Quality control of raw tomatoes in industry is still mainly based on visual screening (for colour and fruit decay) and soluble solids content (SSC). Our current studies aimed at assessing the accuracy of mid-infrared (MIR) spectroscopy as a rapid and convenient tool to predict quality traits for the tomato industry. First, we assessed the ability of MIR to predict not only SSC, but also other biochemical traits of raw tomatoes. Therefore, MIR spectroscopy (4000-650 cm(-1)) coupled with chemometrics using partial least squares (PLS) was correlated with classical measurements, and its potential was assessed by calculating the coefficient of determination (R-2) and the root-mean-square error of cross-validation (RMSECV). Using a wide sampling strategy considering cultivars, ripening stages (from mid to overripe), two production areas (south-west and south-east of France) and irrigation practices, we showed a good ability to estimate not only SSC (error of 3.5%), titratable acidity (TA) (4.4%) and dry matter (4.3%), but also individual sugars (glucose, 4.7%, and fructose, 7%) and citric acid (7%) in fresh tomato purees. For malic acid, the higher error of prediction (14%) was probably related to its low level in tomatoes. Second, we evaluated the ability of MIR spectroscopy to discriminate cooked samples according to the origin of the raw material (varieties, maturity stages, production area) and to processing methods (discrimination between hot-break (HB) and cold-break (CB) samples). Therefore, tomatoes harvested in 2015 were processed using standard HB or CB modes, and then analysed using MIR spectroscopy. Multivariate analyses allow for clear discrimination between processing methods, production area and cultivars. This study indicates that MIR spectroscopy allows for 1) a considerable gain in analysis time compared with current methods, and 2) a prediction of a more detailed description of quality parameters than only global measurements such as SSC or dry matter. MIR spectroscopy could be developed as an efficient tool for quality control of raw material, as is already the case for other food industries, and might also be developed for quality control of processed products.