A marker weighting approach for enhancing within-family accuracy in genomic prediction
Genomic selection is revolutionizing plant breeding. However, its practical implementation is still very challenging, since predicted values do not necessarily have high correspondence to the observed phenotypic values. When the goal is to predict within-family, it is not always possible to obtain r...
| Autores principales: | , , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Oxford University Press
2024
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/137924 |
Ejemplares similares: A marker weighting approach for enhancing within-family accuracy in genomic prediction
- Optimizing genomic prediction with transfer learning under a ridge regression framework
- Machine learning algorithms translate big data into predictive breeding accuracy
- Improving wheat grain yield genomic prediction accuracy using historical data
- Genotype performance estimation in targeted production environments by using sparse genomic prediction
- Boosting genomic prediction transferability with sparse testing
- Deep learning methods improve genomic prediction of wheat breeding