Sheep breeding schemes utilising artificial insemination; large-scale simulation with a complex breeding goal

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Sheep Production Systems

Background:

• Optimizing breeding schemes is crucial for enhancing genetic gain in livestock populations.
• Traditional natural mating (NM) schemes may limit genetic progress compared to advanced methods.
• Evaluating alternative breeding strategies is essential for sustainable sheep production.

Purpose of the Study:

• To compare the effectiveness of four distinct Norwegian sheep breeding schemes.
• To assess genetic gain and inbreeding rates under different mating and insemination strategies.
• To identify optimal parameters for artificial insemination (AI) and natural mating schemes.

Main Methods:

• Stochastic simulation of a large Norwegian sheep breeding population (approx. 120,000 ewes).
• Evaluation of aggregate genotype including nine economically important traits.
• Analysis of schemes: AI, NMAI2, NMAI1, and Natural Mating (NM), with parameter variations.

Main Results:

• The AI and NMAI2 schemes yielded significantly higher genetic gain (approx. 40% more) than the NM scheme under a restricted inbreeding rate (≤0.8%).
• The NMAI1 scheme also showed substantial improvement over NM (approx. 25% more gain).
• Optimal parameters identified: low ewe insemination percentage to elite rams (10%) in AI schemes, and high natural mating rates with specific AI ewe numbers in NMAI schemes.

Conclusions:

• Advanced breeding schemes incorporating artificial insemination offer superior genetic gain for Norwegian sheep.
• Careful management of ram usage and insemination rates is key to maximizing benefits while controlling inbreeding.
• The AI and NMAI2 schemes represent more efficient strategies for genetic improvement in sheep breeding programs.