Detection of virgin olive oil adulteration using low field unilateral NMR

Xu, Z, Morris, RH ORCID: https://orcid.org/0000-0001-5511-3457, Bencsik, M ORCID: https://orcid.org/0000-0002-6278-0378 and Newton, MI ORCID: https://orcid.org/0000-0003-4231-1002, 2014. Detection of virgin olive oil adulteration using low field unilateral NMR. Sensors, 14 (2), pp. 2028-2035. ISSN 1424-8220

Preview

Text 215855_sensors-14-02028.pdf Download (296kB) | Preview

Abstract

The detection of adulteration in edible oils is a concern in the food industry, especially for the higher priced virgin olive oils. This article presents a low field unilateral nuclear magnetic resonance (NMR) method for the detection of the adulteration of virgin olive oil that can be performed through sealed bottles providing a non-destructive screening technique. Adulterations of an extra virgin olive oil with different percentages of sunflower oil and red palm oil were measured with a commercial unilateral instrument, the profile NMR-Mouse. The NMR signal was processed using a 2-dimensional Inverse Laplace transformation to analyze the transverse relaxation and self-diffusion behaviors of different oils. The obtained results demonstrated the feasibility of detecting adulterations of olive oil with percentages of at least 10% of sunflower and red palm oils.

Item Type:	Journal article
Publication Title:	Sensors
Creators:	Xu, Z., Morris, R.H., Bencsik, M. and Newton, M.I.
Publisher:	MDPI
Place of Publication:	Basel, Switzerland
Date:	2014
Volume:	14
Number:	2
ISSN:	1424-8220
Identifiers:	Number Type 10.3390/s140202028 DOI
Rights:	© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Divisions:	Schools > School of Science and Technology
Record created by:	EPrints Services
Date Added:	09 Oct 2015 09:50
Last Modified:	09 Jun 2017 13:12
URI:	https://irep.ntu.ac.uk/id/eprint/3611

Actions (login required)

Edit View

Statistics

Views

Downloads