Article Sidebar
Published:
Nov 18, 2020Keywords:
Article Details
Submission of a manuscript to this journal is a representation that the manuscript has not been published previously and is not under consideration for publication elsewhere.
All authors named in each manuscript would be required to sign a form (to be supplied by the Editor) so that they may retain their copyright in the article but to assign to us (the Publishers) and its licensees in perpetuity, in all forms, formats and media (whether known or created in the future) to (i) publish, reproduce, distribute, display and store the contribution, (ii) translate the contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or abstracts of the contribution, (iii) create any other derivative works(s) based on the contribution, (iv) to exploit all subsidiary rights in the contribution, (v) the inclusion of electronic links from the contribution to third party material where-ever it may be located, and (vi) license any thrid party to do any or all of the above.
Main Article Content
Quality evaluation based on color grading - relationship between chemical susbtances and commercial grades by machine version in Corni fructus
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
