Repositori URV

Identifier: imarina:6008379

Handle: https://hdl.handle.net/20.500.11797/imarina6008379

Authors:
Cavaglia, JulietaSchorn-Garcia, DanielGiussani, BarbaraFerre, JoanBusto, OlgaAcena, LauraMestres, MontserratBoque, Ricard

Abstract:
Wine production processes still rely on post-production evaluation and off-site laboratory analyses to ensure the quality of the final product. Here we propose an at-line methodology that combines a portable ATR-MIR spectrometer and multivariate analysis to control the alcoholic fermentation process and to detect wine fermentation problems. In total, 36 microvinifications were conducted, 14 in normal fermentation conditions (NFC) and 22 intentionally contaminated fermentations (ICF) with different lactic acid bacteria (LAB) concentrations. ATR-MIR measurements were collected during alcoholic and malolactic fermentations and relative density, pH, and L-malic acid were analyzed by traditional methods. Partial Least Squares Regression could suitably predict density and pH in fermenting samples (root mean squared errors of prediction of 0.0014 g mL(-1) and 0.06 respectively). With regard to ICF, LAB contamination was detected by multivariate discriminant analysis when the difference in L-malic acid concentration between NFC and ICF was in the order of 0.7-0.8 g L-1, before the end of malolactic fermentation. This methodology shows great potential as a fast and simple at-line analysis tool for detecting fermentation problems at an early stage.