Origin Of Virgin Olive Oils Research Articles

A Preliminary Study on the Potential of FT-IR Spectroscopy and Chemometrics for Tracing the Geographical Origin of Moroccan Virgin Olive Oils.

The authentication of the geographical origin of virgin olive oils (VOO) generally requires the use of sophisticated and time-consuming analytical techniques. There is a need for quick and simple analytical techniques to predict the origin of olive oils. This study aims to examine the physico-chemical data of olive oils collected in six regions of Morocco during two consecutive years 2020 and 2021, and also to evaluate the ability of FT-IR in combination with discrimination tools to study the geographical origin of Moroccan olive oils. Fourier transform infrared spectroscopy (FTIR) was used in this study as an emerging analytical technique to express a unique "fingerprint." A preliminary processing of the ATR-FTIR spectral data was performed by preprocessing algorithm to reduce the noise and the effect of signal variation as well as to minimize the effects of light scattering to extract the maximum analytical information from the spectra. A multivariate statistical procedure based on principal component analysis (PCA) coupled with linear discriminant analysis (LDA) as well as partial least-squares discriminant analysis (PLS-DA) was developed to provide a powerful classification approach. Based on the PCA, six clusters were identified. The application of PCA-LDA and PLS-DA procedures demonstrate a powerful capacity in predicting the geographic origin of olive oils; this capacity is shown by the high value of correct classification rate (CCR), varying between 84.09 and 100%. The suggested procedure has given reliable results for the classification of olive oils according to their geographical origin, with advantages such as being fast, inexpensive, and not requiring any prior separation process. The performance of this approach is significantly faster and possesses a higher degree of selectivity and sensitivity. The implementation of this technique for routine analysis of olive oil would save significant time, resources, and solvents.

Laser-induced breakdown spectroscopy coupled with machine learning as a tool for olive oil authenticity and geographic discrimination

Olive oil is a basic element of the Mediterranean diet and a key product for the economies of the Mediterranean countries. Thus, there is an added incentive in the olive oil business for fraud through practices like adulteration and mislabeling. In the present work, Laser Induced Breakdown Spectroscopy (LIBS) assisted by machine learning is used for the classification of 139 virgin olive oils in terms of their geographical origin. The LIBS spectra of these olive oil samples were used to train different machine learning algorithms, namely LDA, ERTC, RFC, XGBoost, and to assess their classification performance. In addition, the variable importance of the spectral features was calculated, for the identification of the most important ones for the classification performance and to reduce their number for the algorithmic training. The algorithmic training was evaluated and tested by means of classification reports, confusion matrices and by external validation procedure as well. The present results demonstrate that machine learning aided LIBS can be a powerful and efficient tool for the rapid authentication of the geographic origin of virgin olive oil.

Development of Chemometric Models Based on a LC-qToF-MS Approach to Verify the Geographic Origin of Virgin Olive Oil.

In the presented study a non-targeted approach using high-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (HPLC-ESI-qToF-MS) combined with chemometric techniques was used to build a statistical model to verify the geographic origin of virgin olive oils. The sample preparation by means of liquid/liquid extraction of polar compounds was optimized regarding the number of multiple extractions, application of ultrasonic treatment and temperature during concentration of the analytes. The presented workflow for data processing aimed to identify the most predictive features and was applied to a set of 95 olive oils from Spain, Italy, Portugal and Greece. Different strategies for data reduction and multivariate analysis were compared. Stepwise variable selection showed for both applied multivariate models—linear discriminant analysis (LDA) and logit regression (LR)—to be the most suitable variable selection strategy. The 10-fold cross validation of the LDA showed a classification rate of 83.1% for the test set. For the LR models the prediction accuracy of the test set was even higher with values of 90.4% (Portugal), 86.2% (Italy), 93.8% (Greece) and 88.3% (Spain). Moreover, the reduction of features allows an easier following up strategy for identification of the unknowns and defining marker substances.

