Extra Virgin Olive Oil Samples Research Articles

Characterization of Phenolic Compounds in Extra Virgin Olive Oil from Granada (Spain) and Evaluation of Its Neuroprotective Action.

The olive oil sector is a fundamental food in the Mediterranean diet. It has been demonstrated that the consumption of extra virgin olive oil (EVOO) with a high content of phenolic compounds is beneficial in the prevention and/or treatment of many diseases. The main objective of this work was to study the relationship between the content of phenolic compounds and the in vitro neuroprotective and anti-inflammatory activity of EVOOs from two PDOs in the province of Granada. To this purpose, the amounts of phenolic compounds were determined by liquid chromatography coupled to mass spectrometry (HPLC-MS) and the inhibitory activity of acetylcholinesterase (AChE) and cyclooxygenase-2 (COX-2) enzymes by spectrophotometric and fluorimetric assays. The main families identified were phenolic alcohols, secoiridoids, lignans, flavonoids, and phenolic acids. The EVOO samples with the highest total concentration of compounds and the highest inhibitory activity belonged to the Picual and Manzanillo varieties. Statistical analysis showed a positive correlation between identified compounds and AChE and COX-2 inhibitory activity, except for lignans. These results confirm EVOO's compounds possess neuroprotective potential.

Valorization of monovarietal Nostrana di Brisighella extra virgin olive oils: focus on bioactive compounds.

A "green breakthough" at the table due to consumer demand for healthy and sustainable foods, which aligns with the typical Mediterranean diet, has recently led to an increase in the consumption of products such as extra virgin olive oil. In fact, Italian olive cultivation, which contributes an average of 15% of world production, has seen the production of extra virgin olive oil with a value of exports that have doubled in the last 20 years. In this context, the olive oil sector of the Emilia-Romagna region (Italy), and in particular the PDO Brisighella, could achieve greater success with consumers by proposing a product obtained through sustainable agriculture that enhances the content of bioactive compounds. For these reasons, in this study, different agronomic variables are investigated in order to optimize the presence of bioactive components in extra virgin olive oil made from monovarietal Nostrana di Brisighella, namely phenolic and positive volatile compounds, thus naturally enriching this product both from health and sensory points of view. The study focuses on the volatile and phenolic fractions (derivatives of hydroxytyrosol and tyrosol) of olive oil and the positive sensory attributes (fruity, bitter and pungent) that are known to be associated with these molecules. The phenolic content is of particular interest due to the potential to support health claims. Extra virgin olive oil samples were produced from olives of the Nostrana di Brisighella cultivar; fruits were obtained through integrated pest management or organic farming and picked at four increasing indices of maturity, corresponding to four successive weeks of harvesting. These agronomic variables influenced the compositional and sensory characteristics of the extra virgin olive oils assessed, highlighting differences that likely derive from the effect of the agronomic system used, i.e., integrated pest management or organic farming.

Chemical Data and Relationships for a Scoring Algorithm of Extra Virgin Olive Oil's Nutritional Value.

Extra virgin olive oil (EVOO) is a valuable product and is highly appreciated by consumers for its great nutritional value. However, to date, there has been a lack of uniform systems capable of ranking the nutritional value of EVOO based on its chemical composition in terms of macro- and micronutrients (including phenolic compounds and tocopherols). The aim of this study was to propose a scoring algorithm to rank the nutritional value of EVOO samples, considering their chemical composition in macro- and micronutrients and their sensitivity to oxidation phenomena. Data from more than 1000 EVOO samples were used to assess the variability of the data, considering the selected negative parameters (free acidity, peroxide value, spectrophotometric indices) and positive components (composition in tocopherols via HPLC-DAD, phenolic compounds via HPLC-DAD, and fatty acids via GC-MS) so as to ensure the universal validity of the scoring algorithm. The dataset included samples from the main producing countries worldwide, in addition to Australia, across several production years; data were selected to represent different production realities. A mathematical model was set up for each chemical component, resulting in six variable values. By combining these values with a dimensionless constant value, the algorithm for computing the nutritional value score (NVS) was defined. It allows the nutritional value of an oil to be ranked on a scale of 0 to 100 based on its chemical composition. The algorithm was then successfully tested using chemical data from about 300 EVOO samples obtained from laboratories from different Italian regions. The proposed NVS is a simple and objective tool for scoring the nutritional value of an EVOO, easy to understand for both producers and consumers.

