Synchronous fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil

Adulteration of extra virgin olive oil with sunflower oil is a major issue for the olive oil industry. In this paper, the potential of total synchronous fluorescence (TSyF) spectra to differentiate virgin olive oil from sunflower oil and synchronous fluorescence (SyF) spectra combined with multivariate analysis to assess the adulteration of virgin olive oil are demonstrated. TSyF spectra were acquired by varying the excitation wavelength in the region 270–720 nm and the wavelength interval (Δλ) in the region from 20 to 120 nm. TSyF contour plots for sunflower, in contrast to virgin olive oil, show a fluorescence region in the excitation wavelength range 325–385 nm. Fifteen different virgin olive oil samples were adulterated with sunflower oil at varying levels (0.5–95%) resulting in one hundred and thirty six mixtures. The partial least-squares regression model was used for quantification of the adulteration using wavelength intervals of 20 and 80 nm. This technique is useful for detection of sunflower oil in virgin olive oil at levels down to 3.4% (w/v) in just two and a half minutes using an 80-nm wavelength interval.     

Linear and non linear chemometric models to quantify the adulteration of extra virgin olive oil

Two mathematical methods to quantify adulterations of extra virgin olive oil (EVOO) with refined olive oil (ROO), refined olive-pomace oil (ROPO), sunflower (SO) or corn (CO) oils have been described here. These methods are linear and non linear models based on chaotic parameters (CPs, Lyapunov exponent, autocorrelation coefficients and two fractal dimensions) which were calculated from UV-vis scans (190-900 nm wavelength) of 817 adulterated EVOO samples. By an external validation process, linear and non linear integrated CPs/UV-vis models estimate concentrations of adulterant agents with a mean correlation coefficient (estimated versus real concentration of cheaper oil) greater than 0.80 and 0.97 and a mean square error less than 1% and 0.007%, respectively. In the light of the results shown in this paper, the adulteration of EVOO with ROO, ROPO, SO and CO can be suitably detected by only one chaotic parameter integrated on a radial basis network model.     

Fluorescence spectroscopy for monitoring deterioration of extra virgin olive oil during heating

The potential of fluorescence spectroscopy for characterizing the deterioration of extra virgin olive oil (EVOO) during heating was investigated. Two commercial EVOO were analysed by HPLC to determine changes in EVOO vitamin E and polyphenols as a result of heating at 170°C for 3 h. This thermal oxidation of EVOO caused an exponential decrease in hydroxytyrosol and vitamin E (R²=0.90 and 0.93, respectively) whereas the tyrosol content was relatively stable. At the same time, amounts of preformed hydroperoxides (ROOH), analysed by an indirect colorimetric method, decreased exponentially during the heating process (R²=0.94), as a result of their degradation into secondary peroxidation products. Fluorescence excitation spectra with emission at 330 and 450 nm were recorded to monitor polyphenols and vitamin E evolution and ROOH degradation, respectively. Partial least-squares calibration models were built to predict these indicators of EVOO quality from oil fluorescence spectra. A global approach was then proposed to monitor the heat charge from the overall fluorescence fingerprint. Different data pretreatment methods were tested. This study indicates that fluorescence spectroscopy is a promising, rapid, and cost-effective approach for evaluating the quality of heat-treated EVOO, and is an alternative to time-consuming conventional analyses. In future work, calibration models will be developed using a wide range of EVOO samples.     

The detection and quantification of adulteration in olive oil by near-infrared spectroscopy and chemometrics.

A new procedure has been developed for the classification and quantification of the adulteration of pure olive oil by soya oil, sun flower oil, corn oil, walnut oil and hazelnut oil. The study was based on a chemometric analysis of the near-infrared (NIR) spectra of olive-oil mixtures containing different adulterants. The adulteration of olive oil was carefully carried out gravimetrically in a 4 mm quartz cuvette, starting with pure olive oil in the cuvette first. NIR spectra of the 525 adulterated mixtures were measured in the region of 12,000-4000 cm(-1). The spectra were subjected batch wise to multiplicative signal correction (MSC) before calculating the principal component (PCA) models. The MSC-corrected data were subjected to Savitzky-Golay smoothing and a mean normalization procedure before developing partial least-squares calibration (PLS) models. The results revealed that the models predicted the adulterants, corn oil, sun flower oil, soya oil, walnut oil and hazelnut oil involved in olive oil with error limits +/-0.57, +/-1.32, +/-0.96, +/-0.56 and +/-0.57% weight/weight, respectively. Furthermore, the PCA developed models were able to classify unknown adulterated olive oil mixtures with almost 100% certainty. Quantification of the adulterants was carried out using their respective PLS models within the same error limits as mentioned above.     

