Olive Oil Grades Research Articles

Identification of characteristic flavour compounds and quality analysis in extra virgin olive oil based on HS‐GC‐IMS

SummaryHow to quickly and accurately identify different grades of olive oil has always been a difficult problem. In this study, fifty‐four volatile flavour compounds were identified by HS‐GC‐IMS analysis of different grades of olive oil, and sensory analysis of volatile compounds was carried out based on literature, among which fifteen compounds were identified from olive oil for the first time. Volatile component fingerprint, principal component analysis and partial least squares discriminant analysis (PLS‐DA) were adopted to establish the classification model of different grades of olive oil, which had good fitting and prediction ability. Combined with the PLS‐DA model and literature, seven characteristic flavour substances having fruity and green properties, including (E)‐2‐hexenal‐D, (E)‐2‐pentenal‐M/D, 3‐pentanone, 1‐penten‐3‐one, 2,3‐pentanedione, (E)‐3‐penten‐2‐one‐D and 2‐methylbutanal were confirmed. The contents of these characteristic flavour substances in extra virgin olive oil and other grades were significantly different, which could be regarded as characteristic markers to distinguish different grades of olive oil. In addition, the grades of 11 olive oils were predicted by this PLS‐DA model. The results showed that the model had a good ability to discriminate different grades of olive oil.

From Extra Virgin Olive Oil to Refined Products: Intensity and Balance Shifts of the Volatile Compounds versus Odor.

To explore relationships between the volatile organic compounds (VOCs) of different grades of olive oils (OOs) (extra virgin olive oil (EVOO), refined olive oil (ROO), and pomace olive oil (POO)) and odor quality, VOCs were measured in the headspace of the oils by proton transfer reaction quadrupole ion guide time-of-flight mass spectrometry. The concentrations of most VOCs differed significantly between the grades (EVOO > ROO > POO), whereas the abundance of m/z 47.012 (formic acid), m/z 49.016 (fragments), m/z 49.027 (fragments), and m/z 115.111 (heptanal/heptanone) increased in that order. Although the refined oils had considerably lower VOC abundance, the extent of the decline varied with the VOCs. This results in differences in VOCs proportions. The high VOC abundance in the EVOO headspace in comparison to ROO and POO results in a richer and more complex odor. The identified C5–C6 compounds are expected to contribute mainly to the green odor notes, while the identified C1–C4 and C7–C15 are mainly responsible for odor defects of OOs. Current results reveal that processing strongly affects both the quantitative and relative abundance of the VOCs and, therefore, the odor quality of the various grades of OOs.

Effect of Extraction Methods and Olive Oil Grades on Physio-Chemical Properties and Sensory Attributes of Olive Oil

Effect of Extraction Methods and Olive Oil Grades on Physio-Chemical Properties and Sensory Attributes of Olive Oil

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.

Discrimination of processing grades of olive oil and other vegetable oils by monochloropropanediol esters and glycidyl esters

In this study, the processing derived contaminants 2- and 3-monochloropropanediol (2- and 3-MCPD) esters and glycidyl esters (GEs) were analysed in 84 oil samples by GC–MS/MS for the discrimination of processing grades of olive oils as a potential authentication tool. Concentrations of 2- and 3-MCPD esters and GEs varied in the ranges 0–6 mg/kg, 0–1.5 mg/kg, and 0–1 mg/kg oil, respectively. The concentrations of the three compounds in lower grade olive oils were significantly higher (P < .001) than that in EVOO. A similar difference was observed for other refined and cold-pressed vegetable oils. The limit of fraud detection of lower grade oils in EVOO was 2% when using 3-MCPD esters, 5% for 2-MCPD esters, and 13–14% for GEs based on calculations of virtual mixtures of the current sample set. Especially the MCPD esters appear very specific and promising for the detection of lower processing grade oils in EVOO.

