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October 3, 2025Veterinary WorldOpen Access

Comparative application of machine learning approaches for body weight prediction in non-descript indigenous goats at different growth stages

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Authors

TTThobela Louis Tyasi

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Overview

This analysis reveals machine learning's superiority in predicting body weight in indigenous goats, highlighting CART's effectiveness over conventional methods.

Key Points

  • Machine learning techniques, especially CART, excel in predicting body weight in goats, outperforming traditional methods.
  • CART achieved R² values of 0.87, 0.94, and 0.99 at birth, weaning, and yearling stages, indicating strong prediction ability.
  • Various body measurements significantly correlate with body weight, suggesting the importance of selecting the right metrics.
  • Implementing these machine learning models can optimize herd management decisions in resource-limited farming systems.

Cite This Study

Thobela Louis Tyasi (2025) studied this question.

synapsesocial.com/papers/68e02f46f0e39f13e7fa2e1bhttps://doi.org/10.14202/vetworld.2025.2878-2887
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