Abstract
1. A model that simulates the total production of eggs (TEP) in broiler breeders was used to predict the optimum initial (20 week) body weight (IBWexp), daily weight gains from 20 to 30 (DWGexp20–30) and 31 to 62 weeks of age (DWGexp31–62), age at photostimulation (affecting age at first egg, AFEexp), coefficients of variation of initial body weight (CV-IBWexp) and age at first egg (CV-AFEexp), and the effect of genetically increasing the numbers of yellow follicles at the onset of lay.
2. The results suggest that TEP in broiler breeders is very sensitive to changes in body weight gain during the first 10 weeks of the production period and body weight at the start of egg production, whereas changes in body weight gain after peak rate of lay showed only minor effects on TEP. Increasing CV-IBWexp was associated with a linear decrease in the mean and increased variability of TEP.
3. Decreasing AFEexp was negatively associated with TEP, whereas higher CV-AFEexp increased variability of TEP and had a trivial affect on the mean.
4. Results of the simulation suggested that reducing ovarian yellow follicle numbers by means of genetic selection could reduce the degree of feed restriction currently used in broiler breeder commercial stocks while maintaining total egg production. Higher numbers of yellow follicles associated with selection for higher growth rate would not result in lower egg production if the body weight target was maintained at the currently recommended commercial level and the effect on TEP of increasing the target in proportion to potential body weight may be relatively small.
Acknowledgements
R.A. gratefully acknowledges financial support from the Programme Alßan, the European Union Programme of High Level Scholarships for Latin America (scholarship No. E04E03945VE) and CDCH-Universidad Central de Venezuela. We are grateful to Jim McAdam and colleagues at Aviagen for supplying the commercial trial data and to Caroline McCorquodale for helpful comments on the presentation of the results. The Roslin Institute is supported by the Biotechnology and Biological Sciences Research Council.