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.

Fast and precise estimation of the available nitrogen content in vermiculite substrates promotes prescription fertilization in desert facility agriculture. This study explored near-infrared spectroscopy for rapid detection of the available nitrogen content in vermiculite substrates in desert facility agriculture. The spectra of vermiculite matrices with different available nitrogen contents were collected through a self-assembled near-infrared spectrometer. Partial least squares expression (PLSR) established the available nitrogen spectrum prediction model optimized using different pretreatments. After pretreatment, the prediction model of the available nitrogen spectrum was simplified by adopting three feature extraction methods. A comprehensive comparison of the results of each prediction model showed that the prediction model combining the first derivative with SG smoothing pretreatment was the best. The correlation coefficients of the corresponding calibration and prediction sets were 0.9972 and 0.9968, respectively. The root mean square errors of the calibration and prediction sets were 149.98 and 159.65 mg/kg, respectively, with 12.57 RPD. These results provide a feasible method for rapidly detecting the available nitrogen content of vermiculite substrates in desert facility agriculture.

Studies on the discrete element method (DEM) parameters of Morchella seeds are limited due to their high moisture content and weak inter-particle adhesion. However, accurate DEM simulations are crucial for the design of agricultural machinery. Physical experiments were conducted to measure the fundamental properties of Morchella seeds, and a DEM model was established using the Hertz–Mindlin with JKR contact model. Subsequently, Plackett–Burman, steepest ascent, and Box–Behnken experiments were employed. They were used to analyze the significance of key contact parameters. A second-order polynomial regression model for the repose angle was developed, and significant contact parameters were optimized and calibrated. The results showed that the seed-to-seed rolling friction coefficient, seed-to-seed surface energy, and seed-to-steel rolling friction coefficient significantly impacted the repose angle. The simulation results using the optimized contact parameters closely matched the repose angle measured in physical experiments. The relative error was only 0.16%, validating the accuracy of the parameter calibration.

The precision of simulation plays a pivotal role in determining the design parameters of the pressure pipe and distributor in a pneumatic centralized seeding system. This study adopted the discrete element method (DEM) to investigate wheat seed models and their motion characteristics within a pneumatic precision seed-metering device. Using Xinchun No. 6 wheat as the experimental subject, multi-sphere combination models (5, 7, 9, and 11 balls) were employed to describe the seed particle morphology. Moreover, by utilizing the coupling method of the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD), along with bench tests, the air suspension velocity of seeds and the motion characteristics of the seed-supplying device were analyzed under different particle models. The physical properties of the wheat seeds were measured during the experiments. The simulation results indicated that, as the seed supply rate increased, the airflow velocity distribution within the model became more uniform, enhancing the stability of the suspension velocity. Comparisons between experiments and simulations validated the reliability of the particle models, with the minimum relative error in the suspension velocity determined as 0.21% for the 9-balls model. In addition, compared to the other models, the 9- and 5-balls models more accurately simulated the dynamic behavior of seeds within the seed-supplying device. For the 9-balls model, the relative error of particle velocity in the seed-supplying device is 1.39%, and, in the simulation of displacements in the X and Y directions of the seed-supplying device, the average error is 9.51%. The effectiveness of the multi-sphere combination models was verified, indicating their ability to accurately reflect the dynamic behavior of wheat seeds and improve the design and optimization efficiency of pneumatic precision seed-metering devices.

Due to the lack of water resources, the main agricultural planting method used in the northwest region of China is plastic film mulching, with precision hole sowing performed on the film after mulching. However, conventional hole-forming devices damage the compactness of the soil hole while moving on the plastic film, causing seed misplacement. Therefore, this study designed a bionic hole-forming device based on the oriental mole cricket. In order to explore the interaction between the hole-forming device and the soil, a typical soil discrete element particle model was established, and its contact parameters were calibrated. An experiment was conducted to compare the performance of the bionic hole-forming device with a conventional device using discrete element method and multi-body dynamics (DEM-MBD) coupled simulations. The results revealed that the bionic hole-forming device caused less soil disturbance during the hole-forming process and could reduce the sowing operation resistance compared to the traditional device. Compared to traditional square and cone-shaped hole-forming devices, the soil resistance of the bionic hole-forming device was the smallest, at 7.51 N. This work provides a reference for the optimization of hole-forming devices for plastic film sowing.

Using the discrete element method to simulate the interaction between cotton stalks and machinery is an effective approach for analyzing the cotton stalk defibration mechanism and optimizing the structural parameters of cotton stalk defibration equipment. To further improve the accuracy of studies on the interaction between cotton stalk defibration devices and cotton stalks, cotton stalks from typical arid regions in southern Xinjiang were selected as the research object, and a discrete element parameter calibration study was conducted based on the discrete element method. Considering the differences in cotton stalk diameters, two discrete element models of cotton stalks with diameters of 8.5 mm and 10.5 mm were established. Plackett–Burman screening tests and Box–Behnken tests were employed to calibrate and optimize the discrete element contact parameters for cotton stalk models with different diameters. Optimization was carried out using the load responses obtained from mechanical tests of cotton stalks as the target values, and the optimal parameter combinations of the cotton stalk discrete element models were determined. Finally, the calibrated parameters were validated through tensile tests, uniaxial compression tests, and bending tests of cotton stalks. The simulation results show that the relative errors between the simulated and measured maximum loads for the 8.5 mm- and 10.5 mm-diameter cotton stalk models were 1.21% and 0.08%, respectively, indicating good agreement. These results verify the accuracy and reliability of the established cotton stalk discrete element models and provide data support and a theoretical basis for numerical simulation of the defibration process of cotton stalks with different diameters and for the structural optimization of cotton stalk defibration devices.