Material classification of decoction pieces based on physical properties of powder.
10.19540/j.cnki.cjcmm.20210310.303
- Author:
Heng-Jin CHEN
1
;
Guang YANG
1
;
Li-Jie ZHAO
2
;
Lan SHEN
3
;
Lei ZHANG
1
;
Xiao LIN
3
;
Yan-Long HONG
1
Author Information
1. Health Service Collaborative Innovation Center of Shanghai Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine Shanghai 201203, China.
2. Engineering Research Center of Modern Preparation Technology of Traditional Chinese Medicine, Ministry of Education, Shanghai University of Traditional Chinese Medicine Shanghai 201203, China.
3. College of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine Shanghai 201203, China.
- Publication Type:Journal Article
- Keywords:
classification of decoction pieces;
personalized traditional Chinese medicine preparations;
physical fingerprint;
physical properties of powder;
torque rheology
- MeSH:
Drugs, Chinese Herbal;
Medicine, Chinese Traditional;
Powders;
Rhizome
- From:
China Journal of Chinese Materia Medica
2021;46(15):3753-3763
- CountryChina
- Language:Chinese
-
Abstract:
Chinese medicinals feature different medicinal parts and enriched components, which makes their powders show obvious microscopic identification characteristics and specific physical properties. On this basis, the commonly used Chinese medicinals can be divided into several categories, such as powdery, fibrous, sugar, oil, and brittle materials, which is of great importance to the research and development of personalized Chinese medicinal preparation technology. However, the existing classification methods are highly subjective and thus difficult to meet the requirements for the development of personalized Chinese medicinal preparations with high quality. In this study, 55 representative Chinese medicinals, such as Dioscoreae Rhizoma and Leonuri Herba, were selected, and the physical properties of their powders were systematically characterized by comprehensive powder tester, torque rheometer, texture analyzer, etc., based on which a data set encompassing physical properties of these powders was built. The typical physical fingerprints of powders from the above 5 categories were established by multivariate statistical analysis. Then, the Chinese medicinals were classified according to the Euclidean distance between each of them and the typical value in the PCA score plot. For those with multiple material properties, whose classification boundary was fuzzy, the proportions of different types of materials were calculated with the combination of Euclidean distance, powder properties, microscopic identification characteristics, and chemical composition, so as to achieve the multivariate quantitative classification of Chinese medicinals. This lays the foundation for the further creation of intelligent personalized Chinese medicinal preparation technology.
