Fast determination of extra-virgin olive oil acidity by voltammetry and Partial Least Squares regression

Abstract

In this paper, an approach for the detection of extra-virgin olive oil (EVOO) free-acidity, based on combination of voltammetric profiles (Voltammetry) and Partial Least Squares (PLS) multivariate regression, is described. Voltammetric measurements are performed with a 12.5 μm radius platinum microdisk, directly in the oil samples mixed with 0.5 M of the room temperature ionic liquid (RTIL) tri-hexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, which acted as a supporting electrolyte, and allows achieving a suitable conductivity in the matrices. Multivariate regression is performed directly on full voltammetric responses recorded over a properly chosen negative potential range and scan rate, where essentially all free fatty acids, characterizing EVOOs, can be reproducibly reduced. PLS regression models are built by employing Italian EVOO samples training sets at different acidity levels (over the range 0.2% w/w - 1.5% w/w; (% w/w) represents mass percentage) and optimized by choosing the optimal complexity, in terms of number of latent variables (LVs). The free-acidity prediction is made through a multivariate model, constructed by using standards of known acidity (determined by the official volumetric titration method) and validated on an external sample set. To show the validity of the proposed method, the PLS/Voltammetry predictions of the free-acidity of a series of commercially available Italian EVOOs, ranging from 0.2 to 0.41 %w/w, are obtained and the values compared with those determined by the official titration approach. Differences found between the two methods are within 5% RSD.