摘要
目的:探讨野菊花中无机元素的特征,从元素组学的角度为野菊花药材建立无机元素的特征图谱提供理论支持。方法:采用电感耦合等离子体发射光谱法(ICP-AES)测定了不同产地野菊花中硼(B),钠(Na),镁(Mg),磷(P),钾(K),钙(Ca),锰(Mn),铁(Fe),铜(Cu),锌(Zn),锶(Sr),硒(Se),钡(Ba)和铅(Pb)共14种元素的含量,应用相关性和主成分分析法对测定结果进行了研究。结果:不同产地野菊花中无机元素的含量呈现相似的元素谱排列,表现为上下起伏的波浪状分布,不同产地的野菊花中各元素的绝对含量存在显著差异;部分元素间存在相关性;经过主成分分析得出4个主因子,其累计方差贡献率达84.437%,第一、二主因子的方差贡献率为60.09%,故所对应的P,K,Ca,Mn,Fe,Cu,Sr,B,Na和Se是野菊花的特征元素。结论:野菊花中元素含量呈现特征性上下起伏的波动折线元素谱,各产地野菊花中元素的绝对含量呈现显著差异,云南昆明和湖南株洲野菊花中元素含量较其他产地高。
Objective: To explore the character of inorganic elements in Flos Chrysanthemi indici and look for relationship between the element concentration and regions.Method: The contents of elements,including borum(B),sodium(Na),magnesium(Mg),phosphorus(P),potassium(K),calcium(Ca),manganese(Mn),iron(Fe),copper(Cu),zinc(Zn),strontium(Sr),cesium(Se),barium(Ba) and lead(Pb) in Chinese traditional herb Flos Chrysanthemi indici from different regions were determined by ICP-AES.The element distrubution diagram were plotted.The principal component analysis and correlation analysis of SPSS were applied for the study of characteristic elements.Result: Similar curves of element concentration have been acquired.It is observed that the content of elements in the samples shows regional diversity.There are 15 correlative element pairs in correlation analysis.Four principal components which accounted for over 84.437% of the total variance were extracted from the original data.The first and second factors accounted for 60.090% of the total variance,which means that P,K,Ca,Mn,Fe,Cu,Sr,B,Na and Se may be the characteristic elements.Conclusion: The showed that element content in Flos Chrysanthemi Indici display special distributing diagram.Remarkable correlation is presented in some element pairs.The elements contents of Flos Chrysanthemi indici gained from Yunan,Hunan are higher than those from other regions.
出处
《中国中药杂志》
CAS
CSCD
北大核心
2010年第18期2432-2436,共5页
China Journal of Chinese Materia Medica
基金
国家科技基础条件平台项目(2005DKA21000)
关键词
野菊花
元素分布
相关性
主成分分析
Flos Chrysanthemi indici
element content
correlation
principal component analysis