optimization. Results demonstrate that the pick-up cost after optimization decreases by 9.6 %, the number of vehicles decreases by one, the total volume utilization rate of vehicles increases by 23 %, and the total load utilization rate of vehicles increases by 15 %. This study provides a model reference and solution method for enterprise operators to formulate schemes of pick-up vehicle routing quickly and reasonably.

To solve the problem that the moving trajectory and operating trajectory are relatively independent and time-consuming when robots transfer agricultural products from harvesting fields to warehouses or transport vehicles, a type of agricultural materials handling robot was designed, the optimal trajectory planning method for the collaborative operating time of agricultural materials handling robots was proposed, and the time optimal trajectory under the collaborative operation of robot operating system and traveling system was acquired. Specifically, the kinematic model and dynamic model for the collaborative operation of robots were established to perform time optimal trajectory planning for materials handling robots, the Beta distribution was then applied to the Whale Optimization Algorithm (WOA) for population initialization, and a nonlinear convergence factor was introduced to prevent local optimum in the later stage of iterations. Finally, WOA was improved combining the variable neighborhood algorithm to enhance the diversity of the neighborhood structure, and this improved algorithm was applied to model solving. The results reveal that the proposed trajectory planning method can facilitate robots to obtain a smooth and time optical moving trajectory in collaborative operations of materials grabbing and discharging and obstacle avoidance. The displacement, speed, acceleration, and force/torque curves of each joint of the robots change gently, and the double-crawler traction can meet the requirements of the robots and rapidly stabilize and track the time optical trajectory.

When a sprayer is operating in the field, the uneven ground excitation causes the spray boom to move irregularly, significantly affecting the spray distribution uniformity and reducing the effectiveness of pesticide application. Installing a suspension between the vehicle and the boom is a crucial method to improve the boom stability. In this paper, experimental research on the stability of a boom with an active and passive pendulum suspension was carried out. The results of the transient response test of the passive suspension demonstrate that an increase in the suspension rotation damping coefficient reduces the overshoot of the system but slows down the response speed. Conversely, an increase in the suspension rotation stiffness coefficient speeds up the response speed. The results of the dynamic response test of the active suspension indicate that a smaller adjustment threshold of the control system for the boom inclination angle results in higher control accuracy. However, when the threshold is less than 1cm, the boom becomes challenging to balance. The results of the combination experiments based on the response surface method reveal that the rotation stiffness coefficient, rotation damping coefficient, unit forward speed, and their interactions significantly impact the adjustment time of the boom and the variation coefficient of the boom inclination angle. Through contribution rate analysis, the influence order of each factor on the adjustment time and variation coefficient was obtained. Additionally, the analysis of variance results show that the established regression model fits the actual situation well, and has reference significance for the design and application of the suspension.

In this paper, the microscopic damage mechanism of Modified Sporidiobolus johnsonii A (MSJA) in spray drying was investigated. The results showed that at a water content of 0.21 or a temperature of 52 oC and at a water content of 0.07 or a temperature of 71oC, irreversible damage such as selective-permeable damage and collapse due to the transformation of the gel phase and the inverse-hexagonal phase of the phospholipid molecular layer of the cell membrane bilayer were the main reasons for the beginning of inactivation and large amount of inactivation of MSJA, respectively, in the spray-drying process.

In this paper, a new horizontal-shaft roller-type cotton stalk puller was designed to address the problems of weak research on cotton stalk pulling and harvesting machines, poor agronomic adaptability, and insufficient research. First, the physical and mechanical properties of cotton stalk were experimentally studied, and the cotton stalk pulling force test was conducted. and it was positively correlated with the cotton stalk diameter. Then, the moisture content and the bending characteristics of cotton stalk were evaluated. The test results showed the bending characteristics were positively correlated with the moisture content but were not evidently influenced by the diameter. Second, with the missed pulling rate and pull-off rate as the evaluation indexes and three independent variables, namely, forward speed, linear speed of stalk pulling rod, and rotation speed of stalk pulling roller, as the influencing factors, a 3D response surface model was established. On this basis, the lack-of-fit term P (p = 0.3650) > 0.05 of the evaluation index—missed pulling rate P1—was acquired, and the P value of pull-off rate P2 was always smaller than 0.0001. Finally, the results demonstrated that the influence of various factors on the missed pulling rate of cotton stalk is significant and followed the order forward speed > linear speed of stalk pulling rod > rotation speed of stalk pulling roller; the significance level regarding the influence on the pull-off rate followed the order rotation speed of stalk pulling roller > linear speed of stalk pulling rod > forward speed. Through the parameter optimization analysis, the optimal parameter combination was obtained which coincide with the model optimization and prediction result. The proposed method provides a basis and experimental reference for studying cotton stalk harvesting machineries.

In order to solve the problems of artificial operation, high labor intensity and low efficiency of frost prevention in hilly orchards, this study takes hilly orchards as the research object. Based on the agronomic requirements of frost prevention in hilly orchards, a smoke anti-frost machine based on the transport track of hilly orchards is designed. With the help of Fluent software, the spatial and temporal distribution characteristics of smoke mass concentration and temperature in the process of smoke diffusion are simulated and analyzed based on the discrete phase model. The results show that the smoke continues to erupt at a speed of 6 m / s, and the plume volume gradually increases. After 9 s, the smoke reaches a stable diffusion state. Based on the established smoke diffusion simulation model, the orthogonal test analysis of the working parameters at the smoke outlet of the frost-proof machine was carried out with the temperature increase near the canopy of the fruit tree as the index. The results showed that the best combination of working parameters at the smoke outlet of the frost-proof machine was the smoke outlet speed of 10 m / s, the smoke outlet angle of 60 °, and the smoke outlet diameter of 140 mm. The field test results show that the frost-proof machine can continuously operate for 0.5 h at a running speed of 0.6 m / s, and the temperature in the height range of 1.5 m to 4 m in the working area can be increased by about 1.7 ° C. This study is of great significance to reduce the frost disaster loss of hilly orchards and improve the economic benefits of hilly orchards.

