The present thesis focuses on differentiating between young semi – young red Peruvian wines and the differentiation of these wines with possibly adulterated wines, using an electronic nose consisting of an arrangement of 10 tin oxide – based sensors doped with Pt and coated with zeolite-Y. The characterization of these materials is performed by FRX, DRX, ATR, FTIR, SEM-EDX, TGA-DTGA, adsorption-desorption of N2, DRX and AA. A computational study of the interaction of the active centers of the zeolite with alcohols and with some volatile components of the wines is carried out, evaluating the adsorption energy for each interaction using the Gaussian program 09.The sensing of the alcohols is performed by the Labview software, of the commercial wines and possibly adulterated wines using the electronic nose, under optimum conditions of temperature, sensing time, concentration of the metallic phase in the doping of the sensor with and without covering of Zeolite.The best response signals from the sensors are obtained in the presence of 12 % ethanol and 3 % methanol. The best sensing of temperature is 260 °C and the best sensors are S-0,1 %Pt/SnO2; S-0,2 %Pt/SnO2; S-0,1 %Pt/SnO2/ZY and S-0,2 %Pt/SnO2/ZY. The data obtained are processed through Principal Component Analysis (PCA).This method is a statistical treatment that allows to reduce the dimensionality of a set of initial data, so that the total variance is as large as possible, the analysis of these new variables serves to obtain a characteristic pattern of a given sample that when is compared with others, allow to observe variations based on an initial pattern.The PCA obtained from the data of the measurements of the wines using the best sensors, show a higher variance and a better differentiation of the commercial wines of the wines possibly adulterated, whereas it is possible to differentiate better the commercial wines by brand and type (red and rose).