Authenticity Assessment of Extra Virgin Olive Oil: Evaluation of Desmethylsterols and Triterpene Dialcohols

AbstractExtra virgin olive oil (EVOO) has a long history of economic adulteration, the detection of which presents significant challenges due to the diverse composition of cultivars grown around the world and the limitations of existing methods for detecting adulteration. In this study, using Method COI/T.20/Doc. No. 30/Rev. 1 of the International Olive Council, the authenticity of 88 market samples of EVOO was evaluated by comparing total sterol contents, desmethylsterol composition, and contents of triterpene dialcohols (erythrodiol and uvaol) with purity criteria specified in the United States Standards for grades of olive oil and olive‐pomace oil. Three of the 88 samples labeled as EVOO failed to meet purity criteria, indicating possible adulteration with commodity oil and/or solvent‐extracted olive oil. Detection of adulteration was also evaluated by spiking an EVOO sample with commodity oil at the 10 % level. As expected, eight of the spiked samples (canola, corn, hazelnut, peanut, safflower, soybean, and sunflower oils, and palm olein) failed to meet purity criteria. Two of the three samples spiked with 10 % hazelnut oil went undetected for adulteration. Overall, a low occurrence rate of adulteration (&lt;5 %), based on purity criteria for desmethylsterols and triterpene dialcohols, was detected for the 88 products labeled as EVOO.

FTIR Spectroscopy and PLS-DA Classification and Prediction of Four Commercial Grade Virgin Olive Oils from Morocco

Fourier transform infrared (FTIR) coupled to chemometrics was shown to be a useful method to classify and predict the quality of four commercial grade virgin olive oils (VOO). FTIR and physicochemical data were collected using a set of 70 samples representing extra virgin (EV), virgin (V), ordinary virgin (OV), and lampante (L) commercial grade olive oils collected in Beni Mellal region (central Morocco). Two partial least squares discriminant analysis (PLS-DA) models using physicochemical data and FTIR data were established and compared. The PLS-DA model using only physicochemical data was not accurate enough to distinguish satisfactorily among OV, V, and EV olive oil grades. On the contrary, the PLS-DA model on FTIR data was better in the calibration, able to describe 98 % of the spectral information and predicting 93 % of the VOO grades. In the external validation, this PLS-DA model accurately classified VOO commercial grades with prediction accuracy of 100 %. The proposed procedure is fast, nondestructive, simple, and easy to operate, and it is recommended for the quick monitoring of olive oil’s quality.

Olive oil as functional component in meat and meat products: a review

Olive oil is a functional food considered to be the major component of Mediterranean diet widely used in cooking, pharmaceuticals, soaps, and in cosmetics. There are different grades of olive oil based on source of extraction and percentage of Free Fatty Acid (FFA) and it has got wider applications. It is used in the preparation of different food products in order to achieve functional properties as a fat replacer, antioxidant properties, health promoting functions and to improve the fatty acid profile in terms of Saturated: Monounsaturated: Polyunsaturated fatty acids as well as ω-6: ω-3 ratio. Various in vitro and in vivo studies revealed health promoting attributes of olive oil like antimicrobial, antioxidant property, lowering of cardiovascular heart diseases, reduction in cancer risks, anti-inflammatory and other attributes. This review paper presents an overview about different grades of olive oil, functional components and their biological roles and also stress the importance of further research in the development of meat products by using processing techniques with regard to functional foods with maximum quality and shelf life.

A multi-compartment vehicle routing problem arising in the collection of olive oil in Tunisia

We introduce, model and solve to optimality a rich multi-product, multi-period and multi-compartment vehicle routing problem with a required compartment cleaning activity. This real-life application arises in the olive oil collection process in Tunisia, where regional collection offices dispose of a fleet of vehicles to collect one or several grades of olive oil from a set of producers. For each grade, the quantity offered by a producer changes dynamically over the planning horizon. We first provide a mathematical formulation of the problem, along with a set of known and new valid inequalities. We then propose an exact branch-and-cut algorithm to solve the problem. We evaluate the performance of the algorithm on real data sets under different transportation scenarios to demonstrate to our industrial partner the advantages of using multi-compartment vehicles.

Raman spectroscopy study of edible oils and determination of the oxidative stability at frying temperatures

Samples of edible oils of different degrees of unsaturation were studied by Raman spectroscopy. We demonstrate the potential of this technique for discriminating these oils. In addition, the Raman spectra for the macadamia, pecan, and Brazil nut oils are for the first time reported here. The fatty acid profile of each type of oil was established by GC. The analytical results obtained from the spectra were highly correlated with those provided by GC as regards the contents in monounsaturated and PUFA of each oil type. Spectra were examined separately in the wavenumber zones 2800–3100 and 800–1800 cm−1, which were those exhibiting the greater differences between oils. Also, as shown in this work, Raman spectroscopy is an effective tool for assessing oxidation in various grades of olive oils. Based on the results, extra virgin olive oil efficiently resists oxidation in the short term by virtue of its increased antioxidant contents.Practical applications: In this paper we show the usefulness of Raman spectroscopy to distinguish between edible oils. Similarly, the technique also allows us to discriminate between different heat‐treated olive oils. At the industrial level Raman spectroscopy can be a useful tool to detect adulteration related to the oxidation of fat. Its ease of use and the absence of sample handling make it very effective for use in production systems on‐line.Raman spectroscopy allows to distinguish oils with different unsaturation level and also allows us to discriminate between different heat‐treated oils.

