Key Laboratory for Quality Evaluation of Bulk Herbs of Hunan Province, Hunan University of Chinese Medicine, Changsha 410208, China.
Molecules. 2022 Jul 20;27(14):4640. doi: 10.3390/molecules27144640.
LJF and LF are commonly used in Chinese patent drugs. In the , LJF and LF once belonged to the same source. However, since 2005, the two species have been listed separately. Therefore, they are often misused, and medicinal materials are indiscriminately put in their related prescriptions in China. In this work, firstly, we established a model for discriminating LJF and LF using ATR-FTIR combined with multivariate statistical analysis. The spectra data were further preprocessed and combined with spectral filter transformations and normalization methods. These pretreated data were used to establish pattern recognition models with PLS-DA, RF, and SVM. Results demonstrated that the RF model was the optimal model, and the overall classification accuracy for LJF and LF samples reached 98.86%. Then, the established model was applied in the discrimination of their related prescriptions. Interestingly, the results show good accuracy and applicability. The RF model for discriminating the related prescriptions containing LJF or LF had an accuracy of 100%. Our results suggest that this method is a rapid and effective tool for the successful discrimination of LJF and LF and their related prescriptions.
LJF 和 LF 是中药中常用的两种药材。在过去,LJF 和 LF 曾属于同一来源。然而,自 2005 年以来,这两个物种已被分别列出。因此,它们经常被误用,中药材在中国被随意放入相关的处方中。在这项工作中,我们首先建立了一个使用 ATR-FTIR 结合多元统计分析来区分 LJF 和 LF 的模型。对光谱数据进行了进一步的预处理,并结合光谱滤波变换和归一化方法。这些预处理数据用于建立 PLS-DA、RF 和 SVM 的模式识别模型。结果表明,RF 模型是最优模型,LJF 和 LF 样本的总体分类准确率达到 98.86%。然后,我们将建立的模型应用于区分它们的相关处方。有趣的是,结果显示出良好的准确性和适用性。用于区分含有 LJF 或 LF 的相关处方的 RF 模型的准确率为 100%。我们的结果表明,该方法是区分 LJF 和 LF 及其相关处方的一种快速有效的工具。