Genomics combined with UAS data enhances prediction of grain yield in winter wheat.

ABSTRACT: With the human population continuing to increase worldwide, there is pressure to employ novel technologies to increase genetic gain in plant breeding programs that contribute to nutrition and food security. Genomic selection (GS) has the potential to increase genetic gain because it can accelerate the breeding cycle, increase the accuracy of estimated breeding values, and improve selection accuracy. However, with recent advances in high throughput phenotyping in plant breeding programs, the opportunity to integrate genomic and phenotypic data to increase prediction accuracy is present. In this paper, we applied GS to winter wheat data integrating two types of inputs: genomic and phenotypic. We observed the best accuracy of grain yield when combining both genomic and phenotypic inputs, whil

SUBMITTER: Montesinos-Lopez OA 

PROVIDER: S-EPMC10090417 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature