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Agricultural paper mulch is an indispensable part of modern agriculture. It had the functions of heat preservation, moisture preservation, insect resistance, disease prevention, and weed growth inhibition. In order to extend the service life of the paper mulch, we use the solution immersion method to modify the surface of the paper mulch. A super-hydrophobic paper mulch is mainly prepared by using hydrophobic silica. The static contact angle of the super-hydrophobic paper mulch with water is 160.6°. The super-hydrophobic paper mulch samples were immersed in acid solution (pH = 4.6 H2SO4) and alkaline solution (pH = 8.5 NaOH). The main instruments are contact angle tester, tensile testing machine and high-speed camera. The hydrophobic properties, mechanical properties and rebound properties of the two kinds of paper mulches were compared. The results showed that the tensile strength and droplet bounce height of the superhydrophobic paper mulch decreased after being soaked in acid or alkaline solution for 48 h. The mass loss rate of paper mulch was more significant in acid solution, but its contact angle was still greater than 145°, and it had good bounce performance. After observing the microscopic morphology of its surface, it was found that silica had a micro-rough structure on the surface of the paper mulch. The method was simple and environmentally friendly, and can alleviate the problem of poor acid and alkali corrosion resistance of the paper mulch, and had extraordinary significance for environmental protection.

This study sets out to address the challenges of improving precision, stability, and efficiency in corn seed metering systems. A novel clip-based precision seed metering device was developed, integrating an optimised seed-filling clip to enhance seed capturing and metering accuracy. The overall structure and working principles of the device were described, focusing on key components such as the seed-filling clip, clamping slot, and torsion spring. The coupled DEM-MBD simulation method was employed to analyse the interaction forces and trajectories of corn seeds during the filling and metering process, enabling parametric optimisation of the device. The effects of clip protrusion width, clamping slot length, and metering speed on seeding performance were systematically investigated. Field validation tests demonstrated a qualification rate of 90.76%, a missing rate of 4.83%, and a multiple rate of 4.4%, with an error of 1.4% compared to simulation results. The results confirm the device’s ability to stably and accurately meter seeds, showcasing its potential for mechanized corn seeding with enhanced precision and operational stability.

The soil water characteristic curve (SWCC) is a fundamental tool for studying the intrinsic mechanical properties of unsaturated soils. The data for SWCCs must be obtained via laboratory tests, which require considerable time and labour. Therefore, in practice, empirical models are often developed with a limited number of laboratory data samples to produce SWCC curves. However, empirical models fitted with limited data often lead to inaccurate modelling of SWCCs. This research aims to propose a data-driven optimization framework to accurately and effectively fit empirical SWCC models with limited amounts of laboratory data. First, the van Genuchten model is adopted as the empirical model to construct the SWCCs. Second, the performance-guided Jaya algorithm (PGJAYA) is introduced to optimize the parameters of the van Genuchten model and increase the fitting accuracy. In the experiments, two cases are investigated, one with limited data and another with abundant data, for four types of soils, i.e., sand, silt, clay and loess. To demonstrate the accuracy and effectiveness of the proposed approach, a comparison with other benchmark optimization algorithms is performed. With limited data, the PGJAYA algorithm outperforms the other optimization algorithms tested. Furthermore, the PGJAYA algorithm produces the smallest fitting error for the SWCCs in the case with full data. Overall, the PGJAYA algorithm is an effective and accurate optimizer with respect to the parameter fitting tasks based on empirical SWCC models.

To prevent soil pollution caused by polyethylene (PE) films in the central region of Gansu, China, liquid mulching made from cow dung (CDLM) was trailed in silage maize fields. The degradation of CDLM and PE films, soil temperature, soil organic matter content, silage maize yield and water use efficiency (WUE) were evaluated for three years (2018–2020). The degradability of CDLM has been found to be much stronger than the one of PE films, with CDLM degrading 40–60 days after sowing and finishing around 100 days. CDLM had a lower insulating impact than PE films but a higher insulating effect than non-mulching films as the control (CK); CDLM could successfully increase soil organic matter, with a total increase of 1.01% over three years. CDLM increased silage maize yield by 6.2% compared to PE films and 17.2% compared to CK. Consequently, CDLM may be an interesting alternative to PE films for enhancing silage maize yield while decreasing soil contamination.

