2026-04-14T07:31:36Zhttps://recercat.cat/oai/request

oai:recercat.cat:20.500.12327/49402026-02-24T00:34:06Zcom_2072_4428com_2072_4427col_2072_487898

00925njm 22002777a 4500 dc Yannam, Venkata Rami Reddy author da Silva Lopes, Marta author Soriano, José Miguel author 2025-12-05 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. 1746-4811 https://hdl.handle.net/20.500.12327/4940 https://doi.org/10.1186/s13007-025-01467-5 Optimizing genomic selection models for wheat breeding under contrasting water regimes in a mediterranean environment