Monitoring of seven pesticide residues by LC-MS/MS in extra virgin olive oil samples and risk assessment for consumers

Residue levels of seven pesticides were analyzed in thirty-five samples of Extra Virgin Olive Oil to assess the health risk of consuming Italian oils correlated with the presence of these pesticides. An in-house analytical procedure was developed and validated, consisting of a specific dispersive solid-phase extraction using the QuEChERS technique and a qualitative-quantitative analysis using liquid chromatography coupled with tandem mass spectrometry. Thirty-four percent of the samples were contaminated with pesticide residues; in the concentration range of 0.53–0.56 ng/mL for imazalil, 1.11–1.56 ng/mL for acetamiprid-N-desmethyl, 1.28–1.46 ng/mL for clothianidin, 0.94–1.49 ng/mL for thiacloprid, 1.08–4.64 ng/mL for dinotefuran, 0.42–1.47 ng/mL for thiamethoxam, 0.42–6.14 ng/mL for imidacloprid). Risk assessment was evaluated using the hazard quotient, hazard index, and Pesticide Residue Intake Model by EFSA. All hazard indices confirmed that the concentrations of pesticides detected in the oil samples did not represent a short or long-term risk for consumers’ health.

Identification of Adulterants in Extra Virgin Olive Oil Using HS-SPME-GC-MS and Multivariate Data Analysis

Food fraud, such as the adulteration of extra virgin olive oil (EVOO), is found to cause substantial negative impacts on both the economy and the health of consumers. This work was aimed at evaluating 19 EVOO samples commercialized in Foz do Iguaçu, a frontier city located around the triple border of Brazil, Argentina, and Paraguay. To detect the presence of adulteration in EVOO samples, the present study employed gas chromatography coupled to flame ionization detector (GC-FID) and headspace solid phase microextraction with gas chromatography coupled to mass spectrometry (HS-SPME-GC-MS) in order to evaluate fatty acids composition and volatile organic compounds (VOCs), respectively. The quantitative results obtained from the analysis of fatty acids composition showed that 32% of the EVOO samples were adulterated, presumably with soy oil, due to the high levels of linoleic, linolenic, and myristic acids present in them. Principal component analysis (PCA) conducted using the complete chromatographic aroma profiles obtained from the VOCs helped distinguish authentic EVOO samples from adulterated ones and the country of origin of the samples. The following aromatic compounds were first described, as possible adulterant markers: 3,3-dimethylheptanoic acid, propyl pentanoate, methyl cyclohexanecarboxylate, ethyl cyclohexanecarboxylate, 2-phenylethyl acetate, 6,10,14-trimethylpentadecan-2-one, and 1,2-dimethoxy-4-methylbenzene.

Rare Earth Element Variability in Italian Extra Virgin Olive Oils from Abruzzo Region.

Extra virgin olive oil is a food product from the Mediterranean area that is particularly and continuously experiencing to increasing instances of fraudulent geographical labeling. Therefore, origin protection must be improved, mainly based on its intrinsic chemical composition. This study aimed to perform a preliminary chemical characterization of Abruzzo extra virgin olive oils (EVOOs) using rare earth elements (REEs). REEs were evaluated in EVOO samples of different varieties produced in different geographical origins within the Abruzzo region (Italy) in three harvest years using ICP-MS chemometric techniques. Principal component, discriminant, and hierarchical cluster analyses were conducted to verify the influence of the variety, origin, and vintage of the REE composition. The results of a three-year study showed a uniform REE pattern and a strong correlation in most EVOOs, in particular for Y, La, Ce, and Nd. However, europium and erbium were also found in some oil samples. Compared with cultivar and origin, only the harvest year slightly influenced the REE composition, highlighting the interactions of the olive system with the climate and soil chemistry that could affect the multielement composition of EVOOs.

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.

