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At present, tomato transplanting in facility agriculture is mainly manual operation. In an attempt to resolve the problems of high labor intensity and low efficiency of manual operation, this paper designs a clip stem automatic transplanting and seedling picking device based on the yolov5 algorithm. First of all, through the study of the characteristics of tomato seedlings of different seedling ages, the age of tomato seedlings suitable for transplanting was obtained. Secondly, the improved yolov5 algorithm was used to determine the position and shape of tomato seedlings. By adding a lightweight upsampling operator (CARAFE) and an improved loss function, the feature extraction ability and detection speed of tomato seedling stems were improved. The accuracy of the improved yolov5 algorithm reached 92.6%, and mAP_0.5 reached 95.4%. Finally, the seedling verification test was carried out with tomato seedlings of about 40 days old. The test results show that the damage rate of the device is 7.2%, and the success rate is not less than 90.3%. This study can provide a reference for research into automatic transplanting machines. [ABSTRACT FROM AUTHOR]

We examined the distribution characteristics of atmospheric microplastics in typical desert agricultural regions, with a focus on the agricultural areas surrounding the Taklamakan Desert, Xinjiang, China. We collected samples of total suspended particulate matter (TSP), atmospheric deposition, and atmospheric dust using both active and passive collection methods. The chemical composition, particle size, shape, and color of atmospheric microplastics were examined using a stereomicroscope and a Fourier‐transform infrared spectrometer to analyze their characteristics. The results showed that the primary chemical compositions of microplastics included polypropylene (PP), polyethylene, polyethylene terephthalate, polymethylmethacrylate, and cellophane. Particle sizes were mainly within the range of 0 to 1000 μm. Fibrous microplastics constituted the majority of the TSP and atmospheric deposition, whereas film‐like microplastics constituted the largest proportion of atmospheric dustfall. The deposition flux of atmospheric microplastics in the first quarter was measured at 103.21 ± 22.12 particles/m2/day, which was lower than that observed in conventional agricultural areas. The abundance of microplastics in atmospheric dustfall was found to be 1.36 particles/g. The proportion of PP microplastics in atmospheric dustfall can be as high as 35%. Through a comparison of microplastic content in TSP during dust storms and under normal weather conditions, it was found that dust storms can lead to an increase in the abundance of microplastics within the atmospheric TSP. The present study provides a scientific basis for understanding the distribution of atmospheric microplastics in typical desert agricultural regions. Environ Toxicol Chem 2024;43:1982–1995. © 2024 SETAC. [ABSTRACT FROM AUTHOR]

This research initiative, developed in response to the need for enhanced mechanization efficiency within solar greenhouses, particularly under yellow sand cultivation conditions, introduces an integrated ditching and film-covering machine. A novel spiral staggered throw-cut combined ditching knife was specifically engineered and optimized to meet the exacting agronomic requirements of embedded substrate cultivation. Extensive analyses of soil interactions and the formulation of dynamic equations for soil particles facilitated the determination of key operational parameters: a tangent height of 650 mm for the ditching knife, a soil-throwing width of 300 mm, a piece width of 120 mm, and an inclination angle of 30°. Performance simulations of the ditching knife, conducted using the discrete element method (DEM), revealed superior soil disturbance control and improved soil return compared to conventional designs. Critical operational variables such as forward speed, knife shaft speed, and ditching depth were rigorously tested, with trench depth quality and power consumption as primary evaluation metrics. The results demonstrated that knife shaft speed profoundly influences performance, with optimal operating parameters established through detailed field testing: a speed of 0.5 m/s, a blade shaft speed of 200 rpm, and a ditching depth of 300 mm. Under these optimized conditions, the machine achieved power consumption of 0.668 kW, trench depth stability of 86.7%, a surface width of 413 mm, a bottom width of 304 mm, and an average ditching depth of 310 mm, achieving a qualification rate of 87.1%. The post-ditching soil crushing rate was 92.4%. Both simulation and field evaluations validated that the innovative ditching knife markedly enhances ditching and soil-throwing quality in sandy soil, fulfills agronomic requirements for tomato sowing, and provides an essential reference for the mechanized planting of crops in the yellow sand matrix cultivation mode of solar greenhouses. [ABSTRACT FROM AUTHOR]

