Genomic Selection in Alfalfa Across Multiple Ploidy Levels: A Comparative Study Using Machine Learning and Bayesian Methods

Genomic Selection in Alfalfa Across Multiple Ploidy Levels: A Comparative Study Using Machine Learning and Bayesian Methods

Agronomic traits and quality traits of alfalfa are of great importance to the feed industry. Genomic selection (GS) based on genotyping-by-sequencing (GBS) data, if it achieves moderate to high accuracy, has the potential to significantly shorten breeding cycles for complex traits and accelerate gen...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaoyue Zhu, Ruixin Zhang, Tianxiang Zhang, Changhong Guo, Yongjun Shu
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Agronomy
Subjects:
genomic selection
alfalfa
Bayesian model
machine learning
SNP density
heritability
Online Access:https://www.mdpi.com/2073-4395/14/12/2768
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items