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

文献类型： 外文期刊

第一作者： Zong, Wanli

作者： Zong, Wanli;Zhao, Shanshan;Li, Yalan;Yang, Xiaoting;Qie, Mengjie;Zhao, Yan;Zong, Wanli;Zhang, Ping

作者机构：

关键词： Tibetan Yak meat; Principal component analysis; Back propagation neural network; Mid-infrared spectroscopy; Fisher discriminant analysis; Origin traceability; Quality control; Machine learning

期刊名称：JOURNAL OF CONSUMER PROTECTION AND FOOD SAFETY （ 影响因子：1.7； 五年影响因子：2.0 ）

ISSN： 1661-5751

年卷期： 2025 年

页码：

收录情况： SCI

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.

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