Identifying camellia oil adulteration with selected vegetable oils by characteristic near-infrared spectral regions

In this paper,a methodology based on characteristic spectral bands of near infrared spectroscopy(1000-2500 nm)and multivariate analysis was proposed to identify camellia oil adulteration withvegetable oils,Sunflower,peanut and corn oils were selected to conduct the test.Pure camlia oiland that adulterated with varying concentrations(1-10%with the gradient of 1%,10-40%withthe gradient of 5%,40-100%with the gradient of 10%)of each type of the three vegetable oilswere prepared,respectively.For each type of adulterated oil,full-spectrum partial least squarespartial least squares(PLS)models and synergy interval partial least squares(SI-PLS)modelswere developed.Parameters of these models were optimized simultaneously by cross-validation,The SI-PLS models were proved to be better than the full-spectrum PLS models.In SI-PLSmodels,the correlation coefficients of predition set(Rp)were 0.9992,0.9998 and 0.9999 foradulteration with sunflower oil,peanut oiloil seperately;the corresponding root meansquare errors of prediction set(RMSEP).66nd 0.37.Furthermore,a new genericPLS model was built based on the chalselected from the intervals of thethree SI-PLS models to identify the oil adulterantsardless of the adultrated oil types.Themodel achieved with Rp=0.9988 and RMSEP==1.52,These results indicated that the charac-teristic near infrared spectral regions could determine the level of adulteration in the camllia oil.