Authentication Of Extra Virgin Olive Oil Research Articles

Direct and rapid profiling of triacylglycerols in extra virgin olive oil using UHPLC-MS/MS

Extra virgin olive oil (EVOO) prices reached record levels in 2023, due to the decline in global production, mainly linked to drought in the Mediterranean. Without effective controls, the already widespread fraud in this sector will irrevocably worsen. However, the reliability of the current standard method (CSM) for controlling the authenticity of EVOO has been questioned. Besides, authors have recently called for the replacement of certain steps to reduce analysis time and solvent consumption. In fact, CSM based on HPLC-RID analysis of triacylglycerols (TAGs) and GC analysis of fatty acid methyl esters (FAMEs) is tedious and very time consuming. Here, we optimized and validated a UHPLC-APCI-MS/MS method capable of unambiguously identifying 33 TAGs in EVOO in less than 6 min. The limit of detection calculated for the available TAG standards is between 0.3 and 2.5 ng/ml (0.02 ng–0.13 ng of injected quantity). The linearity of the method in real samples is satisfactory (r2 > 0.99, n = 6) for 27 TAGs with an average area greater than 0.04 %. In real samples, the between-run precision (RSD %) for 29 TAGs with mean area greater than 0.02% does not exceed 11.6%, provided that the injected amount is equal to or greater than 4 μg of EVOO sample. The application of this method to eleven EVOO samples, including a control sample from the International Olive Council, and the processing of the data with a PCA model allow their fine discrimination according to their TAG profiles. In addition to eliminating the GC step of FAME analysis, the high productivity of the proposed method significantly reduces the cost of this essential control step compared to CSM.

Rapid Non-Invasive Capacitive Assessment of Extra Virgin Olive Oil Authenticity

Economically motivated adulteration (EMA) and/or cross-contamination are the two major factors resulting in the substandard quality of premium edible oil like extra virgin olive oil (EVOO) produced in food and beverage (F&B) fast-moving consumer goods (FMCG) industries. Current quality assurance methods (e.g., spectroscopy and chromatography) in FMCG involve intrusive sample extraction and ex situ analysis in a laboratory using expensive bulky instrumentation, which is neither integrable inline nor scalable to match the production throughput. Such techniques do not meet the industrial requirements of in situ testing, non-intrusive analysis, and high throughput inspection (100% product verification) leading to food loss and package waste from unwanted batch rejects. Herein, a low-cost electrical approach based on capacitance is proposed to show the proof of concept for screening EVOO-filled containers non-invasively for adulteration without any sample extraction by capturing the differences in the dielectric properties of mixed oils. The sensor system displayed a fast response (100 ms) and low detection limits for different adulterants (olive oil (32.8%), canola oil (19.4%), soy oil (10.3%) and castor oil (1.7%)), which is suitable for high-throughput (>60 sample/min) screening. Furthermore, a low-cost automated system prototype was realized to showcase the possibility of translating the proof of concept for possible scaling up and inline integration.

Combining untargeted profiling of phenolics and sterols, supervised multivariate class modelling and artificial neural networks for the origin and authenticity of extra-virgin olive oil: A case study on Taggiasca Ligure

Extra-virgin olive oil (EVOO) is subjected to different frauds. This work aimed at integrating the untargeted phenolic and sterol signatures with supervised multivariate discriminant analysis (OPLS-DA) and Artificial Neural Networks (ANN) for tracing the authenticity (as a function of variety, origin, and the blending) of Taggiasca Ligure, a renowned Italian EVOO. Overall, 408 samples from three consecutive growing seasons were used. Despite the cultivar, season, growth altitude, and geographical origin were all contributing to phytochemical profile, OPLS-DA models allowed identifying specific markers of authenticity. Cholesterol-derivatives and phenolics (tyrosols and oleuropeins, stilbenes, lignans, phenolic acids, and flavonoids) were the best markers, based on statistics. Thereafter, ANN was used to discriminate authentic Taggiasca, and the sensitivity was 100% (32/32) thus indicating an excellent classification.Our results strengthen the concept of “terroir” for EVOO and indicate that profiling sterols and phenolics can support EVOO integrity if adequate data treatments are adopted.

Nuclear magnetic resonance spectroscopy in extra virgin olive oil authentication.

