Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using Raman spectroscopy and chemometrics

Advanced analytical techniques for authenticity identification and quality evaluation in Essential oils: A review

Essential oils (EO), secondary metabolites of plants are fragrant oily liquids with antibacterial, antiviral, anti-inflammatory, anti-allergic, and antioxidant effects. They are widely applied in food, medicine, cosmetics, and other fields. However, the quality of EOs remain uncertain owing to their high volatility and susceptibility to oxidation, influenced by factors such as the harvesting season, extraction, and separation techniques. Additionally, the huge economic value of EOs has led to a market marked by widespread and varied adulteration, making the assessment of their quality challenging. Therefore, developing simple, quick, and effective identification techniques for EOs is essential. This review comprehensively summarizes the techniques for assessing EO quality and identifying adulteration. It covers sensory evaluation, physical and chemical property evaluation, and chemical composition analysis, which are widely used and of great significance for the quality evaluation and adulteration detection of EOs.

Detection of Hazelnut and Almond Adulteration in Olive Oil: An Approach by qPCR

Virgin olive oil (VOO), characterized by its unique aroma, flavor, and health benefits, is subject to adulteration with the addition of oils obtained from other edible species. The consumption of adulterated olive oil with nut species, such as hazelnut or almond, leads to health and safety issues for consumers, due to their high allergenic potential. To detect almond and hazelnut in olive oil, several amplification systems have been analyzed by qPCR assay with a SYBR Green post-PCR melting curve analysis. The systems selected were Cora1F2/R2 and Madl, targeting the genes coding the allergenic protein Cor a 1 (hazelnut) and Pru av 1 (almond), respectively. These primers revealed adequate specificity for each of the targeted species. In addition, the result obtained demonstrated that this methodology can be used to detect olive oil adulteration with up to 5% of hazelnut or almond oil by a single qPCR assay, and with a level as low as 2.5% by a nested-qPCR assay. Thus, the present research has shown that the SYBR-based qPCR assay can be a rapid, precise, and accurate method to detect adulteration in olive oil.

A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends

Edible oil blends are composed of two or more edible oils in varying proportions, which can ensure nutritional balance compared to oils comprising a single component oil. In view of their economical and nutritional benefits, quantitative analysis of the component oils in edible oil blends is necessary to ensure the rights and interests of consumers and maintain fairness in the edible oil market. Chemometrics combined with modern analytical instruments has become a main analytical technology for the quantitative analysis of edible oil blends. This review summarizes the different oil blend design methods, instrumental techniques and chemometric methods for conducting single component oil quantification in edible oil blends. The aim is to classify and compare the existing analytical techniques to highlight suitable and promising determination methods in this field.

Combining multilayered wrinkled polymer SERS substrates and spectral data processing for low concentration analyte detection

A series of thermally shrinkable polymer surface-enhanced Raman scattering (SERS) substrates were prepared with bimetallic Au and Ag (oxidized or not) films and with Au nanoparticles (AuNPs) located at different places in the layered structure to evaluate the synergistic effect of different known SERS amplification methods to enhance the Raman signal for low concentration dopamine detection. A bimetallic Au and Ag layered structure improved the Raman signal by 5 and 2 times compared to the single-layered Au and Ag films. Oxidizing the Ag layer prior to deposition of Au further improved the signal by a factor of 2, while adding AuNP on wrinkled films increased another 10 times the intensity of the Raman signal. It was found that the enhancement was another 10 times stronger when using AuNPs in combination with other means of enhancement such as with a silver underlayer or surface wrinkling. Wrinkling alone only gave a few-fold increase compared to a flat film, but the combination of wrinkling with AuNPs and a silver underlayer improved the SERS intensity by more than 3 orders of magnitude, showing the synergistic effect of these enhancement methods. The optimized sensors were then tested in dynamic SERS with low concentration dopamine solutions, where the signal showed characteristics of a digital SERS response. Raman spectra preprocessing and sorting software was developed to triage the SERS-active spectra from the null spectra, to count the detection events such as the ones observed in single molecule experiments.

Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey

Zhejiang Suichang native honey, which is included in the list of China’s National Geographical Indication Agricultural Products Protection Project, is very popular. This study proposes a method of Raman spectroscopy combined with machine learning algorithms to accurately detect low-concentration adulterated Suichang native honey. In this study, the native honey collected by local beekeepers in Suichang was selected for adulteration detection. The spectral data was compressed by Savitzky–Golay smoothing and partial least squares (PLS) in sequence. The PLS features taken for further analysis were selected according to the contribution rate. In this study, three classification modeling methods including support vector machine, probabilistic neural network and convolutional neural network were adopted to correctly classify pure and adulterated honey samples. The total accuracy was 100%, 100% and 99.75% respectively. The research result shows that Raman spectroscopy combined with machine learning algorithms has great potential in accurately detecting adulteration of low-concentration honey.

Portable through Bottle SORS for the Authentication of Extra Virgin Olive Oil

The authenticity of olive oil has been a significant long-term challenge. Extra virgin olive oil (EVOO) is the most desirable of these products and commands a high price, thus unscrupulous individuals often alter its quality by adulteration with a lower grade oil. Most analytical methods employed for the detection of food adulteration require sample collection and transportation to a central laboratory for analysis. We explore the use of portable conventional Raman and spatially-offset Raman spectroscopy (SORS) technologies as non-destructive approaches to assess the adulteration status of EVOO quantitatively and for SORS directly through the original container, which means that after analysis the bottle is intact and the oil would still be fit for use. Three sample sets were generated, each with a different adulterant and varying levels of chemical similarity to EVOO. These included EVOO mixed with sunflower oil, pomace olive oil, or refined olive oil. Authentic EVOO samples were stretched/diluted from 0% to 100% with these adulterants and measured using two handheld Raman spectrometers (excitation at 785 or 1064 nm) and handheld SORS (830 nm). The PCA scores plots displayed clear trends which could be related to the level of adulteration for all three mixtures. Conventional Raman (at 785 or 1064 nm) and SORS (at 830 nm with a single spatial offset) conducted in sample vial mode resulted in prediction errors for the test set data ranging from 1.9–4.2% for sunflower oil, 6.5–10.7% for pomace olive oil and 8.0–12.8% for refined olive oil; with the limit of detection (LOD) typically being 3–12% of the adulterant. Container analysis using SORS produced very similar results: 1.4% for sunflower, 4.9% for pomace, and 10.1% for refined olive oil, with similar LODs ranging from 2–14%. It can be concluded that Raman spectroscopy, including through-container analysis using SORS, has significant potential as a rapid and accurate analytical method for the non-destructive detection of adulteration of extra virgin olive oil.

Advanced techniques in edible oil authentication: A systematic review and critical analysis

Adulteration of edible substances is a potent contemporary food safety issue. Perhaps the overt concern derives from the fact that adulterants pose serious ill effects on human health. Edible oils are one of the most adulterated food products. Perpetrators are adopting ways and means that effectively masks the presence of the adulterants from human organoleptic limits and traditional oil adulteration detection techniques. This review embodies a detailed account of chemical, biosensors, chromatography, spectroscopy, differential scanning calorimetry, non-thermal plasma, dielectric spectroscopy research carried out in the area of falsification assessment of edible oils for the past three decades and a collection of patented oil adulteration detection techniques. The detection techniques reviewed have some advantages and certain limitations, chemical tests are simple; biosensors and nuclear magnetic resonance are rapid but have a low sensitivity; chromatography and spectroscopy are highly accurate with a deterring price tag; dielectric spectroscopy is rapid can be portable and has on-line compatibility; however, the results are susceptible to variation of electric current frequency and intrinsic factors (moisture, temperature, structural composition). This review paper can be useful for scientists or for knowledge seekers eager to be abreast with edible oil adulteration detection techniques.

Authentication of the Botanical and Geographical Origin and Detection of Adulteration of Olive Oil Using Gas Chromatography, Infrared and Raman Spectroscopy Techniques: A Review

Olive oil is among the most popular supplements of the Mediterranean diet due to its high nutritional value. However, at the same time, because of economical purposes, it is also one of the products most subjected to adulteration. As a result, authenticity is an important issue of concern among authorities. Many analytical techniques, able to detect adulteration of olive oil, to identify its geographical and botanical origin and consequently guarantee its quality and authenticity, have been developed. This review paper discusses the use of infrared and Raman spectroscopy as candidate tools to examine the authenticity of olive oils. It also considers the volatile fraction as a marker to distinguish between different varieties and adulterated olive oils, using SPME combined with gas chromatography technique.

