Application of lag-k autocorrelation coefficient and the TGA signals approach to detecting and quantifying adulterations of extra virgin olive oil with inferior edible oils

The combination of lag-k autocorrelation coefficients (LCCs) and thermogravimetric analyzer (TGA) equipment is defined here as a tool to detect and quantify adulterations of extra virgin olive oil (EVOO) with refined olive (ROO), refined olive pomace (ROPO), sunflower (SO) or corn (CO) oils, when the adulterating agents concentration are less than 14%. The LCC is calculated from TGA scans of adulterated EVOO samples. Then, the standardized skewness of this coefficient has been applied to classify pure and adulterated samples of EVOO. In addition, this chaotic parameter has also been used to quantify the concentration of adulterant agents, by using successful linear correlation of LCCs and ROO, ROPO, SO or CO in 462 EVOO adulterated samples. In the case of detection, more than 82% of adulterated samples have been correctly classified. In the case of quantification of adulterant concentration, by an external validation process, the LCC/TGA approach estimates the adulterant agents concentration with a mean correlation coefficient (estimated versus real adulterant agent concentration) greater than 0.90 and a mean square error less than 4.9%.     

Determination of betaines in vegetable oils by capillary electrophoresis tandem mass spectrometry--application to the detection of olive oil adulteration with seed oils

A CE–tandem mass spectrometry (MS²) methodology enabling the simultaneous determination of betaines (glycine betaine, trigonelline, proline betaine and total content of carnitines) in vegetable oils was developed. Betaines were derivatized with butanol previous to their baseline separation in 10 min using a 0.1 M formic acid buffer at pH 2.0. Ion trap conditions were optimized in order to maximize the selectivity and sensitivity. Analytical characteristics of the proposed method were established by evaluating its selectivity, linearity, precision (RSDs ranged from 4.8 to 10.7% for corrected peak areas) and accuracy by means of recovery studies (from 80 to 99%) and LODs and LOQs at 0.1 ppb level. The method was applied for the determination of the selected betaines in seed oils and extra virgin olive oils. MS² experiments provided the fingerprint fragmentation for the betaines identified in vegetable oils. In extra virgin olive oils, carnitines were not detected, making it possible to propose them as a feasible novel marker for the detection of adulterations of olive oils. Application of the developed method for the analysis of different mixtures of extra virgin olive oil with seed oil (between 2 and 10%) enabled the detection and quantitation of the total content of carnitines. The results obtained show the high potential of the developed method for the authentication and quality control of olive oils.     

Sequential (step-by-step) detection,identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles

An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria.     

Investigations of the adulteration of extra virgin olive oils with seed oils using their weak chemiluminescence

A weak chemiluminescence (CL) emission was observed in commercial Greek extra virgin olive oils (Knossos, Spitiko, Ananias, Altis, Minerva, Xenia) and in refined seed oils such as sunflower oils (Marata, Sanola, Sun, Mana, Sol, Minerva) as well as in corn oils (Flora, Minerva, Marata Sun and Sol) with potassium superoxide in the aprotic solvent dimethoxyethylene.On measuring the CL of mixtures of extra virgin olive oils with the cheaper refined seed oils, calibrations were produced which can be used for the determination of the adulteration of olive oils with seed oils down to 3%. Furthermore, depending on the kind of oils, “low” authenticity-CL-factors for olive oils (0.8-2.15 μmol l⁻¹ gallic acid) and “high” for seed oils (4.5-11.2 μmol l⁻¹ gallic acid) were calculated.     

