Expert system for evaluation of reproductive performance and management

Area of Science:

• Veterinary Medicine
• Animal Science
• Dairy Management

Background:

• Dairy herd reproductive efficiency is crucial for profitability.
• Traditional methods for diagnosing reproductive issues can be time-consuming.
• Accurate data analysis is essential for effective herd management.

Purpose of the Study:

• To develop and evaluate a microcomputer expert system for dairy herd reproductive management.
• To assess the system's ability to identify reproductive problems and provide recommendations.
• To compare the expert system's performance against a human reproduction specialist.

Main Methods:

• Development of an expert system using an expert system shell and Turbo Pascal.
• Initial evaluation of key reproductive traits: days open, days to first breeding, estrus detection, and conception rate.
• Utilizing user input and Dairy Herd Improvement (DHI) reports for detailed analysis.
• Systematic questioning to pinpoint specific management and data accuracy issues.

Main Results:

• The expert system categorizes reproductive performance from 'excellent' to 'severe'.
• It prioritizes areas with the most negative impact on days open.
• In evaluations, the system and a specialist agreed on 85% of identified problem areas (47 out of 100).

Conclusions:

• The microcomputer expert system is a viable tool for dairy herd reproductive management.
• The system demonstrates strong concordance with expert human evaluation.
• It offers a structured approach to diagnosing and addressing reproductive inefficiencies in dairy herds.