Quinoa is renowned for its high nutritional value, which not only meets the nutritional needs of the human body but also makes it a suitable option for individuals with diabetes and celiac disease due to its low sugar and gluten-free characteristics. In China, the primary cultivation regions of quinoa are the Tibetan Plateau, the Yunnan–Guizhou Plateau, and Northwest China, which are predominantly characterized by hilly and mountainous terrain, resulting in the gradual development of mechanized harvesting processes. The efficacy of the mechanized harvesting process in these regions is suboptimal, exhibiting poor clearance and efficiency. In this paper, the design and MBD-EDEM coupling analysis of the quinoa combine harvester’s cleaning and screening mechanism is carried out to simulate the cleaning process of quinoa threshing materials. The results show that the vibrating screen can complete the forward sliding and dispersed throwing up of the materials and effectively avoid the accumulation of the threshing materials. The coupling results of the permeability of each material in the cleaning and screening mechanism, as well as the vibrating screen movement condition, indicate that when the herringbone screen opening degree is set in the range of 15° to 30°, the cleaning and screening device can achieve a high cleaning efficiency while maintaining a low impurity rate. Field trial data further confirm that within this opening range, the cleaning effect and efficiency both exhibit significant advantages.

Variable-amplitude vibrating screens are widely adopted for screening frozen sea buckthorn berry particles. Investigating their motion characteristics and particle behaviors on the screen surface is essential for optimizing the screening process and improving equipment performance and screening efficiency. In this work, a variable-amplitude vibrating screen is taken as the research subject. Its structural composition and working principle are elaborated, and kinematic simulations are conducted via RecurDyn. The results reveal that the vertical amplitude and velocity of the screen surface increase gradually from the feed end to the discharge end, which facilitates rapid particle penetration. Meanwhile, the horizontal velocity remains stable across all sections of the screen. Specifically, crank length governs the screen amplitude, while crank rotational speed determines the vibration frequency. A dynamic model of particles and the screen surface is established by combining EDEM 2024 and RecurDyn V9R4, and two-way coupling of the discrete element model is realized. Coupled simulation results indicate that the dynamic screening efficiency rises with increasing crank length and rotational speed, reaching the maximum at a crank length of 20 mm and a rotational speed of 208 r/min. Crank parameters exert remarkable effects on the thickness of the particle layer and the quantity of penetrated particles: a thicker particle layer leads to a longer residence time of materials on the screen. Field tests are carried out to verify the model accuracy. It turns out that the simulation results are basically consistent with experimental data. In conclusion, crank length and rotational speed are critical influencing factors for variable-amplitude vibrating screens. Research on the screen’s motion characteristics and particle behaviors can provide a theoretical reference for its efficient operation and optimal design.

Minor cereals are an important part of the Chinese grain industry, accounting for about 8 percent of the country’s total grain-growing area. Minor cereals include millet, buckwheat, Panicum miliaceum, and other similar grains. Influenced by topographical and climatic factors, the distribution of minor cereals in China is mainly concentrated in the plateau and hilly areas north of the Yangtze River. In addition, there are large concentrations of minor cereals in Inner Mongolia, Heilongjiang, and other areas with flatter terrain. However, the level of mechanized harvesting in these areas is still low, and there is little research on the whole process of mechanized harvesting of minor cereals. This paper aims to discuss the current status of the minor cereal industry and its mechanization level, with particular attention to the challenges encountered in research related to the mechanized harvesting of minor cereals, including limited availability of suitable machinery, high losses, and low efficiency. The article provides a comprehensive overview of the key technologies that must be advanced to achieve mechanized harvesting throughout the process, such as header design, threshing, cleaning, and intelligent modular systems. It also summarizes current research progress on advanced equipment for mechanized harvesting of minor cereals. In addition, the article puts forward suggestions to promote the development of mechanized harvesting of minor cereals, focusing on aspects such as crop variety optimization, equipment modularization, and intelligentization technology, aiming to provide a reference for the further development and research of mechanized harvesting technology for minor cereals in China.

