Adulteration detection of corn oil, rapeseed oil and sunflower oil in camellia oil by in situ diffuse reflectance near-infrared spectroscopy and chemometrics

Abstract Camellia oil is always found to be adulterated with corn oil, rapeseed oil, and sunflower oil in the market. In this study, a new, real-time, and quantitative detection method for such adulteration was developed based on in situ near-infrared (NIR) spectroscopy and chemometrics. After the first derivative pretreatment of spectra, discriminant analysis (DA) successfully identified cheap oils’ types adulterated in CAO with the accuracy of 96.7%. Excellent prediction performance of adulteration levels was obtained by partial least square (PLS) after optimization with different pretreatment methods, including multiple scatter correction, standard normal variate, Savitzky-Golay smoothing, and normalization, with the determination coefficient (R2) higher than 0.995, root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) lower than 6.79 and 4.98 respectively. Overall, this study provided an in situ NIR method as a real-time monitoring tool to replace traditional qualitative testing and manual sampling, for the authenticity determination of CAO.