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红外光谱法结合系统聚类和SIMCA模式识别法快速鉴别羌活种子
引用本文:沈 亮,蒋舜媛,黄荣韶,周 毅,李良波,孙 辉,甘凤琼.红外光谱法结合系统聚类和SIMCA模式识别法快速鉴别羌活种子[J].医学教育探索,2011,42(10):2114-2118.
作者姓名:沈 亮  蒋舜媛  黄荣韶  周 毅  李良波  孙 辉  甘凤琼
作者单位:1.中国医学科学院 北京协和医学院药用植物研究所,北京 100193 2.广西大学农学院,广西 南宁 530005 3.四川省中医药科学院,四川 成都 610041 4.四川大学 环境科学与工程系,四川 成都 610065
基金项目:国家科技部“重大新药创制”科技重大专项(民口)课题;“中药材种子种苗和种植(养殖)标准平台”课题(2009ZX09308-002);广西科学研究与技术开发计划项目(桂科攻0992003A-20)资助
摘    要:目的 采用傅里叶变换红外光谱法鉴别羌活种子。方法 在4 000~400 cm?1内测定羌活种子光谱吸收峰,应用系统聚类和SIMCA模式识别法鉴别羌活和宽叶羌活的种子。结果 运用系统聚类法,当聚类距离为15时,两种羌活可明显分为2类;运用SIMCA模式识别法,所建模型对羌活和宽叶羌活的种子识别率分别达96%和97%,拒绝率均为100%,两者盲样检测准确率也在90%以上,所建模型可用于样品检测。结论 应用红外光谱法结合系统聚类和SIMCA模式识别法,可以简单、快速、准确地鉴别羌活种子,该方法为鉴别羌活种子的来源及真伪提供了一种新的技术手段。

关 键 词:羌活  种子鉴定  红外光谱  系统聚类  SIMCA

Rapid seed identification of Notopterygii Rhizoma et Radix by SIMCA based on FTIR
SHEN Liang,JIANG Shun-yuan,HUANG Rong-shao,ZHOU Yi,LI Liang-bo,SUN Hui,GAN Feng-qiong.Rapid seed identification of Notopterygii Rhizoma et Radix by SIMCA based on FTIR[J].Researches in Medical Education,2011,42(10):2114-2118.
Authors:SHEN Liang  JIANG Shun-yuan  HUANG Rong-shao  ZHOU Yi  LI Liang-bo  SUN Hui  GAN Feng-qiong
Institution:1.Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China 2.College of Agriculture, Guangxi University, Nanning 530005, China 3.Sichuan Academy of Traditional Chinese Medicine Sciences, Chengdu 610041, China 4.Department of Environmental Science and Engineering, Sichuan University, Chengdu 610065, China
Abstract:Objective To identify the seeds of Notopterygii Rhizoma et Radix by Fourier transform infrared spectrometry (FTIR). Methods Based on the fingerprint infrared spectrum from 4 000 to 400 cm?1, hierarchical cluster and Soft Independent Modeling of Class Analogy (SIMCA) analyses were developed to identify the seeds of Notopterygium incisum and N. franchetii. Results The seeds could be divided into two categories with 15 Euclidean distance by using hierarchical cluster analysis. Using SIMCA analysis, the recognition rate of N. incisum and N. franchetii reached to 96% and 97%, respectively, and the rejection rate reached to 100%. When testing with the blind sample which the authors picked out from the chosen samples, the accuracy rate reached over 90%. The established model could be used for sample testing. Conclusion Both clustering analysis and FTIR combined with SIMCA provide an effective way to evaluate the seeds of Notopterygii Rhizoma et Radix rapidly and accurately. Therefore, this method provides a new technique for evaluating the source and authenticity of the seeds of Notopterygii Rhizoma et Radix.
Keywords:Notopterygii Rhizoma et Radix   seed identification  FTIR  hierarchical cluster  Soft Independent Modeling of Class Analogy (SIMCA)
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