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

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...

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Autores principales: Cano Marchal, Pablo, Sanmartin, Chiara, Satorres Martínez, Silvia, Gómez Ortega, Juan, Mencarelli, Fabio, Gámez García, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037113/
https://www.ncbi.nlm.nih.gov/pubmed/33806002
http://dx.doi.org/10.3390/s21072298
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author Cano Marchal, Pablo
Sanmartin, Chiara
Satorres Martínez, Silvia
Gómez Ortega, Juan
Mencarelli, Fabio
Gámez García, Javier
author_facet Cano Marchal, Pablo
Sanmartin, Chiara
Satorres Martínez, Silvia
Gómez Ortega, Juan
Mencarelli, Fabio
Gámez García, Javier
author_sort Cano Marchal, Pablo
collection PubMed
description 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 [Formula: see text] 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.
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spelling pubmed-80371132021-04-12 Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose Cano Marchal, Pablo Sanmartin, Chiara Satorres Martínez, Silvia Gómez Ortega, Juan Mencarelli, Fabio Gámez García, Javier Sensors (Basel) Article 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 [Formula: see text] 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. MDPI 2021-03-25 /pmc/articles/PMC8037113/ /pubmed/33806002 http://dx.doi.org/10.3390/s21072298 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Cano Marchal, Pablo
Sanmartin, Chiara
Satorres Martínez, Silvia
Gómez Ortega, Juan
Mencarelli, Fabio
Gámez García, Javier
Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title_full Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title_fullStr Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title_full_unstemmed Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title_short Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose
title_sort prediction of fruity aroma intensity and defect presence in virgin olive oil using an electronic nose
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037113/
https://www.ncbi.nlm.nih.gov/pubmed/33806002
http://dx.doi.org/10.3390/s21072298
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