Extra virgin olive oil (EVOO) is a high-quality product that has become one of the stars in the food fraud context in recent years. EVOO can encounter different types of fraud, from adulteration with cheaper oils to mislabeling, and for this reason, the assessment of its authenticity and traceability can be challenging. There are several officially recognized analytical methods for its authentication, but they are not able to unambiguously trace the geographical and botanical origin of EVOOs. The application of nuclear magnetic resonance (NMR) spectroscopy to EVOO is reviewed here as a reliable and rapid tool to verify different aspects of its adulteration, such as undeclared blends with cheaper oils and cultivar and geographical origin mislabeling. This technique makes it possible to use both targeted and untargeted approaches and to determine the olive oil metabolomic profile and the quantification of its constituents.

Detection of soft-refined oils in extra virgin olive oil using data fusion approaches for LC-MS, GC-IMS and FGC-Enose techniques: The winning synergy of GC-IMS and FGC-Enose

Extra virgin olive oil (EVOO) is frequently adulterated by mixing it with soft refined oils (SROO). The differentiation of EVOO from its blends with SROO is not possible with the most common approaches, and, for this reason, the discriminating power of liquid chromatography-high resolution mass spectrometry (LC-MS), gas-chromatography ion mobility spectrometry (GC-IMS) and flash gas-chromatography electronic nose (FGC-Enose) was examined previously. Here, the combination of the above-mentioned techniques for an improvement in classification power of the methods is explored. A total of 43 commercial EVOOs and 18 illegal mixtures of SROO with EVOO were previously analysed by LC-(+/−)MS, GC-IMS and FGC-Enose. Low-level and mid-level data fusion of the four datasets were performed. The merged unique fingerprints were submitted to partial least squared discriminant analysis (PLS-DA), and the extrapolated most informative variables were used to build support vector machine (SVM) classifiers. Statistical indicators were calculated and compared to find out the best classifier. The results of PLS-DA-SVM strategies on the combination of datasets demonstrated that, after low-level data fusion, the discriminatory capability of the two merged GC-based techniques was remarkably improved as compared to the individual techniques. This indicates that merging the datasets before PLS-DA better retrieves the most informative variables and, thus, enhances group separation and classification of unknowns. The combination of LC(+/−)MS datasets, both by mid- and low-level data fusion, did not show significant enhancement in terms of discrimination of EVOO from SROO as compared to the individual LC(+)MS matrix. The low-level combination of the four datasets (LC(+/−)MS, GC-IMS, FGC-Enose) was successful, although this laborious option is not a viable path in industry quality assurance. This study primarily provides new paths for the authentication of EVOO, taking advantage of merging multimodal LC-(+/−)MS, GC-IMS and FGC-Enose data, with consequent improvement in the performances of the classification models. The most promising results were achieved by the low-level data fusion of GC-IMS and FGC-Enose data.

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

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.

Multielement Characterization and Antioxidant Activity of Italian Extra-Virgin Olive Oils.

Food product safety and quality are closely related to the elemental composition of food. This study combined multielement analysis and chemometric tools to characterize 237 extra-virgin olive oil (EVOO) samples from 15 regions of Italy, and to verify the possibility of discriminating them according to different quality factors, such as varietal or geographical origin or whether they were organically or traditionally produced. Some elements have antioxidant properties, while others are toxic to humans or can promote oxidative degradation of EVOO samples. In particular, the antioxidant activity of oils’ hydrophilic fraction was estimated and the concentrations of 45 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS). At first, univariate and multivariate analyses of variance were used to compare the element concentrations, and statistically significant differences were found among samples from different regions. Successively, discriminant classification approaches were used to build a model for EVOO authentication, considering, in turn, various possible categorizations. The results have indicated that chemometric methods coupled with ICP-MS have the potential to discriminate and characterize the different types of EVOO, and to provide “typical” elemental fingerprints of the various categories of samples.

Clarifications of the Carbonyl and Water Absorptions in Fourier Transform Near Infrared Spectra from Extra Virgin Olive Oil

