Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
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Title
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
Authors
Keywords
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Journal
HEREDITY
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-08-27
DOI
10.1038/s41437-020-00353-1
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- (2017) Xuecai Zhang et al. G3-Genes Genomes Genetics
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- Modeling Epistasis in Genomic Selection
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- synbreed: a framework for the analysis of genomic prediction data using R
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- (2012) Vanessa S. Windhausen et al. G3-Genes Genomes Genetics
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