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Publishing Language: Chinese | Open Access

Optimization of an Automatic Thermal Desorption-Gas Chromatography-Mass Spectrometry Detection Method for Oolong Tea and Analysis of Aroma Components in Different Grades of Rougui Oolong Tea

Wanjun BI Yucheng ZHENGZhenzhang LIUBin CHENHuili DENGQingcai HUYun SUN ( )
College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 530002, China
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Abstract

An automatic thermal desorption-gas chromatography-mass spectrometry (ATD-GC-MS) method was developed, optimized and applied in combination with chemometrics for the detection of the aroma components of three different grades (superfine, grade A and grade B) of Rougui oolong tea. In automatic thermal desorption, the operating parameters adsorption temperature, adsorption time and cold trap temperature were optimized by single factor experiments and response surface methodology. The optimal parameters were determined as follows: adsorption temperature of 55 ℃, adsorption time of 37 min and cold trap temperature of -29 ℃. A total of 173 aroma components were identified, 90 of which were common to all the three grades. In addition, a partial least squares discriminant analysis (PLS-DA) model to distinguish the different grades of Rougui oolong tea was established based on the peak areas of the aroma components of Rougui oolong tea. and the distribution of 47 characteristic aroma components in the three different grades of Rougui oolong tea was discussed by hierarchical cluster analysis. The results of this study could provide a theoretical basis for the identification of the aroma quality and grade of Rougui oolong tea.

CLC number: TS272.7 Document code: A Article ID: 1002-6630(2022)12-0243-09

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Food Science
Pages 243-251

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Cite this article:
BI W, ZHENG Y, LIU Z, et al. Optimization of an Automatic Thermal Desorption-Gas Chromatography-Mass Spectrometry Detection Method for Oolong Tea and Analysis of Aroma Components in Different Grades of Rougui Oolong Tea. Food Science, 2022, 43(12): 243-251. https://doi.org/10.7506/spkx1002-6630-20210729-344

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Received: 29 July 2021
Published: 25 June 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/).