An evaluation of IR spectroscopy for authentication of adulterated turmeric powder using pattern recognition

Turmeric powder is a widely consumed spice, making it an attractive target for adulteration, which is not easily detected. The study examined the simultaneous use of IR spectroscopy in combination with controlled (PCA) and uncontrolled (PLS-DA and CMCA) pattern recognition techniques to detect and classify Sudan Red, starch and metanil yellow fraud in turmeric powder nondestructively. The results showed that the two major peaks in turmeric powder at 1625 cm^-1 and 1600 cm^-1 are not present in Sudan Red, starch and metanil yellow because these materials lack this functional group. Data distribution at the two PC locations showed clearly scattered clusters according to the four mixing studied models (turmeric powder, turmeric powder-Sudan Red mixture, turmeric powder-starch mixture and turmeric powder-metanil yellow mixture), but there was a clear overlap between turmeric powder and turmeric powder - Sudan red mixture. Both PLS-DA and SIMCA supervised methods showed satisfactory discrimination. The results also showed that in all the sample groups, when the samples were classified by PLS-DA, the values were higher compared to the SIMCA model. The overall precision of the SIMCA and PLS-DA classifier were 82% and 92%, respectively. However, when considering only two main categories adulterated (the samples at the groups 2, 3 and 4) and pure (the samples at the group 1), an acceptable degree of separation between the resulting classes was obtained. Consequently, IR spectroscopy with pattern recognition methods was found to be a promising tool for nondestructive grouping of turmeric powder samples with different types of adulteration in turmeric powder.

Olive oil consumption can prevent non-communicable diseases and COVID-19 : Review

The Mediterranean diet is appraised as the premier dietary regimen and its espousal is correlated with the prevention of degenerative diseases and extended longevity. The consumption of olive oil stands out as the most peculiar feature of the Mediterranean diet. Olive oil rich in various bioactive compounds like oleanolic acid, oleuropein, oleocanthal, and hydroxytyrosol is known for its anti-inflammatory as well as cardioprotective property. Recently in silico studies have indicated that phytochemicals present in olive oil are a potential candidate to act against SARS-CoV-2. Although extensive studies on olive oil and its phytochemical composition; still, some lacunas persist in understanding how the phytochemical composition of olive oil is dependent on upstream processing. The signaling pathways regulated by olive oil in the restriction of various diseases is also not clear. To answer these queries, a detailed search of research and review articles published between 1990 to 2019 were reviewed in this effect. Olive oil consumption was found to be advantageous for various chronic non-communicable diseases. Olive oil's constituents are having potent anti-inflammatory activities and thus restrict the progression of various inflammation-linked diseases ranging from arthritis to cancer. But it is also notable that the amount and nature of phytochemical composition of household olive oil are regulated by its upstream processing and the physicochemical properties of this oil can give a hint regarding the manufacturing method as well as its therapeutic. Moreover, daily uptake of olive oil should be monitored as excessive intake can cause body weight gain and change in the basal metabolic index. So, it can be concluded that olive oil consumption is beneficial for human health, and particularly for the prevention of cardiovascular diseases, breast cancer, and inflammation. The simple way of processing olive oil maintains the polyphenol constituents and provides more protection against non-communicable diseases and SARS-CoV-2.

Rapid detection of green-pea adulteration in pistachio nuts using Raman spectroscopy and chemometrics

BACKGROUND

Ground pistachio nut is prone to adulteration because of its high economic value and wide usage. Green pea is known as the main adulterant in frauds involving pistachio nuts. The present study developed a new, rapid, reliable and low-cost methodology by using a portable Raman spectrometer in combination with chemometrics for the detection of green pea in pistachio nuts.

RESULTS

Three different methods of Raman spectroscopy-based chemometrics analysis were developed for the determination of green-pea adulteration in pistachio nuts. The first method involved the development of hierarchical cluster analysis (HCA) and principal component analysis (PCA), which differentiated authentic pistachio nuts from green pea and green pea-adulterated samples. The best classification pattern was observed in the adulteration range of 20-80% (w/w). In addition to classification methods, partial least squares regression (PLSR) and genetic algorithm-based inverse least squares (GILS) were also used to develop multivariate calibration models to determine quantitatively the degree of green-pea adulteration in grounded pistachio nuts. The spectral range of 1790-283 cm-1 was used in the case of multivariate data analysis. A green-pea adulteration level of 5-80% (w/w) was successfully identified by PLSR and GILS. The correlation coefficient of determination (R2 ) was determined as 0.91 and 0.94 for the PLSR and GILS analyses, respectively.

