A deterministic computer simulation model of life-cycle lamb and wool production.

Area of Science:

• Agricultural Science
• Animal Science
• Computational Biology

Background:

• Optimizing sheep production efficiency requires understanding the interplay between genetics and management.
• Existing models may not fully capture the complex interactions influencing lamb and wool output.

Purpose of the Study:

• To develop a deterministic mathematical computer model simulating life-cycle efficiency in lamb and wool production.
• To evaluate the impact of genetic improvement in performance traits under diverse management systems.

Main Methods:

• Developed a deterministic computer model incorporating genetic parameters (fertility, growth, wool) and management options (mating, feeding, weaning).
• Simulated animal growth, nutrient requirements (ME intake), feed intake, and tissue catabolism.
• Validated biological function equations with experimental data.

Main Results:

• The model quantifies lifetime intake (TDN, DM, protein) and output (lean meat, wool) for lambs and ewes.
• It integrates genetic, management, and marketing variables to assess efficiency.
• Provides economic weighting for traits to guide genetic selection.

Conclusions:

• The model offers a framework for deriving optimal genetic selection criteria within defined sheep production systems.
• It enables relative economic evaluation of different traits and management strategies.
• Facilitates informed decision-making for improving sheep industry productivity.