Optimization and application of methods of triacylglycerol evaluation for characterization of olive oil adulteration by soybean oil with HPLC-APCI-MS-MS

Triacylglycerols (TAGs) are the main constituents of vegetable oils where they occur in complex mixtures with characteristic distributions. Mass spectrometry using an atmospheric pressure chemical ionization interface (APCI-MS) run in positive mode and an Ion Trap mass analyser were applied in the study of olive and soybean oils and their mixtures. Direct injections of soybean and olive oil solutions allowed the identification of ions derived from the main TAGs of both oils. This procedure showed to be a simple and powerful tool to evaluate mixtures or addition of soybean to olive oil. TAG separation was optimized by high performance liquid chromatography (HPLC) using an octadecylsilica LiChrospher column (250 mm × 3 mm; 5 μm) and a gradient composed of acetonitrile and 2-propanol allowed the separation of the main TAGs of the studied oils. APCI vaporization temperature was optimized and best signals were obtained at 370 °C. Multiple reaction monitoring (MRM) employing the transition of the protonated TAG molecules ([M+H]⁺) to the protonated diacylglycerol fragments ([M+H−R]⁺) improved the selectivity of TAG detection and was used in quantitative studies. Different strategies were developed to evaluate oil composition following TAG analysis by MRM. The external standard calibration and standard additions methods were compared for triolein quantification but the former showed to be biased. Further quantitative studies were based on the estimates of soybean and olive oil proportions in mixtures by comparison of TAG areas found in mixtures of known and unknown composition of both oils. Good agreement with expected or labeled values was found for a commercial blend containing 15% (w/w) of olive oil in soybean oil and to a 1:1 mixture of both oils, showing the potential of this method in characterizing oil mixtures and estimating oil proportions. Olive oils of different origins were also evaluated by mass spectra data obtained after direct injections of oil solutions and principal component analysis (PCA). Argentinean olive oils were clustered in a different area of the principal components plot (PC2 × PC1) in comparison with European olive oils. The commercial blend containing 15% (w/w) of olive oil in soybean oil appeared in a completely different area of the graphic, showing the potential of this method to screen out for olive oil adulterations.     

Fast quantitative detection of sesame oil adulteration by near-infrared spectroscopy and chemometric models

Adulteration of foods has been known to exist for a long time and various analytical tests have been reported to address this problem. Among them, authenticity of sesame oil has attracted much attention. Near-infrared (NIR) spectral quantitative detection models of sesame oil adulterated with other oils are constructed by chemometric methods, i.e., competitive adaptive reweighted sampling (CARS), elastic component regression (ECR) and partial least squares (PLS). Sixty samples adulterated with different proportions of five kinds of other oils of lower price were scanned by a Fourier-transform-NIR spectrometer and the NIR spectra were collected in 4500–10000 cm⁻¹ region by transmission mode. All samples were divided into the training set and an independent test set. Model population analysis has also been carried out and confirms the importance of selecting representative samples. The experimental results indicate that the PLS model using only 10 variables from CARS and the ECR model show similar performance and both are superior to the full-spectrum PLS model. CARS focuses on selecting variables and ECR focuses on optimizing the parameters, implying that both roads lead to the same destination. It seems that NIR technique combined with CARS or ECR is feasible for rapidly detecting sesame oil adulterated with other vegetable oils.     

Chemometric applications to assess quality and critical parameters of virgin and extra-virgin olive oil. A review

Today virgin and extra-virgin olive oil (VOO and EVOO) are food with a large number of analytical tests planned to ensure its quality and genuineness. Almost all official methods demand high use of reagents and manpower. Because of that, analytical development in this area is continuously evolving. Therefore, this review focuses on analytical methods for EVOO/VOO which use fast and smart approaches based on chemometric techniques in order to reduce time of analysis, reagent consumption, high cost equipment and manpower.     

High‐performance liquid chromatography with fluorescence detection for the rapid analysis of pheophytins and pyropheophytins in virgin olive oil

Pheophytins and pyropheophytin are degradation products of chlorophyll pigments, and their ratios can be used as a sensitive indicator of stress during the manufacturing and storage of olive oil. They increase over time depending on the storage condition and if the oil is exposed to heat treatments during the refining process. The traditional analysis method includes solvent‐ and time‐consuming steps of solid‐phase extraction followed by analysis by high‐performance liquid chromatography with ultraviolet detection. We developed an improved dilute/fluorescence method where multi‐step sample preparation was replaced by a simple isopropanol dilution before the high‐performance liquid chromatography injection. A quaternary solvent gradient method was used to include a fourth strong solvent wash on a quaternary gradient pump, which avoided the need to premix any solvents and greatly reduced the oil residues on the column from previous analysis. This new method not only reduces analysis cost and time but shows reliability, repeatability, and improved sensitivity, especially important for low‐level samples.     

