Raman spectra-based structural classification analysis of flavone and isoflavone

Li Li; Yangyao Peng; Dongjie Zhang; Qi Zeng; Xueli Chen

doi:10.1117/12.2655548

15 March 2023 Raman spectra-based structural classification analysis of flavone and isoflavone

Li Li, Yangyao Peng, Dongjie Zhang, Qi Zeng, Xueli Chen

Proceedings Volume 12392, Advanced Chemical Microscopy for Life Science and Translational Medicine 2023; 123920E (2023) https://doi.org/10.1117/12.2655548
Event: SPIE BiOS, 2023, San Francisco, California, United States

Conference Poster

Abstract

Flavonoids are natural compounds with diverse structures. This type of nature product is considered to possess a wide range of health beneficial effects. Different skeleton structures and substituent groups lead to different Raman spectral features. In this work, we developed three Raman spectrum analysis methods based on artificial intelligence to classify 18 flavonoids. Firstly, applying principal component analysis (PCA) as dimension reduction method, we compress the 1300cm^-1 -1600cm^-1 spectral band into several important variables. The results obtained by the preprocessing methods were combined with K-Nearest Neighbor algorithm (KNN), support vector machine (SVM) for classification. Secondly, the combination of relevant features was taken by advanced machine learning method of random forest (RF). In terms of the accuracy of the results, all the methods achieved acceptable classification accuracy, which was almost over 84% on the test set. The experimental results demonstrated that the Raman spectroscopy study based on corresponding unique vibration mode exhibited application prospects in chemical structure classification and pharmacological activity prediction.

Citation Download Citation

Li Li, Yangyao Peng, Dongjie Zhang, Qi Zeng, and Xueli Chen "Raman spectra-based structural classification analysis of flavone and isoflavone", Proc. SPIE 12392, Advanced Chemical Microscopy for Life Science and Translational Medicine 2023, 123920E (15 March 2023); https://doi.org/10.1117/12.2655548

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