Nuclear magnetic resonance analysis of extra virgin olive oil: classification through secoiridoids.

Extra virgin olive oil (EVOO), a natural product with a multidisciplinary role, has been and is continuing to be studied from several points of view. Among them, its chemical analysis is of major importance and several methods have been used. Nuclear magnetic resonance (NMR) spectroscopy has inherent advantages, among them monitoring the chemical constituents without the need for a separation technique and without, for instance, possible carry-over effects. Additionally, several magnetic resonance spectroscopic techniques can provide a novel powered insight into the nature and properties of a sample under study. Moreover, -omics procedure can reveal new information and can lead to the classification of populations under study. The main objective of the present work was the possible classification of the EVOO samples based on their aldehyde content using a proposed unreferenced 1 H-NMR spectroscopic quantification method combined with a metabolomic approach. Moreover, the study of the impact of such elevated aldehyde content on several spectra regions of importance in the proton NMR spectra led to the proposal of a possible new isomer indicator. Univariate analysis of 12 EVOO samples showed that oleacein, oleocanthal, elenolic acid, hydroxytyrosol/hydroxytyrosol derivatives and tyrosol/tyrosol derivatives strongly differentiated two classes of EVOO: OEH (for high aldehyde EVOO content) and OE (for non-high aldehyde content). Moreover, we pointed out the 'impact' of such elevated secoiridoid and derivatives content, through their moieties' units, on a range of several resonances of the 1 H-NMR spectrum. The metabolomic approach demonstrated the classification of EVOO samples based on their secoiridoid and derivatives content. Multivariate analysis showed a strong influence on the discrimination of the EVOO classes based on the protons resonating at the aldehyde region of the 1 H-NMR spectrum; the aldehyde protons corresponding to 5S,4R-ligstrodial and 5S,4R-oleuropeindial, oleacein, oleocanthal, elenolic acid, p-HPEA-EA, 3,4-DHPEA-EA, 5S,4R- and 5S,4S-ligstrodial and the proton corresponding to a new compound were reported for the first time. This isomer compound, reported for the first time, could serve as a possible indicator for EVOO classification. An unreferenced quantification method was proposed and EVOO samples were classified into two classes: OEH and OE, according to their aldehyde content, gaining thus probably higher nutrient and possible pharmacological value. Moreover, we point out the 'impact' of such elevated aldehyde content on several spectral regions of the 1 H spectrum. Finally, a new compound was detected in the OEH samples and is reported for the first time. This compound could possibly be an indicator. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Discrimination amongst olive oil categories by means of high performance-ion mobility spectrometry: A step forward on food authentication

High-performance-ion mobility spectrometry (HPIMS) has been employed for the first time in the analysis of olive oil samples after a simple liquid-liquid extraction procedure. The HPIMS-based methodology herein developed is user friendly, fast (30 s per analysis) and inexpensive. Moreover, solvent consumption is minimal, thus complying with the principles of green chemistry. The potential of the proposed approach in combination with multivariate analysis has been evaluated for classification of olive oil samples according to their organoleptic quality: extra virgin olive oil (EVOO), virgin olive oil (VOO) and lampante olive oil (LOO). In this work, 115 olive oil samples among the three categories, previously tasted by two Panel Tests, were used as reliable analytical standards to calibrate and validate the chemometric models. The average success rate of classifying samples was 68.9% for validating the ternary model (EVOO, VOO, and LOO). However, the binary model to differentiate between non-defective (EVOO) and defective (VOO and LOO) samples provided a mean classification success rate of 88.3%. In addition, EVOO samples were better classified, with a success rate of ∼90%. The proposed strategy could be used as a valuable tool to support Panel Tests in the industry, allowing for a rapid discrimination between EVOO and non-EVOO samples.

