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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