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不同品种产地麻黄的FTIR快速分析鉴别研究 被引量:2

Identification of Ephedra from Different Species and Areas Using Fourier Transform Infrared Spectrometry
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摘要 目的对不同品种产地麻黄进行快速鉴别,为其正确使用提供科学依据。方法采用傅里叶变换红外光谱(FTIR)测定了6个不同品种产地的36个麻黄样品的红外光谱。选择1000—1400cm^-1范围内的光谱数据进行了主成分聚类分析和径向基神经网络预测。结果主成分分析(PCA)表明,前3个主成分的累积可信度已达96.44%,能够表征出麻黄在不同品种产地的多样性分化。建立概率径向基神经网络模型对12个麻黄样本进行了预测,正确率达83.33%。结论傅里叶变换红外光谱技术结合化学统计学方法可用于麻黄药材品种产地的分类和鉴别,可为麻黄药材的质量控制提供一个快捷、准确、可行的方法。 Objective The aim of this study was to provide a fast and reliable scientific approach to identified different species and areas of epbedra. Methods Using Fourier transform infrared (FTIR) spectroscopy measured 36 samples of ephedra from 6 dif- ferent species and areas. Based on the indices of wave number absorbance from 1 000 cm- ~ to 1 400 cm- 1, Ephedra samples were analyzed by FTIR combined with the principal component analysis (PCA) and radial basis function neural network. Results The results of PCA showed that, the cumulate reliabilities of the first 3 principal components reached 96.44%. Principal component a- nalysis can reflect ephedra in different species and areas diversity. 12 ephedra samples were predicted by radial basis probabilistic neural network model, the correct rate of 83.33 %. Conclusion FTIR combined with statistical methods can be used to classify and identify species and areas of ephedra. It is a rapid, accurate and operable method in the quality control of ephedra herbs.
出处 《时珍国医国药》 CAS CSCD 北大核心 2014年第2期357-359,共3页 Lishizhen Medicine and Materia Medica Research
基金 国家自然科学基金(No.21265021)
关键词 麻黄 傅里叶变换红外光谱 主成分分析 径向基神经网络分析 Ephedra FTIR Principal component analysis Radial basis function networks
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