In order to solve the problems of easy seed shedding and poor seed population mobility during sowing, a precision seed metering tray for edible sunflowers with seed guide strips was designed in this paper. This article aims to adjust the adsorption posture of sunflower seeds by designing three types of structures: triangular seed guide strip, rectangular seed guide strip, and diamond seed guide strip. Seed population motion simulation and seeding performance experiments were conducted on the seeder. The experimental results show that adding a triangular seed guide strip to the seeding tray has the best disturbance effect on the seed population, with the highest proportion of seeds in the first adsorption stance seed (the seed centroid was adsorbed) and the highest qualification index. The working parameters for the best seed metering performance were obtained: the rotating speed of the seed metering disc was 8.41 r/min, and the vacuum degree was 3.5 kPa.

To improve the accuracy of apple fruit recognition, enhance the efficiency of automatic picking robots in orchards, and provide effective visual guidance for the picking robot, a target recognition network model based on improved YOLOv5 is proposed. Firstly, the original apple images collected and the data images obtained by different data enhancement methods are used to establish a dataset of 1,879 images, and the dataset is divided into the training set and the test set under 8:2; then for the problem of low detection accuracy of apple fruits in the natural environment due to the mutual obstruction of apple fruits, this paper modifies the backbone network of YOLOv5 by adding the attention mechanism of the Transformer module, the Neck structure is changed from the original PAFPN to BiFPN that can perform two-way weighted fusion, and the Head structure adds the P2 module for shallow down sampling; finally, the recognition test is performed on the dataset, and a comparative analysis is performed according to different evaluation indexes to verify the superiority of the proposed model. The experimental results show that: compared with other existing models and the single-structure improved YOLOv5 model, the comprehensive improved model proposed in this paper has higher detection accuracy, resulting in an increase of 3.7% in accuracy.

In order to study the effect of population disturbance on the filling performance of the seed metering device, this paper uses the pneumatic precision seed metering device as the model, and uses EDEM software to simulate the population movement of three different seed metering devices. The bench test was carried out at different pressures at 12 km/h and at different speeds at 3.5 kPa. The results show that the designed seed disk with grooves has the most intense disturbance and the highest qualified rate. In order to verify the performance of the disk, full factor tests are carried out on the air pressure and speed, The test results show that when the operating speed is 10~12 km/h and the positive pressure is 3~3.5 kPa, the leakage rate is no higher than 5.42%, the replay rate is no higher than 0.42%, and the qualified rate is no lower than 94.58%. When the operating speed is 14 ~ 16 km/h and the positive pressure is 3.5~4 kPa, the leakage rate is not higher than 6.7%, the replay rate is not higher than 1.04%, and the pass rate is not lower than 93.12%. All the indicators are better than the national standard.

This research is dedicated to enhancing the accuracy and processing speed of grape disease recognition. As a result, a real-time grape disease detection model named MSCI-YOLOv8s, based on an improved YOLOv8s framework is proposed. The primary innovation of this model lies in replacing the backbone network of the original YOLOv8s with the more efficient MobileNetV3. This alteration not only strengthens the ability of the model to capture features of various disease manifestations in grape leaf images but also improves its generalization capabilities and stability. Additionally, the model incorporates the SPPFCSPC pyramid pooling structure, which maintains the stability of the receptive field while significantly enhancing processing speed. The integration of the CBAM attention mechanism further accentuates the ability of the model to identify key features, substantially increasing the accuracy of disease detection. Moreover, the model employs Inner-SIoU as the loss function, optimizing the precision of bounding box regression and accelerating model convergence, thereby further enhancing detection efficiency. Rigorous testing has shown that the MSCI-YOLOv8s model achieves an impressive average precision (mAP) of 97.7%, with an inference time of just 37.2 milliseconds and a memory footprint of 39.3 MB. These advancements render the MSCI-YOLOv8s not only highly efficient but also extremely practical for real-time grape disease detection, meeting the actual demands of grape orchard disease identification and demonstrating significant potential for application.

Mini-tiller is an indispensable agricultural machinery in hilly and mountainous areas of China. Rotary blade is an important working part of mini-tiller, which directly affects the operation quality and power consumption of mini-tiller. In order to reduce the cutting resistance and power consumption of the rotary blade of mini-tiller, the cutting process of the rotary blade was analyzed by numerical simulation, and the tangential bending radius (R), bending angle (ß) and edge thickness (c) of the rotary blade were selected as factors to optimize it. After comparing the cutting resistance and cutting power consumption of the rotary blade before and after optimization, the results show that the cutting force of the optimized rotary blade is smaller than that of the rotary blade before optimization. The cutting power consumption of the optimized rotary blade is 2.4% lower than that of the unoptimized rotary blade, which achieves the purpose of drag reduction and consumption reduction.

