Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Innovation Center in Zhejiang University, State Key Laboratory of Component-Based Chinese Medicine, Zhejiang University, Hangzhou, China.
J Pharm Pharmacol. 2022 Jul 15;74(7):1040-1050. doi: 10.1093/jpp/rgab177.
To investigate the feasibility of using near-infrared spectroscopy for rapid determination of main organic acids in Ginkgo biloba leaf extract (EGBL).
Main organic acids in EGBL were assayed using the HPLC method. Critical factors of the chromatographic separation were optimized by a novel analytical quality by design approach. Partial least squares-discriminant analysis (PLS-DA) was performed to screen the marker components, and principal component analysis (PCA) was utilized to distinguish the different samples. Then, spectral quantification potential was investigated using PLS and support vector machine (SVM) approaches. For modelling, different spectral preprocessing and wavelength selection methods were systematically compared.
It was found that quinic acid, protocatechuic acid and 6-hydroxykynurenic acid were identified as possible index components. PLS-DA based on contents and PCA based on near-infrared spectra can both effectively distinguish the different EGBL samples. The calibration models with wonderful prediction performance can be both developed by the PLS and SVM algorithms.
NIR spectroscopy combined with chemometrics can realize the rapid and non-destructive qualitative and quantitative analysis of EGBL. The proposed method may be applied to quality control of EGBL and other natural products in commercial use.
研究近红外光谱法快速测定银杏叶提取物（EGBL）中主要有机酸的可行性。
采用 HPLC 法测定 EGBL 中的主要有机酸。通过新颖的分析质量设计方法优化了色谱分离的关键因素。采用偏最小二乘判别分析（PLS-DA）筛选标志物成分，主成分分析（PCA）用于区分不同样品。然后，采用偏最小二乘（PLS）和支持向量机（SVM）方法研究光谱定量潜力。对于建模，系统比较了不同的光谱预处理和波长选择方法。
发现奎宁酸、原儿茶酸和 6-羟基犬尿氨酸可作为可能的指标成分。基于含量的 PLS-DA 和基于近红外光谱的 PCA 均可有效区分不同的 EGBL 样品。PLS 和 SVM 算法均可建立具有出色预测性能的校准模型。
NIR 光谱结合化学计量学可实现 EGBL 的快速、无损定性和定量分析。该方法可应用于 EGBL 和其他商业用途的天然产物的质量控制。
