气相色谱—质谱法和模式识别技术用于雷公藤和昆明山海棠的分类鉴定

在样品色谱分离较完全的条件下,依据一定原则,将样品的成分质谱叠加,形成总质谱。用总质谱表征每一样本,并以总质谱的质量信道编码作指标。经Shannon信息理论特征选取,采用模式识别方法对雷公藤去皮根和根皮进行了分类,并对同属植物昆明山海棠作了定性预报。模式识别方法是SIMCA和LDA法,总预示率均为100.0%。结果表明:雷公藤去皮根心和根皮差异明显,可分为两类;昆明山海棠和雷公藤亲缘关系密切,被划为同类。本法灵敏、快速,不仅为联用技术中信息的综合应用,而且为从化学本质上研究中药质量提供了依据。

Determination of Chemical Classes from Mass Spectra of Medicinal Plants by GC-MS and Pattern Recognition

Under the complete chromatographic seperation of samples, the sum mass spectra of a set of 29 extraction of medicinal plants were obtained by overlapping of mass spectrum of components (using 10% of the reference peak as the threshold level), examined for information concerning chemical classes. The Shannon information content for each mass channel was calculated for the sum spectra, the 26 mass channels with the highest information were retained as a compressed basic set for SIMCA and LDA pattern recognition. The inherent class structure of the date showed two major classes by NLM; T. unlfordii bark and root, T. hypoglaucum roots were classified into T. wilfordii root class. Classification accuracy was 100% for the above two classes.