摘要
【目的】对国内桔梗主产地的桔梗样品中的无机元素进行测定,以实现对国内桔梗主产地进行有效区分和识别.【方法】采用电感耦合等离子体原子发射光谱法(ICP-AES),对国内6大桔梗主产地的45个桔梗样品中14种无机元素(K、Na、Fe、Mg、Zn、Mn、Ca、Cu、Al、As、B、Ba、Cd和Hg)的含量进行测定,并结合主成分分析(PCA)的特征值对方差的贡献率、各元素在每一主成分(PCs)载荷的正负对所采集的桔梗样品进行了评价分析.【结果】PCA分析优筛出一个四因素的最佳模型,该优筛模型解释了各产地桔梗中14种无机元素含量的内在的联系,在一定程度上揭示了所采集的桔梗样品的亲缘关系及其地域性分布特征规律.因此,以14种无机元素含量为主成分分析对象,采用PCA分析法对国内主产地桔梗食用资源不同产地样品进行聚类评价,可实现对国内桔梗主产地进行有效区分和识别.【结论】该方法将对桔梗的产地判别和综合评价具有重要意义.
【Objective】In order to achieve the effective distinction and identification of the main producing areas of Platycodon grandiflorum(Jacq.)A.DC.in China,the mineral elements in P.grandiflorum(Jacq.)A.DC.samples from the main producing areas in China were measured.【Method】The concentrations of 14 kinds of mineral elements(K,Na,Fe,Mg,Zn,Mn,Ca,Cu,Al,As,B,Ba,Cd,Hg)of 45 P.grandiflorum(Jacq.)A.DC.samples collected from the six major domestic origins were determined by inductively coupled plasma-atomic emission spectrometry(ICP-AES).The principal component analysis(PCA)was used to evaluate the samples.【Result】The results showed that the PCA analysis yielded a four-factor optimal model which explained the intrinsic linkages of 14 mineral elements in P.grandiflorum(Jacq.)A.DC.from various origin.The relationship between the samples of Platycodon grandiflorum(Jacq.)A.DC.and the characteristics of regional distribution characteristics were revealed to some extent.【Conclusion】The method shows important significance for the discriminant and comprehensive evaluation of P.grandiflorum(Jacq.)A.DC.
作者
张忠明
王强
曹磊
张卫兵
ZHANG Zhong-ming;WANG Qiang;CAO Lei;ZHANG Wei-bing(College of Food Science and Engineering,Gansu Agricultural University,Lanzhou 730070,China;Chongqing University of Education,Chongqing 400067)
出处
《甘肃农业大学学报》
CAS
CSCD
北大核心
2018年第5期191-196,共6页
Journal of Gansu Agricultural University
基金
甘肃农业大学青年导师扶持基金项目(GAU-QNDS-201502)
