Classification and Authentication of Lonicerae Japonicae Flos and Lonicerae Flos by Using 1H-NMR Spectroscopy and Chemical Pattern Recognition Analysis

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-1-NMR) spectroscopy and chemical pattern recognition analysis. The obtained H-1-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-1-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.

Automated summary

H-1-NMR spectroscopy combined with chemical pattern recognition was used to analyze samples of Lonicerae japonicae flos with different species, growth modes, and processing methods. Linear discriminant analysis (LDA) showed good classification abilities for distinguishing the samples based on species, growth modes, and processing methods. The study also identified the main differential components and explored the potential compounds for distinguishing cultivated and wild Lonicerae japonicae flos.