To address the problems of high digging resistance, elevated energy consumption, and severe soil adhesion encountered during mechanized potato harvesting, a bionic potato digging shovel inspired by the corrugated dorsal structure of the white grub was developed. Based on reverse-engineered geometric curves, two longitudinally corrugated shovel models (L-S-1 and L-S-2) were constructed, and a coupled soil–potato–shovel model was established using the Discrete Element Method (DEM) to evaluate soil disturbance characteristics and digging resistance at a forward speed of 0.5 m/s and an entry angle of 35°. The simulation results indicated that the longitudinally corrugated shovel L-S-2 exhibited the best overall performance, reducing digging resistance by 13.87% and increasing the soil fragmentation rate by 20.67% compared with a conventional flat shovel (P-S). Using L-S-2 as the baseline design, additional DEM simulations were conducted at forward speeds ranging from 0.4 to 0.6 m/s to systematically investigate the influence of operating speed on digging performance. To further enhance anti-adhesion performance, a composite bionic shovel (H-L-S-2) was developed by embedding polytetrafluoroethylene (PTFE) hydrophobic material into the surface of L-S-2 and reinforcing the shovel tip using laser cladding. Soil-bin experiments were then performed under controlled conditions with forward speeds of 0.4–0.6 m/s and soil moisture contents of 15–20% at an entry angle of 35°, and the results showed an average resistance reduction rate of 17.46%, with a maximum reduction of 18.02%. Both DEM simulations and soil-bin tests confirmed the effectiveness of the composite bionic shovel in reducing soil adhesion, with the number of adhered soil particles decreasing by 41.2% in simulations and the mass of adhered soil reduced by 37.5% in physical tests. These results demonstrate that coupling a bionic corrugated structure with surface material modification can effectively reduce digging resistance, enhance soil fragmentation, and mitigate soil adhesion, providing a practical approach for optimizing the design of potato digging shovels.

Flax, an important oil and fiber crop, is widely cultivated in temperate and sub-frigid regions worldwide. China is one of the major producers of flax, with Gansu Province predominantly practicing cultivation in hilly areas. However, common issues such as feeding difficulties, stem entanglement, and low threshing efficiency significantly restrict the improvement of planting efficiency. This study addresses the key technical challenges in flax combine harvesting in hilly regions by developing a discrete element model of the flax plant and utilizing DEM-FEA co-simulation technology. The performance of two threshing drum models (T1 and T2) was analyzed, focusing on motion trajectory, stress distribution, and threshing effects. The simulation results show that the T2 model, with its combination of rib and rod tooth design, significantly improves threshing and separation efficiency. The loss rate was reduced from 5.6% in the T1 model to 1.78% in the T2 model, while the maximum stress and deformation were significantly lower, indicating higher structural stability and durability. Field validation results revealed that the T1 model had a total loss rate of 3.32%, an impurity rate of 3.57%, and an efficiency of 0.09 hm2/h. In contrast, the T2 model achieved a total loss rate of 2.29%, an impurity rate of 3.39%, and an efficiency of 0.22 hm2/h, representing a 144.4% improvement in working efficiency. These findings indicate that the T2 model has a higher potential for flax harvesting in hilly and mountainous regions, especially in improving threshing efficiency and operational stability, providing an important theoretical basis for optimizing threshing equipment design.

The shape of corn seeds not being spherical affects their mobility. This study focuses on modeling the typically shaped corn seeds and calibrating the coefficient of rolling friction for different shape types to improve simulation reliability. By analyzing the corn seed shape characteristics and size statistics, this study establishes a classification system that enables the determination of the average value and quantity of different types of corn seed using the spherical granule cluster method. The discrete element method is used to model simplified corn models, and contact parameters are validated through two types of repose angle and a seed metering experiment. In the collapse repose experiment, the relative error between the simulation and the experiment was only 0.72%, while the relative error in another repose experiment was 0.2%. The verification experiment for the metering of seeds showed that the relative error between the simulation and the experiment was below 15% at both low and high speeds, and the multi-grain rate error was less than 10%. This shows that the method proposed in this paper is somewhat accurate.