红外光谱与聚类分析法无损快速鉴别肉苁蓉  

Rapid and Undamaged Determination of C.deserticola by Fourier-Transform Infrared Spectroscopy and Clustering Analysis

作　　者：徐荣[1] 孙素琴[2] 刘友刚[3] 于晶[1] 周峰[1] 刘同宁 陈君[1] 陈士林[1] 

机构地区：[1]中国医学科学院北京协和医学院药用植物研究所濒危药材繁育国家工程实验室,北京100193 [2]清华大学化学系,北京100084 [3]天津中医药大学基础医学院,天津300193 [4]宁夏永宁县本草苁蓉种植基地,宁夏银川750010

出　　处：《光谱学与光谱分析》2009年第7期1860-1863,共4页Spectroscopy and Spectral Analysis

基　　金：国家科技支撑计划项目(2006BAI06A13-05);国家自然科学基金项目(30772727);中国医学科学院药用植物研究所中央级公益性科研院所基本科研业务专项(YZ-1-09)资助

摘　　要：应用傅里叶变换红外光谱（FTIR）法测定了栽培和野生肉苁蓉，以450～2 000 cm-1范围内的吸收峰吸光度为指标，以红外光谱图为对象，应用SMICA聚类分析（Cluster analysis）法对栽培和野生肉苁蓉进行了聚类分析。结果表明，红外光谱结合聚类分析技术可对不同来源的肉苁蓉进行鉴别，识别率和拒绝率达到90%以上，盲样检测的准确率也在95%以上。因此，红外光谱与聚类分析法相结合可以快速、无损识别中药材。Cistanche deserticola, an endemic species in China, has been one of the grade Ⅱ national key conservation rare and endangered plants. The spectra of cultivated and wild C. deserticola samples were determined by Fourier transform infrared （FTIR） spectrometry. Based on the fingerprint infrared spectrum from 450 to 2 000 cm^-1, C. deserticola samples were rapidly classfied and closely studied by using the method of clustering analysis. Results showed that although there were tiny differences between the spectra of different origin, including the wild and cultivated C. deserticola samples, these samples could be successfully classified by soft independent modeling of class analogy （SIMCA）. Recognition rate and rejection rate of different C. deserticola samples were up to 90%. When testing with the blind sample which the authors picked out from the chosen samples, the accuracy of clustering reaches up to 95 %. On the whole, combined with clustering analysis, FTIR provides a effective way to evaluate the origin of the Chinese medicines rapidly and undamagedly.

关 键 词：红外光谱法 聚类分析 SIMCA肉苁蓉 

分 类 号：R282.5[医药卫生—中药学]