The correlation between the chemical composition and the sensory data for 28 cachaça samples was investigated using principal component analysis (PCA). A chemical model was then developed using linear discriminant analysis (LDA) to classify the distillate samples according to their sensory qualities. This model presented predictive abilities of calibration and validation of 87.4 and 100%, respectively, and was able to recognize correctly 7 out of 9 additional samples according to their sensory evaluations, showing itself as a potential alternative tool of recognizing cachaça sensory qualities.
sugarcane spirits; cachaça sensory and chemical properties; multivariate analysis