Application of new emerging techniques in combination with classical methods for the determination of the quality and authenticity of olive oil: a review

The substitution of extra virgin olive oil with other edible oils is the primary method for fraud in the olive-oil industry. Developing inexpensive analytical methods for confirming the quality and authenticity of olive oils is a major strategy towards combatting food fraud. Current methods used to detect such adulterations require complicated time- and resource-intensive preparation steps. In this work, a comparative study incorporating Raman and infrared spectroscopies, photoluminescence, and thermal-conductivity measurements of different sets of adulterated olive oils is presented. The potential of each characterization technique to detect traces of adulteration in extra virgin olive oils is evaluated. Concentrations of adulterant on the order of 5% can be detected in the Raman, infrared, and photoluminescence spectra. Small changes in thermal conductivity were also found for varying amounts of adulterants. While each of these techniques may individually be unable to identify impurity adulterants, the combination of these techniques together provides a holistic approach to validate the purity and authenticity of olive oils.

Adulteration of olive oil is a common practice in the industry, where old and commercial oils are mixed with fresh olive oils. Adulteration can negatively affect the quality and authenticity of olive oil, leading to economic fraud and health concerns. Therefore, identifying and quantifying adulteration in olive oil is crucial for ensuring product quality and consumer protection. The objective of this study was to identify and measure the adulteration of fresh olive oils with old oil and commercial oil from the previous harvest year. The study aimed to achieve this goal using spectroscopic techniques in combination with chemometrics. Different spectroscopic techniques, such as FT-MIR and UV-vis spectroscopy, were utilized in this study. Partial least squares (PLS) regression was applied to predict the levels of adulteration in the samples with varying concentrations (0.84 - 52.13 % w/w). Various pre-treatment methods were employed for both FTMIR and UV-Vis spectral data. All the PLS models generated for FT-MIR and UV-Vis spectral data were successful in predicting the levels of adulteration, with high coefficients of determination for both calibration (0.963 - 0.995) and cross validation (0.935 - 0.993) models. The error values for calibration (0.621 % - 2.728 %) and cross validation (0.730 % - 3.314 %) were also low. Based on the results, it was found that the use of second derivative preprocessing for FT-MIR data and SNV preprocessing for UV-Vis data led to the best performance results in quantifying the level of adulteration of olive oil. Spectroscopic techniques in combination with chemometrics can be used to identify and measure the adulteration of olive oil.

The sensory, nutritional and pharmacological value of olive oil (OO) is scientifically documented and highly acknowledged [1, 2]. The beneficial effects of OO are attributed mainly to monounsaturated fatty acids but also to biophenols. Indeed, in 2011, the European Food Safety Authority (EFSA) published a scientific opinion approving the correlation of certain OO polyphenols (hydroxytyrosol and its derivatives) and protection of LDL from oxidative damage [3]. However, OO comprises a versatile and mutable mixture since its composition is strongly associated to multiple factors such as production procedure, olive origin, variety, collection season, etc. Moreover, many constituents are still unknown and most of them commercially unavailable. Thus, the main goal of the current study is the development of efficient LC-PDA and LC-HRMSn methodologies for authentication and quality control of OO [4]. Several constituents were isolated and identified while special attention was given to the chromatographic and spectrometric behavior of secoiridoids such as oleocanthal and oleacein which are major compounds in OO but highly unstable. Different platforms such as UPLC, PR-HPLC, NP-HPLC, SFC-UV and stationary phases (RP, NP, chiral) as well as diverse sample preparation procedures have been employed for the development of specific and reproducible methods for the qualitative and quantitative analysis of OO.

ABSTRACTOver the last decades, olive oil quality and authenticity control has become an issue of great importance to consumers, suppliers, retailers, and regulators in both traditional and emerging olive oil producing countries, mainly due to the increasing worldwide popularity and the trade globalization of this product. Thus, in order to ensure olive oil authentication, various national and international laws and regulations have been adopted, although some of them are actually causing an enormous debate about the risk that they can represent for the harmonization of international olive oil trade standards. Within this context, this review was designed to provide a critical overview and comparative analysis of selected regulatory frameworks for olive oil authentication, with special emphasis on the quality and purity criteria considered by these regulation systems, their thresholds and the analytical methods employed for monitoring them. To complete the general overview, recent analytical advances to overcome drawbacks and limitations of the official methods to evaluate olive oil quality and to determine possible adulterations were reviewed. Furthermore, the latest trends on analytical approaches to assess the olive oil geographical and varietal origin traceability were also examined.

Traceability and authenticity of olive oils have become a major instrument to guarantee the consumer’s protection. Recently, determination of adulteration of olive oils is based on the analysis of simple sequence repeats. In this study, we evaluate the feasibility of identifying above cultivars and the derived oils by the analysis of SSR markers. To this purpose, 22 virgin olive oils were prepared in the laboratory and DNA was extracted using a commercial kit, and 8 SSR markers were analyzed. The obtained results indicated that the comparison of the genetic profile of DNA extracted from oil and leaves of the cultivars studied concluded different genetic profiles in some cultivars when studied for their genome as well as for their oils. These additional alleles in oil’s profile appear as minor peaks can be originating from the pollinators and which are present in the genome of the seed embryo. Hierarchical classification of varieties based on similarity measures and clustering was globally inconsistent with the grouping of varieties by end use and the geographical origin. Finally, we set up a categorization means to discriminate all the types of oil among them with the minimum of markers (three markers).

