Projects per year
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.
Original language | English |
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Number of pages | 4 |
Journal | NIR News |
Early online date | 21 Nov 2019 |
DOIs | |
Publication status | E-pub ahead of print - 21 Nov 2019 |
Keywords
- quality
- non-destructive
- origin
- multivariate
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Dive into the research topics of 'Classifying green teas with near infrared hyperspectral imaging'. Together they form a unique fingerprint.Projects
- 1 Finished
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Modlife (H2020 MCSA ETN)
Nordon, A. (Principal Investigator)
European Commission - Horizon Europe + H2020
1/11/15 → 31/10/19
Project: Research