文献类型：期刊文献

中文题名：基于FTIR的黄芪药材产地鉴别及预测研究

英文题名：Origin Identification and Prediction of Astragali Radix Based on Fourier Transform Infrared Spectroscopy

作者：李芳[1];李钦[2];顾志荣[3];吴国泰[1];胡继宏[1]

第一作者：李芳

机构：[1]甘肃中医药大学;[2]甘肃省中医学校;[3]甘肃省人民医院

第一机构：甘肃中医药大学

年份：2016

卷号：28

期号：11

起止页码：1712

中文期刊名：天然产物研究与开发

外文期刊名：Natural Product Research and Development

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：国家自然科学基金(81260597);甘肃省中医药管理局科研项目(GZK-2015-45)

语种：中文

中文关键词：黄芪;傅里叶变换红外光谱;指纹图谱;正交偏最小二乘-判别分析;反向传播-人工神经网络

外文关键词：Astragali Radix; fourier transform infrared spectroscopy; fingerprint; orthogonal partial least squares-discriminant analysis; back-propagation neural network

摘要：采集12个主产县90批黄芪药材的FTIR指纹图谱,分析各产地药材的光谱特征,采用正交偏最小二乘判别分析（OPLS-DA）及反向传播人工神经网络（BP-ANN）建立其产地的快速鉴别及预测模型。结果表明,不同产地黄芪药材FTIR指纹图谱及平均光谱均具有一定差异;所建OPLS-DA模型能够对不同产地黄芪药材进行较为明确的分类鉴别;不同产地黄芪药材的FTIR光谱差异主要分布在3400-2920、1650-1420、1370-1050、930-770 cm-1及590-520 cm-1波数范围;所建BP-ANN模型对测试集黄芪药材产地的预测准确率大于83%。因此,基于FTIR指纹图谱的OPLS-DA模型及BP-ANN模型能够用于黄芪药材的产地鉴别及预测。
In this study,collecting the fingerprints of 90 batches of Astragali Radix from 12 counties,investigating the spectral characteristics of Astragali Radix from different origins,and establishing model of OPLS-DA（ orthogonal partial least squares-discriminant analysis） and BP-ANN（ back-propagation neural network） to realize the rapid identification and prediction of origin. The results showed that the FTIR fingerprints and its average spectrums of Astragali Radix from different origins showed some differences; the established OPLS-DA model can be used to accurately classify Astragali Radix from different origins; the differences of FTIR fingerprints of Astragali Radix from different origins were mainly existing in the wave number ranges of 3400-2920,1650-1420,1370-1050,930-770 cm-1,and 590-520 cm-1; the prediction accuracy of testing set was higher than 83% based on BP-ANN model. Hence the established OPLS-DA and BP-ANN model based on FTIR fingerprints can be used to identify and predict the origin of Astragali Radix.