当归的气—质联用色谱的模式识别

Pattern Recognition Analysis of Angelica sinensis and Angelica gigas by GC-MS

采用GC-MS法,对来自中国与韩国的41个模式组当归药材进行测定,并运用主成分分析法、聚类分析法和判别分析等多变量分析方法对各样品指纹图谱进行化学模式识别研究.结果表明Z-藁本内酯在中国当归中相对含量较高,紫花前胡素和紫花前胡醇当归酯在朝鲜当归中相对较高.同时,论证了该方法的可行性和有效性.利用气—质联用色谱的模式识别方法是一种科学有效的当归药材的质量评价方法.

Objective： To compare 41 root samples of Angelica sinensis and A. gigas from China and Korea for the quality control of Chinese Angelica. Method： HP-5 （30 m × 0.32 mm,0.25μm） column was used for the GC-MS analysis. The oven temperature was programmed from 120 to 280℃ at a rate of 5℃/min. Carrier gas： He; Injector temperature： 280℃ ; Detector： Flame ionization detector （ FID）, 300℃. Subsequently, multivariate analytical methods, such as principal component analysis （PCA）, cluster analysis （CA）, and discriminant analysis （DA）, were applied to the samples for chemical fingerprint pattern recognition research. Results： Z-lignstilide was the most contributive principle distinguishing Chinese samples from Korean, and decursin and decursinol angelate were more contained in Korean samples. Moreover, using discriminant analysis, seven samples （four from A. sinensis, three from A. gigas ） were validated. All tested samples were successfully classified according to their species origin. Conclusion：GC-MS-pattem recognition method is one kind of scientific and effective methods for the quality evaluation of A. sinensis.