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矿物药禹余粮微波消解/ICP-AES无机元素分析及综合评价 被引量:15

Evaluation and Analysis of Inorganic Elements in Mineral Chinese Medicine Limonitum by ICP-AES after Microwave Digestion
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摘要 目的:测定不同产地禹余粮药材中无机元素的含量并进行综合分析评价。方法:采用微波消解/ICPAES及主成分分析法对禹余粮药材所含元素进行分析和产地综合评价,同时对各元素进行相关性分析及无机元素指纹图谱分析。结果:检测的21种元素中,Fe、Al、Ca、K、Mg、Mn含量较高,重金属Hg、Pb、Cd、Cu均有检出,有害元素As、微量元素Se未检出。建立了含13种无机元素的特征指纹图谱,均数相似度(夹角余弦值)、中位数相似度(夹角余弦值)均大于0.90。元素相关性分析表明,14对元素显著正相关,2对元素显著负相关(P<0.01),10对元素正相关,6对元素负相关(P<0.05)。主成分分析选择了5个因子,从无机元素的角度对禹余粮质量和产地进行了综合评价,结果表明江苏宿迁、建湖产禹余粮质量较好。结论:本研究为禹余粮药材的质量控制标准的制定提供了基础数据,并为矿物类药材的研究提供了研究方法和思路。 Objective: To determine and analyze the inorganic elements in Limonitum by ICP-AES after microwave digestion. Methods: Inorganic elements fingerprints were researched. Principal components and elements correlations were analyzed with the SPSS16. 0 software. Results: The result showed that elements Fe,Al,Ca,K,Mg and Mn were the major elements in twenty one inorganic elements determined. Hg、Pb、Cd、Cu were detected in all samples,Se and As were not detected. Thirteen elements were selected to establish fingerprint for describing and identifying the quality of Limonitum samples. And similarity( angle cosine value) were all more than 0. 90. The result showed that fourteen pairs of elements were significant positive correlated,two pairs of elements were significant negative correlated( P 〈 0. 01). There were ten pairs of elements were positive correlated,six pairs of elements were negative correlated( P 〈 0. 05). The PCA with five factors selected could be used to evaluate the quality of Limonitum and the origin places were selected. Conclution: The result showes some correlations among the inorganic elements. The presented research would have guiding significance to study other mineral medicines.
出处 《中国现代中药》 CAS 2015年第9期899-904,共6页 Modern Chinese Medicine
基金 <中华人民共和国药典>2015版一部标准研究课题 江苏省高校优势学科建设工程资助项目(二期) 江苏高校品牌专业建设工程资助项目(PPZY2015A070) 国家自然科学基金项目(81303178) 江苏省自然基金项目(BK20130957)
关键词 矿物药 禹余粮 电感耦合等离子-原子发射光谱法 无机元素 指纹图谱 主成分分析 Mineral Chinese Medicine Limonitum ICP-AES inorganic elements fingerprints PCA
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