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Original Research Article | OPEN ACCESS

Quality evaluation based on color grading - relationship between chemical substances and commercial grades by machine vision in Corni fructus

Yongxia Cui, Lili Wang, Liangliang Duan, Suiqing Chen

Henan University of Chinese Medicine, Zhengzhou, Henan, China, 450046;

For correspondence:-  Suiqing Chen   Email: suiqingchen0371@163.com   Tel:+8637165676686

Accepted: 21 June 2020        Published: 31 July 2020

Citation: Cui Y, Wang L, Duan L, Chen S. Quality evaluation based on color grading - relationship between chemical substances and commercial grades by machine vision in Corni fructus. Trop J Pharm Res 2020; 19(7):1495-1501 doi: 10.4314/tjpr.v19i7.23

© 2020 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..

Abstract

Purpose: To evaluate the correlation between the commercial grade of Corni fructus determined by machine vision technology, and its chemical composition.
Methods: Loganin, morroniside, ursolic acid, water-soluble extractives, alcohol-soluble extractives, polysaccharides and total organic acids were quantitated in four Corni fructus grades classified by machine vision technology. The content of each component was determined and analyzed by mathematical statistics.
Results: Compared with low-grade samples, higher-grade counterparts contained elevated concentrations of alcohol-soluble extractives, water-soluble extractives, loganin and morroniside. In addition, principal component analysis revealed a correlation coefficient of -0.723 between Corni fructus grade and Holistic Scoring based on chemical composition, indicating a significant correlation (p < 0.01).
Conclusion: These findings indicated the rationality of the classification method based on machine vision, and further confirmed the notion of "quality evaluation based on color" of traditional Chinese medicine.

Keywords: Corni fructus, Commercial grade, Machine vision technology, Chemical substance

Impact Factor
Thompson Reuters (ISI): 0.6 (2023)
H-5 index (Google Scholar): 49 (2023)

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