Evaluation of the Capability of Horizontal ATR-FTMIR and UV-Visible Spectroscopy in the Discrimination of Virgin Olive Oils from the Moroccan Region of Beni Mellal-Khenifra

One of the most important challenges in the authentication of olive oil is the determination of the geographical origin of virgin olive oil. In this work, we evaluated the capacity of two spectroscopic techniques, UV-Visible and ATR-FTMIR, coupled with chemometric tools to determine the geographical origin of olive oils. These analytical approaches have been applied to samples that have been collected during the period of olive oil production, in the Moroccan region of Beni Mellal-Khenifra. To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. The application of the PCA-LDA method on the spectral data of UV-Visible and ATR-FTMIR shows a good ability to classify olive oils according to their geographical origin with a percentage of correct classification that represents 90.24% and 85.87%, respectively, and the processing of the spectral data of UV-Visible and ATR-FTMIR by PCA-SVM allows differentiating correctly between five olive oils with a correct classification rate of 100% and 97.56, respectively. This study demonstrated the feasibility of UV-Visible and ATR-FTMIR fingerprinting (routine technique) for the geographical classification of olive oils in the Moroccan region of Beni Mellal-Khenifra. Such developed methods can be proposed as alternative and complementary methods to authenticate the geographical origin of virgin olive oil.

Authentication of the geographical origin of virgin olive oils from the main worldwide producing countries: A new combination of HS-SPME-GC-MS analysis of volatile compounds and chemometrics applied to 1217 samples

Authentication of geographical origin of virgin olive oils is necessary to protect consumer and producers from frauds. A method able to classify virgin olive oils from the main worldwide producing countries is still missing. In this work, we developed 3 chemometric approaches for classification of virgin olive oils from Italy, Spain, Greece, Portugal, Tunisia and other countries all over the world. The approaches were developed starting from a data-set containing fatty acid composition and the amount of 72 volatile compounds, evaluated by a never applied HS-SPME-GC-MS quantitation method, of 1217 oil samples from three different olive oil campaign. The approach that gave the best predictive results is based on Linear Discriminant Analysis run on quantitative data from only 25 volatile compounds selected by one-way ANOVA as the most capable in discriminating between the diverse origins. The method was built and internally validated using a training-set of 1000 samples and externally validated with a test-set of 217 independent samples. The method was able to classify the geographical origin of 94.5% samples, with a percentage of correct classification even higher than 97% for some origins. Preliminary studies also suggested the proposed approach is able to correctly classify the geographical origin of binary mixtures of oils from different origins. The approach proposed in this manuscript is easily applicable in testing laboratories and represents a very useful tool for the olive oil field, helping in protecting consumers and producers from frauds.

Assessment of Vibrational Spectroscopy Performance in Geographical Identification of Virgin Olive Oils: A World Level Study

AbstractIn order to guarantee food integrity, testing methods should also include the tools needed to verify the geographical origin described on the label. In the particular case of virgin olive oil (VOO), regulatory bodies have yet to establish a standard for geographical identification. This manuscript describes a procedure based on Raman spectroscopy to identify the provenance of these oils based on a classification criterion (European vs non‐European VOOs). The sample collection is considered a relevant step in which multiple factors are taken into account (cultivar distribution, complexity of production in each location, new agricultural practices, and new/old cultivars). A total of 78 virgin olive oils collected around the world allow checking the classification accuracy of the model for identifying sample origin. The PLS‐model built around the Raman spectroscopic data is validated with a blind set of samples, and the results are evaluated in terms of false negative and false positive quality parameters. This study provides an analytical application to detect mislabeling and fraudulent practices related to the geographical provenance of virgin olive oils declared on the labels.Practical Applications: The results of this study provide a robust mathematical model to assess the origin of virgin olive oils (EU vs non‐EU) based on spectroscopic data. Nowadays, the extensive knowledge of olive oil chemical composition has proven that this composition varies according to pedoclimatic conditions, while non‐targeted methods can be proposed in geographical traceability for their ability to analyze the chemical profile of samples. However, it was deemed necessary to conduct a study through a collaborative work initiative. Thus, this study provides a strict evaluation of Raman spectroscopy through a defined strategy for evaluating non‐targeted methods for geographical identification.