Soluble solid content (SSC) is one of the important evaluation indexes of the internal quality and taste of fresh jujube. In order to realize the online nondestructive detection of SSC of fresh jujube, this paper took Huping jujube as the research object, adopted self-constructed nondestructive online testing system to collect the spectral information of jujubes (350~2500 nm), and studied the influence of the rotational speed of 4 r/min on the online prediction model of SSC of jujube. Kennard-Stone (KS) algorithm was used to divide the sample into correction set and prediction set. Six commonly used preprocessing methods such as SG smoothing (S-G), multiplicative scatter correction (MSC), standard normal variate (SNV), orthogonal signal correction (OSC), first derivative (FD), and second derivative (SD) were applied to the spectral data, and the regression coefficient (RC) algorithm and the successive projections algorithm (SPA) were utilized to select informative wavelengths, and a quantitative prediction model for the SSC of Huping jujube was established using partial least squares regression (PLSR). The results indicate that the PLSR prediction model established by preprocessing the original spectrum with OSC and combining it with RC algorithm to select characteristic wavelengths was optimal. Therefore, when predicting the SSC of Huping jujube, the optimal model was OSC-RC-PLSR, and the correlation coefficients of the correction set and prediction set were 0.846 and 0.782, respectively, and the corrected root mean square error (RMSEC) and predicted root mean square error (RMSEP) were 1.962 and 2.247, respectively. The results show that non-destructive detection of soluble solid content of jujube can be achieved by combining visible-near-infrared spectroscopy and appropriate regression model, which provides an innovative way for online sorting and identifying fresh jujube.

The study focused on enhancing a movable rotating plate type grading device for potatoes, prioritizing safety and weight reduction. By optimizing the body frame and movable rotating plate using ANSYS Workbench 2022, a static analysis was conducted to confirm compliance with design requirements for strength and deformation. The optimized frame experienced a remarkable 32.3% weight reduction. Additionally, the direct optimization module of ANSYS Workbench 2022 was employed to lighten the movable rotating plate, resulting in a 22.86% reduction in the total mass of the device. This research serves as an invaluable reference for the structural design and optimization analysis of potato grading devices.

In general, sentinel-2 imagery can be used for crop mapping. Crop types mapping aims to develop future strategies for sustainable agricultural systems. This study used Sentinel-2 from June 25 to July 6, 2023, with 10% cloud cover. The research was conducted in Pasrujambe and Candipuro sub-districts (± 242.23 km2). The image is processed using a random forest on the GEE platform. Accuracy was generated using a confusion matrix with an overall accuracy of 85.82% and a kappa of 71.19%. Five main types of land use/cover were produced, namely: paddy (17.31%), sugarcane (0.93%), vegetation (69.74%), sand (7.4%) and built-up land (4.59%).

In response to the issues of missed and repeated planting during the operation of the chain-spoon type potato planter in China, as well as the low recognition rate for missed planting and the difficulty in identifying repeated planting using existing detection methods, an innovative Potato Planter Missed and Repeated Planting Detection System has been designed. This system is built with a PLC as the lower-level controller and an industrial computer as the core, incorporating the YOLO object detection algorithm for detecting missed and repeated plantings during the operation of the potato planter. Using the YOLOv7-tiny object detection network model as the core, and combining model training with hardware integration, the system performs real-time detection of the potato seed situation within the seed spoon during the operation of the potato planter. It can quickly distinguish between normal planting, missed planting, and repeated planting scenarios. By incorporating the working principles of the planter, the system designs a positioning logic to identify the actual coordinates of missed and repeated planting locations when a lack or excess of planting is detected. This is achieved through the positioning module, enhancing the systems capability to accurately obtain coordinate information for actual missed and repeated planting positions. The system was deployed and tested on a 2CM-2C potato planter. The results indicate that the detection accuracy for missed and repeated plantings reached 96.07% and 93.98%, respectively. Compared to traditional sensor detection methods, the system improved the accuracy of missed planting detection by 5.29%. Additionally, it successfully implemented the functionality of detecting repeated plantings, achieving accurate monitoring of quality-related information during the operation of the potato planter.

The seeder was tested and evaluated for field operations vibration characteristics in light of the issue that the spoon-wheel maize precision seeder vibrates due to the field operating conditions, which impairs the performance of the seed-metering device. During field testing, it was discovered that the seed-metering device vibrated greater as the forward speed increased, resulting in a higher peak vibration acceleration. However, fluctuations in forward speed did not affect the frequency distribution of the peak vibration acceleration. Time-domain and spectrogram investigations revealed that the vibration frequency of the seed-metering device was predominantly within 0~10 Hz for seeder operating speeds ranging from 2~6 km/h, with acceleration values spanning from 0.85~1.86 m/s2. An electromagnetic seeding test stand was established in response to the discoveries. The essential variables governing the seeding performance of the spoon-wheel seed-metering device were then investigated using orthogonal tests, such as forward speed, vibration frequency, and vibration acceleration. The empirical results elucidated a hierarchical relationship between these factors and seeding quality. Specifically, vibration frequency emerged to be the predominant factor, followed by vibration acceleration, and forward speed. The seeding quality of the seed-metering device was negatively correlated with increases in forward speed and vibration acceleration, which led to a lower qualified rate, higher leakage rate, and variation coefficient. Overall, the qualified rate, leakage rate, and variation coefficient were all significantly influenced by the three factors.

