The result of this work is important for the wine industry. At the
certification phase and by Portuguese law, the sensory analysis has to
be performed by human tasters. Yet, the evaluations are based in the
experience and knowledge of the experts, which are prone to
subjective factors. The proposed data-driven approach is based on
objective tests and thus it can be integrated into a decision support
system, aiding the speed and quality of the oenologist performance.
For instance, the expert could repeat the tasting only if her/his grade is
far from the one predicted by the DM model. In effect, within this
domain the T=1.0 distance is accepted as a good quality control
process and, as shown in this study, high accuracies were achieved for
this tolerance. The model could also be used to improve the training of
oenology students. Furthermore, the relative importance of the inputs
brought interesting insights regarding the impact of the analytical
tests. Since some variables can be controlled in the production process
this information can be used to improve the wine quality. For instance,
alcohol concentration can be increased or decreased by monitoring
the grape sugar concentration prior to the harvest. Also, the residual
sugar in wine could be raised by suspending the sugar fermentation
carried out by yeasts. Moreover, the volatile acidity produced during
the malolactic fermentation in red wine depends on the lactic bacteria
control activity. Another interesting application is target marketing
[24]. Specific consumer preferences from niche and/or profitable
markets (e.g. for a particular country) could be measured during
promotion campaigns (e.g. free wine tastings at supermarkets) and
modeled using similar DM techniques, aiming at the design of brands
that match these market needs.