中国中药杂志

2021, v.46(15) 3753-3763

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基于粉体特征物理性质的中药饮片分类研究
Material classification of decoction pieces based on physical properties of powder

陈恒晋;杨光;赵立杰;沈岚;张磊;林晓;洪燕龙;
CHEN Heng-jin;YANG Guang;ZHAO Li-jie;SHEN Lan;ZHANG Lei;LIN Xiao;HONG Yan-long;Health Service Collaborative Innovation Center of Shanghai Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine;Engineering Research Center of Modern Preparation Technology of Traditional Chinese Medicine, Ministry of Education, Shanghai University of Traditional Chinese Medicine;College of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine;

摘要(Abstract):

中药因其药用部位和富含成分的不同,其粉体表现出明显的显微鉴别特征和特定的物理属性。以此为基础,将常用中药分为粉性料、纤维料、糖性料、油性料、脆性料等类别,对中药临方制剂技术的研发具有重要意义。但是目前现有的分类方法主观性较强,难以满足高质量中药临方制剂技术开发的需求。该文选择山药、益母草等代表性中药55味,采用粉体综合性质测定仪、转矩流变仪、物性测定仪等,对其粉体的物理属性进行系统表征,构建了代表性中药粉体的物理性质数据集,并进行多元统计分析,绘制了粉性料、纤维料、糖性料、油性料、脆性料等各类物料的典型物理指纹图谱。在此基础上通过计算主成分得分图中各中药与典型值间的欧氏距离对其进行分类。此外,对于部分因兼有多重物料性质导致分类界限模糊的中药,以欧氏距离为基础,并结合粉体性状、显微鉴别特征及化学成分组成,计算不同类别物料在整体中的占比,从而实现基于粉体特征物理性质的中药的多元定量分类,为进一步构建中药临方智能化制剂技术奠定基础。
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.

关键词(KeyWords): 中药临方制剂;中药饮片分类;物理指纹图谱;转矩流变性;粉体物理性质
personalized traditional Chinese medicine preparations;classification of decoction pieces;physical fingerprint;torque rheology;physical properties of powder

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(81973490);; 上海市自然科学基金项目(18ZR1436600,19ZR1457700,18ZR1439800);; 上海市“科技创新行动计划”技术标准项目(20DZ2200900);; 上海市卫计委中医药事业发展三年行动计划项目[ZY(2018-2020)-CCCX-2001-03];; 2021年度上海市协同创新中心建设项目(2021科技01-01-30)

作者(Authors): 陈恒晋;杨光;赵立杰;沈岚;张磊;林晓;洪燕龙;
CHEN Heng-jin;YANG Guang;ZHAO Li-jie;SHEN Lan;ZHANG Lei;LIN Xiao;HONG Yan-long;Health Service Collaborative Innovation Center of Shanghai Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine;Engineering Research Center of Modern Preparation Technology of Traditional Chinese Medicine, Ministry of Education, Shanghai University of Traditional Chinese Medicine;College of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine;

DOI: 10.19540/j.cnki.cjcmm.20210310.303

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