Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat

Study overview

The study integrates genomic markers, high-throughput phenotyping, and deep learning to improve prediction of Fusarium head blight-related traits in winter wheat. Grain/trait phenotypes are combined with genomic information to model disease- and quality-associated outcomes, demonstrating improved predictive performance versus conventional approaches.