Literature DB >> 32846565

Monitoring the authenticity of pu'er tea via chemometric analysis of multielements and stable isotopes.

Hong-Lin Liu1, Yi-Tao Zeng2, Xin Zhao3, Yu-Long Ye4, Bei Wang5, Hua-Rong Tong6.   

Abstract

Mineral elements and stable isotopes combined with stoichiometric methods were used as a potential tool for first authenticating Chinese tea according to it's production year. A total of 86 mineral elements and stable isotope compositions were determined from the Xiangzhujing Pu'er tea in five different production years using ICP-MS and ICP-OES. On the basis of 78 statistically significant mineral elements and stable isotopes, HCA, PCA, PLS-DA, BP-ANN, and LDA were employed to build authentication models for predicting the Pu'er tea with different production years. The clustering results of the HCA and PCA were worse than that of PLS-DA, BP-ANN, and LDA. The PLS-DA model displayed a perfect model performance (R2X = 0.86, R2Y = 0.974, and Q2 = 0.922). The authentication performance of LDA and BP-ANN revealed their 100% recognition sensitivity and prediction ability and was thus better than that of PLS-DA. Mn, 68Zn, and 203Tl were the markers for enabling the successful authentication of Pu'er tea with different production years. This study contributes toward generalizing the use of mineral element and stable isotope fingerprinting combined with LDA and BP-ANN as a promising tool for authentication of tea worldwide.
Copyright © 2020. Published by Elsevier Ltd.

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Keywords:  Chemometrics; ICP-MS; ICP-OES; Multi-element and stable isotope fingerprinting; Production year; Pu'er tea; Quality control

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Year:  2020        PMID: 32846565     DOI: 10.1016/j.foodres.2020.109483

Source DB:  PubMed          Journal:  Food Res Int        ISSN: 0963-9969            Impact factor:   6.475


  2 in total

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Authors:  Jian Zhang; Ruidong Yang; Yuncong C Li; Xinran Ni
Journal:  Biol Trace Elem Res       Date:  2021-01-06       Impact factor: 3.738

2.  The specific DNA barcodes based on chloroplast genes for species identification of Theaceae plants.

Authors:  Shuai Jiang; Fenglin Chen; Pai Qin; Hai Xie; Guo Peng; Yongliang Li; Xinhong Guo
Journal:  Physiol Mol Biol Plants       Date:  2022-04-19
  2 in total

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