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Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat


Type:
Article
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.;
Khan, N.
ORCID iD iconhttps://orcid.org/0000-0002-0379-4622
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McBreen, J.;
Guihua Bai;
Guihua Bai
ORCID iD iconhttps://orcid.org/0000-0002-1194-319X
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Reynolds, M.P.;
ORCID iD icon
Reynolds, M.P.
ORCID iD iconhttps://orcid.org/0000-0002-4291-4316
ScopusScopus ID
researcheridResearcher ID
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Foulkes, M.J.;
Foulkes, M.J.
ORCID iD iconhttps://orcid.org/0000-0002-7765-8340
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Babar, A.
Babar, A.
ORCID iD iconhttps://orcid.org/0000-0001-9951-6856
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Year:
2022
URI:
https://hdl.handle.net/10883/22064
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
Pages:
298
DOI:
10.1186/s12864-022-08487-8
Place of Publication:
London (United Kingdom)
Publisher:
BioMed Central
Citation:
Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat. 2022. 23 (1) DOI: 10.1186/s12864-022-08487-8 BioMed Central.

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Related Datasets

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  • Link to dataset 2






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Genetic ResourcesInstitutionalMaizeSocioeconomicsSustainable Agrifood SystemsSustainable IntensificationWheat

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