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ICP-MS分析鱼腥草不同部位中无机元素差异 被引量:9

Analysis of inorganic elements in different parts of Houttuynia cordata by ICP-MS
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摘要 目的:分析鱼腥草地上部分和根茎中无机元素差异。方法:采用微波消解处理鱼腥草样品,电感耦合等离子体质谱(ICP-MS)测定鱼腥草不同部位中Mg,K,Ca等27种无机元素含量,利用SIMCA-P 13.0软件对数据进行主成分分析和偏最小二乘判别分析。结果:27种元素线性关系良好,相关系数r≥0.9986;精密度和重复性实验的RSD≤6.0%;回收率在95.12%~109.48%,RSD≤6.0%。鱼腥草样品中Mg,K,Ca和Fe含量较高,主成分分析(PCA)可将地上部分和根茎明显区分为两组。结论:本方法简便、灵敏、快捷,可用于鱼腥草样品的测定,不同部位中无机元素存在一定差异。 Objective:To analyze the differences of inorganic elements in Houttuynia cordata aerial part and rhizome.Methods:The contents of 27 inorganic elements of Houttuynia cordata samples,such as Mg,K,and Ca,were analyzed by microwave digestion coupled with Inductively Coupled Plasma Mass Spectrometry(ICP-MS)method.The data of principal components and partial least squares discriminant analysis were analyzed with the SIMCA-P 13.0 software.Results:The 27 elements showed good linearities in the selected concentration ranges(r≥0.9986).The relative standard deviations(RSDs)of the precision and repeatability were less than 6.0%.The average recovery ranged from 95.12%to 109.48%,with RSD≤6.0%.Mg,K,Ca and Fe were the major inorganic elements of H.cordata.Principal component analysis(PCA)analysis significantly separated H.cordata aerial part and rhizome into two groups.Conclusion:The method with high sensitivity and good accuracy was simple and fast.There were some differences among the contents of inorganic elements in Houttuynia cordata aerial part and rhizome.
作者 陈宏降 罗益远 刘佳楠 姚鑫 薛平 CHEN Hong-jiang;LUO Yi-yuan;LIU Jia-nan;YAO Xin;XUE Ping(Zhejiang Pharmaceutical College,Ningbo 315100,China;Department of Pharmacy,the First Affiliated Hospital of Soochou)University,Suzhou 215006,China;Changzhou Institute for Food and Drug Control,Changzhou 213001,China)
出处 《中国新药杂志》 CAS CSCD 北大核心 2019年第22期2769-2775,共7页 Chinese Journal of New Drugs
基金 浙江省公益技术研究计划资助项目(LGF18H280005) 浙江省食品药品监管系统科技计划资助项目(2018017) 浙江省大学生科技创新活动计划暨新苗人才计划资助项目(2017R435006) 苏州市产业创新专项资助项目(SYSD2017149)
关键词 鱼腥草 电感耦合等离子体质谱法 无机元素 主成分分析 偏最小二乘判别分析 Houttuynia cordata ICP-MS inorganic elements principal component analysis PLS-DA
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