AbstractThe Fourier transform near infrared (FT‐NIR) spectrum of extra virgin olive oils (EVOO) shows two minor carbonyl absorptions at 5280 and 5180 cm–1 that has been used to assess their authenticity. To establish components absorbing at 5280 cm–1, volatile aldehydes and ketones, triacylglycerol (TAG), diacylglycerols (DAG), free fatty acids (FFA), phenolics, and water are investigated and sometimes added to refined olive oil (ROO). Except TAG, the remaining carbonyls contribute to 5280 cm–1 by broadening peak. Water absorption is demonstrated by its removal using Na2SO4 or deuterium oxide addition; FT‐NIR spectral changes are reconstituted by water addition. Water absorption depends on being free or complexed with polar compounds in oil. The size of absorption is not related to abundance, but on unique absorption specificity of components; water shows the strongest absorption. Heat removes water and volatiles, leaving behind DAG, FFA, and phenolics, and makes it possible to differentiate absorption of water, volatile and non‐volatile carbonyls. Cloudy olive oils are analyzed using FT‐NIR methodology after warming for 3 min at 50 °C. FT‐NIR index values are replaced by a new calibration model based on correlating gravimetric mass loss of water plus volatiles with spectral changes. The FT‐NIR methodology is expanded to include EVOOs with 15.5% to 21% linoleic acid.Practical Applications: Testing for authenticity of EVOOs remains a challenge because adulterations continue to be a problem due to economic gains. Spectroscopy methods, specifically FT‐NIR, are much preferred to targeted chemical methods because they measure all constituents in products and are non‐destructive and fast. The current universal FT‐NIR methodology assesses 13 different parameters: five major FAs, and the DAG and FFA contents. The FT‐NIR index value measuring the content of moisture plus volatiles is now replaced by a gravimetric determination. The methodology identifies four major types of adulterants, high in oleic acid, linoleic acid, palm olein or ROO. The composition of olive oils makes it necessary to develop five oil‐specific groups, but cloudy samples still need to be clarified by slight warming before measuring. The value of this universal FT‐NIR methodology will increase after being adopted by commercial and in regulatory settings.

Effect of chlorophyll fluorescence quenching on quantitative analysis of adulteration in extra virgin olive oil

Extra virgin olive oil (EVOO) is both edible oil and health care product. Adulteration in high quality vegetable oil is a ubiquitous fraud, especially in the market of EVOO. Spectroscopy is an effective means to realize the rapid detection of adulteration in EVOO, but the accuracy of quantitative analysis is the short board of spectral detection. Traditional Raman spectroscopy is used to detect the adulteration of EVOO by analyzing the content of monounsaturated fatty acids. However, high oleic acid content is not unique to EVOO. Confocal Raman and Fluorescence Spectroscopy (CRFS) was employed to characterize EVOO along with potential adulterant oils based on their Oleic acid and photosensitive substances content. Statistical analysis of these Oleic acid and photosensitive substances using Multiple Linear Regression (MLR) allowed for a rapid approach to determine EVOO authenticity. The quantitative analysis model of adulteration in EVOO was established using this approach, and the RMSE was 0.0068, and the R-Squaredof external Prediction was 0.9996. In addition, Fluorescence quenching which interfered with the quantitative analysis of chlorophyll was found in the adulteration experiment of EVOO. Compared to traditional Raman methods, CRFS with MLR involves minimal sample preparation combined with fast analysis.

Rapid screening for hazelnut oil and high‐oleic sunflower oil in extra virgin olive oil using low‐field nuclear magnetic resonance relaxometry and machine learning

As extra virgin olive oil (EVOO) has high commercial value, it is routinely adulterated with other oils. The present study investigated the feasibility of rapidly identifying adulterated EVOO using low-field nuclear magnetic resonance (LF-NMR) relaxometry and machine learning approaches (decision tree, K-nearest neighbor, linear discriminant analysis, support vector machines and convolutional neural network (CNN)). LF-NMR spectroscopy effectively distinguished pure EVOO from that which was adulterated with hazelnut oil (HO) and high-oleic sunflower oil (HOSO). The applied CNN algorithm had an accuracy of 89.29%, a precision of 81.25% and a recall of 81.25%, and enabled the rapid (2 min) discrimination of pure EVOO that was adulterated with HO and HOSO in the volumetric ratio range of 10-100%. LF-NMR coupled with the CNN algorithm is a viable candidate for rapid EVOO authentication. © 2020 Society of Chemical Industry.

