Application of Visible and Near Infrared Spectroscopy for Rapid Analysis of Chrysin and Galangin in Chinese Propolis

Abstract

A novel method for the rapid determination of chrysin and galangin in Chinese propolis of poplar origin by means of visible and near infrared spectroscopy (Vis-NIR) was developed. Spectral data of 114 Chinese propolis samples were acquired in the 325 to 1,075 nm wavelength range using a Vis-NIR spectroradiometer. The reference values of chrysin and galangin of the samples were determined by high performance liquid chromatography (HPLC). Partial least squares (PLS) models were established using the spectra analyzed by different preprocessing methods. The effective wavelengths were selected by successive projections algorithm (SPA) and employed as the inputs of PLS, back propagation-artificial neural networks (BP-ANN), multiple linear regression (MLR) and least square-support vector machine (LS-SVM) models. The best results were achieved by SPA-BP-ANN models established with the Savitzky-Golay smoothing (SG) preprocessed spectra, where the r and RMSEP were 0.9823 and 1.5239 for galangin determination and 0.9668 and 2.4841 for chrysin determination, respectively. The results show that Vis-NIR demosntrates powerful capability for the rapid determination of chrysin and galangin contents in Chinese propolis.

Keywords

• Chinese propolis
• chrysin
• galangin
• visible and near infrared spectroscopy (Vis-NIR)
• successive projection algorithm
• partial least squares
• back propagation-artificial neural networks