Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project

Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics. New and improved methods to genomic prediction are continually being developed that attempt to deal with the integration of data types beyond ge...

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Bibliographic Details
Main Authors: Diego Jarquin, Natalia de Leon, Cinta Romay, Martin Bohn, Edward S. Buckler, Ignacio Ciampitti, Jode Edwards, David Ertl, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, David Hooker, Shawn M. Kaeppler, Joseph Knoll, Elizabeth C. Lee, Carolyn J. Lawrence-Dill, Jonathan P. Lynch, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Torbert Rocheford, James C. Schnable, Patrick S. Schnable, Margaret Smith, Nathan Springer, Peter Thomison, Mitch Tuinstra, Randall J. Wisser, Wenwei Xu, Jianming Yu, Aaron Lorenz
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Genetics
Subjects:
genotype-by-environment interaction (G×E)
Genomes to Fields (G2F) initiative
general combining ability (GCA)
specific combining ability (SCA)
hybrid prediction
genomic prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.592769/full

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https://www.frontiersin.org/articles/10.3389/fgene.2020.592769/full

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