Discrimination of different oil types and adulterated safflower seed oil based on electronic nose combined with gas chromatography-ion mobility spectrometry

Due to its high food value, safflower seed oil (SSO) is easily adulterated by using other edible oils, which poses a serious threat to human health and determines economic losses. In the present study, electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS) were applied in the analysis of SSO adulterated with various proportions of three edible oils (sunflower oil, soybean oil, corn oil). E-nose data was shown to be effective in clustering different edible oils and distinguishing between pure and adulterated oils using linear discriminant analysis (LDA), albeit with poor performance in quantitative analysis of adulteration rates by partial least squares (PLS). GC-IMS analysis was also performed to determine the volatile fingerprinting of the five edible oils and the adulterated oils. Principal component analysis (PCA) enabled distinction between the five edible oils and clustering of samples with different adulteration rates. Moreover, the PLS model based on GC-IMS data led to adequate differentiation of adulteration rates in SSO. This study is the first comprehensive report on SSO adulteration detection employing GC-IMS and E-nose methods, and provides a basis for assessing the quality of SSO available on the market.