Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat
Type:
Title:
Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat
Creator:
Shahi, D.;
Jia Guo;
Pradhan, S.;
Afridi, K.;
Avci, M.;
Khan, N.;
McBreen, J.;
Guihua Bai;
Reynolds, M.P.;
https://orcid.org/0000-0002-4291-4316
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Researcher ID
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Foulkes, M.J.;
Babar, A.
Jia Guo;
Pradhan, S.;
Afridi, K.;
Avci, M.;
Khan, N.;
McBreen, J.;
Guihua Bai;
Reynolds, M.P.;
Reynolds, M.P.
https://orcid.org/0000-0002-4291-4316
Scopus ID
Researcher ID
Items in this Repository
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Foulkes, M.J.;
Babar, A.
Year:
2022
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 Genomics
Journal volume:
23
Journal issue:
1
Article number:
298
Place of Publication:
London (United Kingdom)
Publisher:
BioMed Central
Related Datasets
CGIAR Initiatives
Initiative:
Accelerated Breeding
Impact Area:
Nutrition, health & food security
Action Area:
Genetic Innovation
Donor or Funder:
CGIAR Trust Fund
United States Department of Agriculture
United States Department of Agriculture
CGSpace URL:
