Optimizing selection with several constraints in poultry breeding.

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Poultry Science

Background:

• Poultry breeding programs require balancing selection for primary objectives with controlling coancestry and antagonistic traits.
• Traditional selection methods may struggle to efficiently manage multiple complex breeding goals simultaneously.

Purpose of the Study:

• To introduce an efficient selection algorithm, adaptative simulated annealing (ASA), for poultry breeding schemes.
• To quantify the impact of coancestry and antagonistic trait constraints on genetic gain for the main breeding objective.

Main Methods:

• Simulated broiler dam and sire lines over 10 generations.
• Implemented adaptative simulated annealing (ASA) for selection under coancestry and antagonistic trait constraints.
• Compared ASA performance against unconstrained Best Linear Unbiased Prediction (BLUP) selection.

Main Results:

• ASA demonstrated speed and high accuracy in meeting selection constraints.
• Constraints on antagonistic traits had a significant impact on genetic gain, comparable to or exceeding coancestry constraints.
• Family structure facilitated coancestry control but was less effective for managing antagonistic traits.
• Multiple constraints showed nearly additive impacts on the main trait's genetic gain.

Conclusions:

• Adaptative simulated annealing (ASA) is a viable and efficient tool for complex poultry breeding schemes.
• Controlling antagonistic traits is crucial and can significantly affect genetic progress.
• The additive nature of multiple constraints suggests their combined use can be justified in practical breeding programs after simulation-based evaluation.