The objective of this study was to investigate the possibility of predicting the quality parameters of tomato by mid-infrared spectroscopy. For 2 years, tomato samples, representing a large variability in the chemical composition, were scanned using the attenuated total reflectance accessory of a Fourier transform spectrometer in the wavenumber region between 4000 and 400 cm−1. Calibration models were developed using partial least squares (PLS) regression method and were tested with internal validation sample set in the first year. Different spectral preprocessing techniques were investigated and different spectral regions were selected to optimise the calibration models. In addition, the models obtained in 2007 were used to predict the soluble solids, dry matter and total acidity in tomato harvested in 2008. The regression models of the spectra showed reasonable ability to estimate the dry matter, soluble solids, total acidity, citric acid and individual sugars contents in tomatoes grown in 2007, with high coefficients of determination (from 0.98 for soluble solids to 0.92 for fructose) and low percentage errors of prediction (from 3% to 7% for soluble solids and citric acid, respectively). By contrast, the predictive capability of model for malic acid was unsatisfactory with error of prediction of 26%. When the best calibration models from 2007 were used to predict the selected parameters in tomato picked in 2008, very high correlations were obtained, confirmed by low errors of prediction, from 4% to 7% for dry matter and total acidity, respectively. Mid-infrared spectroscopy is an attractive alternative for standard methods for determination of internal quality parameters in tomato