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