Multi-trait Genomic Selection Methods for Crop Improvement.

ABSTRACT: Plant breeders make selection decisions based on multiple traits, such as yield, plant height, flowering time, and disease resistance. A commonly used approach in multi-trait genomic selection is index selection, which assigns weights to different traits relative to their economic importance. However, classical index selection only optimizes genetic gain in the next generation, requires some experimentation to find weights that lead to desired outcomes, and has difficulty optimizing nonlinear breeding objectives. Multi-objective optimization has also been used to identify the Pareto frontier of selection decisions, which represents different trade-offs across multiple traits. We propose a new approach, which maximizes certain traits while keeping others within desirable ranges. Optimal sel

SUBMITTER: Moeinizade S 

PROVIDER: S-EPMC7404246 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature