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Multi-disciplinary experimental model for the characterization of the "fermentation" system

Paolo Capra, Ever Srl | Paolo Antoniali, Italiana Biotecnologie Srl | Marco Roverso, University of Padua | Nicola Biasi, Nicola Biasi Consulting

Multi-disciplinary experimental model for the characterization of the "fermentation" system

"Learning from wine" means making innovation and research together with oenologists and producers; collaborating and sharing knowledge to preserve and improve the quality of Wine every day.

After ten years of the Y-TEAM program to develop the quality of yeast and its derivatives for oenological fermentation, Paolo Capra of Ever presents WINE-LEARNING: an innovative experimental, multi-disciplinary model for characterizing the "grape-fermentation-wine" system. 

Predicting the progress of a fermentation is extremely useful and allows appropriate corrective measures to be taken, where necessary, to ensure that winemaking ends successfully, whether it is primary fermentation or secondary fermentation for sparkling wine production.
In order to develop a robust, flexible and reliable predictive model of wine fermentation, it is necessary to have a large database that includes data inherent to fermentations of a range of grape varieties, from different areas and vintages; information regarding the treatment of musts or base wines, the yeast strain used and the nutrition employed and, last but not least, the operating conditions adopted.
Several mathematical models focusing on must composition and yeast physiology have been proposed to predict the kinetics of alcoholic fermentation. These models require the estimation of a large number of parameters, which can make them difficult to apply in an industrial winery situation and, in particular, during harvest.
The WINE LEARNING project, rather than defining a predictive model of wine fermentation, outlines an empirical diagnostic system that contributes, through a practical approach and experimental observation, to characterize the state of the "grape-fermentation-wine" system and to define thoughtful operational choices prior to fermentations.

This is followed by a presentation by Paolo Antoniali, Italiana Biotecnologie Srl, in which he delves into the experimental model, from the characterization of musts (chemistry, trace elements, aromatic precursors), to that of wines (chemistry and aromatics), through real-time monitoring of fermentations.

Marco Roverso explains the measurement of thiols, through the method in UPLC-MS: this is the study and implementation of the method for the determination and quantification of thiols in wines carried out by the University of Padua, of which the young chemical sciences researcher is a member. 

Nicola Biasi, Nicola Biasi Consulting, closes with the case study and results of three-year experience of predictive harvesting at the MASUT DA RIVE winery (Sauvignon Blanc wines).

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Recordings of the module run in collaboration with Ever held during Enoforum Italia 2023 from May 16-18, 2023

Published on 07/12/2023
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