Prediction of Japanese green tea ranking by fourier transform near-infrared reflectance spectroscopy

J Agric Food Chem. 2007 Nov 28;55(24):9908-12. doi: 10.1021/jf0717642. Epub 2007 Nov 1.

Abstract

A rapid and easy determination method of green tea's quality was developed by using Fourier transform near-infrared (FT-NIR) reflectance spectroscopy and metabolomics techniques. The method is applied to an online measurement and an online prediction of green tea's quality. FT-NIR was employed to measure green tea metabolites' alteration affected by green tea varieties and manufacturing processes. A set of ranked green tea samples from a Japanese commercial tea contest was analyzed to create a reliable quality-prediction model. As multivariate analyses, principal component analysis (PCA) and partial least-squares projections to latent structures (PLS) were used. It was indicated that the wavenumber region from 5500 to 5200 cm(-1) had high correlation with the quality of the tea. In this study, a reliable quality-prediction model of green tea has been achieved.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Multivariate Analysis
  • Predictive Value of Tests
  • Principal Component Analysis
  • Quality Control*
  • Sensitivity and Specificity
  • Spectroscopy, Fourier Transform Infrared / methods*
  • Tea / chemistry*
  • Tea / standards*

Substances

  • Tea