CONCLUSION

A Raman spectrometer combined with chemometrics has a high capability with regard to the detection of adulteration in pistachio nuts, combined with low cost, strong reliability, a high level of accuracy, rapidity of analysis, and minimum sample preparation. © 2020 Society of Chemical Industry.

State-of-the-Art of Analytical Techniques to Determine Food Fraud in Olive Oils

The benefits of the food industry compared to other sectors are much lower, which is why producers are tempted to commit fraud. Although it is a bad practice committed with a wide variety of foods, it is worth noting the case of olive oil because it is a product of great value and with a high percentage of fraud. It is for all these reasons that the authenticity of olive oil has become a major problem for producers, consumers, and legislators. To avoid such fraud, it is necessary to develop analytical techniques to detect them. In this review, we performed a complete analysis about the available instrumentation used in olive fraud which comprised spectroscopic and spectrometric methodology and analyte separation techniques such as liquid chromatography and gas chromatography. Additionally, other methodology including protein-based biomolecular techniques and analytical approaches like metabolomic, hhyperspectral imaging and chemometrics are discussed.

Detection of lard in butter using Raman spectroscopy combined with chemometrics

There is a contentious need for robust and rapid methodologies for maintaining the authenticity of foods and food additives. The current paper presented a new Raman spectroscopy-based methodology for detection and quantification of lard in butter. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully performed for the classification and discrimination of butter and lard-adulterated samples. Strong discrimination pattern was observed in the HCA analysis. Also, partial least squares regression and principal component regression (R² = 0.99) were applied for quantification of lard in butter samples. Quite favorable prediction capabilities were observed in the cross-validation of PLS and PCR analysis for the adulteration levels between 0% and 100% lard fat (w/w). Raman spectroscopy coupled chemometrics was employed effectively for quantification of lard fat in butter fat samples with easy, robust, effective, low-cost and reliable application in the quality control of butter.

Differentiation of Edible Oils by Type Using Raman Spectroscopy and Pattern Recognition Methods

The application of Raman spectroscopy and pattern recognition methods to the problem of discriminating edible oils by type was investigated. Two-hundred and eighty-six Raman spectra obtained from 53 samples spanning 15 varieties of edible oils were collected for 90 s at 2 cm^-1 resolution. Employing a Whittaker filter, all Raman spectra were baseline corrected after removing the high-intensity fluorescent background in each spectrum. The Raman spectral data were then examined using the three major types of pattern recognition methodology: mapping and display, discriminant development and clustering. The 15 varieties of edible oils could be partitioned into five distinct groups based on their degree of saturation and the ratio of polyunsaturated fatty acids to monounsaturated fatty acids. Edible oils assigned to one group could be readily differentiated from those assigned to other groups, whereas Raman spectra within the same group more closely resembled each other and therefore would be more difficult to classify by type.

Determination of the Reactivity Degree of Various Alkaline Solutions: A Chemometric Investigation

Knowledge of alkaline silicate solutions is crucial in order to optimize geopolymer properties. Geopolymers are new binders resulting from the activation of an aluminosilicate by an alkaline solution. It is well established that the solution reactivity strongly affects the geopolymerization and therefore the geopolymer working properties. As a consequence, an evaluation of the reactivity degree of alkaline silicate solutions prior synthesis is of the utmost interest. However, the determination of the solution reactivity is currently tedious, and for geopolymer commercialization, it would be necessary to find an easy way to determine it. Therefore, Raman spectroscopy, combined with chemometric techniques, is proposed as a solution to easily determine the alkaline silicate solution reactivity. To conduct this investigation, 65 silicate solutions were characterized by Raman spectroscopy, and reference values of their reactivity degree were determined. Finally, principal component analysis and partial least squares regression were performed to build a statistical model able to predict the alkaline silicate solution reactivity from Raman spectra.

