Application of machine learning algorithms in quality assurance of fermentation process of black tea-- based on electrical properties

Fermentation process directly determines the product quality of black tea. This work aimed to develop a rapid method for detecting the degree of fermentation of black tea based on electrical properties of tea leaves. An LCR meter employed to identify 11 electrical parameters of tea leaves during the...

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Bibliographic Details
Published in:	Journal of food engineering Vol. 263; pp. 165 - 172
Main Authors:	Zhu, Hongkai, Liu, Fei, Ye, Yang, Chen, Lin, Liu, Jingyuan, Gui, Anhui, Zhang, Jianqiang, Dong, Chunwang
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.12.2019
Subjects:	Black tea cluster analysis Electrical properties Fermentation flavanols high performance liquid chromatography leaves Machine learning algorithms neural networks principal component analysis product quality Quality components quality control Random forest rapid methods support vector machines ultraviolet-visible spectroscopy Machine learning algorithms Random forest Electrical properties Black tea Fermentation Quality components
ISSN:	0260-8774, 1873-5770
Online Access:	Get full text
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