Evaluation and Origin Discrimination of Two Monocultivar Extra Virgin Olive Oils, Cultivated in the Coastline Part of North-Western Greece

Extra virgin olive oil (EVOO) quality and authenticity are important and challenging factors nowadays for the assurance of consumers’ protection, prevention of unfair competition, and disruption of the national economy by a false declaration of origin. Hence, the recognition of EVOO authenticity is of great interest in terms of commercial and quality aspects. The objective of this study was to evaluate and discriminate monovarietal extra virgin olive oils of the two dominant olive cultivars, Lianolia Kerkyras and Koroneiki, produced in the coastline part of Western Greece, based on their chemical characteristics, followed by statistical and chemometric analysis in order to profile for the first time the typical characteristics of Lianolia Kerkyras as well as to identify possible markers for authenticity purpose. A total of 104 olive oil samples were collected. Both cultivars had an overall high quality profile as far as their basic qualitative parameters (free fatty acid, peroxide value, and UV spectrometric indices) are concerned. A higher concentration in the mono-unsaturated oleic acid characterize olive oils of cv. Koroneiki compared to cv. Lianolia Kerkyras, while a clearly higher concentration in the poly-unsaturated linoleic acid was observed in olive oils of cv. Lianolia Kerkyras. In addition, olive oil samples of cv. Koroneiki showed a clear lower total sterols concentration with a percentage of 40.9% not surpassing the required EU Regulatory limit of 1000 mg/kg, an observation which strengthens previous published results of our research group and depicts an overall “intrinsic characteristic” of cv. Koroneiki. As far as the profile of the individual sterols is concerned, Lianolia Kerkyras samples exhibited higher mean value for the total sterol content as well as for β-sitosterol, the major phytosterol in olive oils, compared to the relative values of Koroneiki. Significant differences in the sterolic and fatty acid composition of the examined olive oil samples were shown by means of statistical analysis demonstrating a strong botanical effect and depicting that those compositional markers can be suggested as possible authenticity tools.

Detecting Food Fraud in Extra Virgin Olive Oil Using a Prototype Portable Hyphenated Photonics Sensor.

BackgroundCurrent developments in portable photonic devices for fast authentication of extra virgin olive oil (EVOO) or EVOO with non-EVOO additions steer towards hyphenation of different optic technologies. The multiple spectra or so-called “fingerprints” of samples are then analyzed with multivariate statistics. For EVOO authentication, one-class classification (OCC) to identify “out-of-class” EVOO samples in combination with data-fusion is applicable.ObjectiveProspecting the application of a prototype photonic device (“PhasmaFood”) which hyphenates visible, fluorescence, and near-infrared spectroscopy in combination with OCC modelling to classify EVOOs and discriminate them from other edible oils and adulterated EVOOs.MethodEVOOs were adulterated by mixing in 10–50% (v/v) of refined and virgin olive oils, olive-pomace olive oils, and other common edible oils. Samples were analyzed by the hyphenated sensor. OCC, data-fusion, and decision thresholds were applied and optimized for two different scenarios. ResultsBy high-level data-fusion of the classification results from the three spectral databases and several multivariate model vectors, a 100% correct classification of all pure edible oils using OCC in the first scenario was found. Reducing samples being falsely classified as EVOOs in a second scenario, 97% of EVOOs adulterated with non-EVOO olive oils were correctly identified and ones with other edible oils correctly classified at score of 91%.ConclusionsPhotonic sensor hyphenation in combination with high-level data fusion, OCC, and tuned decision thresholds delivers significantly better screening results for EVOO compared to individual sensor results.HighlightsHyphenated photonics and its data handling solutions applied to extra virgin olive oil authenticity testing was found to be promising.

Targeted analysis for detection the adulteration in extra virgin olive oil’s using LC-DAD/ESI–MS/MS and combined with chemometrics tools

The hand-held LC-DAD/ESI–MS/MS approach was employed, for the first time, for the quantification of extra virgin olive oil (EVOO) adulteration with refined pomace olive oil (RPOO). The total polyphenols (TP) and sterols were quantified according to their chemical methods, with more reliable methods required in this field to avoid undue dependence on chlorophylls, carotenoids contents and antioxidant activity (DPPH assays), which were evaluated by spectrophotometric methods. Some differences concerning the antioxidant activity and the TP content were observed. Actually, Chemlali EVOO activity was the most pronounced (13.84 ± 0.21%) and it contained the highest TP content (284.54 ± 4.27 mg/kg). Indeed, a correlation between antioxidant activity, TP and oxidative stability was established herewith. The metabolomics data were elaborated with the help of chemometric tools i.e. principal component analysis (PCA) and hierarchical cluster analysis (HCA). This approach allowed the estimation of the best discrimination markers for EVOO authenticity evaluation (i.e. Hydroxytyrosol quinone, oxidized hydroxytyrosol, 3,4-DHPEA-EA, p-HPEA (tyrosol), p-coumaric acid, luteolin, decarboxymethyl 10-hydroxyoleuropein aglycon, β-sitosterol apparently; campesterol, stigmasterol, ∆-7-stigmastenol and ∆-7-avenasterol).

