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Sensors 2015, 15(9), 21660-21672; doi:10.3390/s150921660

Unmasking of Olive Oil Adulteration Via a Multi-Sensor Platform

1
Center for Integrated Research—CIR, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico, Via Alvaro del Portillo 21–Rome 00128, Italy
2
Center for Integrated Research—CIR, Unit of Food Science and Human Nutrition, Università Campus Bio-Medico, Via Alvaro del Portillo 21–Rome 00128, Italy
3
Department of Industrial and Information Engineering and Economics, University of L'Aquila, Via Gronchi 18–L'Aquila 67100, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Arun Bhunia
Received: 27 May 2015 / Revised: 29 July 2015 / Accepted: 26 August 2015 / Published: 31 August 2015
(This article belongs to the Special Issue Sensors for Food Safety and Quality)
View Full-Text   |   Download PDF [2464 KB, uploaded 31 August 2015]   |  

Abstract

Methods for the chemical and sensorial evaluation of olive oil are frequently changed and tuned to oppose the increasingly sophisticated frauds. Although a plethora of promising alternatives has been developed, chromatographic techniques remain the more reliable yet, even at the expense of their related execution time and costs. In perspective of a continuous increment in the number of the analyses as a result of the global market, more rapid and effective methods to guarantee the safety of the olive oil trade are required. In this study, a novel artificial sensorial system, based on gas and liquid analysis, has been employed to deal with olive oil genuineness and authenticity issues. Despite these sensors having been widely used in the field of food science, the innovative electronic interface of the device is able to provide a higher reproducibility and sensitivity of the analysis. The multi-parametric platform demonstrated the capability to evaluate the organoleptic properties of extra-virgin olive oils as well as to highlight the presence of adulterants at blending concentrations usually not detectable through other methods. View Full-Text
Keywords: olive oil authentication; olive oil adulteration; artificial sensorial system; food quality control; gas analysis; liquid analysis; BIONOTE (BIOsensor-based multisensorial system for mimicking Nose; Tongue and Eyes) olive oil authentication; olive oil adulteration; artificial sensorial system; food quality control; gas analysis; liquid analysis; BIONOTE (BIOsensor-based multisensorial system for mimicking Nose; Tongue and Eyes)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Santonico, M.; Grasso, S.; Genova, F.; Zompanti, A.; Parente, F.R.; Pennazza, G. Unmasking of Olive Oil Adulteration Via a Multi-Sensor Platform. Sensors 2015, 15, 21660-21672.

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