基于EGCG,ECG和咖啡碱含量的乌龙茶产地鉴定

doi:10.13305/j.cnki.jts.2018.03.003

Abstract

Abstract: A quantitative method to discriminate the geographical origins of Oolong teas was proposed to promote the fair of tea trade. A total of 130 Oolong tea samples were collected across China, and the chemical compositions including gallic acid, catechins, caffeine and theanine were quantified by high performance liquid chromatography. Genetic algorithm and successive projections algorithm were applied to identify important compounds, and then support vector machine, back propagation artificial neural networks and random forest models were used to classify and predict Oolong tea samples from Minnan, Minbei, Guangdong and Taiwan based on the selected compounds. The overall results indicated that compounds selected by genetic algorithm (caffeine, EGCG and ECG) combined with back propagation artificial neural networks could achieve a high efficiency in identifying Oolong tea samples from four origins, and the total identification rate in the training and prediction sets were 97.13% and 98.34%. The results provided scientific credibility to identify Oolong tea origins.

Key words: Oolong tea, geographical origins, identification, chemical compositions

CLC Number:

CAO Qiong, SU Huan, WAN Xiaochun, NING Jingming. Identification of the Geographical Origins of Oolong Tea Based on EGCG, ECG and Caffeine Contents[J]. Journal of Tea Science, 2018, 38(3): 237-243.

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Identification of the Geographical Origins of Oolong Tea Based on EGCG, ECG and Caffeine Contents

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