The analysis of the clearing process of the cutting deck of a small plot wheat combine harvester requires the use of discrete element simulation methods. However, the current simulation test lacks the contact parameters such as wheat stalk and stalk-seed. In this paper, the wheat stalks and seeds at harvest time were taken as the research objects, and the calibration study of the discrete element simulation model parameters of stalks and stalk-seeds was carried out by means of mechanical test determination and EDEM software simulation. The stiffness coefficients of wheat stalks were determined by mechanical tests; the average values of wheat stalk stacking angle of 39.22° and wheat stalk-seed stacking angle of 44.41° were obtained by stacking angle tests. By the steepest climb test and binary regression test, the stalk normal stiffness coefficient was determined to be 5e+08N/m2 and tangential stiffness was determined to be 6.35e+08N/m2; the stalk-stalk collision recovery coefficient was obtained to be 0.551, static friction coefficient was obtained to be 0.797, and rolling friction coefficient was obtained to be 0.079 by the two-level analytical factorization test, the steepest climb test, and the three-factor response surface test. Based on this, the average value of wheat stalk-seed stacking angle was obtained to be 39.22° and the average value of wheat stalk-seed stacking angle was obtained to be 44.41° by the stacking angle test. On this basis, the coefficient of recovery of stalk-stalk collision was 0.434, the coefficient of static friction was 0.884, and the coefficient of rolling friction was 0.339 obtained by the three-factor response surface test. Three validation experiments were carried out by substituting the obtained parameters into the simulation test, and the error values were close to the error value %0.255 in the model, which proved that the experimental data were reliable.

In order to be consumed whole year at a nutritional value close to the freshly picked product, seasonal vegetal products (vegetables, fruits, aromatic and medicinal plants, seeds, berries, mushrooms etc.) are preserved by artificial dehydration. Unlike other preservation methods and techniques, dehydration leads to obtaining products with a weight 8-10 times reduced and a volume 3-4 times smaller, a fact that contributes to the reduction of the spaces required for storage and the substantial reduction of handling and transport costs, compared to those for fresh vegetal products. Taking into account the general context related to global warming, as well as the need to reduce energy consumption from fossil fuels, the paper approaches the preliminary experimental research of a small capacity convective dryer, with total energy independence from the electricity network, intended for small agricultural producers from isolated hill and mountain areas. The technical equipment consists of a thermal generator operating on TLUD principle, which utilizes existing biomass at the local level, a high-efficiency air-air heat exchanger and a drying room with trays. The aim was to determine some important technical-functional parameters in the working process of the equipment, such as: the temperature of the burnt gases, the biomass loading capacity of the gasification reactor, the capacity to regulate the air flow required for the thermo-chemical processes, the temperature at various keypoints inside equipment etc. Following the analysis of the experimental data, there were highlighted quantitative values useful for estimating the inputs required for a normal operation of the equipment.

In view of the lack of accurate contact parameters and the difficulty of measuring contact parameters in the discrete element simulation of mechanized harvesting of highland barley, this study took the wax-ripening highland barley as the object, carried out the discrete element simulation of highland barley stem based on EDEM, and calibrated the discrete element simulation parameters of highland barley stem by response surface optimization. In this paper, Plackett-Burman test was used to screen 8 initial parameters. It was found that the static friction coefficient between highland barley stems, the rolling friction coefficient between highland barley stems, and the rolling friction coefficient between highland barley stems and steel plates have significant effects on the particle angle of repose. Based on the optimal value range of significant factors determined by the steepest ascent test, a second-order regression model of the angle of repose and significant parameters was established and optimized based on the results of Box-Behnken test. The optimal parameter combination of significant parameters was obtained as follows: static friction coefficient between highland barley stems is 0.27, rolling friction coefficient between highland barley stems is 0.07, and rolling friction coefficient between highland barley stems and steel is 0.26. Finally, the simulation results under the optimal parameter combination are compared with the actual test angle of repose. The relative error is 0.52 %. That indicates that the parameters of the simulation calibration are credible, which can provide a reference for the future research on the cleaning device in the mechanized harvesting of highland barley.

Aiming at the traditional peanut planter seed and fertilizer sowing depth inconsistency caused by seed burning and injury, fertilizer waste and low seed emergence rate, the design of a peanut planter with high-speed operation and controllable seed and fertilizer sowing depth was performed. The laser sensor is added to detect the height of the ridge and the furrow opener position feedback, and the speed sensor detects the operating speed of the peanut planter. The mechanical analysis of the four-link rod clarifies the control principle, improves the PID algorithm of the integral term, designs the control strategy based on the operating speed of the planter, controls the electro-hydraulic system, and realizes the sowing and fertilizing depth adjustment of the furrow opener. Through the design of three-factor three-level orthogonal simulation test, it is concluded that the vehicle speed and height deviation value are significant factors affecting the sowing and application depth, and under the verification of the field test, it is obtained that when the sowing depth is 50 mm under the speed of 3 km/h, the dynamic sowing depth qualification rate is 96.26%, and the maximum coefficient of variation of the sowing depth is 2.58%, which improves the effect of the existing control of the sowing depth of the peanut by 6.05%, and reduces the variation of the sowing depth by 2.85%. The research has demonstrated superior performance compared to traditional mechanical adjustment in regulating the planting depth of peanuts, thereby achieving the intended design objective.

