Zvi Peleg

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%.

The paper quantifies drought plasticity in tetraploid wheat using QTL analysis and identifies candidate genes for stress adaptation.

The paper adjusts ionome element concentrations for phosphorus and sulfur variation in wheat, identifying QTLs and improving genetic understanding of mineral composition.