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Predicting Bull Behavior in Pastures by Arman Habib is a document available to read on EtoBox.

What is Predicting Bull Behavior in Pastures about?

This study investigates bull behavior in multiple-sire pastures using accelerometer data and classification algorithms to predict events such as lying, standing, walking, and mounting. The random forest classifier demonstrated the highest accuracy in predicting these behaviors, with accuracies ranging from 73% to 99%. Further research is needed to understand how these behaviors influence overall parentage data in cattle breeding operations.

Author

Arman Habib

Language

EN