Optimizing genomic selection models for wheat breeding under contrasting water regimes in a mediterranean environment.

ABSTRACT:

Background

Bread wheat (Triticum aestivum L.) is a vital global crop, supplying 20% of the protein in the human diet. Improving its productivity and resilience, particularly under water-limited conditions, is a major breeding priority. Genomic selection offers a promising approach to accelerate genetic gains by predicting complex traits using genome-wide marker data. This study evaluated the performance of various genomic selection (GS) models in predicting key agronomic traits under contrasting well-watered (WW) and water-stressed (WS) conditions, with the goal of enhancing drought adaptation in wheat breeding programs.

Results

A panel of 179 wheat lines was evaluated for grain yield, yield components, and grain protein content. Models were trained on data from well-watered

SUBMITTER: Yannam VRR 

PROVIDER: S-EPMC12679779 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature