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July 26, 2026AnimalsOpen Access

Body Weight Prediction in Karayaka Lambs Using Morphometric Measurements: A Comparison of Regression and Machine Learning Approaches

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Authors

LBLütfi BayyurtTokat Gaziosmanpaşa Üniversitesi

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Overview

Randomized trial evaluates body weight prediction in Karayaka lambs, suggesting effective use of morphometric traits and machine learning approaches.

Key Points

  • The aim is to predict body weight in Karayaka lambs using morphometric measurements and compare regression with machine learning approaches.
  • Utilized biometric data from 150 Karayaka lambs, including morphometric traits.
  • Applied multiple linear regression, Ridge Regression, LASSO, Random Forest, and Gradient Boosting for prediction.
  • Conducted correlation analysis and principal component analysis to evaluate variable relationships.
  • Gradient Boosting achieved the highest prediction performance with training R2 of 0.962 and test R2 of 0.862.
  • Body weight showed significant differences between sexes and strong correlations with abdominal and heart girth.
  • The Random Forest model had a test R2 of 0.828, demonstrating effective prediction capabilities.

Cite This Study

Lütfi Bayyurt (2026) studied this question.

synapsesocial.com/papers/6a65a422d3aea3239cd76e13https://doi.org/10.3390/ani16152288
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