Handheld Near‐Infrared Spectroscopy for Distinction of Extra Virgin Olive Oil from Other Olive Oil Grades Substantiated by Compositional Data

AbstractMiniaturization of analytical technology has paved the way for in‐situ screening of foods. In the current study, the spectral features of olive oils are examined by handheld near‐infrared spectroscopy to explore the technology's capabilities to distinguish extra virgin olive oil (EVOO) from lower grade oils. Eighty EVOO, forty refined olive oil (ROO), and ten pomace olive oil (POO) samples are analysed for their spectral and compositional features. The latter included analysis of the fatty acids (FAs), the chlorophylls and carotenoids, chromatic coordinates and moisture contents. The 1350–1570 nm wavelength range appeared most suitable for distinction of the oils. One‐class classification models with three different classifiers are subsequently estimated using this range, and their quantitative performance is assessed from probabilistic data. Soft independent modeling of class analogies models appears to predict the identity of the oils with a high success rate. Compared to the other oils, POO comprises a significantly higher and lower proportion of polyunsaturated and monounsaturated FAs, respectively. Higher contents of chlorophylls, carotenoids, and moisture are noted for EVOO. The relevant spectral information for distinction of the oils correlates strongly with the degree of unsaturation of the oils as well as their levels of chlorophylls, carotenoids, and moisture.Practical Applications: The findings of this study demonstrate that the handheld NIRS technique is promising for future rapid screening of olive oil grades. The statistical methods used and the robust validation procedure will help potential users to select the optimal strategy for multivariate data analysis. In addition, the exploration of correlations with compositional characteristics provides insight into the handheld NIRS working mechanism in regard to EVOO authentication.

A rapid method for the detection of extra virgin olive oil adulteration using UHPLC-CAD profiling of triacylglycerols and PCA

Adulteration in extra virgin olive oil (EVOO) is a common fraud due to its superior value over other edible oils. Traditional methods of fatty acid and sterol profiling for detecting adulteration demand large amounts of time and excessive use of labor and solvents therefore, new methodologies are needed to determine the authenticity of EVOO that are both time-efficient and cost-effective. Ultra-high-performance liquid chromatography (UHPLC) with charged aerosol detection (CAD) was employed to characterize EVOO along with potential adulterant oils based on their triacylglycerol (TAG) profiles. Statistical analysis of these TAGs using principal component analysis (PCA) allows for a rapid approach to determine EVOO authenticity. Using this approach, adulteration of EVOO with cheaper vegetable and seed oils and lower-quality olive oils had detection limits at or below 10%, depending on the adulterant. Compared to traditional methods, UHPLC-CAD with PCA involves minimal sample preparation combined with fast analysis, for a rapid determination of EVOO authenticity.

Developing FT-NIR and PLS1 Methodology for Predicting Adulteration in Representative Varieties/Blends of Extra Virgin Olive Oils.

It was previously demonstrated that Fourier transform near infrared (FT-NIR) spectroscopy and partial least squares (PLS1) were successfully used to assess whether an olive oil was extra virgin, and if adulterated, with which type of vegetable oil and by how much using previously developed PLS1 calibration models. This last prediction required an initial set of four PLS1 calibration models that were based on gravimetrically prepared mixtures of a specific variety of extra virgin olive oil (EVOO) spiked with adulterants. The current study was undertaken after obtaining a range of EVOO varieties grown in different countries. It was found that all the different types of EVOO varieties investigated belonged to four distinct groups, and each required the development of additional sets of specific PLS1 calibration models to ensure that they can be used to predict low concentrations of vegetable oils high in linoleic, oleic, or palmitic acid, and/or refined olive oil. These four distinct sets of PLS1 calibration models were required to cover the range of EVOO varieties with a linoleic acid content from 1.3 to 15.5% of total fatty acids. An FT-NIR library was established with 66 EVOO products obtained from California and Europe. The quality and/or purity of EVOO were assessed by determining the FT-NIR Index, a measure of the volatile content of EVOO. The use of these PLS1 calibration models made it possible to predict the authenticity of EVOO and the identity and quantity of potential adulterant oils in minutes.

