A new electrochemical sensor for extra-virgin olive oils classification. (March 2020)

• Record Type: Journal Article
• Authors: Zappi, D.; Sadun, C.; Gontrani, L.; Dini, D.; Antonelli, M.L.
• Is Part Of: Food control. Volume 109(2020)
• Publication Date: 2020-03
• Subjects: Olive oils -- Cultivar -- Sensor -- Bio-based RTIL -- Nanomaterials -- Screen-printed electrode; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2019.106903
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: A screen-printed electrode was modified using multi-walled carbon nanotubes (MWCNT) and titanium oxide nanoparticles (TiO2 ), with a bio-based ionic liquid (RTIL) as a drop-casting medium. The RTILs here used have been proved to be useful for immobilizing nanomaterials on the working electrode surface. The proposed platform has been used to analyze extra-virgin olive oils (EVOOs), produced with olives of known cultivar and geographic origin. The EVOOs were produced with the olives that have been collected in the Italian region of Lazio during 2016, 2017 and 2018 harvesting seasons. The analyses of the oils were done by means of cyclic voltammetry measures. The results here obtained encourage the establishment of criteria for the classification of oils in terms of the corresponding cultivar. Both the electrode modification and the olive oil analysis do not involve any organic solvents. Therefore, the proposed approach represents an environmentally friendly method for field analyses of EVOOs. Highlights: Screen-printed electrode modified with nanomaterial and bio-based RTIL. 42 single-cultivar olive oil samples from three harvesting seasons. Platform performs quick and easy measures with minimal sample pre-treatment. Discrimination of olive oils based on cultivar was obtained with proposed platform.