Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding
Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to...
| Autores principales: | , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/126502 |
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