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Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices.
Lopez-Cruz, Marco; Beyene, Yoseph; Gowda, Manje; Crossa, Jose; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo.
Affiliation
  • Lopez-Cruz M; Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA. lopezcru@msu.edu.
  • Beyene Y; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA. lopezcru@msu.edu.
  • Gowda M; Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
  • Crossa J; Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
  • Pérez-Rodríguez P; Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Mexico, Mexico.
  • de Los Campos G; Colegio de Postgraduados, Montecillos, Edo. de México, Mexico.
Heredity (Edinb) ; 127(5): 423-432, 2021 11.
Article in En | MEDLINE | ID: mdl-34564692
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Zea mays / Models, Genetic Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Heredity (Edinb) Year: 2021 Document type: Article Affiliation country: Estados Unidos
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Zea mays / Models, Genetic Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Heredity (Edinb) Year: 2021 Document type: Article Affiliation country: Estados Unidos