A model for economic comparison of swine insemination programs

Area of Science:

• Animal Science
• Reproductive Biology
• Agricultural Economics

Background:

• Artificial insemination (AI) is crucial for swine reproduction.
• Optimizing AI schedules balances high farrowing rates and litter sizes with cost-efficiency.
• Current AI protocols require refinement to maximize economic returns in commercial swine operations.

Purpose of the Study:

• To compare the economic viability of seven AI schedules combined with once or twice daily estrus detection.
• To identify AI schedules that maximize farrowing rate, litter size, and economic return in swine herds.
• To evaluate the impact of insemination timing relative to estrus on reproductive performance.

Main Methods:

• A simulation model was developed using commercial spreadsheet software.
• Seven distinct AI schedules were simulated across 500 herds of 100 sows each.
• Estrus detection was simulated as once or twice daily, with inseminations timed at 0, 12, 24, and 36 hours post-estrus detection.

Main Results:

• Schedule 1 (0, 12, 24, 36h) predicted the highest farrowing rate and litter size.
• Schedule 2 (12, 24, 36h) with twice-daily estrus detection yielded the highest economic return ($14.90/bred sow).
• Schedule 1 with once-daily estrus detection closely followed in economic return ($13.75/bred sow).

Conclusions:

• The timing of insemination relative to ovulation significantly impacts swine reproductive outcomes.
• Strategic AI scheduling, particularly inseminating 12, 24, and 36 hours post-estrus, enhances economic efficiency.
• Maximizing the proportion of sows inseminated at optimal times is key to high-performance swine breeding programs.