Idan Sabag

This study uses high-throughput phenotyping and genomic models to improve yield prediction in sesame by analyzing temporal trait dynamics and multi-trait associations.

This study compares single- and multi-environment genomic prediction models for agronomic traits in sesame, finding that multi-environment analysis improves prediction accuracy by 15%-58%.