During the field application of pesticides by plant protection UAV, due to the interference of meteorological factors or operating parameters, the deposition effect of droplets is poor. In order to explore the impact of the nozzle angle of plant protection UAV on droplet deposition distribution, this article is based on field experiments and collects data on different flight speeds (1, 3, 5 m/s) and nozzle angles (±60°, ±45°, ±30°, 0°), and performs variance analysis and regression analysis on the test results. The results showed that adjusting the nozzle angle had a significant effect on the amount of droplet deposition and deposition uniformity. Compared with 0°, the nozzle angle of -30° increased the amount of deposition by 76.94% and 61.04% at flight speeds of 1.2 m/s and 3 m/s, respectively. The flight speed had a significant effect on the amount of droplet deposition, and the increase in flight speed decreased the amount of droplet deposition by 55.97%-77.06% and had no significant effect on the uniformity of droplet deposition. This study provides a reference for improving the droplet deposition effect of plant protection UAV field pesticide application operations.

In this study, the discrete artificial bee colony (DABC) algorithm was proposed to plan the path of agricultural robots traversing multiple fields in hilly areas. Based on the basic ABC algorithm as the framework, the path coding method was adopted, and the discrete crossover operator, reverse operator, immune operator, and single/multi-step 2-opt operator were comprehensively used to help hired bees, observing bees, and scout bees to generate new food sources. Finally, the optimized field traversal order and the entrance and exit distribution of each field were obtained. The simulation results showed that compared with the traditional ABC algorithm, the average shortest path of the DABC algorithm proposed in this study was shortened by 1.59%, accompanied by the less iterations contributing to algorithm convergence and good ability to jump out of the local optimal solution. The simulation experiment was carried out using real field data and field operation parameters. The field traversal order and the entrance and exit distribution obtained by the proposed method can effectively reduce the length of the transfer path and its repeatability. This study exhibits superiority and feasibility in the field traversal path planning of agricultural robots in hilly areas, and the trajectory coordinates output by the algorithm can provide a path reference for large-area operations of agricultural machinery drivers or unmanned agricultural machineries.

The rolling friction coefficient was a fundamental parameter for particle modeling, but it was challenging to quantify for unevenly shaped corn seeds. If the rolling friction coefficients of corn with different guiding seeds and different shapes were not believed to be significantly different, direct simulation in EDEM would produce simulation distortion. This paper began by selecting three models with a relatively high proportion from five corn samples with various shapes (such as horse-tooth shape, spherical shape, oblate shape, and irregular shape, etc.) and modeling them according to the actual seeds. Due to the large disparity between seed models with different shapes, the study adopted the method of combining physical experiment and discrete element simulation, took the rolling friction coefficient as the independent variable and the angle of repose in the simulation test as the target value, and calibrated the rolling friction of various shapes of corn seed particles separately. Coated corn seeds rolling friction coefficients were accurately predicted (0.0047 for horse tooth, 0.0058 for pyramid, and 0.049 for spherical shape). During the validation test, the calibrated simulation parameters were entered into EDEM for simulation, and the distribution of seeds on the seed platter was compared between the actual test and the simulation test. The results demonstrated that the difference in the sizes of key features was less than 5.60 percent, and the population boundary in the seed platter after calibration was closer to the actual situation, which improved the accuracy of the simulation.

The mechanized harvesting of mulberry is important for its production. In the process of harvesting, it is considered not only the mechanical damage of mulberry fruit but also its harvesting efficiency. It is very important to improve the vibration harvesting efficiency of mulberry. In this study, modal analysis of mulberry trees and harmonic response analysis of branches were carried out to determine the harvesting frequency of the branchs vibration and other parameters. The effects of excitation frequency and vibration position on the triaxial acceleration of the mulberry branch at different positions were analyzed by vibration test. Then the triaxial acceleration of branches at different positions was analyzed. The conditions of the mulberry fruit shedding were obtained through theoretical analysis. Through the 20-order modal analysis of mulberry, it is concluded that a better vibration effect can be achieved when the vibration frequency is controlled at 4-16 Hz. According to the harmonic response analysis, the best excitation frequencies are 5-6 Hz, 10-13 Hz, and 14-16 Hz. The harmonic response analysis of fruit branches was carried out, and the stress of fruit stalks at 5 Hz, 10 Hz, and 15 Hz were analyzed. The result shows that the maximum stress is 2.9252×107 Pa, the excitation position is the first-order branch, and the excitation frequency is 15 Hz. The frequencies obtained from modal analysis and harmonious response analysis were used to conduct experiments. When the excitation frequency was 15 Hz, the triaxial accelerations aX, aY, and aZ were 2.12 g, 4.16 g, and 3.99 g, respectively, which were more conducive to the shedding of mulberry fruits.

In order to solve the problem of mechanical direct seeding of rice seeds on the exposed soil surface, which is affected by bird and mouse damage, rain and sun exposure, etc., a pendulum-type synchronous soil-covered rice direct seeding machine was developed. In order to clarify the leakage and anti-entanglement performance of the mulching plate, linear function type, quadratic function type and exponential function of the sliding blade mulching plate were designed, and the mulching plate structure, straw distribution spacing and suspension rotation speed were used as independent variables. Using straw entanglement rate and straw interference rate as evaluation indicators, a full-factor experimental study was carried out to determine the optimal structure of the mulching plate; a pendulum-type synchronous soil covering live broadcast EDEM simulation model was established, and field experiments were conducted to verify its synchronous soil covering performance. The test results show that the exponential function of the sliding blade mulching plate has the best performance, and the soil covering rate of the three soil covering plate structures is 87.37~98.54 under the conditions of forward speed 0.6~1.0 m/s and suspension rotation speed 90~150 r/min. %, the covering soil thickness is 5.08~5.84 mm. This research can provide reference for rice mechanical direct seeding technology and equipment.

