WANG Shibo, NING Hongxin, HUANG Longyue, et al. HPLC Fingerprints of White Tea Based on Cluster Analysis[J]. Science and Technology of Food Industry, 2021, 42(16): 255−262. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020100150.
Citation: WANG Shibo, NING Hongxin, HUANG Longyue, et al. HPLC Fingerprints of White Tea Based on Cluster Analysis[J]. Science and Technology of Food Industry, 2021, 42(16): 255−262. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2020100150.

HPLC Fingerprints of White Tea Based on Cluster Analysis

  • The catechins and alkaloids in white tea samples were analyzed by high performance liquid chromatography (HPLC), and the characteristic fingerprint of white tea was established to provide reference for the quality evaluation of white tea. Taking many kinds of white tea from Fuding, Zhenghe and other places as samples, through the selection of extraction solvent, mobile phase, wavelength, flow rate and column temperature, the HPLC conditions of white tea fingerprint were determined as follows: 70% methanol, extracted at 70 ℃, the chromatographic column was Agilent Eclipse Plus C18 (4.6 mm×250 mm, 5 μm), the gradient elution was carried out with acetonitrile −0.5% acetic acid as the mobile phase, the detection wavelength was 258 nm, the column temperature was 35 ℃, and the injection volume was 10 μL. Caffeine as a reference peak, the relative retention time and relative peak area of the common peak were calculated. The similarity evaluation system of chromatographic fingerprint of traditional Chinese medicine(version 2012) was selected to evaluate the similarity, and the systematic cluster analysis method (HCA) was used for cluster analysis.The fingerprint of white tea was established, and 28 common peaks were identified in the fingerprint. The similarity evaluation results showed that the similarity of 12 different varieties of white tea was above 0.98, which indicated that the composition of white tea samples from different years and different habitats were consistent. Gallic acid (GA), caffeine (CAF), epicatechin (EC), epigallocatechin gallate (ECG), epigallocatechin gallate (EGCG) and epigallocatechin (EGC) were identified by peak identification. The results of hierarchical cluster analysis showed that the storage time had a certain effect on the composition and content of white tea, and these white tea samples were divided into two categories: 2013, 2014 and 2017~2020. The method was convenient, fast, simple, accurate and reliable. It could provide a reliable evaluation method for quality control of white tea.
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