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基于智能光谱分析策略的紫外和傅里叶变换红外光谱指纹:在复方甘草片质量评价中的应用。

A smart spectral analysis strategy-based UV and FT-IR spectroscopy fingerprint: Application to quality evaluation of compound liquorice tablets.

机构信息

School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China.

School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China.

出版信息

J Pharm Biomed Anal. 2021 Aug 5;202:114172. doi: 10.1016/j.jpba.2021.114172. Epub 2021 May 25.

Abstract

This study focuses on development of a smart spectral analysis strategy for rapid quality evaluation of complex sample. Firstly, the ultraviolet (UV) and Fourier Transform Infrared (FT-IR) spectroscopy were established. Secondly, the second derivative UV spectral was obtained and showed 7 major absorption peaks, which was the projection of the 3D-spectrum profile. It can perform peak matching like chromatogram, thus, helpful for 3D UV spectrum analysis, qualitatively and quantitatively. The qualitative and quantitative similarity results based on systematic quantified fingerprint method displayed basically a consistency with their hierarchical cluster analysis results. Notably, the quality evaluation of the first proposed FT-IR spectral quantized fingerprints and the good correlation of P% with PA (R = 0.80296), as well as the excellent quantitative prediction model for liquiritin, glycyrrhizinic acid and sodium benzoate all indicated the promising of FT-IR spectral quantized fingerprint in quantitative analysis and QC of compound liquorice tablets. Finally, an integrated evaluate strategy was developed by mean algorithm to reduce the error caused by single technique. 54 samples integrally had a good quality consistency as their quality ranged grade 1-5. This study illustrated that the smart data analysis strategy based on spectral fingerprint has potential to enhance existing methodologies for further rapid and integrated studies evaluating the quality of herbal medicine and its related products.

摘要

本研究聚焦于开发一种智能光谱分析策略,用于快速评估复杂样品的质量。首先,建立了紫外(UV)和傅里叶变换红外(FT-IR)光谱。其次,获得了二阶导数 UV 光谱,显示出 7 个主要吸收峰,这是 3D 光谱轮廓的投影。它可以像色谱一样进行峰匹配,因此有助于 3D UV 光谱的定性和定量分析。基于系统量化指纹方法的定性和定量相似性结果与它们的层次聚类分析结果基本一致。值得注意的是,首次提出的 FT-IR 光谱量化指纹的质量评价以及 P%与 PA(R = 0.80296)之间的良好相关性,以及对甘草酸、甘草酸和苯甲酸钠的出色定量预测模型,都表明 FT-IR 光谱量化指纹在复方甘草片中的定量分析和质量控制方面具有广阔的应用前景。最后,通过均值算法开发了一种综合评价策略,以减少单一技术引起的误差。54 个样品的整体质量一致性良好,质量等级为 1-5 级。本研究表明,基于光谱指纹的智能数据分析策略具有增强现有方法的潜力,以进一步快速综合研究草药及其相关产品的质量。

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