Bayesian divergence-based approach for genomic multitrait ordinal selection
Effective genomic selection for ordinal traits, such as disease resistance scores, is a persistent challenge in plant breeding due to the discrete, ordered nature of these phenotypes. This study presents a novel Bayesian divergence-based framework for multitrait ordinal selection, implemented in the...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Oxford University Press
2025
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/179091 |
Similar Items: Bayesian divergence-based approach for genomic multitrait ordinal selection
- A Bayesian optimization R package for multitrait parental selection
- Bayesian multitrait kernel methods improve multienvironment genome-based prediction
- Optimizing genomic parental selection for categorical and continuous-categorical multi-trait mixtures
- Balancing sensitivity and specificity enhances top and bottom ranking in genomic prediction of cultivars
- An approach for improving the sampling efficiency in the Bayesian calibration of computationally expensive simulation models
- Estimating the supply elasticity of cotton in Mali with the Nerlove Model: A bayesian method of moments approach: