DEM calibration of high-oleic peanut seeds for precision seed metering

To improve the precision seed-metering performance of high-oleic peanuts, Yuhua 37 seeds were used to establish a discrete element method (DEM) model and calibrate contact parameters, followed by seed-metering validation. The parameter ranges of the seeds were determined experimentally, and the angle of repose was measured using a natural slope tester. A DEM model was constructed using an automatic multi-sphere filling method. With the angle of repose as the evaluation index, the Plackett-Burman design, steepest ascent method, and Box-Behnken design were combined to optimize the seed-seed coefficients of static and rolling friction and the seed-steel coefficient of static friction. Single-factor tests were further used to calibrate the seed-nylon and seed-acrylic coefficients of static friction. The optimized coefficients of static friction were 0.413, 0.505, 0.482, and 0.416 for seed-seed, seed-steel, seed-nylon, and seed-acrylic contacts, respectively, and the seed-seed coefficient of rolling friction was 0.028. Additional validation using funnel discharge rate and bulk density tests yielded relative errors of 3.22% and 1.48%, respectively, indicating that the calibrated parameters could reproduce both dynamic flow behavior and static packing behavior. Seed-metering simulations were compared with bench tests under different disc rotational speeds. According to the two-seed-per-hole sowing requirement for peanut planting, the qualified seeding rate was defined as the proportion of holes containing exactly two seeds. The maximum relative errors of the under-seeding rate, over-seeding rate, and qualified seeding rate were 8.3%, 9.1%, and 1.4%, respectively. The maximum over-seeding error occurred at 25 r/min, where the measured over-seeding rate was only 2.62%; therefore, a small absolute difference of 0.24 percentage points was amplified in the relative error calculation. Overall, the simulated and experimental seed-metering indices showed consistent trends, demonstrating that the calibrated parameters can support DEM simulation and structural optimization of seed-metering devices for high-oleic peanuts.