Raman Spectroscopy Analysis of Free Fatty Acid in Olive Oil

Free fatty acid (FFA) is one of the most critical parameters for evaluating the quality of olive oil. In this paper, we present a simple and rapid Raman spectroscopy method for analyzing free fatty acid in olive oil. First, FFA degradation of carotenoids in olive oil is confirmed by analyzing the relative intensity of characteristic vibrational modes and introducing an intensity decrease factor. Second, it is demonstrated that the relative intensity ratio of the two characteristic vibrational modes at 1525 cm−1 and 1655 cm−1 presents a good and rapid analysis of FFA content in olive oil; the relative intensity ratio decreases linearly with FFA content. In addition, resonance Raman scattering of carotenoid is discussed, showing that a green laser should be utilized to study FFA in olive oil.

Authenticity and Concentration Analysis of Extra Virgin Olive Oil Using Spontaneous Raman Spectroscopy and Multivariate Data Analysis

Adulteration of extra virgin olive oil (EVOO) with cheaper edible oils is of considerable concern in the olive oil industry. The potential of Raman spectroscopy combined with multivariate statistics has been investigated for evaluating the authenticity (or purity) and concentration of EVOO irrespective of it being adulterated with one or more adulterants. The adulterated oil samples were prepared by blending different concentrations of EVOO (10–100% v/v) randomly with cheaper edible oils such as corn, soybean and rapeseed oil. As a result, a Raman spectral database of oil samples (n = 214 spectra) was obtained from 11 binary mixtures (EVOO and rapeseed oil), 16 ternary mixtures (EVOO, rapeseed and corn oil) and 44 quaternary mixtures (EVOO, rapeseed, corn and soybean oil). Partial least squares (PLS) calibration models with 10-fold cross validation were constructed for binary, ternary and quaternary oil mixtures to determine the purity of spiked EVOO. The PLS model on the complex dataset (binary + ternary + quaternary) where the spectra obtained with different measurement parameters and sample conditions can able to determine the purity of spiked EVOO inspite of being blended with one or more cheaper oils. As a proof of concept, in this study, we used single batch of commercial oil bottles for estimating the purity of EVOO. The developed method is not only limited to EVOO, but can be applied to clean EVOO obtained from the production site and other types of food.

Safety analysis of edible oil products via Raman spectroscopy

Raman spectroscopy is a spectroscopic technique based on Raman scattering effects and provide a structural fingerprint by which molecules can be identified. Owing to its non-destructive, high sensitivity and allowing on-line detection, Raman spectroscopy is now increasingly being applied in various fields from fundamental research to engineering in food safety. Edible oils provide high nutritional value in the human diet and their safety and quality have become a major concern and issue. Thus, edible oils have been the subject of a number of applications of Raman spectroscopy. This present review briefly evaluates Raman spectroscopy applications in the quality and safety analysis of oil products in the latest decade. In addition, by integrating the introduction of the detection of harmful substances and bioactive components in oil product, this paper also summarizes a series of emerging analytical technologies in applications of Raman spectroscopy.

Direct Photometric Assay for Copper Chlorophyll Adulterants in Edible Oil by the Aid of an Ultraviolet-Photobleaching Pretreatment

Adulterating edible oil with copper chlorophyll derivatives (E141i) has made a substantial impact on the edible oil industry and food safety. This study demonstrates an efficient and reliable screening method to directly identify the color adulteration by the aid of a simple photobleaching pretreatment using a 365 nm ultraviolet-light-emitting diode working at a photon flux density of 480 mmol m^-2 s^-1 for 24 min. The content of copper chlorophyll [predominantly Cu-pyropheophytin a (Cu-py a)] can be calculated by A₆₀₀, A₆₅₀, and A₇₀₀ with satisfactory spike recovery [97.9-103.6%; six kinds of edible oils spiked with 1 ppm of Cu-py a; n = 3 for each kind of oil; relative standard deviation (RSD) < 5%], linearity ( R² = 0.9961 when spiking 0.1-10 ppm of Cu-py a into soybean oil standard; n = 3 for each concentration; RSD < 5%), and reproducibility (RSD < 5% for spiking 1 ppm of Cu-py a into soybean oil standard; n = 3 over 3 days). The detection limit (S/N > 5) was 0.05 ppm. The analytical results of 50 commercially available oil samples were verified by the official high-performance liquid chromatography method.

