Peanuts are prone to insect damage, breakage, germination, mildew, and other defects, which makes the quality of peanuts uneven. The difference in peanut pod quality makes the price and economic benefit also have a big difference. The classification of peanut pods according to quality is an important part of improving the product grade and market competitiveness. Real-time, accurate, and non-destructive quality detection of peanut pods can effectively improve the utilization and commercial value of peanuts. The strong subjectivity of manual detection and the low efficiency and low accuracy of mechanical detection have caused considerable wastage. Therefore, the present study proposed a new convolutional neural network for the peanut pod quality detection algorithm (PQDA) based on an improved ResNet. Compared to previous models, this model is more practical with high accuracy, lightweight, and easy nesting. Firstly, the detection and classification effects of ResNet18, AlexNet, and VGG16 are compared, and ResNet18 was determined to be the best backbone feature extraction network for model training. Secondly, three models were designed to optimize and improve the algorithm. The KRSNet module was added to the algorithm to make the model lightweight. The CSPNet module was added to the algorithm to improve the learning efficiency of each feature layer. The Convolutional Block Attention Module (CBAM) was added to the algorithm to improve its ability to capture more feature information about peanut pods. The experimental ablation results show that the precision of the improved model PQDA reaches 98.1%, and the size of parameters is only 32.63 M. Finally, the optimized model was applied to other peanut pod varieties for generalization experiments, and the accuracy reached 89.6% and 90.0%, indicating the effectiveness of the proposed peanut pod quality detection model. Furthermore, the model is suitable for deployment on embedded resource-limited devices, such as mobile terminals, to achieve the real-time and accurate detection of peanut pod quality.

Considering the problems of low soil fragmentation rates, high working resistance, and high energy consumption in the harvesting process of Cyperus esculentus in China, a method of Cyperus esculentus harvesting based on counter-rotation digging is proposed. The mechanism of interaction between the rotary tillage blade and Cyperus esculentus–soil is systematically investigated, and the vertical and horizontal disturbance performance of the positive and counter-rotating harvesting methods on soil and Cyperus esculentus is compared and analyzed. The results of the experiment showed that the intensity of soil and Cyperus esculentus disturbance by counter-rotation increased by 166.67% and 297.78%, respectively, and the effective disturbance time of soil and Cyperus esculentus increased by 133.33% compared to that of positive rotation. The working depth and rotation speed of the rotary tillage blade were the most significant for soil and Cyperus esculentus disturbance intensity. The working depth increased from 150 mm to 170 mm, and the soil disturbance intensity increased by 17.91% and 21.37% for positive and counter-rotating operation, respectively, and the rotation speed of the rotary tillage blade increased from 270 rpm to 330 rpm, and the soil disturbance intensity increased by 28.85% and 35.29%, respectively. Compared with the positive rotation operation, the Cyperus esculentus counter-rotation soil fragmentation rate increased by 4.09%, the Cyperus esculentus damage rate decreased by 10.69%, and the buried fruit rate decreased by 7.38%. This paper helps to understand the interaction mechanism between the rototiller and Cyperus esculentus–soil and lays a theoretical foundation for the subsequent design and optimization of the Cyperus esculentus digging device.

There are approximately 36.7 million hectares of saline alkali land available in China. To enhance the comprehensive utilization value of coastal saline alkali land and boost crop yields in such areas, it is essential to conduct research on optimizing the operational performance of high-performance soil contact components in light of the soil characteristics of coastal saline alkali land. Discrete element simulation can be employed to investigate the operational mechanisms of various key components. Nevertheless, at present, there is a dearth of discrete element models for the key physical parameters and soil structure of coastal saline alkali land soil. In this article, typical coastal saline alkali field soil was sampled, and the physical properties of the saline alkali soil, including salt content, moisture content, particle size distribution, and particle size, as well as intrinsic parameters such as soil compaction, density, Poisson’s ratio, and shear modulus, were measured. The Hertz Mindlin with Bonding contact model was employed. Physical experiments on soil accumulation angles at different depths were carried out using the cylindrical lifting method. Subsequently, by means of the discrete element method and the BBD experimental design method, a response surface model was established, and an optimization analysis was performed on the optimal parameters for the soil–soil collision recovery coefficient, static friction coefficient, and dynamic friction coefficient at each depth. Test benches for measuring the collision recovery coefficient, static friction coefficient, and rolling friction coefficient of saline alkali soil at -65Mn were set up, calculation formulas for each parameter were derived, and the contact parameters between soil at different depths and 65Mn were obtained. The results of the sliding friction angle test on different depths of saline alkali soil at -65Mn were further verified using the discrete element method, with a maximum error of 3.11%, which falls within the allowable range. This suggests that the calibration results of the discrete element simulation parameters for the interaction between soil and contact components are reliable, providing data and model support for future research on enhancing the operational performance of high-performance contact components.

