Related Experiment Videos
Predicted response in food conversion ratio for growth by selection on the ratio or on linear component traits, in a
1Ross Breeders Ltd, Newbridge, Midlothian, Scotland.
British Poultry Science
|May 1, 1996
Summary
Direct versus indirect selection for food conversion ratio (FCR) in broilers showed similar responses, but significant differences emerged with varying heritabilities or correlations. Including live body weight (LWT) offset FCR response losses.
Area of Science:
- Animal Breeding and Genetics
- Quantitative Genetics
- Poultry Science
Background:
- Selection for live body weight (LWT) is common in broiler breeding.
- Food conversion ratio (FCR) is a critical trait for economic efficiency.
- Sequential selection schemes are often applied to balance multiple breeding objectives.
Purpose of the Study:
- To compare direct versus indirect selection for FCR after LWT selection.
- To investigate the impact of including LWT in selection indices on FCR response.
- To assess the robustness of statistical methods to non-normality in FCR data.
Main Methods:
- Selection index methodology was used to evaluate different selection strategies.
- Comparison of single-step and sequential selection schemes.
- Restricted Maximum Likelihood (REML) was employed for (co)variance component estimation, including for log-transformed FCR.
Main Results:
- Relative responses in FCR and aggregate genotype (H) were similar for direct and indirect selection.
- Significant differences in FCR response (5-12%) occurred with unequal heritabilities or high correlations between component traits.
- Including LWT in the aggregate genotype partially or fully offset losses in FCR response.
- REML demonstrated robustness to non-normality in FCR data, even with varying coefficients of variation.
Conclusions:
- The choice between linear index and ratio selection for FCR depends on trait heritabilities and correlations.
- Including LWT in selection indices can mitigate negative impacts on FCR response.
- REML is a reliable method for estimating genetic parameters for FCR, even with non-normal data.