Accurate potato sprout detection is the key to automatic seed potato cutting, which is important for potato quality and yield. In this paper, a lightweight DAS-YOLOv8 model is proposed for the potato sprout detection task. By embedding DAS deformable attention in the feature extraction network and the feature fusion network, the global feature context can be efficiently represented and the attention increased to the relevant pixel image region; then, the C2f_Atten module fusing Shuffle attention is designed based on the C2f module to satisfy the attention to the key feature information of the high-level abstract semantics of the feature extraction network. At the same time, the ghost convolution is introduced to improve the C2f module and convolutional module to realize the decomposition of the redundant features to extract the key features. Verified on the collected potato sprout image data set, the average accuracy of the proposed DAS-YOLOv8 model is 94.25%, and the calculation amount is only 7.66 G. Compared with the YOLOv8n model, the accuracy is 2.13% higher, and the average accuracy is 1.55% higher. In comparison to advanced state-of-the-art (SOTA) target detection algorithms, the method in this paper offers a better balance between comprehensive performance and lightweight model design. The improved and optimized DAS-YOLOv8 model can realize the effective detection of potato sprouts, meet the requirements of real-time processing, and can provide theoretical support for the non-destructive detection of sprouts in automatic seed potato cutting.

At present, electric tractors experience significant battery energy loss during operation, resulting in a short continuous running time. Therefore, in order to reduce the power consumption of the tractor drive system, minimize battery energy loss, and extend the operating time under various conditions, this paper presents a method for driving an electric tractor based on dual-motor coupling. Based on the characteristics of the transmission structure, an online torque distribution strategy for dual-motor coupling-driven electric tractors using a fuzzy control approach is proposed. First, an enhanced genetic algorithm is utilized to optimize the fuzzy rule table. Simultaneously, it is compared with the offline optimization strategy of dynamic programming. Subsequently, a method that integrates test data models and theoretical models is employed to establish an efficiency model of key components of the electric tractor drive system and a longitudinal dynamics model of the entire machine. The performance of the entire vehicle was simulated and analyzed under plowing conditions. Finally, on the experimental bench, conduct steady-state load tests and dynamic performance tests on the dual-motor coupled drive system. The results show that the State of Charge (SOC) change trends of the fuzzy control strategy based on the improved genetic algorithm and the dynamic programming strategy are similar. The SOC change values are close, which enhances the adaptability of the electric tractor in various operating conditions. Compared with the fuzzy control strategy, the improved strategy reduced average power consumption by 8.8%, demonstrating that the fuzzy control energy management strategy based on the enhanced genetic algorithm is both economical and superior. The bench experiment demonstrated that the dual-motor drive system can adapt to load changes to achieve power distribution between the two motors, meeting the required workload while reducing power consumption.

Aiming at the potato soil separation device of potato harvester, which generally has the problem of potato high damage in potato-soil separation, a three-stage potato soil low-loss separation device was developed, and orthogonal experiments were designed with the help of RecurDyn-EDEM coupled simulation method. A field bench was built for verification tests. The test proved that: when the lift transport chain speed was 1.40 m/s, travel speed was 0.60 m/s, amplitude was 32.0 mm, the impurity rate was 1.49% and the average force on potato was 1.801 N. The potato damage rate was 2.7%, indicating that the design of the three-stage potato soil low-loss separator device worked well.

The paper examines the intensification of drying apple slices to low residual moisture content. It is proposed to use an energy-efficient multi-stage mode of convective drying at 80/60 °C and a combined multi-stage mode with IR radiation and IR convective heating (100 W) + 60 °C / 60 °C. The paper presents the temperature and kinetic curves and changes in drying speed for the studied dehydration regimes. A formula was obtained for determining the total duration of the process of drying apple slices using a combined method, and a dependence of the Rebinder number for the studied dehydration modes was constructed. Based on the experimental data analysis and generalization of research results, a method of determining the drying intensity based on the average moisture exchange and the average temperature of material heating per minute, at the first stage of drying and during the entire drying time, was proposed for the first time. The efficacy of the proposed modes is confirmed by a reduction in drying duration 1.9 times compared to the stationary mode at a coolant temperature of 60 °C. The obtained dried product is characterized by high recoverability (78–80%) and appropriate organoleptic properties.

Both cruising ability and safety should be considered in the 3D inspection path planning of agricultural unmanned aerial vehicles (UAVs). Specific to a complex working environment, the 3D inspection environment of agricultural UAVs was simulated through terrain modeling and threat modeling. First, the dynamic constraints of flight approaching rate and response time were added to the threat cost, and the 3D mission space model and flight path cost function were constructed considering the influence of UAVs’ turning performance. Second, the offset estimation strategy, variable spiral search strategy, quasi-reverse learning strategy and dimension-by-dimension mutation strategy were introduced into the dung beetle optimizer (DBO) algorithm to improve the global optimization ability and convergence rate of the algorithm. By establishing a three-dimensional trajectory planning model for unmanned aerial vehicles, the trajectory planning is transformed into a multi-objective function optimization problem, and an improved algorithm is used to solve the three-dimensional trajectory planning of unmanned aerial vehicles. The fitness is evaluated by considering the objective function of trajectory cost, terrain cost, and danger level, and the trajectory planning is iteratively optimized. The results indicate that the proposed improved dung beetle algorithm for trajectory planning has lower overall cost and stability in adapting to different complex terrain environments.

