Edible oils and fats are one of the foods most frequently counterfeited in many countries. Therefore, monitoring
the authenticity and overall quality of these products is ultimately required. Chemometric analyses, such as Partial Least Square (PLS), Linear Discriminant Analysis (LDA), Soft Independent Modeling of Class Analogy (SIMCA),
and others, applied to vibrational spectroscopic data have enabled the development of methods useful to assess
quality aspects (authenticity, adulteration, free fatty acids and trans content, iodine, peroxide and saponification
values, and others) of edible fats and oils. The methods are potential analytical tools for industries and inspection
agencies for characterization of samples during the development, processing, quality control and inspection of
oils and fats. In this original review, applications of near, mid and Raman infrared spectroscopy combined with
multivariate analysis to authenticate, detect adulteration and determine intrinsic quality parameters in edible
fats and oils are discussed.