Andalusian Protected Designations of Origin of Virgin Olive Oil: The Role of Chemical Composition in Their Authentication

The latest regulation to protect unique virgin olive oils that have particular properties is called protected designations of origin (PDOs), and it has proven to be a successful way to protect quality and geographical authenticity. Nevertheless, sometimes the registration of new PDOs associated to new demarcations of geographic areas are almost based on administrative aspects rather than objective chemical data. In this study, the ability of chemical compounds of virgin olive oils with PDO is analyzed that are not labile and their concentrations do not vary over time − fatty acids, alcohols, hydrocarbons, methyl‐sterols and sterols − to differentiate them from those produced in their neighboring geographical areas. Three cases in the Andalusia region (Southern Spain) that combine pedoclimatic characteristics and variations of cultivar have been studied (9 areas with PDO and 3 non‐PDO areas). With a modified procedure of ANOVA analysis − the Brown–Forsythe test, chemical compounds that show good characteristics for the classification of samples are selected, and this ability is later checked by applying the unsupervised algorithm of Principal Component Analysis. Differences in their chemical composition are found when comparing the PDO oils with those produced in the neighboring olive tree groves despite chemical criteria are not among the most decisive factors for registering PDOs.Practical Applications: The practical application of this study is centered in the possibilities of the chemical composition of virgin olive oil being used to differentiate the PDO authenticity. The results of this study proves that it is difficult to establish discreet limits defining the PDO areas. The current physical‐chemical information should be used by both administration and PDO councils to supplement arguments for approving or denying new PDOs.Chemistry can assist the authenticity of virgin olive oil PDOs. The registration of new PDOs associated with new demarcations of geographic areas are almost based on administrative aspects rather than objective chemical data. In this work, chemical compounds that show good characteristics for the classification of samples are selected, and their classifying ability is later checked.

Rapid and innovative instrumental approaches for quality and authenticity of olive oils

The quality of virgin olive oils is assessed through the determination of several analytical parameters, whose values must be within the ranges established by the different institutions involved. In addition to official methods, there is a strong need for simple, rapid, and environmentally friendly techniques for the quality control of virgin olive oils and for addressing the challenging task of determining geographical origin and detecting adulterants. Toward this purpose, some of the most interesting applications based on optical spectroscopic techniques, on the measurement of electrical characteristics and on the use of instruments equipped with electronic chemical sensors, including also other promising techniques are herein discussed. These techniques, adequately coupled with an appropriate statistical approach, appear to be promising for assessment of several quality‐related parameters. The prediction of sensory attributes and of the oxidative status of virgin olive oils have also been reviewed by adopting these selected techniques, which are also considered to be potentially appropriate solutions for identification of the geographical origin of virgin olive oils and to assess their adulteration with cheaper oils. Overall, the techniques discussed are promising and cutting‐edge approaches for the establishment of useful portable instruments for in situ monitoring of the quality of virgin olive oils.Practical applications: The simple, rapid, and environmentally friendly analytical approaches discussed herein represent promising analytical tools for assuring the authenticity and monitoring the quality of virgin olive oils. Such innovative techniques and tools need to be ring‐tested and validated. Some innovative reviewed approaches will permit to develop useful portable instruments able to perform in situ appropriate controls also by small laboratories or olive oil mills with limited technical facilities. These equipments will be potentially usable also by trained “non‐professional analytical skilled” people. Some other approaches, rapid but more expensive, will be applicable mainly by quality control labs and will increase the number of samples analyzed per day, thus fostering laboratory proficiency and an effective fighting against olive oil fraud.Quality analysis of virgin olive oil can be achieved by a set of chemical and sensory determinations. Reference chemical analyses are usually carried out in a laboratory by trained personnel and requires high costs and lengthy times to obtain results. Innovative techniques characterized by high accuracy, short response time, and possibility of in situ analysis to evaluate olive oil quality are reviewed herein. Such techniques can be divided in different groups depending on the principle of the methodology: 1) optical techniques, such as UV‐Vis, NIR, MIR, Raman, and fluorescence spectroscopy; 2) electrical techniques, such as electrical impedance spectroscopy, amperometry, and time domain reflectometry; and 3) electronic noses, electronic tongues and other promising approaches, where an array of electrodes or other technical solutions (PTR‐MS, FGC E‐nose, NMR) are used in conjunction with multivariate data analysis to obtain a chemical fingerprint of the product.

