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.     

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.     

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.     

The ability of spectrum autocorrelation models to predict the lycopene concentration in foods through visible spectroscopic data

We developed a novel computerized approach based on lag-k autocorrelation coefficients (LCCs) and linear models (LMs) to estimate the concentration of lycopene in foods by the spectroscopy. The LCCs were calculated using the data obtained using whole visible scans from 400 to 600 nm (vide supra) of lycopene standards and food samples (ketchup, tomato juice and tomato sauce). The chaotic parameter (CP) was then transferred into a LM to estimate the concentration of lycopene compound. The integrated LCC/visible spectroscopy method developed can be considered as a satisfactory analytical technique able to estimate lycopene concentration in food samples in a fast accurate way, with a mean prediction error lower than 5.7% and a mean correlation coefficient higher than 0.957.     

Olive oil microemulsions: enzymatic activities and structural characteristics

Microemulsions composed of olive oil, either extravirgin (EVOO) or refined (ROO), as the continuous oil phase, water as the dispersed phase, and a mixture of lecithin-propanol as the emulsifier were prepared and investigated as potential biocompatible media for biotransformations. The area of the microemulsion zone increased considerably by increasing the lecithin to propanol weight ratio in both EVOO- and ROO-based systems. However, the nature of the oil used does not seem to affect the ability of the system to incorporate water. The catalytic activities of two oxidizing enzymes that have been detected in virgin olive oil, namely, tyrosinase and peroxidase, and the activity of a proteolytic enzyme such as trypsin were studied in olive oil microemulsions. In all cases a reduced catalytic activity was observed when ROO was considered as the continuous oil phase. The interfacial properties of lecithin layers were studied by electron paramagnetic resonance spectroscopy employing the nitroxide spin probe 5-doxylstearic acid. By varying the weight ratio of lecithin to propanol and the water content of the microemulsions, the mobility of the probe and the rigidity of the interface were altered. Droplet sizes were measured by dynamic light scattering. At higher water content of the system the size of the droplets was increased. When EVOO was considered as the oil phase, smaller aqueous droplets were formed. Lecithin-based olive oil microemulsions were also characterized with regard to the phenomenon of electrical percolation. At a water content above 3% (w/w) and a lecithin/propanol weight ratio of 2, a sharp increase in conductivity was observed, indicating a structural transition in the bicontinuous form.     

Visible and near-infrared absorption spectroscopy by an integrating sphere and optical fibers for quantifying and discriminating the adulteration of extra virgin olive oil from Tuscany

Because of its high price, extra virgin olive oil is frequently targeted for adulteration with lower quality oils. This paper presents an innovative optical technique capable of quantifying and discriminating the adulteration of extra virgin olive oil caused by lower-grade olive oils. An original set-up for diffuse-light absorption spectroscopy in the wide 400–1,700 nm spectral range was experimented. It made use of an integrating sphere containing the oil sample and of optical fibers for illumination and detection; it provided intrinsically scattering-free absorption spectroscopy measurements. This set-up was used to collect spectroscopic fingerprints of authentic extra virgin olive oils from the Italian Tuscany region, adulterated by different concentrations of olive-pomace oil, refined olive oil, deodorized olive oil, and refined olive-pomace oil. Then, a straightforward multivariate processing of spectroscopic data based on principal component analysis and linear discriminant analysis was applied which was successfully capable of predicting the fraction of adulterant in the mixture, and of discriminating its type. The results achieved by means of optical spectroscopy were compared with the analysis of fatty acids, which was carried out by standard gas chromatography.     

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.     

