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近红外光谱法快速分析葛根

Rapid analysis of Radix puerariae by near-infrared spectroscopy.

作者信息

Lau Ching-Ching, Chan Chi-On, Chau Foo-Tim, Mok Daniel Kam-Wah

机构信息

State Key Laboratory of Chinese Medicine and Molecular Pharmacology, Shenzhen, China.

出版信息

J Chromatogr A. 2009 Mar 13;1216(11):2130-5. doi: 10.1016/j.chroma.2008.12.089. Epub 2009 Jan 8.

Abstract

A new, rapid analytical method using near-infrared spectroscopy (NIRS) was developed to differentiate two species of Radix puerariae (GG), Pueraria lobata (YG) and Pueraria thomsonii (FG), and to determine the contents of puerarin, daidzin and total isoflavonoid in the samples. Five isoflavonoids, puerarin, daidzin, daidzein, genistin and genistein were analyzed simultaneously by high-performance liquid chromatography-diode array detection (HPLC-DAD). The total isoflavonoid content was exploited as critical parameter for successful discrimination of the two species. Scattering effect and baseline shift in the NIR spectra were corrected and the spectral features were enhanced by several pre-processing methods. By using linear discriminant analysis (LDA) and soft independent modeling class analogy (SIMCA), samples were separated successfully into two different clusters corresponding to the two GG species. Furthermore, sensitivity and specificity of the classification models were determined to evaluate the performance. Finally, partial least squares (PLS) regression was used to build the correlation models. The results showed that the correlation coefficients of the prediction models are R=0.970 for the puerarin, R=0.939 for daidzin and R=0.969 for total isoflavonoid. The outcome showed that NIRS can serve as routine screening in the quality control of Chinese herbal medicine (CHM).

摘要

开发了一种使用近红外光谱(NIRS)的新型快速分析方法,用于区分葛根的两个品种,即野葛(YG)和粉葛(FG),并测定样品中葛根素、大豆苷和总异黄酮的含量。通过高效液相色谱-二极管阵列检测(HPLC-DAD)同时分析了五种异黄酮,即葛根素、大豆苷、大豆苷元、染料木苷和染料木素。总异黄酮含量被用作成功区分这两个品种的关键参数。通过几种预处理方法校正了近红外光谱中的散射效应和基线漂移,并增强了光谱特征。使用线性判别分析(LDA)和软独立建模类比法(SIMCA),样品被成功分为对应于两个葛根品种的两个不同类别。此外,确定了分类模型的灵敏度和特异性以评估其性能。最后,使用偏最小二乘(PLS)回归建立相关模型。结果表明,预测模型的相关系数分别为:葛根素R = 0.970,大豆苷R = 0.939,总异黄酮R = 0.969。结果表明,近红外光谱可作为中药材质量控制的常规筛选方法。

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