| 径向基函数神经网络和近红外光谱用于大黄中有效成分的定量预测 |
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| 引用本文： | 于晓辉,张卓勇,马群,范国强.径向基函数神经网络和近红外光谱用于大黄中有效成分的定量预测[J].光谱学与光谱分析,2007,27(3):481-485. |
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| 作者姓名： | 于晓辉 张卓勇 马群 范国强 |
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| 作者单位： | 1. 首都师范大学化学系,资源环境与GIS北京市重点实验室,北京,100037
2. 北京同仁堂股份有限公司科学研究所,北京,100011 |
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| 基金项目： | 北京市教委科技发展计划项目 |
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| 摘 要： | 采用近红外光谱(NIRS)法和人工神经网络定量预测大黄样品中4种有效成分的含量,包括:蒽醌 及其单糖甙类、水溶性蒽甙类、芪甙类、鞣质及其有关化合物.在1 100～2 500 nm波长范围内扫描大黄粉末样品,采用径向基函数神经网络(RBFNN)建立了近红外光谱与HPLC分析值之间的校正模型.上述四类化合物的交叉验证均方差(RMSECV)分别为2.572,0.442,2.794,9.438;预测均方差(RMSEP)分别为4.598,8.657,0.458 6,5.106.该方法快速,无损,结果令人满意,可作为中药材复杂体系中化学组分定量测定的方法.
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| 关 键 词： | 近红外光谱 径向基函数神经网络 中草药 大黄 定量预测 |
| 文章编号： | 1000-0593（2007）03-0481-05 |
| 收稿时间： | 2005-12-30 |
| 修稿时间： | 2006-03-28 |
Quantitative Prediction of Active Constituents in Rhubarb by Near Infrared Spectroscopy and Radial Basis Function Neural Networks |
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| YU Xiao-hui,ZHANG Zhuo-yong,MA Qun,FAN Guo-qiang.Quantitative Prediction of Active Constituents in Rhubarb by Near Infrared Spectroscopy and Radial Basis Function Neural Networks[J].Spectroscopy and Spectral Analysis,2007,27(3):481-485. |
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| Authors: | YU Xiao-hui ZHANG Zhuo-yong MA Qun FAN Guo-qiang |
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| Institution: | 1. Department of Chemistry, Resources Environment and GIS Key Lab of Beijing, Capital Normal University, Beijing 100037, China 2. Research Institute, Tongrentang Group Co. Ltd. , Beijing 100011, China |
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| Abstract: | Near infrared spectroscopy(NIRS) and artificial neural networks were used for the quantitative prediction of four active constituents in rhubarb: anthraquinones,anthraquinone glucosides,stilbene glucosides,Tannins and related compounds. The near infrared spectra of the samples were acquired in 1 100-2 500 nm from powdered rhubarb samples.Four calibration models using radial basis function neural networks(RBFNN) were set up to correlate the spectra with the values determined by HPLC.RMSECVs of the models for the constituents studied were 2.572,0.442,2.794 and 9.438,respectively.RMSEPs for the were 4.598,8.657,0.458 6,and 5.106,respectively.The method is fast,and satisfactory results were obtained.The proposed method can be used for determining the active constituents in Chinese herbal medicine. |
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| Keywords: | Near infrared spectrum Radial basis function neural networks Chinese herbal medicine Rhubarb Quantitative prediction |
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