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Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield


Type:
Article
Title:
Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield
Creator:
Jin Sun;
Rutkoski, J.;
Rutkoski, J.
ORCID iD iconhttps://orcid.org/0000-0001-8435-4049
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Poland, J.A.;
Poland, J.A.
ORCID iD iconhttps://orcid.org/0000-0002-7856-1399
ScopusScopus ID
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Crossa, J.;
ORCID iD icon
Crossa, J.
ORCID iD iconhttps://orcid.org/0000-0001-9429-5855
ScopusScopus ID
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Jannink, J.L.;
Jannink, J.L.
ORCID iD iconhttps://orcid.org/0000-0003-4849-628X
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Sorrells, M.E.
Sorrells, M.E.
ORCID iD iconhttps://orcid.org/0000-0002-7367-2663
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Year:
2017
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:
10
Journal issue:
2
Pages:
1-12
DOI:
10.3835/plantgenome2016.11.0111
Place of Publication:
Madison, WI (USA)
Publisher:
CSSA :; Wiley
Citation:
Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield. 2017. 10 (2) DOI: 10.3835/plantgenome2016.11.0111 CSSA :. Wiley.

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Genetic ResourcesInstitutionalMaizeSocioeconomicsSustainable IntensificationWheatIntegrated Development

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