Classification of single-cultivar Tunisian olive oils according to the geographical origin using an electronic tongue

• Author(s): Souayah, Fatma ; Rodrigues, Nuno ; Veloso, Ana C. A. ; Dias, L. G. ; Oueslati, Souheib ; Oueslati, Souheib ; Peres, António M.
• Date: 2017
• Persistent ID: http://hdl.handle.net/1822/64736
• Origin: RepositóriUM - Universidade do Minho
• Project/scholarship: info:eu-repo/grantAgreement/FCT/5876/147416/PT; info:eu-repo/grantAgreement/FCT/5876/147337/PT; info:eu-repo/grantAgreement/FCT/5876/147451/PT
• Document Type: Conference poster
• Language: English
• Contributor(s): Universidade do Minho

Description

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.

info:eu-repo/semantics/publishedVersion