Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach

Abstract

The capabilities of dynamic headspace entrainment followed by thermal desorption in combination with gas chromatography (GC) coupled to single quadrupole mass spectrometry (MS) have been tested for the determi- nation of volatile components of olive oil. This technique has shown a great potential for olive oil quality classi fi cation by using an untargeted approach. The data processing strategy consisted of three di ff erent steps: component detection from GC – MS data using novel data treatment software PARADISe, a multivariate analysis using EZ-Info, and the creation of the statistical models. The great number of compounds determined enabled not only the development of a quality classi fi cation method as a complementary tool to the o ffi cial established method “ PANEL TEST ” but also a correlation between these compounds and di ff erent types of defect. Classi fi cation method was fi nally validated using blind samples. An accuracy of 85% in oil classi fi cation was obtained, with 100% of extra virgin samples correctly classi fi ed