Update: 30 September, 2023
This application note describes a non-targeted metabolomic analysis approach to the classification of wine varieties, employing LC/QTOF MS and MassHunter Workstation software. Molecular feature extraction, data filtering, and statistical analysis utilizing ANOVA and PCA identified 26 marker compounds that were then used to build a PLSDA prediction model. An overall accuracy of 95.6% in discriminating between Cabernet Sauvignon, Merlot and Pinot Noir red wine varieties was obtained using the model. This approach may be widely applicable to the analysis and characterization of foods.
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MD5 Checksum: CA847052C137A0D97592812A05652EE2
Publication date: 11 June, 2012
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