Repeatability vs. multiple-trait models to evaluate shell dynamic stiffness for layer chickens.

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Poultry Science

Background:

• Shell quality is a critical trait for layer chickens, directly impacting economic returns.
• Utilizing repeated records in genetic evaluations enhances the accuracy of estimated breeding values.
• Previous studies have explored various genetic models, but optimal approaches for repeated shell quality records require further investigation.

Purpose of the Study:

• To compare the performance of different genetic models for evaluating shell quality traits in layer chickens.
• To determine the most suitable model for genetic evaluation considering repeated records across different ages.
• To assess the impact of model complexity on heritability and repeatability estimates.

Main Methods:

• Analysis of 81,646 dynamic stiffness records from brown egg layers and 93,748 from white egg layers across four generations.
• Comparison of seven genetic models: five repeatability models, a random regression model, and a multi-trait model.
• Model comparison using Akaike Information Criteria and Log Likelihood Ratio tests for nested models.

Main Results:

• Heritability estimates ranged from 0.31-0.36 (brown) and 0.23-0.26 (white).
• Repeatability was higher with age-specific permanent environment effects (0.59) compared to overall permanent effects (0.41-0.47).
• The multi-trait model demonstrated superior fit and predictive ability over repeatability and random regression models.

Conclusions:

• Models accounting for age-specific permanent environmental effects and heterogeneous residual variances improve fit over traditional models.
• The multi-trait model is recommended for genetic evaluation of shell quality traits with repeated records across ages.
• Consideration of repeatability across and within ages, alongside genetic correlations, is crucial for optimizing data collection and model selection.