Physico-chemical parameters as possible markers of sensory quality for ‘Barbera’ commercial red wines
Wine quality is defined by sensory and physico-chemical characteristics. In particular, sensory features are very important since they strongly condition wine acceptability by consumers. However, the evaluation of sensory quality can be subjective, unless performed by a tasting panel of experienced tasters. Therefore, it is of great relevance to establish relationships between objective chemical parameters and sensory perceptions, even though the complexity of wine composition makes it difficult. In this sense, more reliable relationships can be found for a particular wine typology or variety. The present study aimed to predict the perceived sensory quality from the physico-chemical parameters of ‘Barbera d’Asti’ DOCG red wines (Italy).
A total of 111 commercial ‘Barbera’ wines from 2015 and 2016 vintages were evaluated by sensory analysis with a trained panel (n = 10). Quality and intensity of color, aroma, and mouthfeel, as well as global quality perception of wines were analyzed using unstructured scales (0-100 mm). After assessing the correlation among the different sensory perceptions analyzed, ‘Barbera’ wines were classified according to global perception values, and three groups were obtained by dividing the unstructured scale range into equal portions: G1 (30-45 mm), G2 (46-61 mm), and G3 (62-77 mm). Twenty-one physico-chemical variables, including standard chemical parameters, phenolic composition, and chromatic characteristics, were determined for the characterization of wines belonging to each sensory profile. Statistical analyses based on ANOVA, Tukey (HSD) test, Pearson correlation, and principal component analysis (PCA) were applied on physico-chemical and sensory data sets.Ten physico-chemical parameters (total anthocyanin index, monomeric anthocyanin content, total flavonoid index, color intensity, the three CIELab color coordinates, alcohol strength, malic acid content, and dry extract) were significantly different among the sensory groups established (G1, G2, and G3). When PCA was applied on these physico-chemical parameters and sensory traits, a good separation of the three sensory groups was observed. Chemical parameters often associated with red wine quality (such as ethanol, dry extract, anthocyanins, and color intensity) were well correlated with the best valued sensory group G3. This study contributes to better know which are the main chemical parameters that allow both to classify the wines according to the perceived sensory profile/quality and to predict some relevant wine sensory traits.
Issue: IVAS 2022
1Dipartimento di Scienze Agrarie, Forestali e Alimentari, Università degli Studi di Torino
2Instituto de Ciencias de la Vid y del Vino (ICVV) Consejo Superior de Investigaciones Científicas CSIC-Universidad de La Rioja-Gobierno de La Rioja
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sensory analysis, phenolic composition, differentiation, prediction, red wines