Application of Fourier transform infrared (FT-IR) spectroscopy combined with chemometrics for authentication of cod-liver oil

Some vegetable oils such as canola (CaO), corn (CO), soybean (SO), and walnut (WO) oils have similar color with cod liver oil (CLO), therefore, the presence of these oils was difficult to detect using naked eye. For this reason, Fourier transform infrared (FTIR) spectroscopy using horizontal attenuated total reflectance (HATR) as sampling accessory and in the combination with chemometrics was developed for detection and quantification of these vegetable oils as adulterants in CLO. The quantification of vegetable oils was carried out by using multivariate calibrations of partial least squares (PLS) and principle component regression (PCR), while the classification between pure CLO and CLOs adulterated with CaO, CO, SO, and WO was performed using discriminant analysis (DA). PLS with FTIR normal spectra was more suitable compared with PCR for quantification purposes with coefficient of determination (R²) higher than 0.99 and root mean square error of calibration (RMSEC) in the range of 0.04-0.82% (v/v). The PLS model was further used to predict the levels of these vegetable oils in independent samples for validation/prediction purpose. The root mean square error of prediction (RMSEP) values obtained were of 1.75% (v/v) (CaO), 1.39% (v/v) (CO), 1.35% (v/v) (SO), and 1.37% (v/v) (WO), respectively. The classification using DA revealed that the developed method can classify CLO and that mixed with these vegetable oils using 9 principal components.     

Recognition of adulteration of Italian wines by thin-film multisensor array and artificial neural networks

The paper reports the use of a chemoresistive multisensor array for recognition of some adulterated Italian wines (two white, four red, two rosè) added with methanol, ethanol or other same-colour wine. A multisensor array constituted by four thin-film semiconducting metal oxide sensors, surface-activated by Pt, Au, Pd, Bi metal catalysts, has been used to generate the chemical pattern of the volatile compounds present in the wine samples. The responses of the multisensor array towards wines tested by headspace sampling have been evaluated. Multivariate analysis including principal component analysis (PCA) as well as back-propagation method trained artificial neural networks (ANNs) have been applied to analytical data generated from the multisensor array to identify both the adulteration of wines and to determine the added content of adulterant agent of methanol or ethanol up to 10 vol.%. The cross-validated ANNs provide the highest achieved percentage of correct classification of 93% and the highest achieved correlation coefficient of 0.997 and 0.921 for predicted-versus-true concentration of methanol and ethanol adulterant agent, respectively.     

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.     

DSC方法在特级初榨橄榄油掺假鉴别中的应用

采用差示扫描量热法(DSC)对进口特级初榨橄榄油中葵花籽油的掺假鉴别进行了系统研究。由橄榄油入手考察了升降温循环实验条件下油品的重复性及数据可靠性,以此为基础提出采用程序降温的方法研究油品的结晶特性。统计了研究体系内的8种特级初榨橄榄油、6种其他食用油以及5种比例的模拟掺假油的结晶峰温度值,建立了回归方程。结果表明:进口特级初榨橄榄油在-60~-46℃区间内具有尖锐的结晶峰;随着掺入葵花籽油比例的升高,模拟掺假油的结晶温度逐渐向低温区移动,结晶峰形由尖锐逐渐变平坦;由结晶起始温度和结晶峰值温度分别相对于掺假油体积分数建立的回归方程具有很好的相关性,可以快速准确地鉴别特级初榨橄榄油。     

Comparative Evaluation of Different Targeted and Untargeted Analytical Approaches to Assess Greek Extra Virgin Olive Oil Quality and Authentication

Extra virgin olive oil (EVOO) is a key component of the Mediterranean diet, with several health benefits derived from its consumption. Moreover, due to its eminent market position, EVOO has been thoroughly studied over the last several years, aiming at its authentication, but also to reveal the chemical profile inherent to its beneficial properties. In the present work, a comparative study was conducted to assess Greek EVOOs’ quality and authentication utilizing different analytical approaches, both targeted and untargeted. 173 monovarietal EVOOs from three emblematic Greek cultivars (Koroneiki, Kolovi and Adramytiani), obtained during the harvesting years of 2018–2020, were analyzed and quantified as per their fatty acids methyl esters (FAMEs) composition via the official method (EEC) No 2568/91, as well as their bioactive content through liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) methodology. In addition to FAMEs analysis, EVOO samples were also analyzed via HRMS-untargeted metabolomics and optical spectroscopy techniques (visible absorption, fluorescence and Raman). The data retrieved from all applied techniques were analyzed with Machine Learning methods for the authentication of the EVOOs’ variety. The models’ predictive performance was calculated through test samples, while for further evaluation 30 commercially available EVOO samples were also examined in terms of variety. To the best of our knowledge, this is the first study where different techniques from the fields of standard analysis, spectrometry and optical spectroscopy are applied to the same EVOO samples, providing strong insight into EVOOs chemical profile and a comparative evaluation through the different platforms.     

