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Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices

Genomic prediction models are often calibrated using multi-generation data. Over time, as data accumulates, training data sets become increasingly heterogeneous. Differences in allele frequency and linkage disequilibrium patterns between the training and prediction genotypes may limit prediction acc...

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Detalles Bibliográficos
Autores principales: Lopez-Cruz, Marco, Beyene, Yoseph, Gowda, Manje, Crossa, Jose, Pérez-Rodríguez, Paulino, de los Campos, Gustavo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551287/
https://www.ncbi.nlm.nih.gov/pubmed/34564692
http://dx.doi.org/10.1038/s41437-021-00474-1