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Appl. Sci. 2017, 7(2), 172;

Accurate Determination of Geographical Origin of Tea Based on Terahertz Spectroscopy

College of Instrumentation & Electrical Engineering, Jilin University, Jilin 130061, China
Chongqing Key Laboratory of Multi-Scale Manufacturing Technology, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Research Center for Terahertz Technology, Chongqing 400714, China
Author to whom correspondence should be addressed.
Received: 25 November 2016 / Revised: 30 January 2017 / Accepted: 6 February 2017 / Published: 10 February 2017
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This paper proposes a structured model for the identification of green tea, as well as tracing its geographical origins. Considering that the features of different types of green tea are similar under THz time-domain spectroscopy, we designed a program to perform principal component analysis (PCA) of the spectroscopic data of various green tea samples and to determine the data sequences of principal components. We then established a training set for the principal components to train a support vector machine (SVM) model via a genetic algorithm (GA). We used this model to optimize the parameters and develop a GA-based SVM model with an identification rate of 96.25% for the tested samples. Taken together, our results confirm that THz time-domain spectroscopy combined with GA-SVM can be effectively applied to rapidly identify types of green tea with different geographical origins. View Full-Text
Keywords: THz; SVM; principal component analysis; genetic algorithm; green tea THz; SVM; principal component analysis; genetic algorithm; green tea

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Li, M.; Dai, G.; Chang, T.; Shi, C.; Wei, D.; Du, C.; Cui, H.-L. Accurate Determination of Geographical Origin of Tea Based on Terahertz Spectroscopy. Appl. Sci. 2017, 7, 172.

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