Abstract: Determination of food authenticity is one of the most crucial issues in food quality control and safety. It touches the consumers’ interests and health. To study on rapid methods for confirming authenticity and classification, in conjunction with greater consumer demands and expectation for safer products, is very important. The objective of this work was to develop a model that would distinguish soybean oils from rapeseed oils, quality rapeseed oils from rancid rapeseed oils according to their type and quality by means of chemical and physical properties with colority, moisture and volatile, density, refractive index, acid value, saponification value and peroxide value as variables. Principal component analysis and cluster analysis plots showed that three different vegetable oils were clustered in distinct groups, while each group could be distinguished clearly. Partial least squares was applied to modeling classes on the basis of the chemical data. The results obtained indicated better performance in terms of classification and prediction for the approaches. These approaches would be useful for primary evaluation of similarity and quality control.

Key words: edible vegetable oils, classification, quality discrimination, pattern recognition