버진, 퓨어, 포마스 올리브유의 이화학적인 특성 비교를 통한 품질등급 구분에 관한 연구

This study investigated the classification of olive oils that are mainly distributed in Korea via imports. The fatty acid contents, degree of color, pigments, anti-oxidants, and sterol contents are analyzed on the different types of olive oil as follows: 10 kinds of extra virgin olive oil, 5 kinds of pure olive oil, and 5 kinds of refined olive-pomace oil. As a result of fatty acid analysis, the majority of oleic acid () and palmitic acid (), and minority of linoleic acid () and stearic acid () were detected without any significant differences between the grades of olive oils. The UV spectrum is related to the , and it is a part of the analysis factor for the purity and degree of degradation of the oil. Extra virgin olive oil had of almost 0, pure olive oil had 0.07~0.12, and refined olive-pomace oil had 0.1~0.13. These differed from extra virgin oil, and the pure or pomace oil had a confirmed distinct difference. The color degrees of chlorophyll with a low value and (green) and carotenoid with (yellow) were confirmed to have correlation between extra virgin and other olive oils. To compare chlorophyll and carotenoid as natural pigment in olive oils, 417 nm and the ratio of the absorbance at 480 nm (417/480) was calculated at 1.62 of extra virgin, 1.85 of pure olive oil, and 3.32 of refined olive-pomace oil. Therefore, it will be possible to distinguish when the extra virgin or pure olive oil are mixed with olive-pomace oil. The total amount of tocopherol, an anti-oxidant, were 19.06 in extra virgin, 10.91 in pure olive oil, and 27.88 in refined olive-pomace oil. The high content of tocopherol in pomace oil caused recovery of solvent extraction from olive pulp. Thus, extra virgin oil and pure olive oil were distinguished by olive-pomace oil. Polyphenol compounds in extra virgin olive oil measured high only in ferulic acid with 0.543 mg/kg, caffeic acid with 0.393 mg/kg, and other vanillic acid, vanillin, and p-coumaric acid had similar amount of 0.3 mg/kg. All grade of olive oils had the highest -sitosterol content. Af (Authenticity factor) value were estimated with campesterol and stigmasterol content ratio (%). Af value was 19.2 in extra virgin olive oil, 17.1 in pure olive oil, 16.9 in refined olive-pomace oil, which were distinctive from sunflower oil with 3.7, corn oil with 2.4, and soybean oil with 2.0. It can provide important indicator of olive oil adulteration with other cheap vegetable oils. The results of this study can be used as a database for the classification of olive oil grade and distinguishing between the different types of oils.

Classification of Turkish Monocultivar (Ayvalık and Memecik cv.) Virgin Olive Oils from North and South Zones of Aegean Region Based on Their Triacyglycerol Profiles

AbstractIn this study, a total of 22 domestic monocultivar (Ayvalık and Memecik cv.) virgin olive oil samples taken from various locations of the Aegean region, the main olive growing zone of Turkey, during two (2001–2002) crop years were classified and characterized by well‐known chemometric methods (principal component analysis [PCA] and hierarchical cluster analysis [HCA]) on the basis of their triacylglycerol (TAG) components. The analyses of TAG components (LLL and major fractions LOO, OOO, POO, PLO, SOO, and ECN 42–ECN 50) in the oil samples were carried out according to the HPLC method described in a European Union Commission (EUC) regulation. In all analyzed samples the value of trilinolein (LLL), the least abundant TAG, did not exceed the maximum limit of 0.5 % given by the EUC regulation for different olive oil grades. The ranges of abundant TAG, namely LOO, OOO, POO, PLO, and SOO, were 13.30–16.08, 37.27–46.36, 21.39–23.24, 4.93–7.03, and 4.72–6.00 %. The TAG data of Aegean virgin olive oils were similar to those of products from important olive‐oil‐producing Mediterranean countries was determined. Also, the estimation of major fatty acids (FA) was carried out by using a formula based on TAG data. The PCA results showed that some TAG components have an important role in the characterization and geographical classification of 22 monocultivar virgin olive oil. The Aegean virgin olive oil samples were successfully classified and discriminated into two main groups as the North and South (growing) subzones or Ayvalık and Memecik olives (cultivars) according to the HCA results based on experimental TAG data and calculated major FA profile.

