Response to early generation genomic selection for yield in wheat
We investigated increasing genetic gain for grain yield using early generation genomic selection (GS). A training set of 1,334 elite wheat breeding lines tested over three field seasons was used to generate Genomic Estimated Breeding Values (GEBVs) for grain yield under irrigated conditions applying...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Frontiers Media
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/126319 |
Similar Items: Response to early generation genomic selection for yield in wheat
- Sparse kernel models provide optimization of training set design for genomic prediction in multiyear wheat breeding data
- A Bayesian optimization R package for multitrait parental selection
- Genomics-assisted breeding in the CIMMYT Global Wheat Program
- Optimizing genomic parental selection for categorical and continuous-categorical multi-trait mixtures
- Bayesian divergence-based approach for genomic multitrait ordinal selection
- Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data