Investigating the seeding mechanism of precision seeders is of great significance for improving the quality of cotton sowing operations. This paper designs a rotary type-hole cotton precision mulching dibbler. The main factors influencing the entry of cotton seeds into the seed wheel holes during the seeding process are then theoretically analyzed. Following this, an accurate discrete element model of coated cotton seeds is established and combined with a discrete element method (DEM) and multi-body dynamics (MBD)-coupled simulation model of the seed drill for seed picking and planting. Simulation experiments on the seeding performance of the precision dibbler were performed to study the influence of the seed wheel structure and motion parameters on the picking and planting performance under different speeds. The optimal parameter combination for the seed wheel is obtained through optimization experiments, and a precision dibbler is manufactured for bench testing. The bench test results are consistent with the simulation test results. At the precision dibbler rotation speed of 16 r/min, the qualified index reaches a maximum value of 93.28%, the skip sowing index increases with the precision dibbler rotation speed, and the re-sowing index decreases as the speed increases. These optimization results significantly improved seeding precision and efficiency and are of great significance for the reliability and effectiveness of cotton sowing operations. [ABSTRACT FROM AUTHOR]

The quality of cotton seed is of great significance to the production of cotton in the cotton industry. In order to reduce the workload of the manual sorting of cotton seeds and improve the quality of cotton seed sorting, this paper proposed an image-detection method of cotton seed damage based on an improved YOLOv5 algorithm. Images of cotton seeds with different degrees of damage were collected in the same environment. Cotton seeds of three different damage degrees, namely, undamaged, slightly damaged, and seriously damaged, were selected as the research objects. Labeling software was used to mark the images of these cotton seeds and the marked images were input into the improved YOLOv5s detection algorithm for appearance-based damage identification. The algorithm added the lightweight upsampling operator CARAFE to the original YOLOv5s detection algorithm and also improved the loss function. The experimental results showed that the mAP_0.5 value of the improved algorithm reached 99.5% and the recall rate reached 99.3% when the uncoated cotton seeds were detected. When detecting coated cotton seeds, the mAP_0.5 value of the improved algorithm reached 99.2% and the recall rate reached 98.9%. Compared with the traditional appearance-based damage detection approach, the improved YOLOv5s proposed in this paper improved the recognition accuracy and processing speed, and exhibited a better adaptability and generalization ability. Therefore, the proposed method can provide a reference for the appearance detection of crop seeds. [ABSTRACT FROM AUTHOR]

To improve the automation, welding efficiency, and welding quality of duckbill welding of the cotton seeder, this study designed a cotton seeder duckbill welding robot. According to the characteristics of the duckbill weldment and welding requirements, the overall structure of the welding robot was determined, including the girdle feeding mechanism, static duckbill feeding mechanism, hinge feeding mechanism, welding fixture, welding actuator, and control system. To realize the continuous automatic feeding, positioning, fixing, welding, and unloading of the workpiece in the duckbill welding, the feeding mechanism adopts the method of cooperative cooperation of inductive proximity switch, electromagnet, and cylinder. The main body of the welding fixture adopts the pneumatic clamping method; the welding actuator adopts the synchronous belt module electric drive so that the welding torch can move in a straight line along the X axis and the Z axis. The welding process of the duckbill was simulated by Simufact Welding software, and the deformation and stress changes of the weldment were compared and analyzed when the single-sided single welding, the bilateral symmetrical double welding torch, two welding forms, and two welding process parameters were used to determine the welding process parameters of the welding robot. The prototype was made and the welding test was carried out. The test results show that the duckbill welding robot of the cotton seeder has stable feeding, solid clamping, accurate positioning, and high welding efficiency. According to the national standard, the appearance of the duckbill weld is inspected. The surface of the duckbill weld and the heat-affected zone has no cracks, incomplete fusion, slag inclusion, crater, and porosity. The forming quality of the welded parts is good. The design of the duckbill welding robot for cotton seeder is helpful in solving the problems of cumbersome positioning and clamping and low efficiency in manual and semi-automatic duckbill welding robots, which provides a strong guarantee for the large-scale and standardized welding production of the dibbler duckbill. [ABSTRACT FROM AUTHOR]