Enhancing sensitivity and selectivity in the determination of aldehydes in olive oil by use of a Tenax TA trap coupled to a UV-ion mobility spectrometer

A Tenax TA trap was coupled to an ion mobility spectrometer in order to improve basic analytical properties such as sensitivity and selectivity. The analytical performance of this combination was assessed in the determination of volatile aldehydes between 3 and 6 carbon atoms present in olive oil. The aldehydes were extracted and adsorbed into the trap, from which they were thermally desorbed for analysis by UV-Ion Mobility Spectrometry (UV-IMS). Sensitivity was increased by the preconcentration step and selectivity by the combination of temperature programmed thermal desorption and the ability of the ion mobility spectrometer to monitor the desorbed analytes in real time. The limits of detection obtained were lower than 0.3 mg kg −1 and the relative standard deviation lower than 10%. A one-way analysis of variance (ANOVA) was used to identify significant differences between olive oil grades in terms of peak heights for the target aldehydes.

Direct classification of olive oils by using two types of ion mobility spectrometers

In this work, we explored the use of an Ion Mobility Spectrometry (IMS) device with an ultraviolet (UV) source, and of a Gas Chromatographic (GC) column coupled to an IM Spectrometer with a tritium source, for the discrimination of three grades of olive oil, namely: extra virgin olive oil (EVOO), olive oil (OO) and pomace olive oil (POO). The three types of oil were analyzed with both equipment combinations as coupled to a headspace system and the obtained ion mobility data were consecutively processed with various chemometric tools. The classification rate for an independent validation set was 86.1% (confidence interval at 95% [83.4%, 88.5%]) with an UV–IMS and 100% (confidence interval at 95% [87%, 100%]) using a GC–IMS system. The classification rate was improved by using a more suitable ionization source and a pre-separation step prior to the IM analysis.

Extra virgin (EV) and ordinary (ON) olive oils: distinction and detection of adulteration (EV with ON) as determined by direct infusion electrospray ionization mass spectrometry and chemometric approaches

Extra virgin (EV), the finest and most expensive among all the olive oil grades, is often adulterated by the cheapest and lowest quality ordinary (ON) olive oil. A new methodology is described herein that provides a simple, rapid, and accurate way not only to detect such type of adulteration, but also to distinguish between these olive oil grades (EV and ON). This approach is based on the application of direct infusion electrospray ionization mass spectrometry in the positive ion mode, ESI(+)-MS, followed by the treatment of the MS data via exploratory statistical approaches, PCA (principal component analysis) and HCA (hierarchical clustering analysis). Ten distinct brands of each EV and ON olive oil, acquired at local stores, were analyzed by ESI(+)-MS and the results from HCA and PCA clearly indicated the formation of two distinct groups related to these two categories. For the adulteration study, one brand of each olive oil grade (EV and ON) was selected. The counterfeit samples (a total of 20) were then prepared by adding assorted proportions, from 1 to 20% w/w, with increments of 1% w/w, of the ON to the EV olive oil. The PCA and HCA methodologies, applied to the ESI(+)-MS data from the counterfeit (20) and authentic (10) EV samples, were able to readily detect adulteration, even at levels as low as 1% w/w.

Rapid Authentication of Olive Oil Adulteration by Raman Spectrometry

The authentication of olive oil and its adulteration with lower priced oils are still serious problems in the olive oil industry. In this study, a method based on the intensity ratio of the Raman spectroscopy vibration bands, especially on the intensity ratio of the cis ( ==C-H) and cis (C=C) bonds normalized by the band at 1441 cm(-1) (CH(2)), was established to authenticate genuine/fake olive oil. These intensity ratios of the vibration bands given in the form of a two-dimensional chart allow first the discrimination between the various grades of olive oil and the seed oils and then the detection of olive oil fraud by the line of y = 0.7, which is observed under most experiments and dot charts. This method can reliably distinguish the genuine olive oils from the olive oils containing 5% (volume percentage) or more of other edible oils, such as soybean oil, rapeseed oil, sunflower seed oil, or corn oil. Compared to the traditional principal component analysis method, this method is more intuitive, more precise, and easier to use. Moreover, this method also has the advantages of simplicity efficiency and has no need for sample preprocessing, being especially suitable for on-site testing in field applications.

