Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques

Venturini, Francesca; Sperti, Michela; Michelucci, Umberto; Herzig, Ivo; Baumgartner, Michael; Caballero, Josep Palau; Jimenez, Arturo; Deriu, Marco Agostino

doi:10.3390/foods10051010

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-22465

Publication type:	Article in scientific journal
Type of review:	Peer review (publication)
Title:	Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques
Authors:	Venturini, Francesca Sperti, Michela Michelucci, Umberto Herzig, Ivo Baumgartner, Michael Caballero, Josep Palau Jimenez, Arturo Deriu, Marco Agostino
et. al:	No
DOI:	10.3390/foods10051010 10.21256/zhaw-22465
Published in:	Foods
Volume(Issue):	10
Issue:	5
Page(s):	1010
Issue Date:	6-May-2021
Publisher / Ed. Institution:	MDPI
ISSN:	2304-8158
Language:	English
Subjects:	Fluorescence spectroscopy; Fluorescence sensor; Quality control; Olive oil; Machine learning; Artificial neural networks
Subject (DDC):	006: Special computer methods 540: Chemistry
Abstract:	Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires advanced equipment and chemical knowledge of certified laboratories, and has therefore limited accessibility. In this work a minimalist, portable, and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing the classification of olive oil in the three mentioned classes with an accuracy of 100%. These results confirm that this minimalist low-cost sensor has the potential to substitute expensive and complex chemical analysis.
Further description:	This article belongs to the Special Issue Advanced Analysis Methods for Food Safety, Authenticity and Traceability Assessment
URI:	https://digitalcollection.zhaw.ch/handle/11475/22465
Fulltext version:	Published version
License (according to publishing contract):	CC BY 4.0: Attribution 4.0 International
Departement:	School of Engineering
Organisational Unit:	Institute of Applied Mathematics and Physics (IAMP)
Published as part of the ZHAW project:	Self-learning optical sensor
Appears in collections:	Publikationen School of Engineering

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Venturini, F., Sperti, M., Michelucci, U., Herzig, I., Baumgartner, M., Caballero, J. P., Jimenez, A., & Deriu, M. A. (2021). Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques. Foods, 10(5), 1010. https://doi.org/10.3390/foods10051010

Venturini, F. et al. (2021) ‘Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques’, Foods, 10(5), p. 1010. Available at: https://doi.org/10.3390/foods10051010.

F. Venturini et al., “Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques,” Foods, vol. 10, no. 5, p. 1010, May 2021, doi: 10.3390/foods10051010.

VENTURINI, Francesca, Michela SPERTI, Umberto MICHELUCCI, Ivo HERZIG, Michael BAUMGARTNER, Josep Palau CABALLERO, Arturo JIMENEZ und Marco Agostino DERIU, 2021. Exploration of Spanish olive oil quality with a miniaturized low-cost fluorescence sensor and machine learning techniques. Foods. 6 Mai 2021. Bd. 10, Nr. 5, S. 1010. DOI 10.3390/foods10051010

Venturini, Francesca, Michela Sperti, Umberto Michelucci, Ivo Herzig, Michael Baumgartner, Josep Palau Caballero, Arturo Jimenez, and Marco Agostino Deriu. 2021. “Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques.” Foods 10 (5): 1010. https://doi.org/10.3390/foods10051010.

Venturini, Francesca, et al. “Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques.” Foods, vol. 10, no. 5, May 2021, p. 1010, https://doi.org/10.3390/foods10051010.