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling vines, taking the crushing mechanism as the research carrier, the interaction mechanism of the seedling vine mechanism was analyzed. Establish the mechanical model and motion trajectory model in the crushing process, simulate the peanut seedling vines crushing process based on the discrete element method, analyze the influence of the cutter shaft rotational speed, movement speed, and bending angle on the crushing of peanut seedling vines, and establish the regression model, and the results of the research show that the influence factors in the main order of priority are: knife shaft speed > movement speed > bending angle The optimal parameter combination is knife shaft speed 2171.94 r/min, movement speed 0.79 m/s, and bending angle 45°. According to the field test conditions, it is determined that the knife shaft rotational speed of 2170 r/min, movement speed of 0.8 m/s, and bending angle of 45° can make the peanut seedling vines crushing mechanism of the work performance to achieve a qualified seedling length rate of 97.292%, the rate of impurity content of 2.746%, and the error with the predicted value is less than 2%, which indicates that this study can provide a reference for the optimal design of the seedling vines crushing mechanism of the peanut pickup combine harvester.

Domestically developed wheat breeding plot combine harvesters in China currently utilize cyclone separation self-cleaning systems. However, these systems struggle to meet the agronomic requirement of zero wheat grain residue. Seed mixing caused by residual grains can compromise the accuracy of entire breeding field trials. This study focused on the structural design of a cyclone separation self-cleaning system based on high self-cleaning agronomic requirements. Research was conducted on the key structural and operational parameters of the cyclone separator and the negative-pressure centrifugal fan, preliminarily determining the ranges for critical parameters such as the diameter of the cylindrical section of the separator wall, the dust outlet diameter, and the rotational speed of the negative-pressure centrifugal fan. A test bench for the cyclone separation self-cleaning system of wheat breeding plot combine harvesters was designed and developed. Through single-factor experiments and Box–Behnken design optimization, the effects of key parameters on system performance were investigated. The optimal parameter combination—cylindrical section diameter of 614 mm, dust outlet diameter of 290 mm, and fan speed of 1495 r/min—achieved a self-cleaning rate of 100%, self-cleaning time ≤ 12 s, loss rate of 1.70%, and impurity rate of 0.16%, fully meeting the requirements for high-quality, rapid, and effective separation and self-cleaning operations.

This study presents a novel pneumatic seed-metering device for precision soybean breeding, engineered to deliver two seeds per hill with high operational reliability. Its design features a compartmentalized structure and an integrated seed-clearing mechanism, explicitly addressing the key limitations of conventional seeders, such as low automation levels and intervarietal contamination during seed switching. The seed-metering and clearing processes were analyzed using coupled discrete element method–computational fluid dynamics (DEM–CFD) simulations. The exploratory DEM–CFD analysis identified distinct operational thresholds for seeding failures: miss-seeding occurred at disc rotational speeds exceeding 2.55 rad s⁻¹, while multiple-seeding issues were frequent at applied vacuum pressures above 5.6 kPa. Following this, a Central Composite Design (CCD) experiment was conducted in a controlled laboratory setting to examine the effects of operational speed and vacuum pressure on seeding quality indices. A multi-objective numerical optimization identified an optimal operational compromise with a seed-metering disc speed of 2.65 rad s⁻¹ (approximately 1.82 km h⁻¹) and an applied negative pressure of 5.80 kPa. This operating point effectively balances the competing failure modes of multiple seeding and miss-seeding, resulting in rates of 2.95% and 0.85% respectively. Field validation in saline–alkali soil conditions confirmed the device’s high precision, with actual multiple and miss-seeding rates maintained below 2% and 0.5%, respectively. Overall, this device significantly enhances seeding efficiency and operational reliability, providing a practical and effective solution for high-throughput soybean breeding programmes.