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Genetic Parameter Estimation and Breeding Value Ranking for Litter Size Traits in Meat Rabbits: REML and Bayesian
Fabián Magaña-Valencia1, Raymundo Rodríguez-de-Lara1, Rodolfo Ramírez-Valverde1
1Department of Animal Science, Universidad Autonoma Chapingo, Chapingo, Texcoco 56230, State of Mexico, Mexico.
Animals : an Open Access Journal From MDPI
|July 28, 2026
Summary
Estimating genetic parameters for litter size in meat rabbits is challenging with limited data. Bayesian methods offer more robust estimates and uncertainty characterization compared to frequentist approaches, improving genetic evaluations.
Area of Science:
- Animal Genetics
- Quantitative Genetics
- Livestock Production
Background:
- Reproductive efficiency is crucial for meat rabbit production.
- Estimating variance components for litter size is difficult in populations with limited data.
Purpose of the Study:
- To estimate genetic parameters for litter size in meat rabbits.
- To compare frequentist (REML) and Bayesian (Gibbs sampling) approaches for genetic evaluation.
Main Methods:
- Analyzed 956 kindling records using univariate and bivariate mixed models.
- Fitted models with additive genetic effects and permanent environmental effects.
- Utilized BLUPF90 software for variance component estimation.
Main Results:
- Heritability estimates for litter size traits were low (<0.10).
- Bayesian approach yielded slightly higher heritability estimates and better model convergence.
- Permanent environmental effects improved model fit but caused convergence issues with REML.
Conclusions:
- Bayesian methods provide a more reliable characterization of uncertainty in genetic evaluations with limited data.
- Model specification and inference methods significantly impact genetic evaluations in meat rabbits.
- Low heritability suggests environmental factors play a major role in litter size variation.
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