摘要
目的:以24批不同产地关木通的HPLC-ESI-MS指纹图谱为基础,采用化学计量学方法对其进行化学模式识别,并对不同的模式识别方法进行比较。方法:将关木通指纹图谱信息进行预处理,采用关木通HPLC-ESI-MS指纹图谱中的29个特征峰为基准,以各峰的保留时间、相对峰面积和质荷比作为数量化基础,采用SIMCA,SPSS 11.5等数据处理软件进行化学模式识别,比较SIMCA分类法和聚类分析法异同。结果:2种模式识别方法可以对关木通样品进行产地鉴别。结论:综合色谱指纹图谱技术和多变量的化学计量学分析方法研究可用于关木通的质量分析。
Objective： To analyze LC-MS fingerprints of Aristolochia manshuriensis for quality assessment with two different chemical pattern recognition models. Method： LC-MS fingerprints of A. manshuriensis were established from 24 batches of samples from different habitats. SIMCA and Clustering analysis were used to compare the parameters of the 29 common peaks. Result： Two methods had good consistency, while they reflected the inherent sample information from different perspectives, respectively. Conclusion： Modem equipment analysis technology and multivariable chemical pattern recognition would be an efficient way for quality control and variety identification of A. manshuriensis.
出处
《中国中药杂志》
CAS
CSCD
北大核心
2008年第24期2928-2931,共4页
China Journal of Chinese Materia Medica