In vitro study of potential prebiotic properties of monovarietal extra virgin olive oils

Olive oil, essential ingredient of the Mediterranean diet, is attracting a growing interest due to increasing evidence on its beneficial effects on human health. This study investigated whether extra virgin olive oil (EVOO) possess prebiotic properties. Twenty different monovarietal EVOO samples from 5 Marche region cultivars (Italy) were studied. The prebiotic activity of EVOOs was assessed monitoring the selective stimulation of gut bacterial species and the short chain fatty acids (SCFAs) production, using an in vitro fermentation system. All EVOOs selectively stimulated Lactobacillus spp., with a stronger activity than that observed in the inulin fermentation (positive control). Also, the bifidobacteria population increased; this bifidogenic stimulation was of EVOOs from Raggia cultivar. SCFAs appeared significantly higher after 24 h in all EVOO fermentations than in the control. Acetic and propionic acids production was particularly stimulated. Overall, most of the investigated EVOOs had a potential prebiotic activity, similar or stronger than inulin.

Toward the Prediction of the Total Phenolic Content of Extra Virgin Olive Oil (EVOO) – A Spectrophotometric Method Combined with Multivariate Statistical Analysis

EVOO is widely considered a superior edible oil due to its unique taste and aroma. Its consumption is associated with several health benefits, many of which are attributed to its phenolic compounds. This work involved the analysis of 203 EVOO samples using the official method recommended by the IOC (COI/T.20/Doc. No 29/Rev.1 2017) to determine their polyphenolic content. In addition, ultraviolet (UV) absorption spectroscopy has been applied to the same EVOO samples in combination with PLS regression to assess the polyphenolic content. This work demonstrates that ultraviolet absorption spectroscopy offers an efficient and cost-effective alternative.

Classification of Greek extra virgin olive oils by Raman spectroscopy in conjunction with sensory and cultivation characteristics, and multivariate analysis

AbstractBackgroundExtra virgin olive oil (EVOO) is a natural product with numerous health benefits and superior quality compared with other vegetable oils. To characterize a sample as EVOO, it is necessary to perform a sensory evaluation through a testing panel, in addition to conducting physicochemical measurements. Moreover, distinguishing between organic and conventional production has captured the attention of those involved in the olive oil industry. The current study demonstrates the utilization of Raman spectroscopy in combination with multivariate statistical analysis for the examination of extra virgin olive oil samples obtained from Greece (Crete) over three consecutive harvest years.ResultsThe Raman technique and orthogonal partial least square‐discriminant analysis (OPLS‐DA) model successfully discriminated high‐ and low‐quality conventional olive oil samples for the 2017–2018 harvest year. Additionally, both organic and conventional olive oil samples were studied and distinct discrimination was achieved using OPLS‐DA on the Raman spectroscopic data for the samples with different cultivation characteristics. The combination of Raman data and statistical models for the classification of organic and conventional olive oils into high and low, and high and medium quality for the 2018–2019 and 2019–2020 harvest years, respectively, yielded satisfactory results. The samples were previously evaluated by a certified tasting panel.ConclusionsThese findings demonstrate that Raman spectroscopy, combined with multivariate statistical analysis, can serve as a complementary alternative to traditional analytical methods for the analysis of olive oils. The technique is rapid, low‐cost, and without sample pretreatment.

Exploring Strategies to Mitigate the Lightness Effect on the Prediction of Soybean Oil Content in Blends of Olive and Avocado Oil Using Smartphone Digital Image Colorimetry.

Extra virgin olive oil (EVOO) and avocado oil (AVO) are recognized for their unique sensory characteristics and bioactive compounds. Declared blends with other vegetable oils are legal, but undeclared mixing is a common type of fraud that can affect product quality and commercialization. In this sense, this study explored strategies to mitigate the influence of lighting in order to make digital image colorimetry (DIC) using a smartphone more robust and reliable for predicting the soybean oil content in EVOO and AVO blends. Calibration models were obtained by multiple linear regression using the images' RGB values. Corrections based on illuminance and white reference were evaluated to mitigate the lightness effect and improve the method's robustness and generalization capability. Lastly, the prediction of the built model from data obtained using a distinct smartphone was assessed. The results showed models with good predictive capacities, R2 > 0.9. Generally, models solely based on GB values showed better predictive performances. The illuminance corrections and blank subtraction improved the predictions of EVOO and AVO samples, respectively, for image acquisition from distinct smartphones and lighting conditions as evaluated by external validation. It was concluded that adequate data preprocessing enables DIC using a smartphone to be a reliable method for analyzing oil blends, minimizing the effects of variability in lighting and imaging conditions and making it a potential technique for oil quality assurance.

