Digital phenotyping for robust seeds variability assessment in Setaria italica (L.) P. Beauv.

Abstract

Foxtail millet (Setaria italica L.) is a cereal crop with potential as a functional food due to its high nutritional value and its wide adaptability to unfavorable environmental conditions. Seed-related traits of foxtail millet are difficult to observe due to its small size. Therefore, the development of an efficient and accurate method for characterizing foxtail millet seeds using digital imaging technology is essential. This study aimed to characterize the seed morphology for variability assessment of Indonesian local foxtail millet genotypes and to develop a model to estimate the 100-seed weight using ImageJ. A total of 28 Indonesian local foxtail millet genotypes were used in this study for seed morphology characterization and the development of the 100-seed weight estimation model. Foxtail millet genotypes from different regions in Indonesia exhibited diverse seed morphologies. The 100-seed weight estimation model (y = 0.123x - 0.0821 (R² = 0.9223)) demonstrated a highly significant positive correlation (r = 0.96, p < 0.01) between the predicted and actual 100-seed weights. The correlation coefficient from model validation was 0.8731 (p < 0.01), indicating that the obtained model could estimate the 100-seed weight of foxtail millet seeds in future studies.