Precision profiling of seed coat phenotypes in maize: 3D surface morphology, color, texture traits for the construction of phenotyping interaction networks

The seed coat serves as a protective barrier between seeds and their environment. This structure plays fundamental roles in protection, environmental sensing, and germination regulation. Current phenotypic characterization methods typically measure the seed coat together with adjacent structures, including the aleurone layer and endosperm. Such combined measurements hinder accurate assessment of seed coat-specific traits. This study presents an integrated analytical approach for phenotyping isolated maize seed coats. The method combines microscopic hyperspectral imaging with atomic force microscopy (AFM), enabling quantitative assessment of 24 phenotypic indicators spanning roughness, light transmittance, color, and texture parameters. The investigation of phenotypic diversity focused on inbred lines from natural association populations. The analytical workflow involved kernel contour extraction from RGB images followed by detailed phenotypic mapping. Population-wide analysis revealed substantial phenotypic variation. Coefficients of variation ranged from 30-45% for light transmittance and color texture phenotypes, while exceeding 60% for roughness parameters. A phenotypic interaction network was constructed to elucidate trait relationships, identifying VLD as key characteristic phenotypes in seed coat morphology. Dimensional reduction analysis highlighted 12 critical indicators: Rp, Ra, Rv, Rz, LAQ, VLI, LAD, TRGSD, TSGSH, TRGSE, CBAve, and SCAve. Germination studies demonstrated significant correlations between seed emergence rate (SER) and multiple seed coat traits, including light transmittance, color, and texture characteristics (R: -0.204 to -0.194, P < 0.05). Notable inbred lines, including Ry737, Dong46, CML486, and CML426, exhibited superior germination rates characterized by low seed coat roughness, high light transmittance, enhanced texture roughness, and increased color saturation and brightness. The methodological advances presented here provide novel insights into maize seed coat characteristics. These findings have significant implications for precise germplasm identification and the development of high-quality, high-vigor maize varieties. • We built an integrated phenotyping approach to identify the 3D surface morphological, color and texture traits of maize seed coats, combining microscopic hyperspectral imaging with atomic force microscopy (AFM). • Phenotypic maps and phenotypic interaction network were constructed to elucidate trait relationships, identifying VLD as characteristic phenotypes crucial to seed coat morphology, and 12 key indicators were identified as: Rp, Ra, Rv, Rz, LAQ, VLI, LAD, TRGSD, TSGSH, TRGSE, CBAve, and SCAve. • Germination studies revealed significant correlations between seed emergence rate (SER) and multiple seed coat characteristics, including light transmittance, color, and texture traits (R: -0.204 to -0.194, P < 0.05).