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Wine fermentation in-process monitoring system (WIPS)

Final Report Summary - WIPS (Wine fermentation In-Process monitoring System)

The quality of wine is largely determined during the fermentation process, which can be monitored to control quality and identify any corrective actions that might be required. Information that needs to be collected is related to the fermenting must that impacts the process kinetics and provides an indication of the final product. Relevant measurements are usually performed in the laboratory, being often affected by manual errors or significant time delays. An improved strategy would be to provide real time measurements which, if combined with mathematical models, would predict the time evolution of the process and, consequently, improve the final product quality by minimising costs and reducing risks.

The WIPS project took into account state of the art research as well as the needs and requirements of small and medium size wine producers in order to design, develop and test a computer assisted system to survey the fermentative processes, both alcoholic and malolactic, in wine production. More specifically, the project objectives were to:

1. improve wine quality and increase the efficiency of winemakers to meet the challenges of the present global market
2. enable vineyards in marginal wine growing regions to improve their products, thereby assisting regional economies
3. forge links between research institutions that could be used to add existing and develop new biosensors based on the knowledge produced via the WIPS system
4. offer high quality, simple to operate analysis with low capital and user costs to winemakers without extensive laboratory facilities
5. apply information technologies that could manage significant data amounts in real time.

A multidisciplinary consortium of partners was set up, including small and medium size enterprises (SME) and research and technological developers (RTD), in order to achieve the project goals.

Low cost sensors were installed inside fermentation tanks and provided data on temperature and pressure variations and carbon dioxide flux. A questionnaire was prepared and distributed to identify additional parameters that should be monitored in response to producers' needs. Moreover, a series of mathematical models of primary and secondary fermentation were determined and validated. A monitoring and prediction system was also developed, composed by the combination of online identification of the fermentation model with a multi sensor data fusion (MSDF) system that integrated information from different sources. The system proved to be robust to failures and provided optimal estimates of the process kinetics. The secondary fermentation process was controlled offline, via novel electrochemical biosensors for the selective, fast and easy measurement of sugars and acid detection.

The proposed innovations were evaluated in two test facilities following a set of preliminary experiments. The results on prototype sensors and methods for measuring the lactic acid were compared and validated using the so-called enzymatic method with spectroscopic detection. In addition, the developed monitoring and prediction software, including a measurement system, a computer programme and databases for information storage and management, was successfully assessed.