Improved multi-trait prediction of wheat end-product quality traits by integrating NIR-predicted phenotypes

Improved multi-trait prediction of wheat end-product quality traits by integrating NIR-predicted phenotypes

Historically, end-product quality testing has been costly and required large flour samples; therefore, it was generally implemented in the late phases of variety development, imposing a huge cost on the breeding effort and effectiveness. High genetic correlations of end-product quality traits with h...

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Bibliographic Details
Main Authors: Shiva Azizinia, Daniel Mullan, Allan Rattey, Jayfred Godoy, Hannah Robinson, David Moody, Kerrie Forrest, Gabriel Keeble-Gagnere, Matthew J. Hayden, Josquin FG. Tibbits, Hans D. Daetwyler
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Plant Science
Subjects:
genomic prediction
multi-trait model
wheat breeding
genomic best linear unbiased prediction
NIR-predictor
forward-prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2023.1167221/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2023.1167221/full

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