The Use of FTIR Spectroscopy and Chemometrics for Rapid Authentication of Extra Virgin Olive Oil

AbstractThe authenticity of high value edible fats and oils including extra virgin olive oil (EVOO) is an emerging issue, currently. The potential employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis has been exploited for rapid authentication of EVOO from canola oil (Ca‐O). The optimization of two calibration models of partial least square (PLS) and principle component regression was performed in order to quantify the level of Ca‐O in EVOO. The chemometrics of discriminant analysis (DA) was used for making the classification between pure EVOO and EVOO adulterated with Ca‐O. The individual oils and their blends were scanned on good contact with ZnSe crystals in horizontal attenuated total reflectance, as a sampling technique. The wavenumbers of 3,028–2,985 and 1,200–987 cm−1 were used for quantification and classification of EVOO adulterated with Ca‐O. The results showed that PLS with normal FTIR spectra was well suited for quantitative analysis of Ca‐O with a value of the coefficient of determination (R2) > 0.99. The error, expressed as root mean square error of calibration obtained was relatively low, i.e. 0.108 % (v/v). DA can make the classification between pure EVOO and that adulterated with Ca‐O with one misclassified reported.

Tocopherol speciation as first screening for the assessment of extra virgin olive oil quality by reversed-phase high-performance liquid chromatography/fluorescence detector

A method based on reversed-phase high-performance liquid chromatography with fluorescence detector has been developed for the determination of tocopherols in vegetable oils. Oils were diluted in acetonitrile/tetrahydrofuran (THF) and injected directly onto HyPurity C 18 column. Methanol and THF (90:10) mixture was used as a mobile phase. Tocopherols were detected by fluorescence detector. The method had good limit of detection (LOD) (7 ng/g for α-tocopherol and 6 ng/g for β-, γ- and δ-tocopherols) and reproducibility (CV% < 2.8%). The method was applied to the determination of α-, (β+γ)- and δ-tocopherols in extra virgin olive oil (EVOO), sunflower, high oleic sunflower oil (HOSO), hazelnut, soy, corn, peanut and almond oil. A new parameter, the ratio of α-/(β+γ)-tocopherol concentration (named α/β tocopherol ratio), in these vegetable oils was systematically assessed and proposed as a first screening marker of the authenticity of EVOO by studying EVOO/sunflower, EVOO/hazelnut and EVOO/peanut mixtures. The use of δ-tocopherol as adulteration marker was also discussed.

Chemistry of Extra Virgin Olive Oil: Adulteration, Oxidative Stability, and Antioxidants

Much analytical work has been published on the chemistry of extra virgin olive oil (EVOO) as a basis for the detection and quantitative analyses of the type and amount of adulteration with cheaper vegetable oils and deodorized olive oils. The analysis and authentication of EVOO represent very challenging analytical chemical problems. A significant amount of literature on EVOO adulteration has depended on sophisticated statistical approaches that require analyses of large numbers of samples. More effort is needed to exploit reliable chemical and instrumental methods that may not require so much statistical interpretation. Large assortments of methods have been used to determine lipid oxidation and oxidative stability and to evaluate the activity of the complex mixtures of phenolic antioxidants found in EVOO. More reliable chemical methods are required in this field to obviate excessive dependence on rapid antiradical methods that provide no information on the protective properties of antioxidants. The extensive literature on olive oil sensory tests, using many descriptors varying in different countries, should be supplemented by more precise gas chromatographic analyses of volatile compounds influencing the odor and flavors of EVOO.

31P NMR spectroscopy in the quality control and authentication of extra‐virgin olive oil: A review of recent progress

This review is a brief account on the application of a novel methodology to the quality control and authentication of extra-virgin olive oil. This methodology is based on the derivatization of the labile hydrogens of functional groups, such as hydroxyl and carboxyl groups, of olive oil constituents with the phosphorus reagent 2-chloro-4,4,5,5-tetramethyldioxaphospholane, and the use of the (31)P chemical shifts to identify the phosphitylated compounds. Various experimental aspects such as pertinent instrumentation, sample preparation, acquisition parameters and properties of the phosphorus reagent are reviewed. The strategy to assign the (31)P signals of the phosphitylated model compounds and olive oil constituents by employing 1D and 2D NMR experiments is presented. Finally, the capability of this technique to assess the quality and the genuineness of extra-virgin olive oil and to detect fraud is discussed.