NMPA Key Laboratory for Quality Research and Evaluation of Traditional Chinese Medicine, Shenzhen Institute for Drug Control, Shenzhen 518057, China.
Molecules. 2023 Sep 28;28(19):6860. doi: 10.3390/molecules28196860.
Lonicerae japonicae flos and Lonicerae flos are increasingly widely used in food and traditional medicine products around the world. Due to their high demand and similar appearance, they are often used in a confused or adulterated way; therefore, a rapid and comprehensive analytical method is highly required. In this case, the comparative analysis of a total of 100 samples with different species, growth modes, and processing methods was carried out by nuclear magnetic resonance (H-NMR) spectroscopy and chemical pattern recognition analysis. The obtained H-NMR spectrums were employed by principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA). Specifically, after the dimensionality reduction of data, linear discriminant analysis (LDA) exhibited good classification abilities for the species, growth modes, and processing methods. It is worth noting that the sample prediction accuracy from the testing set and the cross-validation predictions of the LDA models were higher than 95.65% and 98.1%, respectively. In addition, the results showed that macranthoidin A, macranthoidin B, and dipsacoside B could be considered as the main differential components of Lonicerae japonicae flos and Lonicerae Flos, while secoxyloganin, secologanoside, and sweroside could be responsible for distinguishing cultivated and wild Lonicerae japonicae Flos. Accordingly, H-NMR spectroscopy combined with chemical pattern recognition gives a comprehensive overview and provides new insight into the quality control and evaluation of Lonicerae japonicae flos.
金银花和山银花在全球范围内的食品和传统医药产品中越来越广泛地使用。由于需求量大且外观相似，它们经常被混淆或掺假使用；因此，非常需要一种快速而全面的分析方法。在这种情况下，通过核磁共振（H-NMR）光谱和化学模式识别分析对总共 100 个具有不同物种、生长方式和加工方法的样本进行了比较分析。所获得的 H-NMR 光谱通过主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）、正交偏最小二乘判别分析（OPLS-DA）和线性判别分析（LDA）进行分析。具体来说，在对数据进行降维后，线性判别分析（LDA）对物种、生长方式和加工方法具有良好的分类能力。值得注意的是，来自测试集的样本预测准确性和 LDA 模型的交叉验证预测准确性均高于 95.65%和 98.1%。此外，结果表明，马钱苷 A、马钱苷 B 和胡芦巴皂苷 B 可以被认为是金银花和山银花的主要差异成分，而三叶豆苷、木兰花苷和瑞香苷可能是区分栽培和野生金银花的原因。因此，H-NMR 光谱结合化学模式识别为金银花的质量控制和评价提供了全面的概述和新的见解。