Composition Profiling and Authenticity Assessment of Camellia Oil Using High Field and Low Field 1H NMR

Camellia oil (CA), mainly produced in southern China, has always been called Oriental olive oil (OL) due to its similar physicochemical properties to OL. The high nutritional value and high selling price of CA make mixing it with other low-quality oils prevalent, in order to make huge profits. In this paper, the transverse relaxation time (T₂) distribution of different brands of CA and OL, and the variation in transverse relaxation parameters when adulterated with corn oil (CO), were assessed via low field nuclear magnetic resonance (LF-NMR) imagery. The nutritional compositions of CA and OL and their quality indices were obtained via high field NMR (HF-NMR) spectroscopy. The results show that the fatty acid evaluation indices values, including for squalene, oleic acid, linolenic acid and iodine, were higher in CA than in OL, indicating the nutritional value of CA. The adulterated CA with a content of CO more than 20% can be correctly identified by principal component analysis or partial least squares discriminant analysis, and the blended oils could be successfully classified by orthogonal partial least squares discriminant analysis, with an accuracy of 100% when the adulteration ratio was above 30%. These results indicate the practicability of LF-NMR in the rapid screening of food authenticity.     

Rapid quantitative analysis of adulterant Lonicera species in preparations of Lonicerae Japonicae Flos

Lonicerae Japonicae Flos is often adulterated with Lonicerae Flos, which is derived from the other four Lonicera species, in both the crude drug and Lonicerae Japonicae Flos preparations. We proposed a methodology for the quantitative analysis of adulterant Lonicerae Flos in Lonicerae Japonicae Flos preparations. Taking macranthoidins A, B, dipsacoside B (saponins), sweroside (iridoids), and luteolin‐7‐O‐d ‐glucoside (flavonoids) as markers, a method of ultra high performance liquid chromatography with triple quadrupole mass spectrometry was employed to determine their amounts in Lonicerae Flos, Lonicerae Japonicae Flos, and Lonicerae Japonicae Flos preparations. The proportion of adulterant Lonicerae Flos in Lonicerae Japonicae Flos preparations was estimated based on the saponin contents of Lonicerae Japonicae Flos and Lonicerae Flos. All analytes separated under isocratic elution in 12 min with acceptable linearity, precision, repeatability, and accuracy. Lonicerae Japonicae Flos was easily distinguished from Lonicerae Flos by the total amount of saponins (0.067 and > 45.8 mg/g for Lonicerae Japonicae Flos and Lonicerae Flos, respectively). Eighteen of twenty one Lonicerae Japonicae Flos preparation samples were adulterated with Lonicerae Flos in proportions of 11.3–100%. The developed ultra high performance liquid chromatography with triple quadrupole mass spectrometry method could be used for the identification of Lonicerae Japonicae Flos and the four species of Lonicerae Flos and for the analysis of Lonicerae Japonicae Flos preparations adulterated with Lonicerae Flos.     

Determination of Bitterness of Extra Virgin Olive Oils by Amperometric Detection

A flow injection system with amperometric detection at potentials poised at +0.4 and +0.9 V was used to evaluate intensity of the bitter taste in monovarietal Extra Virgin Olive Oils (EVOO). Results from the proposed method were based on the extraction of the bitter constituents of the virgin olive oil samples in methanol‐water, followed by the direct amperometric measurement. These potentials were selected according to the hydrodynamic voltammogram of oleuropein, one of the most prominent and bitter phenolic compound found in EVOO. The amperometric detection was applied on 32 monovariatal EVOO samples. Results were correlated with the phenolic profile measured by high performance liquid chromatography (HPLC). The amperometric signal at +0.9 V mainly correlated with the total phenols of the samples (R²=0.81), whereas the signal at +0.4 V mainly correlated with oleuropein aglycone (3,4 DHPEA‐EDA, R²=0.79). Bitterness intensity of the samples was evaluated by a trained sensory panel of experts and the results compared to those obtained by the amperometric flow system. The best correlation with the bitter taste was achieved by the sensor at +0.4 V (R²=0.72). A calibration model based on partial least squares was built with three variables, namely the sensors set at +0.4 and +0.9 V and the total phenol content of the EVOO extracts. The model showed a moderate capacity to predict the bitterness of the EVOO samples using leave one out method, (R²=0.75) and in prediction of a test set of samples (R²=0.7). Such approach is very promising for future studies.     

