Pistachio is one of the most expensive nuts with having high economic importance in Turkey. It has become more prone to adulteration because of its high commodity value. Peanut with color additives and green pea are generally used to adulterate ground pistachio. Vibrational spectroscopy is a potential technique to detect adulterations in pistachio. The objective of this study was to generate a non-targeted method for portable FT-IR and UV–Vis spectrometers to authenticate pistachio and detect green pea and peanut adulterations. Pistachio granules were adulterated with green pea and peanut at different concentrations (5 to 40% w/w). Spectra were collected by a portable FT-IR spectrometer and by a conventional UV–Vis spectrometer and analyzed by Soft Independent Modeling of Class Analogy (SIMCA) to generate classification algorithms to authenticate pistachio, and Partial Least Square Regression (PLSR) to predict the concentrations of adulterants. SIMCA showed very distinct clusters for pure samples. Moreover, adulterated pistachio samples were discriminated by SIMCA even in low levels of adulteration (5%). Portable FTIR showed excellent performance (rval > 0.93) of predicting the adulterant levels with a standard error of prediction (SEP) 0.66% and 0.80% for green pea and peanut, respectively. Similarly, UV–VIS predicted (rval > 0.93) the adulterant levels with SEP 0.58% and 0.14% for green pea and peanut, respectively. The results supported that portable FT-IR, and UV–Vis units present great potential for real-time surveillance of green pea and peanut adulteration in pistachio.