基于紫外光谱和偏最小二乘回归算法的畲药地稔中浸出物和6种活性成分快速预测方法

Rapid Prediction of Extractum and Six Active Components in Traditional She Medicine-Melastoma Dodecandrum Lour. by Ultraviolet Spectroscopy and Partial Least Squares Regression Algorithm

关键词:  地稔  紫外光谱  偏最小二乘回归

Key words:  Melastoma dodecandrum Lour.  ultraviolet spectroscopy  partial least squares regression

摘要:

目的 建立基于紫外光谱的畲药地稔中浸出物、没食子酸、阿魏酸、芦丁、槲皮素、木犀草素、山奈酚的快速分析方法。方法 测定地稔水提液中的浸出物和6种化合物浓度，采集紫外光谱。采用SIMCA-P+软件，分别建立浸出物、6种化合物浓度与紫外光谱的偏最小二乘回归模型。采用Visual Basic开发应用软件，将所建模型嵌套入软件，为同时快速分析待测溶液中浸出物和6种化合物浓度提供工具。结果 验证集浸出物和6种化合物浓度的预测均方根误差分别为39.1，0.263，19.0，93.8，0.894，0.593，0.896 ng·mL^-1，预测值和真实值的相关系数均>0.9，并通过软件在10 s内得到了浸出物和6种化合物浓度的预测结果。结论 本方法可为地稔的快速质量评价提供依据。

Abstract:

OBJECTIVE To establish a rapid method for the determination of the extractum, gallic acid, ferulic acid, rutin, quercetin, luteolin and kaempferol in traditional She medicine-Melastoma dodecandrum by ultraviolet spectroscopy. METHODS The contents of extractum and 6 components in aqueous extract solutions of Melastoma dodecandrum were detected and the ultraviolet spectra were collected. The partial least squares regression models of extractum and 6 components were established separately with the use of SIMCA-P+ software. The software was devised by using Visual Basic, embeded the model into software. This method provided a convenient tool for the simultaneous and rapid determination of extractum and 6 components in unknown samples. RESULTS The root mean square error of predictions for extractum and 6 components were 39.1, 0.263, 19.0, 93.8, 0.894, 0.593, 0.896 ng·mL^-1, respectively. The correlation coefficients between the predicted and the reference values for validation set were >0.9 and the predicted contents of extractum and 6 components were calculated automatically within 10 s. CONCLUSION This study provides a rapid method for the quality evaluation of Melastoma dodecandrum Lour.