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<p>Yak meat from different geographical origins exhibits distinct quality traits. Accurate identification of its origin is essential for protecting consumer rights and promoting the sustainable development of the yak industry. This study aimed to trace the origin of Tibetan yak meat using mid-infrared spectroscopy combined with multivariate analysis and machine-learning methods. The training set and test set achieved high accuracy using the back propagation neural network (100% and 95%, respectively), and 99% and 95%, respectively, using the Fisher discriminant analysis. Compared to methods that involve expensive instruments and complex operations, this approach offers a rapid, cost-effective and reliable solution.</p>

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Quality control and origin traceability of Tibetan yak meat using mid-infrared spectroscopy combined with multivariate analysis and machine learning

  • 期刊论文

  • 发表日期：

    2025年6月18日

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  • Wanli Zong,
  • Shanshan Zhao,
  • Yalan Li,
  • Xiaoting Yang,
  • Mengjie Qie,
  • Ping Zhang,
  • Yan Zhao

摘要

Yak meat from different geographical origins exhibits distinct quality traits. Accurate identification of its origin is essential for protecting consumer rights and promoting the sustainable development of the yak industry. This study aimed to trace the origin of Tibetan yak meat using mid-infrared spectroscopy combined with multivariate analysis and machine-learning methods. The training set and test set achieved high accuracy using the back propagation neural network (100% and 95%, respectively), and 99% and 95%, respectively, using the Fisher discriminant analysis. Compared to methods that involve expensive instruments and complex operations, this approach offers a rapid, cost-effective and reliable solution.