13C nuclear magnetic resonance spectroscopy to determine olive oil grades

13C nuclear magnetic resonance spectroscopy was used in a first attempt to differentiate olive oil samples by grades. High resolution 13C NMR Distortionless Enhancement by Polarization Transfer (DEPT) spectra of 137 olive oil samples from the four grades, extra virgin olive oils, olive oils, olive pomace oils and lampante olive oils, were measured. The data relative to the resonance intensities (variables) of the unsaturated carbons of oleate (C-9 and C-10) and linoleate (L-9, L-10 and L-12) chains attached at the 1,3- and 2-positions of triacylglycerols were analyzed by linear discriminant analysis. The 1,3- and 2- carbons of the glycerol moiety of triacylglycerols along with the C-2, C-16 and C-18 resonance intensities of saturated, oleate and linoleate chains were also analyzed by linear discriminant analysis. The three discriminanting functions, which were calculated by using a stepwise variable selection algorithm, classified in the true group by cross-validation procedure, respectively, 76.9, 70.0, 94.4 and 100% of the extra virgin, olive oil, olive pomace oil and lampante olive oil grades.

Detection of Extra Virgin Olive Oil Adulteration with Lampante Olive Oil and Refined Olive Oil Using Nuclear Magnetic Resonance Spectroscopy and Multivariate Statistical Analysis

High-field 31P NMR (202.2 MHz) spectroscopy was applied to the analysis of 59 samples from three grades of olive oils, 34 extra virgin olive oils from various regions of Greece, and from different olive varieties, namely, 13 samples of refined olive oils and 12 samples of lampante olive oils. Classification of the three grades of olive oils was achieved by two multivariate statistical methods applied to five variables, the latter being determined upon analysis of the respective 31P NMR spectra and selected on the basis of one-way ANOVA. The hierarchical clustering statistical procedure was able to classify in a satisfactory manner the three olive oil groups. Subsequent application of discriminant analysis to the five selected variables of oils allowed the grouping of 59 samples according to their quality with no error. Different artificial mixtures of extra virgin olive oil-refined olive oil and extra virgin olive oil-lampante olive oil were prepared and analyzed by 31P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of extra virgin olive oil adulteration as low as 5% w/w for refined and lampante olive oils. Further application of the classification/prediction model allowed the estimation of the percent concentration of refined olive oil in six commercial blended olive oils composed of refined and virgin olive oils purchased from supermarkets.

Carbon Stable Isotopes and Olive Oil Adulteration with Pomace Oil

Adulteration of olive oils can be detected by comparison of the 13C/12C ratios as obtained subsequently by high-resolution gas chromatography (HRGC) and isotope ratio mass spectrometry (IRMS). In δ13C values determined for the aliphatic alcoholic fraction of pomace oil, the adulterant was significantly more negative than those of virgin and refined olive oils. Quantitative analysis of isoprenoids and methylsterols isolated from each grade of olive oil supports the decreasingly negative values of 13C/12C ratios for the better grades of olive oil. These results have turned out to be a good tool for detecting adulteration of olive oil with the cheaper pomace olive oil, even down to a 5% level. Keywords: Carbon stable isotopes; olive oil; adulteration; aliphatic alcohols; waxes

Identification and classification of olive oils by high‐resolution13C nuclear magnetic resonance

AbstractUnsaponifiable matter from 19 olive and olive pomace oils were studied by high‐resolution13C nuclear magnetic resonance spectroscopy. Their spectra showed characteristic peaks that corresponded to molecular substructures rather than the individual constituents present in the unsaponifiable matter. The presence of squalene and other hydrocarbons, sterols and triterpenic alcohols, in addition to other groups of minor compounds, were observed. Based on the analysis of these spectra, it was possible to distinguish among different grades of olive oils by using stepwise discriminant analysis. This direct method of analysis is suggested to be used in artificial neural networks to define oil identity and quality.