Classifying the Variety, Production Area and Season of Taiwan Partially Fermented Tea by Near Infrared Spectroscopy
SHIH LUN LIU1, YUNG SHENG TSAI2 AND ANDI SHAU-MEI OU1,3*
1. Department of Food Science and Biotechnology, National Chung Hsing University,
250 KuoKuang Road, South District, Taichung 402, Taiwan, R.O.C.
2. Taiwan Tea Research and Extension Station, Council of Agriculture, Executive Yuan,
324 ChungHsing Road, Young-Mei, Taoyuan 326, Taiwan, R.O.C.
3. Graduate Institute of Food Science and Technology, Central Taiwan University of Science and Technology,
666 Buzih Road, Beitun District, Taichung 406, Taiwan, R.O.C.
(Received: May 7, 2009; Accepted: January 21, 2010)
ABSTRACT
The purpose of this study is to investigate the feasibility of discriminating the different varieties, production areas and seasons of Taiwan partially fermented tea by using Near Infrared Spectroscopy (NIRS). A total of 308 partially fermented tea samples with 6 different tea varieties, 6 production areas and 2 different production seasons were collected and analyzed. The principal component analysis (PCA) result of NIRS spectra data showed that the first three principal components could explain the sample variation up to 95.0%. The ability of classifying different production areas of tea samples by PCA was the best followed by tea varieties. The discriminant model further established by NIRS data with partial least square (PLS) could recognize and identify the varieties, production areas and seasons of tea samples up to 98.4% (299 of 305), 97.4% (296 of 304), and 100%, respectively. Using the established discriminant model, the tea samples with different varieties, production areas and seasons could be correctly predicted and identified at the levels of 96.3%, 94.1% and 99.2%, respectively.
Key words: partially fermented tea, discrimination, NIRS, PCA, PLS