Classifying green teas with near infrared hyperspectral imaging

Mishra, Puneet and Nordon, Alison (2019) Classifying green teas with near infrared hyperspectral imaging. NIR News. ISSN 0960-3360

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    Abstract

    Tea products analysis is currently limited to high-end analytical techniques such as high-performance liquid chromatography, gas chromatography and isotope analysis. However, these techniques are time-consuming, expensive, destructive and require trained experts to perform the experiments. In the present work, an application of near infrared hyperspectral imaging for the classification of similarly appearing green tea products is demonstrated. The tea products were classified based on their origin utilising a support vector machine classifier. Results showed good accuracy (96.36 ± 0.17%) for the classification of green tea products from seven different countries of origin.

    Creators(s): Mishra, Puneet and Nordon, Alison ORCID logoORCID: https://orcid.org/0000-0001-6553-8993;
    Item type:Article
    ID code:71185
    Keywords:quality, non-destructive, origin, multivariate, Chemistry, Spectroscopy
    Subjects:Science > Chemistry
    Department:Faculty of Science > Pure and Applied Chemistry
    Strategic Research Themes > Advanced Manufacturing and Materials
    Strategic Research Themes > Measurement Science and Enabling Technologies
    Depositing user: Pure Administrator
    Date deposited:23 Jan 2020 15:35
    Last modified:21 Jan 2021 11:35
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/71185
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