Natural variation and genomic prediction of growth, physiological traits, and nitrogen-use efficiency in perennial ryegrass under low-nitrogen stress.

Zhao, Xiongwei; Nie, Gang; Yao, Yanyu; Ji, Zhongjie; Gao, Jianhua; Wang, Xingchun; Jiang, Yiwei

Zhao, Xiongwei; Nie, Gang; Yao, Yanyu; Ji, Zhongjie; Gao, Jianhua; Wang, Xingchun; Jiang, Yiwei.

Afiliação

Zhao X; College of Life Sciences, Shanxi Agricultural University, Taigu, Shanxi Province, China.
Nie G; Department of Grassland Science, Animal Science and Technology College, Sichuan Agricultural University, Chengdu, Sichuan Province, China.
Yao Y; Department of Agronomy, Purdue University, West Lafayette, IN, USA.
Ji Z; Department of Agronomy, Purdue University, West Lafayette, IN, USA.
Gao J; College of Life Sciences, Shanxi Agricultural University, Taigu, Shanxi Province, China.
Wang X; College of Life Sciences, Shanxi Agricultural University, Taigu, Shanxi Province, China.
Jiang Y; Department of Agronomy, Purdue University, West Lafayette, IN, USA.

J Exp Bot ; 71(20): 6670-6683, 2020 10 22.

Article em En | MEDLINE | ID: mdl-32827031

Assuntos

Lolium; Teorema de Bayes; Genômica; Lolium/genética; Nitrogênio; Melhoramento Vegetal

Palavras-chave

Lolium perenne; Genomic prediction; low nitrogen; natural variation; perennial ryegrass; population structure

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lolium Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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