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
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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.
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.
Year:
2021
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal volume:
126
Pages:
92-106
Place of Publication:
Harlow (United Kingdom)
Publisher:
Springer Nature
