During corn harvesting operations, machine–straw–soil contact often occurs, but there is a lack of research related to the role of straw–soil contact. Therefore, in this study, a composite contact model of corn straw‒soil particles was established based on the discrete element method (DEM). First, the discrete element Hertz‒Mindlin method with bonding particle contact was used to establish a numerical model of the double-bonded bimodal distribution of corn straw, and bonding particle models of the outer skin‒outer skin, inner pulp‒inner pulp, and outer skin‒inner pulp were developed. The nonhomogeneous and deformable material properties were accurately expressed. The straw compression test combined with simulation calibration was used to determine some of the bonding contact parameters by means of the PB (Plackett–Burman) test, the steepest ascent test, and the BB (Box–Behnken) test. Additionally, Additionally, the Hertz-Mindlin with JKR (Johnson-Kendall-Roberts) + bonding key model was used to establish the numerical model of the soil particles, which was used to describe the irregularity and adhesion properties of the soil particles. The geometric model of the soil particles was established using the multisphere filling method. Finally, a composite contact model of corn straw‒soil particles was established, the contact parameters between straw and soil were calibrated via collision tests, inclined tests and inclined rolling tests, and the established composite contact model was further verified through direct shear tests between straw and soil. A theoretical foundation for the optimal design of equipment linked to maize harvesting is provided by this work.

During precision sowing, the contact process between the soil and seeds cannot be ignored. The constitutive relationship of soil is relatively complex, with characteristics such as high nonlinearity, while the contact mechanism between the soil and seeds is unclear. To better understand the contact between seeds and soil, it is necessary to establish a reasonable contact model. Ellipsoidal seeds, such as soybean, red bean, and kidney bean seeds, were adopted as research objects. In this paper, we used the discrete element method to establish an ellipsoidal seed–soil contact model. The JKR + bonding model was adopted for describing the adhesion between soil particles, and the Hertz–Mindlin new restitution (HMNS) model was used for ellipsoidal seed particles to eliminate the multiple contact point issue when modeling with the multi-sphere filling method. Moreover, both simulations and experiments were conducted to calibrate the interaction parameters between soil and seeds. The path of steepest ascent test and Box‒Behnken design (BBD) tests were also used, as well as direct shear tests. Thus, certain soil parameter values were obtained, namely the JKR surface energy was 4.436 J/m², the normal stiffness per unit area was 2.86 × 10⁶ N/m³, the shear stiffness per unit area was 5.54 × 10⁵ N/m³, the critical normal stress was 1833 Pa, and the critical shear stress was 3332 Pa. In addition, the simulation parameters for ellipsoidal seeds were obtained from previous works. Moreover, to obtain more accurate ellipsoidal seed–soil interaction parameters, collision tests, static friction tests, and rolling friction tests were adopted. A single-factor test was used to calibrate the ellipsoidal seed–soil interaction parameters. The calibration results were as follows: the collision restitution coefficients of ellipsoidal seeds with soil were all 0.25. The static friction coefficient of soybeans with soil was 0.6, that of red beans with soil was 0.65, and that of kidney beans with soil was 0.5. The rolling friction coefficient of soybeans with soil was 0.1, that of red beans with soil was 0.14, and that of kidney beans with soil was 0.14. Finally, the rationality of parameter selection was verified through piling tests between ellipsoidal seeds and soil. The relative error of the angle of repose of soybean/soil was 2.99%, that of red bean/soil was 0.60%, and that of kidney bean/soil was 0.55%. Thus, the feasibility and rationality of the contact models between the ellipsoidal seeds and soil established in this paper, as well as the parameter selection, were verified.

To improve the crushing efficiency and crushing pass rate of high-moisture corn ears (HMCEs), a multi-stage crushing scheme is proposed in this paper. A two-stage crushing device for HMCEs is designed, and the ear crushing process is analyzed. Firstly, a simulation model for HMCEs was established in EDEM software (2018), and the accuracy of the model was verified by the shear test. Subsequently, single-factor simulation experiments were conducted, with the crushing rate serving as the evaluation index. The optimal working parameter ranges for the HMCE device were identified as a primary crushing roller speed of 1200–1600 revolutions per minute (r/min), a secondary crushing roller clearance of 1.5–2.5 mm, and a secondary crushing roller speed of 2750–3750 r/min. A Box–Behnken experiment was conducted to establish a multiple regression equation. With the objective of maximizing the qualified crushing pass rate, the optimal combination of parameters was revealed: a primary crushing roller speed of 1500 r/min, a secondary crushing roller clearance of 2.5 mm, and a secondary crushing roller speed of 3280 r/min. The pass rate of corn cob crushing in the simulation test was 98.2%. The physical tests, using the optimized parameter combination, yielded a qualified crushing rate of 97.5%, which deviates by 0.7% from the simulation results, satisfying the requirement of a qualified crushing rate exceeding 95%. The experimental outcomes validate the rationality of the proposed crushing scheme and the accuracy of the model, providing a theoretical foundation for subsequent research endeavors.

Establishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. This study focuses on high-moisture corn ears during the early harvest stage, developing a fragmentable corn ear model and calibrating its bonding parameters. First, based on the Hertz–Mindlin method in the Discrete Element Method, a three-layer corn cob bonding model consisting of pith, woody ring structure, and glume was established. Through a combined experimental and simulation calibration approach, the bonding parameters of the cob were determined using Plackett–Burman tests, the steepest ascent tests, and Box–Behnken tests. Subsequently, the same method was applied to establish a corn kernel bonding model, with the kernel bonding parameters calibrated through the steepest ascent and Box–Behnken tests. In order to arrange the kernel models on the cob model to achieve the construction of a complete ear model, this paper proposes a “matrix coordinate positioning method”. Through calculations, this method enables the uniform arrangement of corn kernels on the cob, thereby accomplishing the establishment of a composite model for the high-moisture corn ear. The bonding parameters between the cob and kernels were determined through compression tests. Finally, the reliability of the model was partially validated through shear testing; however, potential confounding variables remain unaccounted for in the experimental analysis. While this study establishes a theoretical framework for the design and optimization of machinery dedicated to high-moisture corn ear fragmentation processes, questions persist regarding the comprehensiveness of variable inclusion during parametric evaluation. This analytical approach exhibits characteristics analogous to incomplete system modeling, potentially limiting the generalizability of the proposed methodology.

In addition to improving the efficacy of the furrow opener by ensuring consistent seeding depth, the gryllulus jaw geometry curve was integrated into the furrow opener. Soil particles were modeled using the DEM combined with the Hertz–Mindlin with JKR model, and simulation tests were conducted using the DEM corn stover model. Three geometric curves of gryllulus jaws were extracted. The effect of each curve and magnification on the manipulation results was clarified by the simulation test. Subsequently, field trials were conducted to evaluate the stability of the seeding depth of the bionic structure. The experiment showed that the No. 1 structure with a magnification of 1000 was the best, and the stability was 42.10% higher than that of the original structure. The results of this research can provide key structural and simulation parameters for the development of planter furrow openers with both efficient straw crushing and stable sowing depth functions, which is of great significance for the improvement of agricultural machinery.

The peanut, a globally important oil and economic crop, has thin, brittle pods that are prone to breakage under external forces during mechanical harvesting, transportation, and processing. To minimize this loss and reduce production costs, we conducted an in-depth study of the pod-breaking process by integrating manual and automatic filling approaches within the discrete element method (DEM) with the Hertz–Mindlin with bonding model. A breakable layered bonding model for peanut pods was developed, which is capable of precisely characterizing the disparities in the mechanical properties of peanut pod shells and kernels. Physical tests were performed to obtain the relevant contact parameters of peanut pods. Compression tests combined with calibration approaches were employed to identify the bonding parameters of peanut pods, which are not easily accessible via direct experimental measurements. The optimal combination of simulation parameters for the model was determined via a Plackett–Burman test, steepest ascent test, and Box–Behnken test. The results indicated that the critical normal stress between pod shells is the most significant influencing factor. The optimal parameter combination for the proposed model is as follows: the normal stiffness per unit area between pod shells is 7.81 × 10¹⁰ N/m³, the shear stiffness per unit area between pod shells is 9.00 × 10⁸ N/m³, the critical normal stress between pod shells is 2.17 × 10⁵ N/m³, and the critical shear stress between pod shells is 2.25 × 10⁵ N/m³. The established layered bonding model for breakable peanut pods was validated using both cylinder-lifting simulation tests and physical shelling experiments. The relative error in the angle of repose between the cylinder-lifting simulation and physical tests was 1.6%, while the deviation in the shelling experiment was only 0.7%. This model provides a theoretical foundation for the design and optimization of machinery used in peanut pod harvesting, transportation, and processing.