Assessing combining abilities, genomic data, and genotype × environment interactions to predict hybrid grain sorghum performance
Abstract Genomic selection in maize (Zea mays L.) has been one factor that has increased the rate of genetic gain when compared with other cereals. However, the technological foundations in maize also exist in other cereal crops that would allow prediction of hybrid performance based on general (GCA...
Guardado en:
Autores principales: | Jales M. O. Fonseca, Patricia E. Klein, Jose Crossa, Angela Pacheco, Paulino Perez‐Rodriguez, Perumal Ramasamy, Robert Klein, William L Rooney |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Wiley
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/2af6ec11fe2d42038db80e7c7927a858 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Phylogenetic relationships in the Sorghum genus based on sequencing of the chloroplast and nuclear genes
por: Galaihalage Ananda, et al.
Publicado: (2021) -
Genome‐enabled prediction for sparse testing in multi‐environmental wheat trials
por: Leonardo Crespo‐Herrera, et al.
Publicado: (2021) -
Comparison of genomic selection models for exploring predictive ability of complex traits in breeding programs
por: Lance F. Merrick, et al.
Publicado: (2021) -
Gain from genomic selection for a selection index in two‐row spring barley
por: Daniel W. Sweeney, et al.
Publicado: (2021) -
Deep‐learning power and perspectives for genomic selection
por: Osval Antonio Montesinos‐López, et al.
Publicado: (2021)