首页> 外文期刊>Journal of Analytical Methods in Chemistry >Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods
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Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods

机译:高效液相色谱和近红外光谱指纹图谱识别方法快速区分传统复杂草药的不同部位,采集时间和来源

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摘要

As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. High-performance liquid chromatography (HPLC) and near-infrared (NIR), with their unique characteristics of reliability, versatility, precision, and simple measurement, played an important role among all the fingerprint techniques. In this paper, a supervised pattern recognition method based on PLSDA algorithm by HPLC and NIR has been established to identify the information of Hibiscus mutabilis L. and Berberidis radix, two common kinds of herbal medicines. By comparing component analysis (PCA), linear discriminant analysis (LDA), and particularly partial least squares discriminant analysis (PLSDA) with different fingerprint preprocessing of NIR spectra variables, PLSDA model showed perfect functions on the analysis of samples as well as chromatograms. Most important, this pattern recognition method by HPLC and NIR can be used to identify different collection parts, collection time, and different origins or various species belonging to the same genera of herbal medicines which proved to be a promising approach for the identification of complex information of herbal medicines.
机译:作为一种有效的方法,强调样品整体成分的指纹技术已被用于各个领域,尤其是在鉴定和评估草药质量方面。高效液相色谱(HPLC)和近红外(NIR)具有独特的可靠性,多功能性,精确度和简单的测量特性,在所有指纹技术中都起着重要的作用。本文建立了一种基于HPLC和NIR的基于PLSDA算法的监督模式识别方法,用于识别两种常见草药木槿和小Ber的信息。通过将成分分析(PCA),线性判别分析(LDA),尤其是偏最小二乘判别分析(PLSDA)与不同的NIR光谱变量指纹预处理进行比较,PLSDA模型在样品分析和色谱图分析中显示出完美的功能。最重要的是,这种通过HPLC和NIR进行模式识别的方法可用于识别不同的采集部位,采集时间,不同的来源或属于同一草药属的各种物种,这被证明是识别复杂信息的一种有前途的方法草药。

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