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...
Saved in:
Main Authors: | Jales M. O. Fonseca, Patricia E. Klein, Jose Crossa, Angela Pacheco, Paulino Perez‐Rodriguez, Perumal Ramasamy, Robert Klein, William L Rooney |
---|---|
Format: | article |
Language: | EN |
Published: |
Wiley
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/2af6ec11fe2d42038db80e7c7927a858 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Phylogenetic relationships in the Sorghum genus based on sequencing of the chloroplast and nuclear genes
by: Galaihalage Ananda, et al.
Published: (2021) -
Genome‐enabled prediction for sparse testing in multi‐environmental wheat trials
by: Leonardo Crespo‐Herrera, et al.
Published: (2021) -
Comparison of genomic selection models for exploring predictive ability of complex traits in breeding programs
by: Lance F. Merrick, et al.
Published: (2021) -
Gain from genomic selection for a selection index in two‐row spring barley
by: Daniel W. Sweeney, et al.
Published: (2021) -
Deep‐learning power and perspectives for genomic selection
by: Osval Antonio Montesinos‐López, et al.
Published: (2021)