Abstract:High-density planting, high-precision operation and high-speed production have become the new paradigm of modern corn production, putting forward strict requirements for sowing equipment. Pneumatic maize planters have attracted much attention because they can maintain a high seeding qualification rate even at high speeds. However, sowing operations confronted with three major challenges: unstructured environment, high agronomic constraints, and strong farming seasons, which led to complex and changeable working conditions. Improper matching of operational parameters to conditions reduced seeding quality and underutilized equipment performance. The DEM-CFD gas-solid two-phase coupling method was employed to elucidate seed motion dynamics and mechanical behavior within the seed metering device at the microscale. Air pressure, seed feed rate, and seed cleaning gap were identified as critical factors affecting seeding quality. Using single grain rate as the evaluation metric, the operating parameters were optimized for two representative corn varieties in the Huang-Huai-Hai region (Huangjinliang MY73 and Zhengdan 958) through Box-Behnken response surface methodology. The optimal parameter combinations were determined as follows: for MY73 at 12 km/ h, maximum singulation rate was achieved at 4 kPa air pressure, with seed feed rate and cleaning gap set to Level 7; for Zhengdan 958 at 12 km/ h, optimal performance occurred at 4. 5 kPa air pressure, Level 8 feed rate, and Level 7 cleaning gap. Orthogonal test results demonstrated that air pressure, seed feed rate, and seed cleaning gap had a very significant effect on single grain rate, with obvious interactions between factors; the established regression model fit well and can accurately predict seed discharge performance. Results demonstrated significant variation in optimal parameters across varieties and operating speeds. The research result can provide a reference for parameter selection in practical operations, which can establish a theoretical foundation for automated parameter configuration in intelligent seeding systems.
