Abstract
The application of 1H and 13C nuclear magnetic resonance (NMR) in conjunction with chemometric methods was applied for the discrimination and authentication of Maltese extra virgin olive oils (EVOOs). A total of 65 extra virgin olive oil samples, consisting of 30 Maltese and 35 foreign samples, were collected and analysed over four harvest seasons between 2013 and 2016. A preliminary examination of 1H NMR spectra using unsupervised principle component analysis (PCA) models revealed no significant clustering reflecting the geographical origin. In comparison, PCA carried out on 13C NMR spectra revealed clustering approximating the geographical origin. The application of supervised methods, namely partial least squares discriminate analysis (PLS-DA) and artificial neural network (ANN), on 1H and 13C NMR spectra proved to be effective in discriminating Maltese and non-Maltese EVOO samples. The application of variable selection methods significantly increased the effectiveness of the different classification models. The application of 13C NMR was found to be more effective in the discrimination of Maltese EVOOs when compared to 1H NMR. Furthermore, results showed that different 1H NMR pulse methods can greatly affect the discrimination of EVOOs. In the case of 1H NMR, the Nuclear Overhauser Effect (NOESY) pulse sequence was more informative when compared to the zg30 pulse sequence, since the latter required extensive spectral manipulation for the models to reach a satisfactory level of discrimination.
Highlights
Several international organisations, including the European Union through its directives (EC No.2568/1991 and its amendments) [1] and the International Olive Oil Council (COI/T.15/NC No 3/Rev 6) [2], have been at the vanguard in the development of methods and establishing limits for physicochemical parameters of extra virgin olive oil (EVOO) to protect against frauds
It was shown that different nuclear magnetic resonance (NMR) methods in conjunction with chemometric methods provided a new insight in the identification of Maltese EVOOs
From the preliminary assessment using only unsupervised principle component analysis (PCA) models, no significant clustering was observed, and this was attributed to the high levels of similarity between the two classes of EVOOs studied, this method was deemed to be unsatisfactory when it comes to discrimination of geographical origin
Summary
Several international organisations, including the European Union through its directives (EC No.2568/1991 and its amendments) [1] and the International Olive Oil Council (COI/T.15/NC No 3/Rev 6) [2], have been at the vanguard in the development of methods and establishing limits for physicochemical parameters of extra virgin olive oil (EVOO) to protect against frauds. The typical approach relies on comparison of the chemical composition with official limits, as it is expected that the presence of adulterants will modify the concentration of these constituents This procedure may be inadequate, especially for oils which are classified as ‘virgin’ but do not conform to official limits of certain constituents due to local climatic or soil peculiarities [3]. These methodologies do not address the problem of geographical traceability and tend to be rather time-consuming with a very low throughput. In 1999, Vlahov [9] proposed NMR
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
