Integration of LC-HRMS and H NMR metabolomics data fusion approaches for classification of Amarone wine based on withering time and yeast strain.

Two untargeted metabolomics approaches (LC-HRMS and H NMR) were combined to classify Amarone wines based on grape withering time and yeast strain. The study employed a multi-omics data integration approach, combining unsupervised data exploration (MCIA) and supervised statistical analysis (sPLS-DA). The results revealed that the multi-omics pseudo-eigenvalue space highlighted a limited correlation between the datasets (RV-score = 16.

Absence of allergenic residues in experimental and commercial wines fined with caseinates.

The possible presence of allergenic residues in wines treated with one of the potassium caseinates used as fining agents has been investigated. Samples of experimental (16) and commercial (63) wines that had been fined with caseinates with or without bentonites were studied. The leading physicochemical characteristics of each wine sample were determined to assess their possible role in promoting or hindering the elimination of allergenic residues.