transversal data analytics for bio-product fermentation

In the case of this project, the goal is to first learn automatically the parameters that affect the alcoholic fermentation process controlling in this way the final quality and flavor of wine; and second, allow better decision making solutions for producers depending on their target market. The first step of this project consists of the collection experimental data on wine fermentation from SPO. On the same time, a deep study in collaboration with Prof. Kenneth N. Brown and Dr. Steven Prestwich on the existing approaches proposed already on similar problems is going to take place. Once the data are selected, different approaches in the context of data analytics are going to be tested having as final goal to identify the approaches that are more adapted to the specific needs of this project. Finally, a transversal approach, that exploits the benefits of existing approaches while introducing new missing features for better data analytics, is going to be proposed.