FINDIK YAĞININ FT-NIR, FT-MIR VE RAMAN SPEKTROMETRELERİ İLE BİRLİKTE ÇOK BİLEŞENLİ VERİ ANALİZLERİ KULLANILARAK DOĞRULANMASI

Abstract

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