Explainable Machine Learning for Genomic Prediction, Subgroup Classification, and Optimal Parent Cross Ranking in Rice Breeding Using 1k-RiCA SNP Data
This study presents an explainable machine-learning framework using 1k-RiCA SNP data to predict flowering time and plant height, classify rice subgroups, and rank optimal parent crosses for breeding, all delivered via a transparent web application that overcomes the "black-box" limitations of traditional genomic selection.