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

Plant and algal lipidomes: Analysis, composition, and their societal significance

Plants and algae play a crucial role in the earth's ecosystems. Through photosynthesis they convert light energy into chemical energy, capture CO2 and produce oxygen and energy-rich organic compounds. Photosynthetic organisms are primary producers and synthesize the essential omega 3 and omega 6 fatty acids. They have also unique and highly diverse complex lipids, such as glycolipids, phospholipids, triglycerides, sphingolipids and phytosterols, with nutritional and health benefits. Plant and algal lipids are useful in food, feed, nutraceutical, cosmeceutical and pharmaceutical industries but also for green chemistry and bioenergy. The analysis of plant and algal lipidomes represents a significant challenge due to the intricate and diverse nature of their composition, as well as their plasticity under changing environmental conditions. Optimization of analytical tools is crucial for an in-depth exploration of the lipidome of plants and algae. This review highlights how lipidomics analytical tools can be used to establish a complete mapping of plant and algal lipidomes. Acquiring this knowledge will pave the way for the use of plants and algae as sources of tailored lipids for both industrial and environmental applications. This aligns with the main challenges for society, upholding the natural resources of our planet and respecting their limits.

A dilute-and-inject liquid-gas chromatography-mass spectrometry method for the analysis of sixteen polycyclic aromatic hydrocarbons in extra-virgin olive oil

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) represent a diverse group of organic compounds characterized by the fusion of two or more benzene rings arranged in various structural forms. Due to their harmful effects on human health, it is essential to implement monitoring systems and preventive measures to regulate human exposure. Given the affinity of PAHs for lipids, extensive research has been focused on their presence in vegetable oils. This study aimed to develop an on-line liquid-gas chromatography (LC-GC) method (using tandem mass spectrometry) with minimized solvent consumption for the determination of 16 PAHs in extra-virgin olive oil (EVOO).

RESULTS

A side-by-side comparison of the selected-ion-monitoring and the pseudo multiple-reaction-monitoring (p-MRM) acquisition modes was performed, in terms of specificity and detectability. The results obtained using the p-MRM mode were superior, and for this reason it was selected. The method was linear over the concentration range 1-200 μg kg-1 (except in five cases, over 2-200 and 5-200 μg kg-1 ranges). Accuracy (at the 2 μg kg-1 and 20 μg kg-1 concentration levels) was in the 86.9-109.3 % range, with an RSD <10 %. Intra-day and inter-day precision (at 2 μg kg-1 and 20 μg kg-1 concentration levels) were in the 1.2-9.7 % and 3.2-10.8 % ranges, respectively. For all the PAHs, a negative matrix effect was observed. Three out of sixteen PAHs were detected in three EVOOs (among ten samples), albeit at the low ppb level. Limits of quantification were satisfactory in relation to EU legislation on the presence of PAHs in vegetable oils.

SIGNIFICANCE

A dilute-and-inject LC-GC-tandem mass spectrometry method is herein proposed fulfilling EU legislation requirements; sample preparation was very simple, inasmuch that it involved only a dilution step, thus avoiding extraction, clean-up, and thus a high consumption of organic solvents. In fact, considering both oil dilution and the LC mobile phase, less than 8 mL of solvents were used.

Formation of Furan from Linoleic Acid Thermal Oxidation: (E,E)-2,4-Decadienal as a Critical Intermediate Product

The linoleic acid reaction models were set at 150 °C for 120 min, and its oxidation process was monitored by nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS). Results showed that no furan was formed from linoleic acid without heating, while furan accumulated throughout the heating process. Linoleic acid ran out within 30 min, which indicated that furan was formed mainly from the intermediate oxidation products of linoleic acid after 30 min. It should be noticed that the content of (E,E)-2,4-decadienal reached maximum once the linoleic acid ran out and then decreased with the formation of furan. Multivariate statistical analysis suggested that (E,E)-2,4-decadienal was the most important aldehyde related to furan formation during linoleic acid oxidation. To prove this assumption, the variation of furan from (E,E)-2,4-decadienal reaction models heating at 150 °C for 60 min was also studied. Results showed that the content of furan increased with the oxidation of (E,E)-2,4-decadienal. Furthermore, NMR and GC-MS data proved that (E,E)-2,4-decadienal could be oxidized to 4,5-epoxy-(E)-2-decenal. In conclusion, our results supported (E,E)-2,4-decadienal and trans-4,5-epoxy-(E)-2-decenal as critical intermediate products of furan formation from linoleic acid oxidation.

