Abstract
Fatty acids are potential biomarkers of some diseases and also key markers and quality parameters of different dietary fats and related products. Thus, untargeted fatty acid profiles are important in the study of dietary fat quality and fat-related diseases, as well as in other fields such as bioenergy. In addition, accurate identification of unknown components is a technological breakthrough for the selected ion monitoring (SIM) mode for untargeted profiles. In this study, we developed untargeted fatty acid profiles based on SIM. We also investigated mass spectral characteristics and equivalent chain lengths (ECL) to eliminate the influence of non-FAMEs for identifying fatty acids in samples. As an application example, fatty acid profiles were used to classify three edible vegetable oils. The results indicated that SIM-based untargeted fatty acid profiles could yield accurate qualitative and quantitative results for more fatty acids and benefit related studies of metabolite profiles.
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