2024
DOI: 10.1038/s41598-024-63280-9
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Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine

Zhuo-Kang Wang,
Na Ta,
Hai-Cheng Wei
et al.

Abstract: To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the… Show more

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