Quality assessment of Compound Yuxingcao Mixture produced by different manufacturers using high performance liquid chromatography and near infrared spectroscopy combined with multivariate algorithms

Abstract

A comprehensive strategy based on high performance liquid chromatography (HPLC) and near infrared (NIR) spectroscopy was developed to assess the quality consistency of Compound Yuxingcao Mixture (CYM) from different manufacturers. Simultaneous determination of 10 marker components (neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, acteoside, forsythoside A, quercitrin, baicalin, wogonoside and wogonin) in CYM and 7 marker components (neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, hyperoside, isoquercitrin, quercitrin and quercetin) in Houttuyniae Herba was carried out. Similarity analysis using chromatographic fingerprints and principal component analysis (PCA) were also performed to assess the quality consistency of CYM from different manufacturers. NIR spectroscopy combined with partial least squares (PLS), feed-forward back-propagation network (BP-ANN), and particle swarm optimization based least square support vector machine (PSO-LS-SVM) algorithms were employed for rapid determination of higher-concentration marker components (baicalin, wogonoside and chlorogenic acid) and rapid identification of product manufacturers. The comparative results showed that the PSO-LS-SVM models exhibited more satisfactory fitting results and predictive abilities. This study demonstrated that the combination of multi-component simultaneous determination and fingerprint analysis can help to gain an in-depth and comprehensive understanding of the quality of CYM; NIR technique combined with chemometric methods is useful for the rapid determination, identity and consistency evaluation of CYM.