Olive oil authentication: A comparative analysis of regulatory frameworks with especial emphasis on quality and authenticity indices, and recent analytical techniques developed for their assessment. A review

Over 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.

Short Distance Standoff Raman Detection of Extra Virgin Olive Oil Adulterated with Canola and Grapeseed Oils

A short distance standoff Raman technique is demonstrated for detecting economically motivated adulteration (EMA) in extra virgin olive oil (EVOO). Using a portable Raman spectrometer operating with a 785 nm laser and a 2-in. refracting telescope, adulteration of olive oil with grapeseed oil and canola oil is detected between 1% and 100% at a minimum concentration of 2.5% from a distance of 15 cm and at a minimum concentration of 5% from a distance of 1 m. The technique involves correlating the intensity ratios of prominent Raman bands of edible oils at 1254, 1657, and 1441 cm^-1 to the degree of adulteration. As a novel variation in the data analysis technique, integrated intensities over a spectral range of 100 cm^-1 around the Raman line were used, making it possible to increase the sensitivity of the technique. The technique is demonstrated by detecting adulteration of EVOO with grapeseed and canola oils at 0-100%. Due to the potential of this technique for making measurements from a convenient distance, the short distance standoff Raman technique has the promise to be used for routine applications in food industry such as identifying food items and monitoring EMA at various checkpoints in the food supply chain and storage facilities.

Profiling and Simultaneous Quantitative Determination of Anthocyanins in Wild Myrtus communis L. Berries from Different Geographical Areas in Sardinia and their Comparative Evaluation

INTRODUCTION

Myrtus communis L. (Myrtaceae) is a self-seeded shrub, widespread in Sardinia, with anti-inflammatory, antiseptic, antimicrobial, hypoglycemic and balsamic properties. Its berries, employed for the production of sweet myrtle liqueur, are characterised by a high content of bioactive polyphenols, mainly anthocyanins. Anthocyanin composition is quite specific for vegetables/fruits and can be used as a fingerprint to determine the authenticity, geographical origin and quality of raw materials, products and extracts.

OBJECTIVE

To rapidly analyse and determine anthocyanins in 17 samples of Myrtus communis berries by developing a platform based on the integration of UHPLC-MS/MS quantitative data and multivariate analysis with the aim of extracting the most information possible from the data.

METHODOLOGY

UHPLC-ESI-MS/MS methods, working in positive ion mode, were performed for the detection and determination of target compounds in multiple reaction monitoring (MRM) mode. Optimal chromatographic conditions were achieved using an XSelect HSS T3 column and a gradient elution with 0.1% formic acid in water and 0.1% formic acid in acetonitrile. Principal component analysis (PCA) was applied to the quantitative data to correlate and discriminate 17 geographical collections of Myrtus communis.

RESULTS

The developed quantitative method was reliable, sensitive and specific and was successfully applied to the quantification of 17 anthocyanins. Peonidin-3-O-glucoside was the most abundant compound in all the extracts investigated.

CONCLUSION

The developed methodology allows the identification of quali-quantitative differences among M. communis samples and thus defines the quality and value of this raw material for marketed products. Moreover, the reported data have an immediate commercial value due to the current interest in developing antioxidant nutraceuticals from Mediterranean plants, including Sardinian Myrtus communis. Copyright © 2016 John Wiley & Sons, Ltd.

The effect of thermal treatment on the enhancement of detection of adulteration in extra virgin olive oils by synchronous fluorescence spectroscopy and chemometric analysis

In this study the effect of thermal treatment on the enhancement of synchronous fluorescence spectroscopic method for discrimination and quantification of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with refined oil was investigated. Two groups of samples were used. One group was analyzed at room temperature (25 °C) and the other group was thermally treated in a thermostatic water bath at 75 °C for 8h, in contact with air and with light exposure, to favor oxidation. All the samples were then measured with synchronous fluorescence spectroscopy. Synchronous fluorescence spectra were acquired by varying the wavelength in the region from 250 to 720 nm at 20 nm wavelength differential interval of excitation and emission. Pure and adulterated olive oils were discriminated by using partial least-squares discriminant analysis (PLS-DA). It was found that the best PLS-DA models were those built with the difference spectra (75 °C-25 °C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration of refined olive oils. Furthermore, PLS regression models were also built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 3.18% of adulteration.