This study measured the intrinsic and contact parameters through physical experiments to improve the accuracy of discrete element simulation analysis of peanut seeds. Discrete element models for five different peanut seed filling ball numbers were established. The simulation parameters were calibrated through a combination of physical and simulation experiments. Firstly, the Plackett-Burman test was used to screen the significance of simulation parameters. Then, the steepest climbing test was conducted to determine the optimal range of significance parameters using the relative error be-tween the simulated and the physical experimental as the evaluation index. Finally, a response surface experiment with three factors and three levels was conducted using the repose angle as the response value. The static and rolling friction coefficients among peanut seeds were set as 0.43 and 0.50 separately, and the rolling coefficient between peanut seeds and steel plate was set as 0.12. During verification experiments, the simulated repose angle was 25.18°, with a relative error of 2.42% compared to the physical repose angle, further verifying the reliability of the simulation model. The re-search group used different numbers of filling balls with optimal parameters in the repose angle experiment. Then they evaluate the simulation time and the error value of repose angle between the simulated and physical experiment. The optimal number of filled balls is the Sphere 1178. The research results indicate that discrete element model of peanut seeds and calibration parameters are reliable. Based on the results of this research, an intelligent peanut precision sowing machine can be developed.

This study measured the intrinsic and contact parameters through physical experiments to improve the accuracy of discrete element simulation analysis of peanut seeds. Discrete element models for five different peanut seed filling ball numbers were established. The simulation parameters were calibrated through a combination of physical and simulation experiments. Firstly, the Plackett-Burman test was used to screen the significance of simulation parameters. Then, the steepest climbing test was conducted to determine the optimal range of significance parameters using the relative error be-tween the simulated and the physical experimental as the evaluation index. Finally, a response surface experiment with three factors and three levels was conducted using the repose angle as the response value. The static and rolling friction coefficients among peanut seeds were set as 0.43 and 0.50 separately, and the rolling coefficient between peanut seeds and steel plate was set as 0.12. During verification experiments, the simulated repose angle was 25.18°, with a relative error of 2.42% compared to the physical repose angle, further verifying the reliability of the simulation model. The re-search group used different numbers of filling balls with optimal parameters in the repose angle experiment. Then they evaluate the simulation time and the error value of repose angle between the simulated and physical experiment. The optimal number of filled balls is the Sphere 1178. The research results indicate that discrete element model of peanut seeds and calibration parameters are reliable. Based on the results of this research, an intelligent peanut precision sowing machine can be developed.

Apple tree branches have the physical characteristics of high cellulose content and high elasticity, and the use of traditional soft straw pickers will miss a large number of branches. It is necessary to design a picking mechanism that adapts to the physical characteristics of fruit tree branches. In the treatment of branches in modern orchards, the picking mechanism is an important part of the picking device. The success rate of picking directly affects the processing performance of the whole machine. To improve the picking rate, the roller branch picking mechanism is studied. The trajectory of the roller picking and the stress state of the branches are analyzed, and five main factors affecting the picking effect are obtained, i.e. the position relationship between the rotation center of the picking roller and the feeding roller, inclination angle of the steel teeth, the effective working length, the speed and the forward speed of the machine. A mathematical model is established to obtain the static and dynamic motion trajectories of the roller picking mechanism are obtained by using Matlab. Taking the analysis results of influencing factors as the optimization goal, the picking trajectory of the mechanism is simulated to obtain a set of non-inferior solutions. A roller branch picker is manufactured according to the parameter values and tested in the field, and the picking rate can reach 91%.

Soil moisture monitoring and control are essential aspects for precision agriculture. The paper presents the designing and calibration of a low-cost soil moisture monitoring system. The system includes 28 capacitive sensors, connected to an Arduino based data acquisition system, allowing simultaneous multi-point measurements. The calibration process was conducted on six reference points within the moisture content range of 0–25%. The calibration results indicate a non-linear variation and reveal a significant deviation between the sensors leading to the determination of individual variation curves for each sensor.

Aiming at the adaptability and safety problems of agricultural machinery in hilly and mountainous areas, the remote driving control system of agricultural full hydraulic chassis is designed based on ARM-Linux platform. The whole remote driving system is composed of Web upper computer, server system and chassis drive system. According to the requirements of chassis operation, the STM32F407 is used as the lower computer to realize the running control and motion status monitoring of the chassis. Taking the I.MX6ULL as the hardware platform, the Linux as the software platform, and 4G communications as the Web Server, the remote driving of the chassis is realized through Web pages on the computer. It can be seen from the test results that the minimum RTT delay from the Web page driving to the lower computer is 170 ms; the maximum RTT delay is 1310 ms, and the average RTT delay is 222.75 ms. The real-time interactivity of the control system meets the needs of remote driving of the agricultural machinery. The research provides a theoretical basis and technical reference for the development of the remote driving system of the agricultural machinery.

