用近红外高光谱成像技术对绿茶进行分类

NIR News Pub Date : 2020-03-01 DOI:10.1177/0960336019889321
P. Mishra, A. Nordon
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引用次数: 2

摘要

茶叶产品分析目前仅限于高效液相色谱、气相色谱、同位素分析等高端分析技术。然而,这些技术耗时、昂贵、具有破坏性,并且需要训练有素的专家来进行实验。在本工作中,展示了近红外高光谱成像在相似外观绿茶产品分类中的应用。利用支持向量机分类器对茶叶产品进行原产地分类。结果表明,该方法对7个不同原产国的绿茶产品进行分类,准确率为96.36±0.17%。
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Classifying green teas with near infrared hyperspectral imaging
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.
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Selected References DIARY Diary Meeting of the International Association of Spectral Imaging (IASIM-2024) Selected References
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