Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2021 Apr 3

PMID 33806002

Citations 7

Authors

Pablo Cano Marchal

Chiara Sanmartin

Silvia Satorres Martinez

Juan Gomez Ortega

Fabio Mencarelli

Javier Gamez Garcia

Affiliations

Soon will be listed here.

Abstract

The organoleptic profile of a Virgin Olive Oil is a key quality parameter that is currently obtained by human sensory panels. The development of an instrumental technique capable of providing information about this profile quickly and online is of great interest. This work employed a general purpose e-nose, in lab conditions, to predict the level of fruity aroma and the presence of defects in Virgin Olive Oils. The raw data provided by the e-nose were used to extract a set of features that fed a regressor to predict the level of fruity aroma and a classifier to detect the presence of defects. The results obtained were a mean validation error of 0.5 units for the prediction of fruity aroma using lasso regression; and 88% accuracy for the defect detection using logistic regression. Finally, the identification of two out of ten specific sensors of the e-nose that can provide successful results paves the way to the design of low-cost specific electronic noses for this application.

Citing Articles

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Influence of the Degree of Fruitiness on the Quality Assessment of Virgin Olive Oils Using Electronic Nose Technology.

Navarro Soto J, Rico S, Martinez Gila D, Satorres Martinez S Sensors (Basel). 2024; 24(8).

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Assessment of fruity aroma intensity in olive oils from different Spanish regions using a portable electronic nose.

Bianchi A, Cano Marchal P, Martinez Gila D, Mencarelli F, Gamez Garcia J J Sci Food Agric. 2023; 105(3):1448-1455.

PMID: 38017697 PMC: 11726602. DOI: 10.1002/jsfa.13179.

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