Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical maize
Type:
Title:
Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical maize
Creator:
Gevartosky, R.;
Fanelli Carvalho, H.;
Costa-Neto, G.;
Montesinos-Lopez, O.A.;
https://orcid.org/0000-0002-3973-6547
Scopus ID
Items in this Repository
View
Crossa, J.;
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
View
Fanelli Carvalho, H.;
Costa-Neto, G.;
Montesinos-Lopez, O.A.;
Montesinos-Lopez, O.A.


View
Crossa, J.;

Fritsche-Neto, R.
Fritsche-Neto, R.

http://www.genetica.esalq.usp.br/alogamas/index2.html Items in this Repository
View
Year:
2023
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:
BMC Plant Biology
Journal volume:
23
Journal issue:
1
Article number:
10
Place of Publication:
London (United Kingdom)
Publisher:
BioMed Central
Citation:
Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical maize. 2023. 23 (1) DOI: 10.1186/s12870-022-03975-1 BioMed Central.