Effect of the Media in the Folin-Ciocalteu Assay for the Analysis of the Total Phenolic Content of Olive Products

The nutritional and economic value of oils is affected by its antioxidant properties linked to their total phenolic content (TPC). The analysis of antioxidants such as phenols may be affected by the lipophilic character of the media. Therefore, the accurate determination of TPC in oils deserves particular attention. This research has tested the effect of the alkaline medium in the quantification of TPC in extra virgin olive oil (EVOO) and olive pomace oil (OPO) using the Folin-Ciocalteu method. Seven different EVOO and OPO oils were used to gain representativity and study matrix effects in the analysis. Among the alkaline conditions assayed, the Folin-Ciocalteu method led to maximum TPC in EVOOs samples using 7.5% Na2CO3, whereas 35% Na2CO3 showed better characterization of TPC in OPOs than milder basic conditions. Therefore, when analyzing olive oil products, adjusting the alkaline media in the Folin Ciocalteu assay is important for optimal TPC determination. TPC analyses via Folin-Ciocalteu with different media was supported with antioxidant activities determined with reference assays: 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid cation radical and 2,2-diphenyl-1-picrylhydrazyl radical.

Detection of common adulterants in olive oils by bench top 60 MHz 1H NMR with partial least squares regression

Olive oil is the oil obtained from the fruit of the olive tree, Olea europaea L., and is commonly used in cooking, cosmetics, and soaps. The high value and demand for olive oil products has led to some producers adding cheaper edible non-olive oils to olive oil to increase their profitability. Many of these adulterant oils have similar taste profiles to extra virgin olive oil; however, these can cause allergic reactions in individuals with sensitivities to the non-olive oil. Given the implications of olive oil adulteration, there is a demand for methods to identify and quantify adulterant oils in olive oil samples. This work explores the utility of low-field benchtop nuclear magnetic resonance (NMR) with a novel chemometrics workflow for the quantification of non-olive oils in authentic extra virgin olive oil samples. The measurements were obtained using a 60 MHz 1H NMR. The icoshift algorithm was utilized for alignment, and partial least squares regression models of the entire NMR spectrum were used for quantification. Here, 17 different varieties of edible non-olive oils were investigated. The models were highly linear, accurate, and precise. Most of these adulterant oils were detectable below 10% v/v in extra virgin olive oil samples.

Application of Dispersive Liquid-Liquid Aerosol Phase Extraction to the Analysis of Total and Individual Phenolic Compounds in Fried Extra Virgin Olive Oils.

Seventeen extra virgin olive oil samples from Valencian Community (Spain) were submitted to a domestic-frying process (180 °C) during different degradation times (5, 10, 30, 60, 120 min). A dispersive liquid-liquid aerosol phase extraction by using a methanol/water (50:50) extracting solution was used to isolate the polyphenol fraction. Total phenolic content (TPC) was determined, whereas the determination of seven individual target polyphenolic compounds (hydroxytyrosol, tyrosol, oleuropein, vanillic acid, p-coumaric acid, ferulic acid, and vanillin) was carried out by using ultrahigh-performance liquid chromatography coupled to a tandem mass spectrometer. Statistically significant differences in the TPC values were found for Blanqueta and Manzanilla samples from different harvesting years. The domestic-frying process impacted the TPC and the individual phenolic compounds content. Thermal treatment for 2 h gave rise to a 94% decrease in the TPC. A first-order kinetic model was suitable to accurately describe the degradation of the individual phenolic compounds.

