Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes

Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes

The performance of genomic prediction (GP) on genetically correlated traits can be improved through an interdependence multi-trait model under a multi-environment context. In this study, a panel of 237 soft facultative wheat (<i>Triticum aestivum</i> L.) lines was evaluated to compare si...

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Bibliographic Details
Main Authors: Jia Guo, Jahangir Khan, Sumit Pradhan, Dipendra Shahi, Naeem Khan, Muhsin Avci, Jordan Mcbreen, Stephen Harrison, Gina Brown-Guedira, Joseph Paul Murphy, Jerry Johnson, Mohamed Mergoum, Richanrd Esten Mason, Amir M. H. Ibrahim, Russel Sutton, Carl Griffey, Md Ali Babar
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Genes
Subjects:
genomic prediction
multi-trait model
multi-environment genomic best linear unbiased predictor
Bayesian multi-trait multi-environment model
Bayesian multi-output regressor stacking model
deep learning multi-trait multi-environment model
Online Access:https://www.mdpi.com/2073-4425/11/11/1270

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https://www.mdpi.com/2073-4425/11/11/1270

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