Application of three spectroscopic techniques, ATR (attenuated total reflection), NIR (near infrared) and DRIFTS (diffuse reflectance infrared FT spectroscopy), in combination with chemometrics for detection of pasta adulteration and egg content determination is reported. The results indicate that PLS models based on ATR spectra allow for determination of the number of eggs in pasta with an RMSEP (root mean square error of prediction) error of the order of 0.1 egg/kg for pasta containing from 1 to 6 eggs per kilogram of flour. This error is found to be 2 times higher for two other techniques used. Partial least squares discriminant analysis (PLS-DA) based on vibrational spectra conducted for a set of samples including pasta adulterated by addition of vegetable oil or lecithin showed that all applied techniques enable fast and reliable detection of adulterated samples as well as pasta samples without eggs, again the most reliable model was obtained for ATR data.