Quality attributes analysis and authentication of Argentinean wine vinegars based on multiple spectral source fusion strategies.

WAGNER, MARCELO; ORTIZ, DANIELA; ZALDARRIAGA HEREDIA, JORGELINA; MONTEMERLO, ANTONELLA; SILVANA MARIELA AZCARATE; CAMIÑA, JOSÉ MANUEL

Congreso; 5. 20th ENQA ? Brazilian Meeting on Analytical Chemistry and 8th Congresso iberoamericano de Química Analítica; 2022

Wine vinegars are highly valued mainly regarding the implemented acetification process. From atechnological point of view, there are two production methods: submerged cultivation method, whichis used in the industry to quickly obtain low-quality vinegars, and traditional method, in which theacetic fermentation is carried out inside wooden barrels, which are filled with wine to ferment, givingrise to high-quality vinegars that are more appreciated for their greater organoleptic complexity1.Particularly in Argentina, most wine vinegars are made through industrial fermentation processesand few of them are produced in a traditional way but without added value2. Currently, the searchfor fast, accurate and low-cost determinations makes UV-Vis and near-infrared (NIR) spectroscopiesone of the most popular alternatives to determine the concentrations of chemical compounds as wellas for authenticity studies3.The aim of this work was to develop an analytical methodology based onUV-vis and NIR measurements in combination with multi-block analysis to quantify a multiparametric analysis for the quality control of wine vinegars and, additionally, to differentiate themaccording to the implemented production method. Different determinations that are normally usedfor the quality control of these products were carried out applying standard methods. For vinegars,the following results were obtained: total acidity 3.70-6.82%, fixed acidity 0.11-1.08%, volatile acidity3.63-6.70%, pH 2.49 - 3.07 and polyphenol concentration 0.1 1.98 g/L eq. Ac. Gallic. Spectra of eachsample were obtained from direct measurement for NIR (944-1670nm) and by dilution for UV-Vis(178-890nm). With the information generated, predictive models were built for the quantification ofeach parameter through partial least squares (PLS) regression analysis with each data set obtainedby each individual technique. Likewise, in order to exploit the particularities of the different datablocks, different data fusion strategies (low and mid-level) were performed and compared. Thepredictive capacity of each model was evaluated from the calibration regression coefficients (R2),the mean square errors of calibration (RMSEC), cross-validation (RMSECV) and prediction(RMSEP), as well as the percentage error of prediction (REP). The best results were achieved whenthe mid-level data fusion strategy with SO-PLS was applied. All the parameters analyzed showedREP values below 12%. From spectral data, a classification approach to differentiate and classifyvinegars produced by traditional and industrial systems was conducted. Principal componentanalysis (PCA) and SO-PLS discriminant analysis (PLS-DA) were performed on the data set asexploratory and classification analysis, respectively. From PCA, a clear differentiation of the samplesof wine vinegars produced industrially from those produced traditionally was observed, and theclassification analysis using SO-PLS-DA yielded a correct classification rate of 96%. The synergisticcombination of spectral information and chemometrics can be a powerful tool to perform a qualitycontrol of wine vinegars and to verify the type of acetification carried out for its production. However,future studies involving a larger number of samples are needed to validate the results andconclusions presented here, in order to allow the implementation of this methodology in thecertification of these products.