Feed Conversion Ratio (FCR) and Performance Group Estimation Based on Predicted Feed Intake for the Optimisation of...

Area of Science:

• Animal Science
• Agricultural Engineering
• Data Science

Background:

• Accurate estimation of individual animal feed intake is crucial for optimizing livestock production.
• Traditional methods for monitoring feed intake can be labor-intensive and may lack precision.
• Electronic feeding systems offer opportunities for automated data collection on feeding behavior.

Purpose of the Study:

• To evaluate the feasibility of predicting individual animal Feed Conversion Ratio (FCR) using time spent feeding data.
• To develop and validate a model for estimating feed intake based on feeding behavior.
• To categorize animals based on predicted FCR for informed management decisions.

Main Methods:

• Collected time spent feeding data for 80 beef animals over a 56-day period.
• Employed Support Vector Regression (SVR) to model and predict feed intake.
• Utilized predicted feed intake to estimate individual animal FCR.

Main Results:

• Demonstrated the feasibility of using 'time spent eating' measurements to estimate feed intake.
• Successfully predicted individual animal Feed Conversion Ratio (FCR).
• Enabled categorization of animals into three groups based on estimated FCR.

Conclusions:

• Time spent feeding is a viable predictor of individual animal feed intake and FCR.
• This approach provides valuable insights for farmers to optimize production costs.
• The methodology supports data-driven decisions for enhancing livestock production efficiency.