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Journal of Analytical Methods in Chemistry
Volume 2014, Article ID 704971, 6 pages
Research Article

Rapid Discrimination of the Geographical Origins of an Oolong Tea (Anxi-Tieguanyin) by Near-Infrared Spectroscopy and Partial Least Squares Discriminant Analysis

1Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Sciences, China Jiliang University, Hangzhou, Zhejiang 310018, China
2China National Institute of Standardization, Beijing 100191, China

Received 13 April 2014; Revised 26 May 2014; Accepted 9 June 2014; Published 26 June 2014

Academic Editor: Chih-Ching Huang

Copyright © 2014 Si-Min Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper focuses on a rapid and nondestructive way to discriminate the geographical origin of Anxi-Tieguanyin tea by near-infrared (NIR) spectroscopy and chemometrics. 450 representative samples were collected from Anxi County, the original producing area of Tieguanyin tea, and another 120 Tieguanyin samples with similar appearance were collected from unprotected producing areas in China. All these samples were measured by NIR. The Stahel-Donoho estimates (SDE) outlyingness diagnosis was used to remove the outliers. Partial least squares discriminant analysis (PLSDA) was performed to develop a classification model and predict the authenticity of unknown objects. To improve the sensitivity and specificity of classification, the raw data was preprocessed to reduce unwanted spectral variations by standard normal variate (SNV) transformation, taking second-order derivatives (D2) spectra, and smoothing. As the best model, the sensitivity and specificity reached 0.931 and 1.000 with SNV spectra. Combination of NIR spectrometry and statistical model selection can provide an effective and rapid method to discriminate the geographical producing area of Anxi-Tieguanyin.