The aim of this work is to study the chemical and functional characterization of balsamic vinegar of Modena (BVM) and traditional balsamic vinegars from Modena (TBVM), using different methods to assay the phenolic content and the antioxidant activity. Besides, NMR analysis was used to obtain information about the principal substances in the samples. One hundred and nine samples of both TBVM and BVM were analyzed in all. Despite the observed high intragroup variability, the statistical analysis showed statistically significant differences between TBVM and BVM. The TBVMs are richer in phenolics, flavonoids, and tannins and show higher antioxidant capacity than BVMs. The general discriminant analysis (GDA) model including all the compositional and NMR data was able to group the samples according to the type of vinegar. The first canonical discriminant function explains 92.2 % of the total variance, and the leave-one out cross-validation show a predictive capacity of 89.6 %.

Antioxidant Activity, Phenolic Compounds, and NMR Characterization of Balsamic and Traditional Balsamic Vinegar of Modena

MAIETTI, Annalisa
Primo
;
TEDESCHI, Paola;BONETTI, Gianpiero;BRANDOLINI, Vincenzo
Penultimo
;
2015

Abstract

The aim of this work is to study the chemical and functional characterization of balsamic vinegar of Modena (BVM) and traditional balsamic vinegars from Modena (TBVM), using different methods to assay the phenolic content and the antioxidant activity. Besides, NMR analysis was used to obtain information about the principal substances in the samples. One hundred and nine samples of both TBVM and BVM were analyzed in all. Despite the observed high intragroup variability, the statistical analysis showed statistically significant differences between TBVM and BVM. The TBVMs are richer in phenolics, flavonoids, and tannins and show higher antioxidant capacity than BVMs. The general discriminant analysis (GDA) model including all the compositional and NMR data was able to group the samples according to the type of vinegar. The first canonical discriminant function explains 92.2 % of the total variance, and the leave-one out cross-validation show a predictive capacity of 89.6 %.
Davide, Bertelli; Maietti, Annalisa; Giulia, Papotti; Tedeschi, Paola; Bonetti, Gianpiero; Riccardo, Graziosi; Brandolini, Vincenzo; Maria, Plessi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2279020
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