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Rapid quantification of flavonoids in propolis and previous study for classification of propolis from different origins by using near infrared spectroscopy

机译:蜂胶中黄酮类成分的快速定量分析和使用近红外光谱技术对不同来源的蜂胶进行分类的先前研究

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A fast, simple and accurate near infrared spectroscopy (NIRs) method was investigated for the geographical origin discrimination and main flavonoid content determination of Chinese propolis. 180 propolis samples from four provinces of China were collected for establishing partial least squares (PLS) models of rutin, myricetin, quercetin, kaempferol, apigenin, izapinin, pinocembrin, chrysin, galangin and total flavonoids. The root mean square error of prediction (RMSEP) and correlation coefficient (R2) in the test set of the optimum models were 0.479 to 1.332% and 76.23 to 96.68%. The residual prediction deviation (RPD) values were all larger than 2.93. A paired t-test result showed that there was no significant difference between NIRs and HPLC methods at a 95% confidence interval. A principal component analysis (PCA)–Mahalanobis distance (MD) method was applied to classify the geographical origin of propolis samples, and 100% accuracy was obtained. Finally, a quality assessment was performed, and the propolis samples from Zhejiang and Liaoning province were classified as good quality. The developed NIRs method was a suitable tool for the rapid analysis of Chinese propolis, and might be also extended to the on-line quality control of propolis raw material in pharmaceutical industries, or monitoring industrial natural products extraction processes...
机译:研究了一种快速,简便,准确的近红外光谱法(NIRs),用于中国蜂胶的地理来源判别和主要黄酮含量的测定。收集了来自中国四个省的180个蜂胶样品,以建立芦丁,杨梅素,槲皮素,山ka酚,芹菜素,izapinin,pinocembrin,chrysin,galangin和总黄酮的偏最小二乘(PLS)模型。在最佳模型的测试集中,预测的均方根误差(RMSEP)和相关系数(R2)为0.479至1.332%和76.23至96.68%。剩余预测偏差(RPD)值均大于2.93。配对的t检验结果表明,在95%的置信区间内,NIR和HPLC方法之间没有显着差异。应用主成分分析(PCA)-马氏距离(MD)方法对蜂胶样品的地理起源进行分类,并获得100%的准确度。最后,进行了质量评估,浙江和辽宁省的蜂胶样品被归类为优质。发达的NIRs方法是用于快速分析中国蜂胶的合适工具,还可以扩展到制药行业蜂胶原料的在线质量控制或监测工业天然产物的提取过程...

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