GC-MS同时测定大果木姜子油中11种挥发性成分的含量

Simultaneous determination of eleven volatile components in Cinnamomi Oleum by GC-MS

建立气相色谱-三重四极杆质谱(GC-MS)同时测定大果木姜子油中11种挥发性成分的方法,并结合化学模式识别法对不同产地大果木姜子药材提取的精油进行质量评价。采用内标法,药材经水蒸气蒸馏后,GC-MS测定,选择离子模式(selective ion monitoring,SIM)检测;使用层次聚类分析(hierarchical clustering analysis,HCA)和主成分分析(principal component analysis,PCA),并结合正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)对多批次大果木姜子油含量测定结果进行统计分析。11种成分在各自浓度范围内线性关系良好(R^(2)>0.9997);平均加样回收率为92.41%~102.1%,RSD为1.2%~3.2%(n=6);HCA、PCA 2种方法均把样品分为了3类,结合OPLS-DA筛选出了导致各批次之间产生差异的差异性标志物为2-壬酮。该方法专属性强、灵敏度高、测定方法简便结果准确,所筛选的成分可为大果木姜子油的质量控制提供检验依据。

A gas chromatography-triple quadrupole mass spectrometry(GC-MS)method was established for the simultaneous determination of eleven volatile components in Cinnamomi Oleum and the chemical pattern recognition was utilized to evaluate the quality of essential oil obtained from Cinnamomi Fructus medicinal materials in various habitats.The Cinnamomi Fructus medicinal materials were treated by water distillation,analyzed using GC-MS,and detected by selective ion monitoring(SIM),and the internal standards were used for quantification.The content results of Cinnamomi Oleum from various batches were analyzed by hierarchical clustering analysis(HCA),principal component analysis(PCA),and orthogonal partial least squares-discriminant analysis(OPLS-DA)for the statistic analysis.Eleven components showed good linear relationships within their respective concentration ranges(R^(2)>0.9997),with average recoveries of 92.41%-102.1%and RSD of 1.2%-3.2%(n=6).The samples were classified into three categories by HCA and PCA,and 2-nonanone was screened as a marker of variability between batches in combination with OPLS-DA.This method is specific,sensitive,simple,and accurate,and the screened components can be utilized as a basis for the quality control of Cinnamomi Oleum.