Paprika powder is a widely consumed spice, making it an attractive target for adulteration, which is not easily detected. In this study, a portable near-infrared (NIR) spectrometer was used for fast detection of paprika adulteration. Nine paprika samples from five suppliers were adulterated with potato starch, acacia gum and annatto at different concentrations (0–36% by weight of potato starch and acacia gum, and 0–18% by weight of annatto). The NIR spectrum of each mixture (n = 315) was used as predictors to determine adulteration by partial least squares-discriminant analysis (PLS-DA) and partial least squares regression (PLSR). First, PLS-DA was applied to discriminate between adulterated and non-adulterated samples, as well as the type of adulterant. This method proved to be efficient, with specificity greater than 90 % and error rate lower than 2 %, for all models constructed. PLSR was used to predict the concentration of adulterants in paprika samples. In addition, PLSR models with reduced number of wavelengths (predictors) were built by selecting the variables with larger weights on the regression coefficients. Coefficient of prediction (R2p) and root mean square errors of prediction (RMSEP) obtained were 0.95 and 2.12; 0.97 and 1.68; 0.87 and 1.74, for potato starch, acacia gum and annatto, respectively. In conclusion, results showed that NIR spectroscopy is a useful screening technique for identification and quantification of adulteration in paprika.