Literature DB >> 27012363

Novel technologies for monitoring the in-line quality of virgin olive oil during manufacturing and storage.

Julio Beltrán Ortega1, Diego M Martínez Gila2, Daniel Aguilera Puerto3, Javier Gámez García2, Juan Gómez Ortega2.   

Abstract

The quality of virgin olive oil is related to the agronomic conditions of the olive fruits and the process variables of the production process. Nowadays, food markets demand better products in terms of safety, health and organoleptic properties with competitive prices. Innovative techniques for process control, inspection and classification have been developed in order to to achieve these requirements. This paper presents a review of the most significant sensing technologies which are increasingly used in the olive oil industry to supervise and control the virgin olive oil production process. Throughout the present work, the main research studies in the literature that employ non-invasive technologies such as infrared spectroscopy, computer vision, machine olfaction technology, electronic tongues and dielectric spectroscopy are analysed and their main results and conclusions are presented. These technologies are used on olive fruit, olive slurry and olive oil to determine parameters such as acidity, peroxide indexes, ripening indexes, organoleptic properties and minor components, among others.
© 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Entities:  

Keywords:  automatic control; computer vision; dielectric spectroscopy; electronic noses; electronic tongues; infrared spectroscopy; virgin olive oil production process

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Year:  2016        PMID: 27012363     DOI: 10.1002/jsfa.7733

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  2 in total

Review 1.  Evaluation of Olive Oil Quality with Electrochemical Sensors and Biosensors: A Review.

Authors:  Alexandra Virginia Bounegru; Constantin Apetrei
Journal:  Int J Mol Sci       Date:  2021-11-24       Impact factor: 5.923

2.  Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression.

Authors:  Diego Manuel Martínez Gila; Pablo Cano Marchal; Juan Gómez Ortega; Javier Gámez García
Journal:  Sensors (Basel)       Date:  2018-03-25       Impact factor: 3.576

  2 in total

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