Effect of Adding Thymus leptobotrys on Extra Virgin Olive Oil’s Quality and Physicochemical Parameters

The present study aimed to evaluate the changes in extra virgin olive oil (EVOO) after enrichment treatments with Thymus leptobotrys, a Moroccan endemic aromatic plant. The EVOO sample was supplemented with two materials obtained from the aerial parts of T. leptobotrys: powder (2.5 and 5%) or essential oil (100 and 200 ppm). The chemical composition analysis of T. leptobotrys extracts (essential oil and powder methanolic extract) allowed the determination of its phenolic profile. Quality parameters (acidity, peroxide value, and specific extinction coefficients), color, fatty acids composition, minor components (pigments and phenol), and Rancimat oxidative stability of the control and enriched oils were measured. Rosmarinic acid and thymusin were the main identified compounds in the powder; thymusin was identified for the first time in the essential oil where it was predominant. Generally, the enrichments did not downgrade the oil from its initial category (EVOO), according to quality indexes. Adding T. leptobotrys to EVOO, especially the essential oil, enriched its phenolic profile by allowing the migration of thymusin, a lipophile flavone, without affecting its quality parameters or color.

Rapid Detection of Benzo[a]pyrene in Extra Virgin Olive Oil Using Fluorescence Spectroscopy.

Extra virgin olive oil (EVOO) should be naturally free of polycyclic aromatic hydrocarbon (PAH) contamination. PAHs are carcinogenic and toxic, and may cause human health and safety problems. This work aims to detect benzo[a]pyrene residues in EVOO using an easily adaptive optical methodology. This approach, which is based on fluorescence spectroscopy, does not require any sample pretreatment or prior extraction of PAH content from the sample, and is reported for the first time herein. The detection of benzo[a]pyrene even at low concentrations in extra virgin olive oil samples demonstrates fluorescence spectroscopy's capability to ensure food safety.

Application of Electronic Nose and Eye Systems for Detection of Adulteration in Olive Oil based on Chemometrics and Optimization Approaches

In this study, a combined system of electronic nose (e-nose) and computer vision was developed for the detection of adulteration in extra virgin olive oil (EVOO). The canola oil was blended with the pure EVOO to provide adulterations at four levels of 5, 10, 15, and 20%. Data collection was carried out using an e-nose system containing 13 metal oxide gas sensors, and a computer vision system. Applying principal component analysis (PCA) on the e-nose-extracted features showed that 93% and 92% of total data variance was covered by the three first PCs generated from Maximum Sensor Response (MSR), Area Under Curve (AUC) features, respectively. Cluster analysis verified that the pure and impure EVOO samples can be categorized by e-nose properties. PCA-Quadratic Discriminant Analysis (PCA-QDA) classified the EVOOs with an accuracy of 100%. Multiple Linear Regression (MLR) was able to estimate the adulteration percentage with the R2 of 0.8565 and RMSE of 2.7125 on the validation dataset. Moreover, factor analysis using Partial Least Square (PLS) introduced the MQ3 and TGS2620 sensors as the most important e-nose sensors for EVOO adulteration monitoring. Application of Response Surface Methodology (RSM) on RGB, HSV, L*,a*, and b* as color parameters of the EVOO images revealed that the color parameters are at their optimal state in the case up to 0.1% of canola impurity, where the obtained desirability index was 97%. Results of this study demonstrated the high capability of e-nose and computer vision systems for accurate, fast and non-destructive detection of adulteration in EVOO and detection of food adulteration may be more reliable using these artificial senses. 

TÜRKİYE PAZARLARINDA SATILAN YEMEKLİK SIVI VE KATI YAĞLARIN BAZI BOZULMA PARAMETRELERİ

In this study, some deterioration parameters were determined in nine different types of edible fats and oils (46 samples) obtained from the Turkish market, their compliance with the Turkish Food Codex and Standards was evaluated and compared with the literature. Six samples including (3 margarines, 2 shortenings and 1 riviera olive oil) had peroxide value (PV) that exceeded the codex limit. The oils with the highest PVs were found to be fish oils (8.5-27.4 meqO2/kg), peanut oils (9.2-32.1 meqO2/kg) and extra virgin olive oils (10.37-17.66 meqO2/kg). Free fatty acidity (FFA) content of one of the riviera olive oils (1.29%) and extra virgin olive oil (0.81-1.13%) sample were above the limit value of the Codex. The highest conjugated-diene and -triene were determined in fish oils (9.12-12.3 and 2.42-5.60, respectively). The p-Anisidine values in hazelnut and fish oils ranged from 2 to 61.