Genomic prediction of maize microphenotypes provides insights for optimizing selection and mining diversity

dc.contributor.author	Timmermans, Marja C. P.
dc.date.accessioned	2020-09-11T13:40:11Z
dc.date.available	2020-09-11T13:40:11Z
dc.date.issued	2020
dc.identifier.issn	1467-7652
dc.identifier.uri	http://hdl.handle.net/10900/106762
dc.language.iso	en	de_DE
dc.publisher	Wiley	de_DE
dc.relation.uri	http://dx.doi.org/10.1111/pbi.13420	de_DE
dc.subject.ddc	570	de_DE
dc.subject.ddc	610	de_DE
dc.title	Genomic prediction of maize microphenotypes provides insights for optimizing selection and mining diversity	de_DE
dc.type	Article	de_DE
utue.quellen.id	20200715072417_00204
utue.personen.roh	Yu, Xiaoqing
utue.personen.roh	Leiboff, Samuel
utue.personen.roh	Li, Xianran
utue.personen.roh	Guo, Tingting
utue.personen.roh	Ronning, Natalie
utue.personen.roh	Zhang, Xiaoyu
utue.personen.roh	Muehlbauer, Gary J.
utue.personen.roh	Timmermans, Marja C. P.
utue.personen.roh	Schnable, Patrick S.
utue.personen.roh	Scanlon, Michael J.
utue.personen.roh	Yu, Jianming
dcterms.isPartOf.ZSTitelID	Plant Biotechnology Journal	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE