Cacha¸ca is a type of distilled drink from sugarcane with great economic importance. Its classification
includes three types: aged, premium and extra premium. These three classifications are
related to the aging time of the drink in wooden casks. Besides the aging time, it is important
to know what the wood used in the barrel storage in order the properties of each drink are
properly informed consumer. This paper shows a method for automatic recognition of the type
of wood and the aging time using information from a computer vision system and chemical
information. Two algorithms for pattern recognition are used: artificial neural networks and
k-NN (k-Nearest Neighbor). In the case study, 144 cacha¸ca samples were used. The results
showed 97% accuracy for the problem of the aging time classification and 100% for the problem
of woods classification.info:eu-repo/semantics/publishedVersio
