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  • Title: Prediction of Japanese green tea ranking by fourier transform near-infrared reflectance spectroscopy.
    Author: Ikeda T, Kanaya S, Yonetani T, Kobayashi A, Fukusaki E.
    Journal: J Agric Food Chem; 2007 Nov 28; 55(24):9908-12. PubMed ID: 17973445.
    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.
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