Nano and rapid resolution liquid chromatography–electrospray ionization–time of flight mass spectrometry to identify and quantify phenolic compounds in olive oil

The applicability of nanoLC‐ESI‐TOF MS for the analysis of phenolic compounds in olive oil was studied and compared with a HPLC method. After the injection, the compounds were focused on a short capillary trapping column (100 μm id, effective length 20 mm, 5 μm particle size) and then nanoLC analysis was carried out in a fused silica capillary column (75 μm id, effective length 10 μm, 3 μm particle size) packed with C18 stationary phase. The mobile phase was a mixture of water + 0.5% acetic acid and ACN eluting at 300 nL/min in a gradient mode. Phenolic compounds from different families were identified and quantified. The quality parameters of the nanoLC method (linearity, LODs and LOQs, repeatability) were evaluated and compared with those obtained with HPLC. The new methodology presents better sensitivity (reaching LOD values below 1 ppb) with less consumption of mobile phases, but worse repeatability, especially inter‐day repeatability, resulting in more difficulties to get highly accurate quantification. The results described in this article open up the application fields of this technique to cover a larger variety of compounds and its advantages will make it especially useful for the analysis of samples containing low concentration of phenolic compounds, as for instance, in biological samples.     

Microwave-assisted extraction at atmospheric pressure coupled to different clean-up methods for the determination of organophosphorus pesticides in olive and avocado oil

An effective extraction method was devised for the determination of organophosphorus pesticides (OPPs) in olive and avocado oil samples, using atmospheric pressure microwave-assisted liquid–liquid extraction (APMAE) and solid-phase extraction or low-temperature precipitation as clean-up step. A simple glass system equipped with an air-cooled condenser was designed as an extraction vessel. The pesticides were partitioned between acetonitrile and oil solution in hexane. Analytical determinations were carried out by gas chromatography-flame photometric detection and gas chromatography–tandem mass spectrometry, using a triple quadrupole mass analyzer, for confirmation purposes. Several factors influencing the extraction efficiency were investigated and optimized through fractional factorial design and Doehlert design. Under optimal conditions the recovery of pesticides from oil at 0.025 μg g⁻¹ ranged from 71% to 103%, except for fenthion in avocado oil, with RSDs ≤13% (n = 5). The LOQ for the entire method ranged from 0.004 to 0.015 μg g⁻¹. Finally, the proposed method was successfully applied to the extraction and determination of the selected pesticides in 20 commercially packed extra virgin olive oils and four commercially packed avocado oils produced in Chile. Detectable residues of different OPPs were observed in 85% of samples.     

Electrospray ionization mass spectrometry and partial least squares discriminant analysis applied to the quality control of olive oil

Direct infusion electrospray ionization mass spectrometry in the positive ion mode [ESI(+)‐MS] is used to obtain fingerprints of aqueous–methanolic extracts of two types of olive oils, extra virgin (EV) and ordinary (OR), as well as of samples of EV olive oil adulterated by the addition of OR olive oil and other edible oils: corn (CO), sunflower (SF), soybean (SO) and canola (CA). The MS data is treated by the partial least squares discriminant analysis (PLS‐DA) protocol aiming at discriminating the above‐mentioned classes formed by the genuine olive oils, EV (1) and OR (2), as well as the EV adulterated samples, i.e. EV/SO (3), EV/CO (4), EV/SF (5), EV/CA (6) and EV/OR (7). The PLS‐DA model employed is built with 190 and 70 samples for the training and test sets, respectively. For all classes (1–7), EV and OR olive oils as well as the adulterated samples (in a proportion varying from 0.5 to 20.0% w/w) are properly classified. The developed methodology required no ions identification and demonstrated to be fast, as each measurement lasted about 3 min including the extraction step and MS analysis, and reliable, because high sensitivities (rate of true positives) and specificities (rate of true negatives) were achieved. Finally, it can be envisaged that this approach has potential to be applied in quality control of EV olive oils. Copyright © 2013 John Wiley & Sons, Ltd.     

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.