Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
Type:
Title:
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
Creator:
Costa-Neto, G.;
Fritsche-Neto, R.;
https://orcid.org/0000-0003-4310-0047
URL Profile
http://www.genetica.esalq.usp.br/alogamas/index2.html Items in this Repository
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Crossa, J.
Fritsche-Neto, R.;
Fritsche-Neto, R.

http://www.genetica.esalq.usp.br/alogamas/index2.html Items in this Repository
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Crossa, J.

Year:
2021
Copyright:
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Journal:
Heredity
Journal volume:
126
Pages:
92-106
Place of Publication:
Harlow (United Kingdom)
Publisher:
Springer Nature
Citation:
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials. 2021. 126 DOI: 10.1038/s41437-020-00353-1 Springer Nature.