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Publishing Language: Chinese | Open Access

Grade Identification of Huangjincha Tea 2 by Aroma Fingerprinting Combined with Multivariate Chemometric Analysis

Jin CHAO1,2 , Lingxin ZHOU2, Feiyan YIN2, Qian LUO2, Mengmeng ZHAO2, Yong YUAN2, Haoren WU2, Pao LI1, Liwen JIANG1 ( )
College of Food Science and Technology, Hunan Agricultural University, Changsha 410128, China
National R&D Center for Tea Processing, Hunan Research Center of Tea Plantation and Processing Technology, Hunan Tea Group Co. Ltd., Changsha 410126, China
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Abstract

The aroma components of two grades of Huangjincha tea 2 were investigated by using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) to establish their aroma fingerprints. The results were analyzed using chemometrics. Totally 81 aroma components were identified, 41 of which were common to both. Based on these common aroma components, the two grades could be discriminated by orthogonal partial least squares-discrimination analysis (OPLS-DA), and nine differential aroma components between them were identified including heptanal, limonene, trans-β-ocimene, 1-octanol, (E)-4,8-dimethylnona-1,3,7-triene, trans-nerolidol, 1,10-diepicubenol, epicubenol, and methyl hexadecanoate. A linear discriminant model to distinguish the two grades was established using the differential aroma components as independent variables. The self-validation and cross-validation accuracy of this model were 100%. These results may provide an objective and quantitative reference for the classification of Huangjincha 2.

CLC number: TS207.3; S571.1 Document code: A Article ID: 1002-6630(2023)04-0321-08

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Food Science
Pages 321-328

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Cite this article:
CHAO J, ZHOU L, YIN F, et al. Grade Identification of Huangjincha Tea 2 by Aroma Fingerprinting Combined with Multivariate Chemometric Analysis. Food Science, 2023, 44(4): 321-328. https://doi.org/10.7506/spkx1002-6630-20211202-019

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Received: 02 December 2021
Published: 25 February 2023
© Beijing Academy of Food Sciences 2023.

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