The chlorophyll and carotenoid pigment profile of 50 mono‐variety virgin olive oils was used to develop an index of authenticity for the product. The presence of carotenoids other than those described, or chlorophyll derivatives at another level of degradation, were found to be determing elements of this index for “virgin” olive oil quality. In addition, the ratio of chlorophyll/carotenoid should be around 1, and the ratio of minor carotenoids/lutein should be about 0.5, with a limited variability. These characteristics may be expected of virgin olive oil in general and are independent of variety. Finally, the percentage of lutein, violaxanthin, and total pigment content may be used to distinguish between mono‐variety virgin olive oils.

The authentication of extra virgin olive oils from different regions of Spain, Italy and Portugal, by means of their fatty acids, alcohols, sterols, methyl sterols and hydrocarbons content, has been investigated. Multivariate statistical methods and Evidence's Theory were applied. The comparative study shows greater predictive ability using this theory than the traditional statistical methods or expert systems that do not implement the possibility theory. A detailed and exhaustive study of Italian (Tuscany and Basilicata), Portuguese and Spanish virgin olive oils has been made. Geographically coloured maps of the studied regions are shown to strengthen the numerical results.

Sterols are important minor constituents of the unsaponifiable fraction of virgin olive oil. They have critical roles in determining the authenticity of the oil and they are known to be affected by process conditions and maturity. Here, optimization of the malaxation temperatures at between 21 and 49 °C and times at between 24 and 66 min by response surface methodology is aimed in terms of oil yield, and contents of individual sterols and triterpene dialcohols of oils from olives at three maturity stages (spotted, purple, black). Results show that the amount of sterols is varied in different extents depending on the malaxation conditions as well as maturity stages. Mathematical models display high prediction performance to explain the variation in the studied responses of apparent β‐sitosterol, total sterol, β‐sitosterol, campesterol, and stigmasterol for all maturity stages. The optimum conditions of malaxation temperature and time are 31 °C/44 min, 36 °C/26 min, and 37 °C/24 min from spotted, purple, and black fruits, respectively. In end, this study proves transition to the highest desired sterols with oil yield, and the lowest undesired sterols and triterpene dialcohols from fruits to oil by malaxating at moderate temperatures, not cold and hot pressing.Practical applications: Sterols and triterpene dialcohols make up a large part of the minor components of olive oil. This group has gained high importance, especially after their significant impacts on the authenticity of olive oil. Sterolic content and triterpene dialcohols of olive oil depend especially on the fruit's maturity and processing methods. Malaxation temperature and time were optimized to achieve the transferability of the highest desired sterols and the lowest undesired sterols and triterpene dialcohols according to limits of the Commission Regulation (EEC). The current study was also evaluated by the change of total sterol content and individual sterol and triterpene diols profile of oils obtained from olives at different maturity stages. The optimized malaxation conditions are successful to achieve goals. Overall, it can be stated that olive oils with high desired sterols and low triterpene diols and undesired sterols in terms of EEC limits are economically precious.

Authentication of Olive Oil Adulterated with Vegetable Oils Using Fourier Transform Infrared Spectroscopy

Olive oil is a highly nutritious food, rich in vitamins and unsaturatted fatty acids. Different grades can be produced, with extra virgin olive oil being the purest and most expensive grade. Adulteration of olive oil can occur by either mixing it with other vegetable oils or by adding cheaper olive oil to more expensive grades (most commonly extra virgin olive oil). A variety of methods are currently used to verify the authenticity of the product and detect adulterants or contaminants, including chromatographic (e.g. High Performance Liquid Chromatography, Gas Chromatography), spectroscopic (e.g. Ultra-violet -Visible, Near-Infrared, Mid-Infrared, Fourier-transform infrared spectroscopy), or DNA-based methods (e.g. Polymerase Chain reaction). Finally a series of methodologies combining the above-mentioned techniques have recently been trialed, leading to potential improvements in the accuracy and effectiveness of the authentication processes.

The objective of the present work is to evaluate the relationship between the edapho-climatic conditions of the cultivation environment and the variability of olive productivity, yield, and quality of olive oil in orchards of the Moroccan Picholine (PM) population variety (Olea europaea L.). This work was carried out on different agricultural territorial units (agroecosystems) of the Beni Mellal-Khenifra region with a semi-arid climate during four agricultural seasons (2016/2017 to 2019/2020). For this purpose, the relevant agronomic and agro-biochemical parameters were studied, namely the stage of maturity, fruit and olive oil yields and quality indices. The data treatments of the results were performed according to descriptive and affiliated statistics by analysis of variance (ANOVA). We have found significant correlations (according to Pearson's R) between agroecosystems, particularly for weight of crude olives produced per hectare and temperature (R= 0.803), olive yield and humidity (R= 0.654), olive oil yield and temperature (R= 0.837), olive oil richness and humidity (R= -0.622), as well as the qualitative characteristics of the extracted oils, through the levels of free acidity and peroxide value (R = 0.467). These results confirm that in the studied semi-arid environments, the properties of the biotope of the cultivated olive groves, combined with the interannual agroclimatic variability, effectively influence the productivity of the olive trees, the oil production and the chemical and organoleptic quality of the extracted olive oil

