College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Sensors (Basel). 2013 Aug 13;13(8):10539-49. doi: 10.3390/s130810539.
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.
建立了一种利用可见近红外光谱（Vis-NIR）快速测定杨树源中国蜂胶中白杨素和高良姜素含量的新方法。使用可见近红外分光辐射计在 325 至 1075nm 波长范围内采集了 114 个中国蜂胶样品的光谱数据。样品中白杨素和高良姜素的参考值采用高效液相色谱法（HPLC）确定。采用不同预处理方法对光谱进行分析，建立了偏最小二乘（PLS）模型。采用连续投影算法（SPA）选择有效波长，并将其作为 PLS、反向传播人工神经网络（BP-ANN）、多元线性回归（MLR）和最小二乘支持向量机（LS-SVM）模型的输入。采用 Savitzky-Golay 平滑（SG）预处理光谱建立的 SPA-BP-ANN 模型取得了最佳结果，其中高良姜素测定的 r 和 RMSEP 分别为 0.9823 和 1.5239，白杨素测定的 r 和 RMSEP 分别为 0.9668 和 2.4841。结果表明，Vis-NIR 对快速测定中国蜂胶中白杨素和高良姜素含量具有强大的能力。
