Prediction of Japanese Green Tea Ranking by Gas Chromatography/Mass Spectrometry-Based Hydrophilic Metabolite Fingerprinting

Wipawee Pongsuwan,†‡ Eiichiro Fukusaki,*† Takeshi Bamba,† Tsutomu Yonetani,§ Toshiyaki Yamahara,§ and Akio Kobayashi†
Department of Biotechnology, Graduate School of Engineering, Osaka University, Japan, and Tea branch, Nara Prefecture Agricultural Experiment Station, Japan
J. Agric. Food Chem., 2007, 55 (2), pp 231–236
DOI: 10.1021/jf062330u
Publication Date (Web): December 20, 2006
Copyright © 2007 American Chemical Society
†

 Osaka University.

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‡

 The study represents a portion of the dissertation submitted by W.P. to Osaka University in partial fulfillment of the requirements for her Ph.D. degree.

,
*

 Author to whom correspondence should be addressed. Tel/Fax:  +81-6-6879-7424. E-mail:  fukusaki@bio.eng.osaka-u.ac.jp.

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§

 Nara Prefecture Agricultural Experiment Station.

Abstract

An innovative technique for green tea's quality determination was developed by means of metabolomics. Gas-chromatography coupled with time-of-flight mass spectrometry and multivariate data analysis was employed to evaluate the quality of green tea. Alteration of green tea varieties and manufacturing processes effects a variation in green tea metabolites, which leads to a classification of the green tea's grade. Therefore, metabolic fingerprinting of green tea samples of different qualities was studied. A set of ranked green tea samples from a Japanese commercial tea contest was analyzed with the aim of creating a reliable quality-prediction model. Several multivariate algorithms were performed. Among those, the partial least-squares projections to latent structures (PLS) analysis with the spectral filtering technique, orthogonal signal correction (OCS), was found to be the most practical approach. In addition, metabolites that play an important role in green tea's grade classification were identified.

Keywords: Metabolomics; metabolic fingerprinting; GC-TOF/MS; quality evaluation; PLS

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History

  • Published In Issue January 24, 2007
  • Received for review August 12, 2006. Revised manuscript received October 21, 2006. Accepted November 12, 2006.

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