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.     

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.     

Analysis of phenolic compounds in extra virgin olive oil by using reversed-phase capillary electrochromatography

In this work, the simultaneous separation of ten phenolic compounds (protocatechuic, p-coumaric, o-coumaric, vanillic, ferulic, caffeic, syringic acids, hydroxytyrosol, tyrosol and oleuropein) in extra virgin olive oils (EVOOs) by isocratic RP CEC is proposed. A CEC method was optimized in order to completely resolve all the analyzed compounds by studying several experimental parameters. The influence of the stationary phase type (C(18) and C(8) modified silica gel), buffer concentration and pH as well as the organic modifier content of the mobile phase on retention factors, selectivity and efficiency were evaluated in details. A capillary column packed with Cogent bidentate C(18) particles for 23 cm and a mobile phase composed by 100 mM ammonium formate buffer pH 3/H(2)O/ACN (5:65:30 v/v/v) allowed the baseline resolution of the compounds under study in less than 35 min setting the applied voltage and temperature at 22 kV and 20 degrees C, respectively. A study, evaluating the intra- and interday precision as well as LOD and LOQ and method linearity was developed in accordance with the analytical procedures for method validation. LODs were in the range of 0.015-2.5 microg/mL, while calibration curves showed a good linearity (r(2) >0.997). The CEC method was applied to the separation and determination of these compounds in EVOO samples after a suitable liquid-liquid extraction procedure. The mean recovery values of the studied compounds ranged between 87 and 99%.     

Tracing the origin of extra virgin olive oils by infrared spectroscopy and chemometrics: A case study

In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling (SIMCA) approach to classification were employed. Results obtained after processing the spectroscopic data by PLS-DA evidenced a rather high classification accuracy, NIR providing better predictions than MIR (as evaluated both in cross-validation and on an external test set). SIMCA confirmed these results and showed how the category models for the class Sabina can be rather sensitive and highly specific. Lastly, as samples from two harvesting years (2009 and 2010) were investigated, it was possible to evidence that the different production year can have a relevant effect on the spectroscopic fingerprint. Notwithstanding this, it was still possible to build models that are transferable from one year to another with good accuracy.     

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%.     

Detection of refined olive oil adulteration with refined hazelnut oil by employing NMR spectroscopy and multivariate statistical analysis

NMR spectroscopy was employed for the detection of adulteration of refined olive oil with refined hazelnut oil. Fatty acids and iodine number were determined by ¹H NMR, whereas ³¹P NMR was used for the quantification of minor compounds including phenolic compounds, diacylglycerols, sterols, and free fatty acids (free acidity). Classification of the refined oils based on their fatty acids content and the concentration of their minor compounds was achieved by using the forward stepwise canonical discriminant analysis (CDA) and the classification binary trees (CBTs). Both methods provided good discrimination between the refined hazelnut and olive oils. Different admixtures of refined olive oils with refined hazelnut oils were prepared and analyzed by ¹H NMR and ³¹P NMR spectroscopy. Subsequent application of CDA to the NMR data allowed the detection of the presence of refined hazelnut oils in refined olive oils at percentages higher than 5%. Application of the non-linear classification method of the binary trees offered better possibilities of measuring adulteration of the refined olive oils at a lower limit of detection than that obtained by the CDA method.     

