Abstract

The adulteration concentration of palm kernel oil (PKO) in virgin coconut oil (VCO) was quantified using near-infrared (NIR) hyperspectral imaging. Nowadays, some VCO is adulterated with lower-priced PKO to reduce production costs, which diminishes the quality of the VCO. This study used NIR hyperspectral imaging in the wavelength region 900–1,650 nm to create a quantitative model for the detection of PKO contaminants (0–100%) in VCO and to develop predictive mapping. The prediction equation for the adulteration of VCO with PKO was constructed using the partial least squares regression method. The best predictive model was pre-processed using the standard normal variate method, and the coefficient of determination of prediction was 0.991, the root mean square error of prediction was 2.93%, and the residual prediction deviation was 10.37. The results showed that this model could be applied for quantifying the adulteration concentration of PKO in VCO. The prediction adulteration concentration mapping of VCO with PKO was created from a calibration model that showed the color level according to the adulteration concentration in the range of 0–100%. NIR hyperspectral imaging could be clearly used to quantify the adulteration of VCO with a color level map that provides a quick, accurate, and non-destructive detection method.

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