Epigenetic Modifications Induced by Olive Oil and Its Phenolic Compounds: A Systematic Review

Many studies demonstrated that olive oil (especially extra virgin olive oil: EVOO) phenolic compounds are bioactive molecules with anti-cancer, anti-inflammatory, anti-aging and neuroprotective activities. These effects have been recently attributed to the ability of these compounds to induce epigenetics modifications such as miRNAs expression, DNA methylation and histone modifications. In this study, we systematically review and discuss, following the PRISMA statements, the epigenetic modifications induced by EVOO and its phenols in different experimental systems. At the end of literature search through “PubMed”, “Web of Science” and “Scopus”, 43 studies were selected.Among them, 22 studies reported data on miRNAs, 15 on DNA methylation and 13 on histone modification. Most of the “epigenomic” changes observed in response to olive oil phenols’ exposure were mechanistically associated with the cancer preventive and anti-inflammatory effects. In many cases, the epigenetics effects regarding the DNA methylation were demonstrated for olive oil but without any indication regarding the presence or not of phenols. Overall, the findings of the present systematic review may have important implications for understanding the epigenetic mechanisms behind the health effects of olive oil. However, generally no direct evidence was provided for the causal relationships between epigenetics modification and EVOO health related effects. Further studies are necessary to demonstrate the real physiological consequences of the epigenetics modification induced by EVOO and its phenolic compounds.     

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.     

The concentration of oleocanthal in olive oil waste

The aim of this study was to determine the concentration of oleocanthal in olive pomace waste and compare this to its concentration in extra-virgin olive oil (EVOO). The concentration of oleocanthal in freshly pressed EVOO and its subsequent waste was analysed at early, mid and late season harvests. Oleocanthal concentrations were quantified using high-performance liquid chromatography-mass spectrometry. In oil, oleocanthal concentration was as follows: 123.24 ± 6.48 mg kg(-1) in early harvest, 114.20 ± 17.42 mg kg(-1) in mid harvest and 152.22 ± 10.54 mg kg(-1) in late harvest. Its concentration in waste was determined to be: 128.25 ± 11.33 mg kg(-1) in early harvest, 112.15 ± 1.51 mg kg(-1) in mid harvest and 62.35 ± 8.00 mg kg(-1) in late harvest. Overall, olive pomace waste is a valuable source of oleocanthal.     

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.     

Development of a methodology based on headspace-gas chromatography-ion mobility spectrometry for the rapid detection and determination of patin fish oil adulterated with palm oil

The present research intends to develop a new method based on headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the detection and determination of patin fish oil adulterated with different percentages of palm oil, because it is a cheaper vegetable oil. Five variables that affect headspace generation (incubation time and temperature, amount of sample, injection volume, and pre-heating time) have been optimized by means of a Box Behnken design in combination with Response Surface Methodology. Then, repeatability and intermediate precision have been studied where coefficients of variation lower than 10% were obtained. This new method has been applied to several samples of patin fish oil adulterated with palm oil at 20 different levels (5–50% palm oil content). The results have confirmed the suitability of the HS-GC-IMS for a rapid, easy, and reliable detection and discrimination of adulterated oil samples since a characteristic fingerprint that allows 100% successful discrimination between adulterated and unadulterated patin oil samples was achieved. Finally, a regression model has been developed to determine each sample’s adulteration level with an error lower than 10% and a coefficient of determination greater than 0.95.