中国现代中药2024，Vol.26Issue(4)：625-634,10.DOI:10.13313/j.issn.1673-4890.20231016005
我国47种中药材中重金属含量分析与数据挖掘
Heavy Metals in 47 Chinese Medicinal Materials:A Data Mining
摘要
Abstract
Objective:To analyze the enrichment characteristics of heavy metals in Chinese medicinal materials and predict their contents in different parts of the medicinal plants,to provide a basis for further analyzing the enrichment mechanism of heavy metals in Chinese medicinal materials and formulating relevant standards.Methods:Forty-seven Chinese medicinal materials were screened out from 238 articles published from 1998 to 2023.Data pre-processing,univariate analysis and multivariate analysis were carried out using R language and Python software to mine the data of five heavy metals.The contents of lead(Pb),mercury(Hg),arsenic(As)and cadmium(Cd)were assessed according to the Traditional Chinese Medicine Determination of Heavy Metals in Herbal Medicines Used in Traditional Chinese Medicine in the International Organization for Standardization(ISO),and the content of copper(Cu)was assessed with reference to the Green Standards of Medicinal Plants and Preparations for Foreign Trade and Economy.Random forest regression was used to predict the contents of the five heavy metals in different parts of the medicinal plants.Results:The contents of heavy metals in the 47 Chinese medicinal materials were in the order of Cu>Pb>Hg>As>Cd,and the exceedance rate was sequenced as Cu>Cd>Hg>As>Pb.Heavy metals were more observed in herbs with dry aboveground part,sclerotium,fruit spike and bark.Except for Beijing,Chongqing,Guangxi,Heilongjiang,Jilin,Liaoning and Xinjiang,where no exceedance of heavy metals has been found,the phenomenon of exceedance of heavy metals in Chinese herbal medicines exists in all other regions of the country.The random forest regression model showed high accuracy in predicting the levels of cadmium,mercury and arsenic in different entry sites.Conclusion:Heavy metal pollution in Chinese medicinal materials poses potential risks to the development of traditional Chinese medicine industry,and it is necessary to strengthen the research on the enrichment mechanism of heavy metals in Chinese medicinal materials.Machine learning showed good application potential in the analysis of heavy metals by data mining in Chinese medicinal materials,providing new ideas for future research on the enrichment mechanism of heavy metals in Chinese medicinal materials.关键词
中药材/重金属/统计分析/数据挖掘/机器学习Key words
Chinese medicinal materials/heavy metals/statistic analysis/data mining/machine learning分类
医药卫生引用本文复制引用
杨乾巍,杨迪,张良,杜光映,张明星,何愿子,唐桐桐,赵雅秋..我国47种中药材中重金属含量分析与数据挖掘[J].中国现代中药,2024,26(4):625-634,10.基金项目
国家自然科学基金项目(82160717) （82160717）
贵州省科技计划项目(黔科合支撑[2020]4Y073号) （黔科合支撑[2020]4Y073号）
中央级公益性科研院所基本科研业务费专项(ZZXT202202) （ZZXT202202）