1H‐NMR and isotopic fingerprinting of olive oil and its unsaponifiable fraction: Geographical origin of virgin olive oils by pattern recognition

1H‐NMR spectral data and H and C isotope abundances of virgin olive oils (VOOs) and their unsaponifiable fractions were analyzed by pattern recognition techniques, such as principal component analysis (PCA) and partial‐least squares discriminant analysis (PLS‐DA). The aim was to develop chemical tools for the authentication of VOOs according to their geographical origin or protected designation of origin (PDO), as well as to detect the mislabeling of the provenance of VOOs, at the regional or national level, or the mislabeling of non‐PDO oils as PDO VOOs. The relationship between stable isotope abundances of the VOOs and their unsaponifiable fractions and the latitude of the VOO geographical origin was confirmed, but these criteria were not completely discriminant to differentiate VOOs according to their geographical origin. However, δ2H and/or δ13C data provided complementary geographical information to 1H‐NMR data in the PLS‐DA binary classification models afforded for VOOs from Greece, Spain, Italy, Izmir (Turkey), Crete (Greece), and the PDOs Riviera Ligure (Italy) and Huile d'olive d'Aix−en−Provence (France). 2H/1H and 13C/12C ratios of the unsaponifiable fractions of VOOs are reported here for the first time. The present approach for PDO Riviera Ligure VOOs, based on 1H‐NMR data and C isotope abundance of the bulk oil and its unsaponifiable fraction, outperformed the previously reported classification models. Moreover, the PLS‐DA models to authenticate VOOs from Greece and detect non‐Greek VOOs achieved over 93% of correct predictions.Practical applications: The research can be applied in the protection of consumers and honest producers and retailers, and provides potential tools for antifraud authorities and regulatory bodies, which face the challenge of detecting fraudulent practices that do not comply with EU regulations in the trade of VOOs, such as the mislabeling of VOOs produced in a certain geographical origin [Commission Implementing Regulation (EC) no 29/2012 and Commission Implementing Regulation (EC) no 1335/2013] and/or under specific EU quality schemes, named PDO or PGI [Council Regulation (EC) no 510/2006].1H‐NMR spectral data and H and C isotope abundances of virgin olive oils (VOOs) and their unsaponifiable fractions were analyzed by pattern recognition techniques, in order to develop chemical tools for the authentication of VOOs according to their geographical origin or protected designation of origin (PDO), as well as to detect the mislabeling of the provenance of VOOs, at the regional or national level, or the mislabeling of non‐PDO oils as PDO VOOs.

Mass spectrometry fingerprinting coupled to National Institute of Standards and Technology Mass Spectral search algorithm for pattern recognition

A new analytical strategy based on mass spectrometry fingerprinting combined with the NIST-MS search program for pattern recognition is evaluated and validated. A case study dealing with the tracing of the geographical origin of virgin olive oils (VOOs) proves the capabilities of mass spectrometry fingerprinting coupled with NIST-MS search program for classification. The volatile profiles of 220 VOOs from Liguria and other Mediterranean regions were analysed by secondary electrospray ionization-mass spectrometry (SESI-MS). MS spectra of VOOs were classified according to their origin by the freeware NIST-MS search v 2.0. The NIST classification results were compared to well-known pattern recognition techniques, such as linear discriminant analysis (LDA), partial least-squares discriminant analysis (PLS-DA), k-nearest neighbours (kNN), and counter-propagation artificial neural networks (CP-ANN). The NIST-MS search program predicted correctly 96% of the Ligurian VOOs and 92% of the non-Ligurian ones of an external independent data set; outperforming the traditional chemometric techniques (prediction abilities in the external validation achieved by kNN were 88% and 84% for the Ligurian and non-Ligurian categories respectively). This proves that the NIST-MS search software is a useful classification tool.

