Author/Authors :
Hu، نويسنده , , Wei and Zhang، نويسنده , , Liangxiao and Li، نويسنده , , Peiwu and Wang، نويسنده , , Xiupin and Zhang، نويسنده , , Qi and Xu، نويسنده , , Baocheng and Sun، نويسنده , , Xiaoman and Ma، نويسنده , , Fei-Xiang Ding، نويسنده , , Xiaoxia، نويسنده ,
Abstract :
Edible oil adulteration is the biggest source of food fraud all over the world. Since characteristic aroma is an important quality criterion for edible oils, we analyzed volatile organic compounds (VOCs) in four edible vegetable oils (soybean, peanut, rapeseed, and sunflower seed oils) by headspace comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (Headspace–GC×GC-TOFMS) in this study. After qualitative and quantitative analysis of VOCs, we used unsupervised (PCA) and supervised (Random forests) multivariate statistical methods to build a classification model for the four edible oils. The results indicated that the four edible oils had their own characteristic VOCs, which could be used as markers to completely classify these four edible oils into four groups.
Keywords :
volatile organic compounds , Edible vegetable oil , Classification , Headspace GC×GC–TOFMS , Chemometrics