| 基于近红外光谱主成分分析-马氏距离法的发汗与未发汗续断的快速鉴别 |
| |
| 引用本文： | 杜伟锋,贾永强,姜东京,张浩.基于近红外光谱主成分分析-马氏距离法的发汗与未发汗续断的快速鉴别[J].中国中药杂志,2014,39(23):4603-4607. |
| |
| 作者姓名： | 杜伟锋 贾永强 姜东京 张浩 |
| |
| 作者单位： | 浙江中医药大学 中药炮制技术研究中心, 浙江 杭州 311401;中国医学科学院 药物研究所 北京协和药厂, 北京 102600;浙江中医药大学 中药炮制技术研究中心, 浙江 杭州 311401;浙江中医药大学 中药炮制技术研究中心, 浙江 杭州 311401 |
| |
| 基金项目： | 国家自然科学基金青年基金项目(81303224) |
| |
| 摘 要： | 为了快速准确的鉴别续断发汗与否, 以续断发汗和未发汗样品为实验材料, 采用近红外光谱法结合主成分分析-马氏距离判别分析方法建立了定性鉴别模型。选取了129个未发汗样品和86个发汗样品的近红外光谱图,应用主成分分析-马氏距离法进行判别分析,选择谱段为9 881.46~4 119.20 cm-1,采用 "标准正则变换 +原始光谱+ 二阶求导" 组合对原始光谱进行预处理,主成分数为14,建立定性鉴别模型;并经预测集验证,鉴别准确率达到100%。说明近红外光谱结合模式识别方法进行续断"发汗"与否定性鉴别在技术上是可行的,可以作为续断产地加工"发汗"定性鉴别的一种辅助手段。
|
| 关 键 词： | 近红外光谱 续断 发汗 主成分分析 马氏距离 判别分析 |
| 收稿时间： | 2014/7/16 0:00:00 |
Rapid identification of crude and sweated Dipsaci Radix based on near-infrared spectroscopy combined with principal component analysis-Mahalanobis distance |
| |
| DU Wei-feng,JIA Yong-qiang,JIANG Dong-jing and ZHANG Hao.Rapid identification of crude and sweated Dipsaci Radix based on near-infrared spectroscopy combined with principal component analysis-Mahalanobis distance[J].China Journal of Chinese Materia Medica,2014,39(23):4603-4607. |
| |
| Authors: | DU Wei-feng JIA Yong-qiang JIANG Dong-jing and ZHANG Hao |
| |
| Institution: | Research Center of Traditional Chinese Medicine Processing Technology, Zhejiang Chinese Medical University, Hangzhou 311401, China;Beijing Union Pharmaceutical Factory, Institute of Materia Medica, Chinese Academy of Medical Sciences&Peking Union Medical College, Beijing 102600, China;Research Center of Traditional Chinese Medicine Processing Technology, Zhejiang Chinese Medical University, Hangzhou 311401, China;Research Center of Traditional Chinese Medicine Processing Technology, Zhejiang Chinese Medical University, Hangzhou 311401, China |
| |
| Abstract: | In order to discriminate the crude and sweated Dipsaci Radix correctly and rapidly, the crude and sweated Dipsaci Radix were scanned by the NIR spectrometer, and an identifying model was developed by near infrared spectroscopy combined with principal component-Mahalanobis distance pattern recognition method. The pretreated spectra data of 129 crude samples and 86 sweated ones were analyzed through principal component analysis (PCA). The identifying model was developed by choosing the spectrum for 9 881.46-4 119.20 cm-1 and "SNV+spectrum+S-G" to the original spectral preprocessing with 14 principal components, and then was verified by prediction set, identifying with 100% accuracy. The rapid identification model of the crude and sweated Dipsaci Radix by NIR is feasible and efficient, and could be used as an assistant means for identifying the crude and sweated Dipsaci Radix. |
| |
| Keywords: | near-infrared spectroscopy (NIR) Dipsaci Radix sweated principal component analysis (PCA) Mahalanobis distance discriminant analysis |
|
|