Tocopherols are natural fluorophores of great importance for the characterization and authentication of virgin olive oil. Herein, a single automatic multicommuted flow method has been developed for the determination of total tocopherol content as well as the semi-quantitative estimation of α-tocopherol in extra virgin olive oil (EVOO) samples. Only appropriate dilution of samples with 2-propanol was necessary for their direct analysis by a multicommuted flow injection (MCFIA) manifold based on three solenoid valves with fluorescence detection. The peak height at λ em = 330 nm (emission) with λ exc at 296 nm was used as analytical signal. Linear response was observed within the range from 50 to 350 mg of tocopherols (expressed as α-tocopherol kg−1 olive oil), suitable to cover the usual range for tocopherols in (extra) virgin olive oil ((E)VOO)). The results were consistent with those obtained by reversed-phase HPLC reference method, whereas the analysis time was significantly reduced. The sample frequency of the proposed automatic method was close to 40 samples h−1, in contrast to typically 15–30 min required by HPLC. The method is fast, straightforward, cost-effective, and easy to implement in routine laboratories for screening purposes.

ABSTRACTNowadays, while the authenticity of agri-food products becomes a major concern for consumers, given the increasing rate of food fraud reports across the world, olive oil records the highest adulterations. The high selling price of olive oil is the main reason for conducting adulteration, which is often caused through false indications on the packaging (mislabeling). On the other hand, consumers are well aware of the alteration, and they are looking for authenticity signals during the purchase process. Authenticity, therefore, becomes an evaluation and decision-making criterion that guides consumer choices. The aim of this paper was twofold: to highlight the attributes in which Greek consumers attach great importance during the evaluation of olive oil’s authenticity, and second, through consumers’ demographic segmentation, to gain more detailed knowledge about the attributes that consumers evaluate in olive oil authenticity. CUB (Covariates in a mixture of Uniform and Binomial random variables) models are employed for the interpretation of ordinal data due to the ability of comparing and clustering the rating distributions consumers express about olive oil features, and due to the ability of detecting significant similarities and differences in consumer responses. Moreover, with the introduction of respondents’ social, demographic, and financial characteristics, CUB models allow the measurement of the influence that the consumers’ profile has upon the attributes of olive oil authenticity. The results showed that consumers attached great importance to taste, acidity, country and region of origin, olive variety, color, organic production, and regional certification in the evaluation of olive oil authenticity. In addition, secondary school graduates tend to use taste and olive variety, also indicating confidence in the authenticity of organic olive oil.

One of the main challenges for olive oil producers is the ability to assess oil quality regularly during the production cycle. The quality of olive oil is evaluated through a series of parameters that can be determined, up to now, only through multiple chemical analysis techniques. This requires samples to be sent to approved laboratories, making the quality control an expensive, time-consuming process, that cannot be performed regularly and cannot guarantee the quality of oil up to the point it reaches the consumer. This work presents a new approach that is fast and based on low-cost instrumentation, and which can be easily performed in the field. The proposed method is based on fluorescence spectroscopy and one-dimensional convolutional neural networks and allows to predict five chemical quality indicators of olive oil (acidity, peroxide value, UV spectroscopic parameters K 270 and K 232 , and ethyl esters) from one single fluorescence spectrum obtained with a very fast measurement from a low-cost portable fluorescence sensor. The results indicate that the proposed approach gives exceptional results for quality determination through the extraction of the relevant physicochemical parameters. This would make the continuous quality control of olive oil during and after the entire production cycle a reality. • We present the application of 1D-CNN to single fluorescence spectra without pre- and post- processing of the data. • We discuss a method for the application of 1D-CNN to small datasets. • The 1D-CNN determines the physicochemical parameters within the instrument errors. • The proposed solution has the potential to substitute chemical analyses to assess the quality of olive oil.

Authenticity of olive oil is a significant concern for producers, consumers, and policymakers. To help address this issue, a rapid, efficient, and accurate flow injection mass spectrometric (FIMS) fingerprinting approach, combined with SVM and PLS classification and regression models, was proposed for the identification and quantitative analysis of olive oil adulteration. Based on the comprehensive comparative analysis, SVM outperformed those of PLS-DA, achieving higher values for accuracy, sensitivity, and specificity, as well as positive predictive and negative predictive values, in identifying adulterated olive oil samples. Furthermore, compared with PLSR model, the SVR model demonstrated superior performance in determining the content of adulterated olive oil, with a higher coefficient of determination and lower Root Mean Square Error. In conclusion, FIMS fingerprinting technology in combination with SVM can be effectively implemented for rapid, reliable, and accurate identification and quantification of olive oil adulteration.