Original normal-phase high-performance liquid chromatographic separation of monoacylglycerol classes from extra virgin olive oil triacylglycerols for their stereospecific analysis

An innovative procedure to separate the 3 isomeric sn-monoacylglycerols (MAG) classes (sn-1-, sn-2-, sn-3-MAG) is described. MAGs, obtained by chemical deacylation of triacylglycerols (TAGs), have been derivatized with (S)-(+)-1-(1-naphtyl)ethyl-isocyanate, and the resulting urethane derivatives have been separated by normal-phase high-performance liquid chromatography. This procedure allows resolution as diasteroisomers of the 2 enantiomeric classes (sn-1-MAG and sn-3-MAG), without the need of a chiral column, and to separate also the isomeric sn-2-MAG class; moreover, by introducing a chromophoric moiety, this reagent makes possible the ultraviolet detection of the analyte molecules. This procedure has been used to obtain the stereospecific analysis of the TAG fraction of extra virgin olive oil samples. The use of a nondestructive detector permitted the collection of the individual urethane classes; the fatty acid composition of each was determined by high-resolution gas chromatography, obtaining directly from the data the fatty acid distribution within each sn- position of TAGs. To validate this new method, the results have been compared with those obtained by 2 other procedures for TAG stereospecific analysis, and the obtained results were satisfactory since the proposed method gave data very similar to the other procedures.     

Quality assessment and authentication of virgin olive oil by NMR spectroscopy: A critical review

Nuclear Magnetic Resonance (NMR) Spectroscopy has been extensively used for the analysis of olive oil and it has been established as a valuable tool for its quality assessment and authenticity. To date, a large number of research and review articles have been published with regards to the analysis of olive oil reflecting the potential of the NMR technique in these studies. In this critical review, we cover recent results in the field and discuss deficiencies and precautions of the three NMR techniques (¹H, ¹³C, ³¹P) used for the analysis of olive oil. The two methodological approaches of metabonomics, metabolic profiling and metabolic fingerprinting, and the statistical methods applied for the classification of olive oils will be discussed in critical way. Some useful information about sample preparation, the required instrumentation for an effective analysis, the experimental conditions and data processing for obtaining high quality spectra will be presented as well. Finally, a constructive criticism will be exercised on the present methodologies used for the quality control and authentication of olive oil.     

The information content of visible spectra of extra virgin olive oil in the characterization of its origin

The information content of visible spectra has been evaluated, by means of some selected chemometrical techniques, for its ability to trace the geographical origin of extra virgin olive oils coming from several Mediterranean regions. Special attention was paid to extra virgin olive oil produced in West Liguria, a North Italy region which leans over the Mediterranean Sea and borders France. The peculiar organoleptic features of this "niche product" deserved the protected designation of origin "Riviera Ligure-Riviera dei fiori". Unfortunately, this expensive oil is often submitted to profitable adulterations, commonly involving addition of other cheaper Mediterranean oils. Using suitable transforms, such as profiles and derivatives, the visible spectra of extra virgin olive oils showed a very important discriminant power in that regards the geographical characterization of the studied samples. In particular, the developed class models for West Liguria oils have 100% sensitivity and specificity. Moreover, even if this paper is focused on West Liguria oil, it is important to emphasize that a similar study, involving a so widespread and timesaving technique, could be analogously developed for all the other Mediterranean regions taken into account and it could be used in other olive oil characterization problems.     

Analysis of olive oil and seed oil triglycerides by capillary gas chromatography as a tool for the detection of the adulteration of olive oil

Individual triglyceride (TG) species of olive oil and several seed oils (corn, cottonseed, palm, peanut, soybean, and sunflower) are baseline separated on a WCOT TAP CB fused-silica capillary column by capillary gas chromatography (CGC) with a flame-ionization detector (FID) and either cold on-column or split injection. An adulteration of olive oil with a low content (< 5%) of these seed oils (except peanut oil) can be verified by the detection of the increasing levels of trilinolein or tripalmitin in olive oil in which these TG species are normally absent or present at very low levels (< 0.5%). An adulteration with over 20% peanut oil can be detected by the increasing levels of palmitodilinolein. TG species that can be coeluted with trilinolein in the reversed-phase high-performance liquid chromatographic (RP-HPLC) mode are baseline separated by the CGC technique, and their structures are identified by selective ion monitoring mass spectrometry. The following comparisons--the CGC-FID and RP-HPLC methods for detection of adulteration, cold on-column and split-injection modes for CGC-FID, and silylation or thin-layer chromatography pretreatment and simple dilution of one or more of the oil samples--are also presented. The normalized percentage area of the TG species is sufficient for the method limits used in this study. Mixtures of virgin olive oil with refined or residue olive oil could not be distinguished from the virgin type by the method used in this study.     