In order to solve the problem of complicated processes, low efficiency and high cost of economic tree trunks girdling, inspired by cam mechanism this study developed a new type of automatic half-ring girdling device, which can automatically complete a series of operations, including the tree trunk profile scanning, girdling trajectory calculating and automatic bark cutting. A pair of laser rangefinders and guide screws were symmetrically arranged on a half-ring rotating rail, which could rotate around the tree trunk, and two chainsaws assembled above the guide screws were controlled to move radially. The laptop was used as upper computer, and a 4-axis motion control card was used as the lower computer, which constituted the control system of precise movement. The programs of the tree trunk profile scanning, the xylem profile curve fitting and the chainsaw centre trajectory calculation were designed in LabVIEW. The scanning tests and girdling experiments were carried out on the different sections of the tree trunks in the laboratory. The feasibility of the automatic girdling device for economic tree trunks was verified with one complete and automatic girdling operation finished by this device, which took 150 seconds, and the error range of automatic girdling was within ±2mm. This device improves the automation degree of girdling operation and provides a support for the development of economic forestry.

This research aimed to address the issue of physical damage caused by long-term work in high-saline fields by electrifying sunflower growing machinery and designing control systems. Firstly, the method of establishing the equation of motion is used to obtain the parameters to carry out motorization modification, and then the control system is built using STM32 as the main controller, which has the functions of control, data acquisition, and alarm. The feasibility and stability of the study are verified by using a model vehicle to conduct tests of straight-line driving and steering in a simulated high-saline field.

The harvesting technology of Chinas lavender industry is in urgent need of improvement, and there is a pressing demand to expedite the development of mechanized collection equipment to facilitate the modernization process and optimize efficiency within the sector. This article adopts a literature review method to introduce the current research status of lavender harvesting techniques, including mechanical properties, harvesting time, and distribution of essential oils in stems and leaves, both domestically and internationally. It is found that there is relatively little research on lavender harvesting techniques in China, and the main research hotspots are focused on industrial development and essential oil extraction. By summarizing the mechanical harvesting equipment and its characteristics of lavender both domestically and internationally, it is analyzed that developed countries have fully achieved mechanical harvesting of lavender, while Chinas level of mechanical harvesting of lavender lags far behind developed countries. It is proposed to develop diversified lavender harvesting equipment, strengthen the research and cooperation of lavender harvesting machinery, promote the integration of agricultural machinery and agronomy, and combine basic research with equipment development. These development measures have a certain reference and promotion effect on accelerating the process of mechanical harvesting of lavender in China.

The study analyses trends in domestic markets and international trade in organic products in some Eastern European countries based on a multifactorial comparative analysis in the regional context and estimates of yield losses about traditional agricultural land processing technologies. Prospects for the development of organic farming by region and in general are determined based on unused reserves of agricultural land suitable for this. The study assessed the organic production development in different regions of Poland and Ukraine: the annual growth rate of transitional and organic lands should be at least +13.3% to meet the strategic goal of reaching 3% of the total agricultural land by 2030.

In order to reduce the crushing rate and energy consumption of corn kernels in the pneumatic conveying process, firstly, the conveying wind speed, material-air ratio and corn kernel moisture content as the influencing factors in the conveying process were carried out as one-factor simulation experiments, respectively.Next, we created a test platform for the pneumatic conveying of grain particles, tested it orthogonal using the crushing rate and pipeline pressure drop as conveying performance indices. We then created a regression equation model that connected each test index to each factor in turn. Lastly, we used the response surface method for multi-objective optimization to determine the ideal parameter combinations for the conveying wind speed, which was 25.42 m/s, the material to gas ratio, which was 10, and the moisture content, which was 13.912%.At this time, the corresponding pneumatic conveying indexes are 1.112% crushing rate, 8.725kPa pressure drop, and 0.328kg/s conveying capacity, which provide theoretical and experimental bases for the prevention of crushing and the reduction of energy consumption during the pneumatic conveying of grain particles.

Apple leaf diseases significantly threaten the yield and quality of apples. In order to detect apple leaf diseases in a timely and accurate manner, this study proposed a detection method for apple leaf diseases based on an improved YOLOv7 model. The method integrated a Similarity-based Attention Mechanism(SimAM) into the traditional YOLOv7 model. Additionally, the regression loss function is modified from Complete Intersection over Union (CIoU) to Structured Intersection over Union (SIoU). Experimental results demonstrates that the improved model exhibits an overall recognition precision of 92%, a recall rate of 99%, and a mean average precision (mAP) of 96.1%. These metrics show a respective improvement of 14.4%, 38.85%, and 18.69% compared to the preimproved YOLOv7. When compared with seven other target detection models in comparative experiments, the improved YOLOv7 model achieves higher accuracy, lower rates of missed and false detections in disease target detection. The model excels in detecting disease categories in complex environments and identifying small targets at early disease stages. It can provide technical support for effective detection of apple leaf diseases.

According to the requirements of soybean stripping planting in the Huang-Huai-Hai region, a new planting mode was proposed, and a no-tillage staggered seedling belt soybean precision planter was designed. A seed-metering device with staggered distribution of sockets was designed. The optimal parameter combination was obtained through simulation analysis, and its structural rationality was verified through bench experiments. It achieved staggered seedling belt seeding; a retractable top rod seeding device was designed to improve seeding efficiency; the arrangement of the rotary cutter for the seedling belt cleaning and preparation device was designed to reduce work energy consumption. The field experiment results showed that when the forward speed was 8 km/h, the reliability and trafficability of the no-tillage staggered seedling belt soybean precision planter were qualified. The qualified rate of sowing depth was 92.6%, the qualified rate of grain spacing was 94.4%, the leak sowing rate was 1.8%, the repeat sowing rate was 38%, the seed exposure rate was 0.74%, and the operation efficiency was 1.92hm2/h.