A Machine-Vision-Based Platform for the Automated and Integrated Measurement of Multiple Seed Physical Properties

作者：Chunfeng Gao, J Q Xu, Ting Yang, Y N Wu, Y. Lu, Yi-Xiang Wang · 发表于：Agriculture · 年份：2026 · DOI：10.3390/agriculture16151604 · 研究领域：Soil Mechanics and Vehicle Dynamics、Agricultural Engineering and Mechanization、Tree Root and Stability Studies

Seed dimensions (length and width), surface color, frictional properties (static and kinetic coefficients of friction), thousand-seed weight, and angle of repose are five important categories of seed physical properties. Conventional methods generally measure these properties separately and rely heavily on manual operation, resulting in limited applicability and difficulty in balancing measurement efficiency and accuracy. To address these limitations, this study developed an automated method and an integrated platform incorporating automatic feeding, individual-seed positioning, state recognition, parameter acquisition, and cyclic control. After a single sample loading, the platform sequentially processed individual seeds, measured their dimensions, surface color, and static and kinetic coefficients of friction, and accumulated the measured seeds for subsequent thousand-seed weight and angle-of-repose determination, thereby enabling continuous automated measurement of the five categories of physical properties. Experiments were conducted using maize kernels, red kidney beans, and sunflower seeds to evaluate the measurement performance, repeatability, and cross-material adaptability of the platform. The standard deviations of repeated seed-dimension measurements were below 0.042 mm for all three seed types. The first moments of H and S in the HSV color space and a* and b* in the CIELAB color space were selected for color analysis and exhibited relatively low sensitivity to ill...