Study of the influence of triacylglycerol composition on DSC cooling curves of extra virgin olive oil by chemometric data processing

In this work, a coupled high-pressure liquid chromatography-differential scanning calorimetry-partial least square (HPLC–DSC–PLS) procedure was applied to clarify the influence of triacylglycerol composition on the shape of cooling curves for extra virgin olive oil (EVOo), as chemometric processing of digitized DSC curves was previously reported to be an attractive alternative to the application of the common procedure of parameter extrapolation for the analysis of thermal transition. 69 samples of EVOo were analysed to obtain triacylglycerol (TAG) composition by means of HPLC and DSC cooling profiles. Results obtained by the application of PLS algorithm on TAG concentration (%) and digitized DSC curves showed that cooling transitions were markedly influenced by OOO, OLO and OOP + SLO that are the most representative TAG for EVOo. Other TAG as LLP + OLnO, LLL + LLPo and POPo developed good PLS models, appearing to influence EVOo cooling curve, although less markedly than the further. Otherwise, the other identified TAG did not render appropriate models. Finally, grouping TAG according to different unsaturation degree, high correlation coefficients (>0.80) and low relative standard deviations (<11 %) were found for sum of tri-unsaturated triacylglycerols in both calibration and validation sets. Starting from these encouraging results, this new and fast coupled approach may be applied to a wider set of EVOo samples to tentatively discriminate among oils according to different geographical and/or botanical origins taking into account relation established among TAG and cooling curves.     

Gas chromatography-atmospheric pressure chemical ionization-time of flight mass spectrometry for profiling of phenolic compounds in extra virgin olive oil

A new analytical approach based on gas chromatography coupled to atmospheric pressure chemical ionization-time of flight mass spectrometry was evaluated for its applicability for the analysis of phenolic compounds from extra-virgin olive oil. Both chromatographic and MS parameters were optimized in order to improve the sensitivity and to maximize the number of phenolic compounds detected. We performed a complete analytical validation of the method with respect to its linearity, sensitivity, precision, accuracy and possible matrix effects. The LODs ranged from 0.13 to 1.05ppm for the different tested compounds depending on their properties. The RSDs for repeatability test did not exceed 6.07% and the accuracy ranged from 95.4% to 101.5%. To demonstrate the feasibility of our method for analysis of real samples, we analyzed the extracts of three different commercial extra-virgin olive oils. We have identified unequivocally a number of phenolic compounds and obtained quantitative information for 21 of them. In general, our results show that GC-APCI-TOF MS is a flexible platform which can be considered as an interesting tool for screening, structural assignment and quantitative determination of phenolic compounds from virgin olive oil.     

On testing quality and traceability of virgin olive oil by calorimetry

Extra Virgin olive oils (7 samples) originating from different areas of Tuscany, defective olive oils (5 samples), commercial edible seed oils (4 samples) and two commercial samples of olive oil (one declared ‘extra virgin olive oil’ and one ‘olive oil’) were studied by different calorimetric techniques: high sensitivity isothermal, differential scanning, and modulated scanning calorimetry. The temperature interval (–60) – (+30)°C was explored for monitoring: i) the main features of the liquid↔solid phase transitions, ii) the nucleation and growth rate of the polymorphous crystalline phases of the triacylglicerols, and iii) the melting process. This investigation was planned for verifying the utility and effectiveness of calorimetry for screening quality and origin of olive oil. To this end, the main calorimetric operation modes have been applied, the experimental results reported and their utility for developing an effective and reliable screening protocol discussed.     

Classification of edible and lampante virgin olive oil based on synchronous fluorescence and total luminescence spectroscopy

Total luminescence and synchronous fluorescence spectroscopies were tested as regards their ability to differentiate edible from lampante virgin olive oils. Total luminescence spectra were recorded by measuring the emission spectra in the range 350-720 nm at excitation wavelengths from 320 to 535 nm. The synchronous fluorescence spectra of 41 edible and 32 lampante virgin olive oils were acquired by synchronous scanning the excitation and emission monochromator maintained at an offset value of 80 nm. Classification of virgin olive oils based on their synchronous fluorescence spectra was performed by hierarchical cluster analysis and principal component analysis using the spectral range of 429-545 nm. Principal component analysis provided better discrimination between the two classes, without any classification error, while hierarchical cluster analysis allowed 97.3% correct classification. These results indicate the capability of fluorescence techniques to differentiate virgin olive oils according to their quality.