PRELIMINARY EVALUATION OF THE APPLICATION OF THE FTIR SPECTROSCOPY TO CONTROL THE GEOGRAPHIC ORIGIN AND QUALITY OF VIRGIN OLIVE OILS

ABSTRACT A rapid Fourier transform infrared (FTIR) attenuated total reflectance spectroscopic method was applied to determine qualitative parameters such as free fatty acid (FFA) content and the peroxide value (POV) in virgin olive oils. Calibration models were constructed using partial least squares regression on a large number of virgin olive oil samples. The best results (R2 = 0.955, root mean square error in cross validation [RMSECV] = 0.15) to evaluate FFA content expressed in oleic acid % (w/w) were obtained considering a calibration range from 0.2 to 9.2% of FFA relative to 190 samples. For POV determination, the result obtained, built on 80 olive oil samples with a calibration range from 11.1 to 49.7 meq O2/kg of oil, was not satisfactory (R2 = 0.855, RMSECV = 3.96). We also investigated the capability of FTIR spectroscopy, in combination with multivariate analysis, to distinguish virgin olive oils based on geographic origin. The spectra of 84 monovarietal virgin olive oil samples from eight Italian regions were collected and elaborated by principal component analysis (PCA), considering the fingerprint region. The results were satisfactory and could successfully discriminate the majority of samples coming from the Emilia Romagna, Sardinian and Sicilian regions. Moreover, the explained variance from this PCA was higher than 96%.PRACTICAL APPLICATIONSThe verification of the declared origin or the determination of the origin of an unidentified virgin olive oil is a challenging problem. In this work, we have studied the applicability of Fourier transform infrared coupled with multivariate statistical analysis to discriminate the geographic origin of virgin olive oil samples from different Italian regions.

Triacylglycerol and fatty acid compositions of French virgin olive oils. Characterization by chemometrics.

There is no data concerning the fatty acid and triacylglycerol composition of French virgin olive oil. Thus, these compositions were determined using 564 samples coming from four olive harvests (1998-1999 to 2000-2001). Among these 564 samples, 372 came from the four main French cultivars (Aglandau, Cailletier, Picholine, and Salonenque) and from both of the oldest French protected designations of origin: "Nyons" (cv. Tanche) and "Vallée des Baux". The fatty acid compositions took the different isomeric monounsaturated fatty acids (C16:1 and C18:1) into account. The eicosenoic acid is gondoic acid (20:1n-9) and was determined by dimethyl disulfide adduct using GC/MS. The use of propionitrile as a mobile phase for the HPLC analysis of the triacylglycerols led to better resolutions between triacylglycerols than those resolutions obtained with the mix of solvents recommended by the normalized method (acetone/acetonitrile). Of the samples, 88 had a 9-heptadecenoic acid level (17:1n-8) higher than 0.3% and 33 had a linolenic acid level higher than 0.9%, which are maximal values accepted by the International Olive Oil Council and the European Union. A linear discriminant analysis was carried out on 372 samples with the SAS system and particularly with STEPISC and CANDISC procedures. Variables (n = 37) representing the different fatty acids, the sum of saturated, monounsaturated, and polyunsaturated fatty acids, squalene, and triacylglycerols were used, thus allowing us to classify samples into six groups defined with 100% of well classified samples. These results constitute an original data bank that can be used to identify the origin of virgin olive oils.

1H and13C NMR of virgin olive oil. An overview

The authentication and quality assessment of virgin olive oil were performed using high-resolution 1H and 13C NMR spectroscopy. An overview of the various determinations currently assessed is presented with emphasis on the detection of adulteration with foreign (seed) oils and esterified or refined olive and olive-pomace oils. Recent results on the NMR analysis of natural compounds (diacylglycerols, free fatty acids, aldehydes, polyphenols, etc.) related to the quality-freshness of virgin olive oil are also reported. The possible contribution of high-resolution NMR to the authentication of geographical origin of virgin olive oil is discussed. © 1997 John Wiley & Sons, Ltd.