Classification of single-cultivar Tunisian olive oils according to the geographical origin using an electronic tongue
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resumo
Developing analytical techniques for EVOO authentication is a
challenging task.
Moreover, if a specific meteorological or geographical factor affects
different geographical regions similarly, olive oils' geographical
discrimination may be a hard task.
Improved classification of olive oils may be achieved by combining
electrochemical fingerprints with multivariate statistical techniques.
In this work, we used an electronic tongue, comprising 40 lipid
membrane sensors, to extract suitable potentiometric fingerprints of
Tunisian monovarietal olive oils that could be used in combination
with linear discriminant analysis to classify olive oils according to the
geographical origin.
The marketing of olive oil is focused to a greater extend on the distinction and
characterization of products according to their geographical origins. Due to the great impact
of geographic, agronomic and technological factors on the physicochemical quality of olive
oils, it is important to be able to discriminate them according to their geographical origins in
order to avoid or minimize the risk of frauds. In this work, it was intended to verify the
capability of an electronic tongue to classify monovarietal Tunisian olive oils (cvs Chemlali or
Sahli) according to geographical origins (i.e. Tunisian districts). For this purpose,
chemometric tools were applied in order to establish linear discriminant models based on
selected sub-sets of potentiometric signals profiles gathered with the electronic tongue. In
this research, 30 samples belonging to the two above-mentioned varieties were analyzed by
the electronic tongue additionally to legally required physicochemical analysis, which
included the free acidity, the peroxide value and the coefficients of extinction K232, K270 and
t::.K. These olive oil samples were grouped according to 3 regions for the Chemlali variety (i.e.
Kairouan, Sidi Bouzid and Sfax- Center Tunisia) and 3 regions as well for the Sahli variety (i.e.
Mahdia, Sousse and Kairouan - North and Center Tunisia). Preliminary results showed that it
was possible to classify Tunisian olive oisl according to the geographical region with a
minimum correct classification rate of 94% for cross-validation procedure. These findings
pointed out the potential use of the electronic tongue as an efficient and low-cost analytical
technique for classifying the Tunisian autochthonous monovarietal olive oils according to
their geographical origin.
