A bioeconomic simulation model for a hierarchical swine breeding structure

Area of Science:

• Animal Science
• Agricultural Economics
• Quantitative Genetics

Background:

• Optimizing breeding programs requires sophisticated tools to evaluate complex genetic and economic factors.
• Hierarchical breeding structures are common in commercial swine production, necessitating efficient management strategies.

Purpose of the Study:

• To develop and present a stochastic bioeconomic computer model for simulating individual pigs within a hierarchical breeding system.
• To provide a tool for evaluating the impact of various selection, culling, and management strategies on swine production.

Main Methods:

• Developed a weekly-simulating stochastic computer model incorporating biological and economic variables.
• Included factors such as mating, farrowing, selection, survival rates, growth performance, and reproductive probabilities.
• Modeled genetic and environmental effects, including heterosis, litter size, and environmental influences, with regression analysis for derived variables.

Main Results:

• The model simulates key production variables, including litter size, survival, growth, and reproductive traits.
• Production costs (feed, operating, fixed, replacement) and income (market, cull, replacement sales) were incorporated.
• Means and variances of variables were shown to differ between genetic lines, highlighting genetic line-specific performance.

Conclusions:

• The developed stochastic bioeconomic model serves as a valuable tool for assessing swine breeding, culling, and management strategies.
• The model can aid decision-making in hierarchical breeding structures by simulating outcomes of different management approaches.
• Further refinement could include modeling backfat effects on market value and sow maintenance costs.