The presence of microplastics in soil has become a significant global concern, posing a threat to environmental, agricultural, and human health. However, the use of various detection methods has led to significant discrepancies in the statistics reported for the abundance of soil microplastics across the available literature, resulting in poor comparability across the available literature. Studies have shown that plastic film residue is among the main primary sources of microplastics in farmland soils. Therefore, we manufactured and selected polyethylene microplastics (PE-MPs) from plastic film and combined them with soil samples after density separation treatment, forming a spiked test soil sample, which was subjected to density separation and extraction using a ZnCl₂ solution. The experiment used visual inspection by stereo microscopy, micro-Fourier transform infrared spectroscopy, micro-Raman spectrometry, laser direct infrared imaging, and pyrolysis-gas chromatography–mass spectroscopy for the quantitative analysis of spiked soil. This study systematically assessed and compared these five common soil microplastic detection methods. The results revealed different quantitative detection accuracies across various particle size ranges. Micro-Fourier transform infrared spectroscopy showed a broader applicable particle size range (20–5000 μm) and higher detection rate (91%), while the detection range (>50 μm) and rate (70%) of visual inspection through stereo microscopy were lower. For the identification of microplastic morphology, laser direct infrared imaging performed better, whereas micro-Fourier transform infrared spectroscopy had the advantage in determining the types of polymers present over micro-Raman spectrometry. The advantages, disadvantages, and detection rates of the above five detection methods were clarified during the detection process. Considering these findings and similar studies, we suggest three combinations of the evaluated methods to optimize the detection of PE-MPs.

Aiming to solve the problems of the poor uniformity of seed flow discharge and serious damage of traditional straight grooved wheels to improve the performance of air-assisted maize high-speed precision seed metering devices, a staggering symmetrical spiral grooved feeding wheel with maize seeds was designed. To explore the influence of the spiral groove inclination angle and the length of the staggered symmetrical spiral groove feed wheel on the uniformity of seed flow discharge, the spiral groove length l and the spiral groove inclination angle ρ were used as the experimental factors, and the variation coefficient of the increase in seed, a full-factor simulation test was carried out for the test indicators, and it was found that both the inclination angle and the length of the spiral groove have an influence on the uniformity of seed flow discharge, and the influence of the inclination angle of the groove is more significant. Comparing the force of a single seed in the traditional straight grooved wheel and that of the spiral feeding wheel, it is found that the staggered symmetrical spiral grooved feeding wheel can reduce the damage of seed fertilizer. Through a bench test, the spiral groove length was found to be 50 mm, and the groove inclination angles are 30°, 45° and 90°. The test results show the variation trend and simulation results of the fluctuating coefficient of variation of the seed flow discharge in the bench test. The trend of change is basically the same. The inclination angle of the spiral groove is 45° and the uniformity of seed flow discharge is the best when the groove length is 50 mm, indicating that this structure can effectively improve the uniformity of material discharge, and the variation coefficient of seed flow discharge fluctuation is 3.12% and the seed breakage rate is 0.69%. Through the seeding performance test, it is verified that the staggered symmetrical spiral grooved feeding wheel can improve the seeding performance of the pneumatic high-speed precision metering device. When the metering device runs smoothly, the qualified rate reaches more than 90%, and the leakage rate is reduced to 0%. Therefore, the results of this study can provide a reference for research on uniform seeding, drill seeding and the uniform application of granular fertilizer.

The absorption of microplastics (MPs; size < 5 mm) by plants has garnered increasing global attention owing to its potential implications for food safety. However, the extent to which leafy vegetables can absorb large amounts of MPs, particularly those > 1 μm, remains insufficiently demonstrated. To address this gap in knowledge, we conducted water culture experiments using water spinach (Ipomoea aquatica F.) as a model plant. The roots of water spinach were exposed to a mixed solution that contained fluorescently labeled polystyrene (PS) beads with particle sizes of 200 nm and 1 μm for 10 d. We utilized laser confocal scanning microscopy and scanning electron microscopy to record the absorption, migration, and patterns of accumulation of these large particle sizes of MPs within water spinach. Our findings revealed that micron-sized PS beads were absorbed by the roots in the presence of submicron PS beads and subsequently transported through the exosomes to accumulate to significant levels in the leaves. Short-term hydroponic experiments further indicated that high concentrations of PS bead solutions significantly inhibited the growth of water spinach owing to their large specific surface area that hindered the uptake of water and nutrients by the roots. In conclusion, both sizes of PS beads were found to be absorbed by water spinach, thereby increasing the risk associated with direct human consumption of microplastics in fruits and vegetables. This study provides valuable scientific insights to assess the pollution risks related to fruits and vegetables, as well as ensuring vegetable safety.

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.

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.

The tomato (Solanum lycopersicum L.) is widely cultivated in yellow sand substrate-based systems in Northwest China, contributing significantly to regional agriculture. However, suboptimal water and fertilizer management hinders the balanced optimization of yield, fruit quality, and resource efficiency. In this two-year solar greenhouse experiment (2023–2024), we employed a four-factor, three-level orthogonal design [L9(3⁴)] to examine three irrigation regimes—full irrigation (FI 100% of crop evapotranspiration, [ET_c]), mild deficit irrigation (DIM 75% ET_c), and severe deficit irrigation (DIS 50% ET_c)—in combination with staged fertilizer applications at the seedling, flowering/fruit-set, and peak-fruit stages. A multi-objective decision-making framework, integrating an improved entropy weight method with a virtual-ideal-solution-based TOPSIS model, was established to address the complexity of water–fertilizer interactions. The results indicated that irrigation amount (IA) was the primary determinant of yield and water use efficiency (WUE), followed by fertilizer application in the second stage (FII). For fruit quality indices (moisture content, vitamin C (VC), lycopene (LC), soluble sugars (SSs), and soluble solids content (SSC)), IA remained the most influential factor, followed by FIII, FII, and FI; IA also had the largest impact on fruit hardness (Hd), soluble protein (SP), and titratable acidity (TA). An integrated scoring analysis revealed that treatment T5 achieved the highest yield, WUE, and partial factor productivity (PFP), whereas T7 excelled in fruit quality (VC, LC, SSC, and SP). Moreover, TOPSIS confirmed T5 as the optimal water–fertilizer strategy to achieve high yield, improved quality, and efficient resource utilization. Overall, these findings underscore a robust approach for optimizing water–fertilizer coupling in tomato cultivation under yellow sand substrate conditions, thereby enhancing resource use efficiency, promoting sustainable greenhouse agriculture in arid regions, and contributing to national water-saving and yield-increasing priorities.