In this work, the ability of an electronic tongue based on Fourier-Transform Mid Infrared (FT-MIR) spectroscopy as a gustative sensor is assessed by emulating the responses of a tasting panel for the gustative mouthfeel "tannin amount". The FT-MIR spectra were modeled against the sensory responses evaluated in 37 red wines by means of partial least squares (PLS) regression models. In order to find the wavenumbers more correlated with the sensorial attribute and thus providing the best predictive models, six different variable selection techniques were tested. The iterative predictor weighting IPW-PLS technique showed the best results with the smallest RMSEC and RMSECV values (0.07 and 0.13, respectively) using 20 selected wavenumbers. The coincident wavenumbers selected by the six variable selection techniques were interpreted based on the absorption bands of tannin and then a calibration model using these wavenumbers was built to validate the interpretation made.