AUTHENTICATION OF HAZELNUT OIL BY PORTABLE FT-NIR, FT-MIR AND RAMAN SPECTROMETERS COMBINED WITH MULTIVARIATE DATA ANALYSIS

This research studied the authentication of hazelnut oil by portable FT-NIR, FT-MIR, and Raman spectrometers. Hazelnut oils were adulterated with vegetable at various concentrations (0-25%) (w/w). Collected spectra analyzed using Principal Component Analysis (PCA) Soft Independent Modelling Class Analogy (SIMCA) to generate classification models authenticate pure Partial Least Squares Regression (PLSR) predict fatty acids adulterant levels. For confirmation, oil’s acid profile was determined gas chromatography. In all three instruments, SIMCA provided distinct clusters for samples interclass distance (ICD)3. All instruments showed excellent performance in predicting adulteration levels rval>0.93 standard error prediction (SEP)<1.75%. Specifically, FT-MIR unit best performances. Still, units can be used as an alternative traditional methods. These great potential in-situ surveillance detect adulterations.