Vinification mining: a case study on wine production

Throughout time wine has performed a relevant role in almost every civilization. Demarcated regions to benefit from an Origin Denomination have to assure that every process on wine production is submitted to a strict control in every phase, since the vineyards till the costumer. The wine vinification process is one of the stages in wine’s production that could influence the achievement of wine’s quality. This assessment is traditionally realized by wine tasters that analyze some organoletic parameters such as colour, foam, flavour and savour being very important for the wine production and for its successful marketing. The use of Data Mining techniques in this field has a great relevance in revealing the importance of the numerous chemical parameters involved in the process of wine production, as well as to define classifying models to determine the parameters based on organoletic parameters from the chemical process of winemaking. The Decision Trees and the Linear Regression were used as Data Mining techniques to achieve the objectives of classification and regression. The experiments were oriented using the new Microsoft's SQL Server 2008 Business Intelligence Development Studio and an open-source Data Minig tool (WEKA). Very good results were achieved, with performances between 85% and 98% for all models