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 ![]() | Item type: | Article |
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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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