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Publishing Language: Chinese | Open Access

Non-targeted Metabolomics Based on Ultra-high Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry for Discrimination of Three Jiangxi Famous Teas

State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
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Abstract

A non-targeted metabolomics method for identifying the quality of Gougunao tea, Lu Mountain Clouds-Mist tea, and Wuyuan green tea was established by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). The original data were screened by MassHunter Mass Profile, and 220 characteristic differential metabolites were obtained. The results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that there was a clear discrimination among the three teas. Partial least squares discriminant analysis (PLS-DA) was used to establish a prediction model for identifying the quality of tea with an accuracy of 100%. Meanwhile, of the 220 characteristic differential metabolites, 22 were identified, mainly including flavonoids, glycoside derivatives and organic acids. Through heatmap analysis, it was found that their contents were significantly different among tea samples. This study is meaningful for guiding tea quality identification, which can be widely used in food analysis and characterization.

CLC number: TS207.3 Document code: A Article ID: 1002-6630(2022)02-0316-08

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Food Science
Pages 316-323

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Cite this article:
XU C, WANG Y. Non-targeted Metabolomics Based on Ultra-high Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry for Discrimination of Three Jiangxi Famous Teas. Food Science, 2022, 43(2): 316-323. https://doi.org/10.7506/spkx1002-6630-20210105-042

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Received: 05 January 2021
Published: 25 January 2022
© Beijing Academy of Food Sciences 2022.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).