目的 建立不同产地细辛药材挥发油的气相色谱-质谱联用(GC-MS)指纹图谱,并结合化学模式识别进行评价。方法 采用GC-MS法建立细辛挥发油的指纹图谱,进行相似度评价,并通过聚类分析(CA)、主成分分析(PCA)、正交偏最小二乘法(OPLS-DA)判别分析不同产地细辛挥发油的质量差异。结果 建立了细辛挥发油的GC-MS指纹图谱,确认24个共有峰,并指认了其中10个共有峰。不同批次细辛挥发油样品相似度在0.908以上。CA、PCA和OPLS-DA结果显示细辛挥发油存在一定的质量差异,以变量投影重要度(VIP)值>1.0为标准,筛选出8个差异性标志成分。结论 GC-MS指纹图谱结合化学模式识别可以全面、系统地评价细辛挥发油的质量特征,为细辛药材的质量评价提供参考。

Objective To establish GC-MS fingerprints of volatile oil in Asari Herba from different origins, and analyze the results by chemical pattern recognition. Methods Fingerprints of volatile oil in Asari Herba were established by GC-MS, and the similarity was evaluate. The quality of volatile oil in Asari Herba from different origins was discussed by cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Results GC-MS fingerprints of volatile oil in Asari Herba were established, 24 peaks in it were confirmed, and 10 peaks of them were identified. The similarity of volatile oil in Asari Herba was above 0.908. CA, PCA, and OPLS-DA results showed that there were certain qualitative differences in volatile oil in Asari Herba. Using the VIP value ＞1.0 as the criterion, eight markers of difference were screened out, which can be used to distinguish between different origins. Conclusion GC-MS fingerprint combined with chemical pattern recognition can comprehensively and systematically evaluate the inherent quality characteristics of volatile oil in Asari Herba, which can provide a reference for the quality evaluation research of Asari Herba.

R286.02

国家自然科学基金资助项目(81673824)