Chemometric study of Andalusian extra virgin olive oils Raman spectra: Qualitative and quantitative information

Authentication of extra virgin olive oil (EVOO) is an important topic for olive oil industry. The fraudulent practices in this sector are a major problem affecting both producers and consumers. This study analyzes the capability of FT-Raman combined with chemometric treatments of prediction of the fatty acid contents (quantitative information), using gas chromatography as the reference technique, and classification of diverse EVOOs as a function of the harvest year, olive variety, geographical origin and Andalusian PDO (qualitative information). The optimal number of PLS components that summarizes the spectral information was introduced progressively. For the estimation of the fatty acid composition, the lowest error (both in fitting and prediction) corresponded to MUFA, followed by SAFA and PUFA though such errors were close to zero in all cases. As regards the qualitative variables, discriminant analysis allowed a correct classification of 94.3%, 84.0%, 89.0% and 86.6% of samples for harvest year, olive variety, geographical origin and PDO, respectively.

A rapid method to authenticate vegetable oils through surface-enhanced Raman scattering

Vegetable oils are essential in our daily diet. Among various vegetable oils, the major difference lies in the composition of fatty acids, including unsaturated fatty acids (USFA) and saturated fatty acids (SFA). USFA include oleic acid (OA), linoleic acid (LA), and α-linolenic acid (ALA), while SFA are mainly palmitic acid (PA). In this study, the most typical and abundant USFA present with PA in vegetable oils were quantified. More importantly, certain proportional relationships between the integrated intensities of peaks centered at 1656 cm⁻¹ (S₁₆₅₆) in the surface-enhanced Raman scattering spectra of different USFA were confirmed. Therefore, the LA or ALA content could be converted into an equivalent virtual OA content enabling the characterization of the USFA content in vegetable oils using the equivalent total OA content. In combination with the S₁₆₅₆ of pure OA and using peanut, sesame, and soybean oils as examples, the ranges of S₁₆₅₆ corresponding to the National Standards of China were established to allow the rapid authentication of vegetable oils. Gas chromatograph-mass spectrometer analyses verified the accuracy of the method, with relative errors of less than 5%. Moreover, this method can be extended to other detection fields, such as diseases.

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. Experimental approaches of chemometrics coupled with fast analytical techniques such as UV-Vis spectroscopy, fluorescence, vibrational spectroscopies (NIR, MIR and Raman fluorescence), NMR spectroscopy, and other more complex techniques like chromatography, calorimetry and electrochemical techniques applied to EVOO/VOO production and analysis have been discussed throughout this work. The advantages and drawbacks of this association have also been highlighted. Chemometrics has been evidenced as a powerful tool for the oil industry. In fact, it has been shown how chemometrics can be implemented all along the different steps of EVOO/VOO production: raw material input control, monitoring during process and quality control of final product.

Thermal oxidation process accelerates degradation of the olive oil mixed with sunflower oil and enables its discrimination using synchronous fluorescence spectroscopy and chemometric analysis

We have investigated the effect of thermal treatment on the discrimination of pure extra virgin olive oil (EVOO) samples from EVOO samples adulterated with sunflower oil. Two groups of samples were used. One group was analyzed at room temperature (25°C) and the other group was thermally treated in a thermostatic water bath at 75°C for 8h, in contact with air and with light exposure, to favor oxidation. All samples were then measured with synchronous fluorescence spectroscopy. Fluorescence spectra were acquired by varying the excitation wavelength in the region from 250 to 720nm. In order to optimize the differences between excitation and emission wavelengths, four constant differential wavelengths, i.e., 20nm, 40nm, 60nm and 80nm, were tried. Partial least-squares discriminant analysis (PLS-DA) was used to discriminate between pure and adulterated oils. It was found that the 20nm difference was the optimal, at which the discrimination models showed the best results. The best PLS-DA models were those built with the difference spectra (75-25°C), which were able to discriminate pure from adulterated oils at a 2% level of adulteration. Furthermore, PLS regression models were built to quantify the level of adulteration. Again, the best model was the one built with the difference spectra, with a prediction error of 1.75% of adulteration.