scholarly journals Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Foods ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 113
Author(s):  
Francesca Calò ◽  
Chiara Roberta Girelli ◽  
Selina C. Wang ◽  
Francesco Paolo Fanizzi
Keyword(s):  
Olive Oil ◽  
Geographical Origin ◽  
Virgin Olive Oil ◽  
Geographic Origin ◽  
Analytical Techniques ◽  
Extra Virgin Olive Oil ◽  
Product Authenticity ◽  
Mature Field ◽  
Analytical Approaches ◽  
Origin Assessment

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

scholarly journals An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer

Foods ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 834 ◽  
Author(s):  
Simona Violino ◽  
Luciano Ortenzi ◽  
Francesca Antonucci ◽  
Federico Pallottino ◽  
Cinzia Benincasa ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Olive Oil ◽  
Open Source ◽  
Geographical Origin ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Ann Model ◽  
First Choice ◽  
Phenolic Components ◽  
Artificial Neural Network Ann

Extra virgin olive oil (EVOO) represents a crucial ingredient of the Mediterranean diet. Being a first-choice product, consumers should be guaranteed its quality and geographical origin, justifying the high purchasing cost. For this reason, it is important to have new reliable tools able to classify products according to their geographical origin. The aim of this work was to demonstrate the efficiency of an open source visible and near infra-red (VIS-NIR) spectrophotometer, relying on a specific app, in assessing olive oil geographical origin. Thus, 67 Italian and 25 foreign EVOO samples were analyzed and their spectral data were processed through an artificial intelligence algorithm. The multivariate analysis of variance (MANOVA) results reported significant differences (p < 0.001) between the Italian and foreign EVOO VIS-NIR matrices. The artificial neural network (ANN) model with an external test showed a correct classification percentage equal to 94.6%. Both the MANOVA and ANN tested methods showed the most important spectral wavelengths ranges for origin determination to be 308–373 nm and 594–605 nm. These are related to the absorption of phenolic components, carotenoids, chlorophylls, and anthocyanins. The proposed tool allows the assessment of EVOO samples’ origin and thus could help to preserve the “Made in Italy” from fraud and sophistication related to its commerce.

scholarly journals Evaluation of the Capability of Horizontal ATR-FTMIR and UV-Visible Spectroscopy in the Discrimination of Virgin Olive Oils from the Moroccan Region of Beni Mellal-Khenifra

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Aimen El Orche ◽  
Mustapha Bouatia ◽  
Siham Yanisse ◽  
Houda Labjar ◽  
Mouad Mouhsin ◽  
...  
Keyword(s):  
Olive Oil ◽  
Spectral Data ◽  
Geographical Origin ◽  
Virgin Olive Oil ◽  
Correct Classification ◽  
Virgin Olive Oils ◽  
Olive Oils ◽  
Uv Visible ◽  
Beni Mellal ◽  
Analytical Approaches

One of the most important challenges in the authentication of olive oil is the determination of the geographical origin of virgin olive oil. In this work, we evaluated the capacity of two spectroscopic techniques, UV-Visible and ATR-FTMIR, coupled with chemometric tools to determine the geographical origin of olive oils. These analytical approaches have been applied to samples that have been collected during the period of olive oil production, in the Moroccan region of Beni Mellal-Khenifra. To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. The application of the PCA-LDA method on the spectral data of UV-Visible and ATR-FTMIR shows a good ability to classify olive oils according to their geographical origin with a percentage of correct classification that represents 90.24% and 85.87%, respectively, and the processing of the spectral data of UV-Visible and ATR-FTMIR by PCA-SVM allows differentiating correctly between five olive oils with a correct classification rate of 100% and 97.56, respectively. This study demonstrated the feasibility of UV-Visible and ATR-FTMIR fingerprinting (routine technique) for the geographical classification of olive oils in the Moroccan region of Beni Mellal-Khenifra. Such developed methods can be proposed as alternative and complementary methods to authenticate the geographical origin of virgin olive oil.

scholarly journals Olive Oil: Processing Characterization, and Health Benefits

Foods ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1612
Author(s):  
Dimitrios Boskou ◽  
Maria Lisa Clodoveo
Keyword(s):  
Olive Oil ◽  
Reference Model ◽  
Scientific Information ◽  
Virgin Olive Oil ◽  
Analytical Techniques ◽  
Olive Tree ◽  
Extra Virgin Olive Oil ◽  
World Health ◽  
Positive Role ◽  
Lipid Source

The Mediterranean diet is now well known worldwide and recognized as a nutrition reference model by the World Health Organization. Virgin olive oil, prepared from healthy and intact fruits of the olive tree only by mechanical means, is a basic ingredient, a real pillar of this diet. Its positive role in health has now been a topic of universal concern. The virtues of natural olive oil, and especially of extra virgin olive oil, are related to the quality of the fruits, the employment of advanced technologies, and the availability of sophisticated analytical techniques that are used to control the origin of the fruits and guarantee the grade of the final product. With the aim of enriching the recent multidisciplinary scientific information that orbits around this healthy lipid source, a new special issue of Foods journal has been published.

Authentication of the geographical origin of extra-virgin olive oil of the Arbequina cultivar by chromatographic fingerprinting and chemometrics

Talanta ◽  
2019 ◽  
Vol 203 ◽  
pp. 194-202 ◽  
Author(s):  
Dainis N. Vera ◽  
Ana M. Jiménez-Carvelo ◽  
Luis Cuadros-Rodríguez ◽  
Itziar Ruisánchez ◽  
M. Pilar Callao
Keyword(s):  
Olive Oil ◽  
Geographical Origin ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Arbequina Cultivar ◽  
Chromatographic Fingerprinting

scholarly journals Application of 1H and 13C NMR Fingerprinting as a Tool for the Authentication of Maltese Extra Virgin Olive Oil

Foods ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 689 ◽  
Author(s):  
Frederick Lia ◽  
Benjamin Vella ◽  
Marion Zammit Mangion ◽  
Claude Farrugia
Keyword(s):  
Olive Oil ◽  
1H Nmr ◽  
13C Nmr ◽  
Nmr Spectra ◽  
Geographical Origin ◽  
Pulse Sequence ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
13C Nmr Spectra ◽  
1H And 13C Nmr

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.

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