基于拉曼光谱法的降糖类药物的判别方法比较  

Comparison of Discriminative Methods of Hypoglycemic Drugs by Raman Spectroscopy

作　　者：高群[1] 张中湖[2] 陆峰[1] 

机构地区：[1]第二军医大学药学院,上海200433 [2]山东省食品药品检验所,山东济南250012

出　　处：《光谱学与光谱分析》2012年第12期3258-3261,共4页Spectroscopy and Spectral Analysis

基　　金：国家科技支撑计划项目(2008BAI55B06);上海市科委重点科技攻关项目(11431922500)资助

摘　　要：采用了四种聚类方法对降糖类药物拉曼光谱进行了快速、无损判别。采集九种降糖类药品共48个样品的拉曼光谱,经截波、基线校正、平滑、矢量归一化等预处理后,分别采用K-均值、系统聚类法、自组织图(SOM)及PCA-SOM四种不同聚类方法做聚类判别。结果表明,自组织图与K-均值、系统聚类法相比,聚类结果较好,并且SOM结合PCA后的PCA-SOM结果最优。为降糖类药品的快速判别从聚类的角度提供了一种新的方法。In the present paper, four kinds of cluster analysis methods were used in rapid, non-destructive discrimination of hypoglycemic tablets by the Raman spectroscopy technology. Nine kinds of hypoglycemic tablets, including 48 samples, were determined using a Raman spectrometer. The sample data were pretreated with the methods of frequency range cutting, baseline correction, smoothing and vector normalization, then were analyzed by K-means, hierachical cluster, self-organizing maps （SOM） and PCA-SOM respectively. The results demonstrated that SOM was better than K-means and hierachical cluster, and it provided the best discrimination when combined with PCA. The research offers a new approach to the rapid discrimination of different kinds of hypoglycemic tablets.

关 键 词：拉曼光谱 聚类分析 自组织图 降糖药 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] O657.3[自动化与计算机技术—计算机科学与技术]