A multivariate approach to evaluating the chemical and sensorial evolution of South African Sauvignon Blanc and Chenin Blanc wines under different bottle storage conditions. (November 2019)

• Record Type: Journal Article
• Authors: Mafata, Mpho; Brand, Jeanne; Panzeri, Valeria; Kidd, Martin; Buica, Astrid
• Is Part Of: Food research international. Volume 125(2019)
• Publication Date: 2019-11
• Subjects: Chenin Blanc -- Sauvignon Blanc -- Pivot profile -- Storage conditions -- Aroma stability -- Multivariate data analysis -- Regression vector coefficient; DTDP 4, 4′-Dithiodipyridine -- RV regression vector -- PLS partial least squares -- PCA principal component analysis -- MDS multidimensional scaling -- CA Correspondence analysis -- ANOVA analysis of variance -- MANOVA multivariate analysis of variance; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2019.108515
• Languages: English
• ISSNs: 0963-9969

Abstract

Abstract: Volatile compound composition contributes to the aroma profile of wine and is susceptible to change due to oxidation which may occur during storage and transportation, especially at high temperatures. Changes in sensory attributes may also occur, altering the sensory profile of wine. Classical univariate analysis only looks at the deviations for one factor at a time and may overlook the overall effect of treatments. In this study, changes in South African Sauvignon Blanc and Chenin Blanc wine sensory profile, volatile and antioxidant-related parameters resulting from storage under different temperatures (room temperature, 15 °C and 25 °C) and durations (0, 3 and 9 months) were investigated using a multivariate approach. Bottled, unwooded wines of both cultivars from six wineries were used. As expected, the chemical evolution of the wines was characterised by increases in absorbance at 420 nm (browning), colour density and hue with prolonged storage at high temperatures. To be able to compare the evolution of the sample sets regardless of the initial (T0/control) wine profile and composition, multivariate regression analysis in the form of regression vector (RV) coefficients were used to assess the correlations in the sensory and chemical changes relative to the control in each set. Using Pivot©Profile for the first time in this type of stability assessment and applying a new algorithm for data handling in addition to the classical one, this study showed that prolonged exposure to higher temperatures resulted in the change from fruity to toasted aroma attributes. Graphical abstract: Unlabelled Image Highlights: White wine evolution was modelled by Multivariate Regression Analysis. RV coefficients on Pivot©Profile and chemical data mapped the changes. Evolution of Chenin Blanc wines was more uniform than that of Sauvignon Blanc. Multivariate regression results demonstrated optimal storage conditions.