Geographical traceability of Chinese green tea using stable isotope and multi-element chemometrics.

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2019
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Abstract
Deliberate and fraudulent origin mislabeling of Chinese green tea motivated by large price differences often brings significant food safety risks and damages consumer trust. Currently, there is no reliable method to verify the origin of green tea produced in China. Stable isotope and multi-element analyses combined with statistical models are widely acknowledged as useful traceability techniques for many agro-products, and could be developed to confirm the geographical origin of Chinese green tea and, more importantly, combat illegal green tea mislabeling and fraud.An analytical strategy combining elemental analyzer/isotope ratio mass spectrometry (EA/IRMS) and inductively plasma coupled mass spectrometry (ICP-MS) with chemometrics tools was used to confirm the origin of green tea grown in the main tea production provinces around China. Stable C, N, H, O isotope ratios and twenty elements were measured to build mathematical discriminant models using unsupervised principal component analysis (PCA) and supervised linear discriminant analysis (LDA). Two main problems: (i) tracing the origin of Chinese green tea from different tea growing provinces (Zhejiang, Shandong, and other provinces); (ii) authentication of high-value Westlake Longjing tea from the Westlake region and surrounding areas in Zhejiang province, were investigated and assessed.The results demonstrated that PCA and follow-up LDA based on stable isotope and multi-element signatures can verify the geographical origin of Chinese green tea from different provinces, and even localized zones in the same province could be distinguishable, with discrimination accuracies higher than 92.3% and 87.8%, respectively.Geochemical fingerprinting techniques coupled with chemometric tools offer an accurate and effective verification method for the geographical origin of Chinese green tea, providing a promising tool to combat fraudulent mislabeling of high-value green tea.
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liu2019geographicalrapid Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Liu, Zhi;Yuan, Yuwei;Zhang, Yongzhi;Shi, Yuanzhi;Hu, Guixian;Zhu, Jiahong;Rogers, Karyne M;
Journal Rapid communications in mass spectrometry : RCM
Year 2019
DOI
10.1002/rcm.8405
URL
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