Mascellani, Anna published the artcile1H NMR chemometric models for classification of Czech wine type and variety, SDS of cas: 121-79-9, the publication is Food Chemistry (2021), 127852, database is CAplus and MEDLINE.
A set of 917 wines of Czech origin were analyzed using NMR spectroscopy (NMR) with the aim of building and evaluating multivariate statistical models and machine learning methods for the classification of 6 types based on color and residual sugar content, 13 wine grape varieties and 4 locations based on 1H NMR spectra. The predictive models afforded greater than 93% correctness for classifying dry and medium dry, medium, and sweet white wines and dry red wines. The trained Random Forest (RF) model classified Pinot noir with 96% correctness, Blaufrankisch 96%, Riesling 92%, Cabernet Sauvignon 77%, Chardonnay 76%, Gewurtztraminer 60%, Hibernal 60%, Gruner Veltliner 52%, Pinot gris 48%, Sauvignon Blanc 45%, and Palava 40%. Pinot blanc and Chardonnay, varieties that are often mistakenly interchanged, were discriminated with 71% correctness. The findings support chemometrics as a tool for predicting important features in wine, particularly for quality assessment and fraud detection.
Food Chemistry published new progress about 121-79-9. 121-79-9 belongs to esters-buliding-blocks, auxiliary class Natural product, name is Propyl 3,4,5-trihydroxybenzoate, and the molecular formula is C10H12O5, SDS of cas: 121-79-9.
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