Rare Earth Element Variability in Italian Extra Virgin Olive Oils from Abruzzo Region

Extra virgin olive oil is a food product from the Mediterranean area that is particularly and continuously experiencing to increasing instances of fraudulent geographical labeling. Therefore, origin protection must be improved, mainly based on its intrinsic chemical composition. This study aimed to perform a preliminary chemical characterization of Abruzzo extra virgin olive oils (EVOOs) using rare earth elements (REEs). REEs were evaluated in EVOO samples of different varieties produced in different geographical origins within the Abruzzo region (Italy) in three harvest years using ICP-MS chemometric techniques. Principal component, discriminant, and hierarchical cluster analyses were conducted to verify the influence of the variety, origin, and vintage of the REE composition. The results of a three-year study showed a uniform REE pattern and a strong correlation in most EVOOs, in particular for Y, La, Ce, and Nd. However, europium and erbium were also found in some oil samples. Compared with cultivar and origin, only the harvest year slightly influenced the REE composition, highlighting the interactions of the olive system with the climate and soil chemistry that could affect the multielement composition of EVOOs.

Applications of Solution NMR Spectroscopy in Quality Assessment and Authentication of Bovine Milk

Nuclear magnetic resonance (NMR) spectroscopy is emerging as a promising technique for the analysis of bovine milk, primarily due to its non-destructive nature, minimal sample preparation requirements, and comprehensive approach to untargeted milk analysis. These inherent strengths of NMR make it a formidable complementary tool to mass spectrometry-based techniques in milk metabolomic studies. This review aims to provide a comprehensive overview of the applications of NMR techniques in the quality assessment and authentication of bovine milk. It will focus on the experimental setup and data processing techniques that contribute to achieving accurate and highly reproducible results. The review will also highlight key studies that have utilized commonly used NMR methodologies in milk analysis, covering a wide range of application fields. These applications include determining milk animal species and feeding regimes, as well as assessing milk nutritional quality and authenticity. By providing an overview of the diverse applications of NMR in milk analysis, this review aims to demonstrate the versatility and significance of NMR spectroscopy as an invaluable tool for milk and dairy metabolomics research and hence, for assessing the quality and authenticity of bovine milk.

Identification of antibiotic residues in aquatic products with surface-enhanced Raman scattering powered by 1-D convolutional neural networks

Universal and fast antibiotic residues detection technology is imperative for the control of food safety in aquatic products. However, accurate surface-enhanced Raman scattering (SERS) quantitative detection of complicated samples is still a challenge. A recognition method powered by deep learning and took advantage of the unique fingerprint information merits of SERS was proposed. Herein, the spectra were collected by Ag nanofilm SERS substrate prepared by self-assembly of Ag nanoparticles on water/oil interface. A SERS-based database of commonly used antibiotics in aquatic products was set up, which is suitable for employed as input data for learning and training. The results show that the five types of antibiotics are successfully distinguished through principal component analysis (PCA) and each antibiotic in every type was successfully distinguished. Furthermore, one-dimensional convolutional neural networks (1-D CNN) was used to distinguish the antibiotics, and the results show that all the test samples were correctly predicted by 1-D CNN model. The results of this research suggest the great potential of the combination of SERS spectra with deep learning as a method for rapid and highly accurate identification of antibiotic residues in aquatic products.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

An Affordable NIR Spectroscopic System for Fraud Detection in Olive Oil

Adulterations of olive oil are performed by adding seed oils to this high-quality product, which are cheaper than olive oils. Food safety controls have been established by the European Union to avoid these episodes. Most of these methodologies require expensive equipment, time-consuming procedures, and expert personnel to execute. Near-infrared spectroscopy (NIRS) technology has many applications in the food processing industry. It analyzes food safety and quality parameters along the food chain. Using principal component analysis (PCA), the differences and similarities between olive oil and seed oils (sesame, sunflower, and flax oil) have been evaluated. To quantify the percentage of adulterated seed oil in olive oils, partial least squares (PLS) have been employed. A total of 96 samples of olive oil adulterated with seed oils were prepared. These samples were used to build a spectra library covering various mixtures containing seed oils and olive oil contents. Eighteen chemometric models were developed by combining the first and second derivatives with Standard Normal Variable (SNV) for scatter correction to classify and quantify seed oil adulteration and percentage. The results obtained for all seed oils show excellent coefficients of determination for calibration higher than 0.80. Because the instrumental aspects are not generally sufficiently addressed in the articles, we include a specific section on some key aspects of developing a high-performance and cost-effective NIR spectroscopy solution for fraud detection in olive oil. First, spectroscopy architectures are introduced, especially the Texas Instruments Digital Light Processing (DLP) technology for spectroscopy that has been used in this work. These results demonstrate that the portable prototype can be used as an effective tool to detect food fraud in liquid samples.

A Comparison of the Stability of Refined Edible Vegetable Oils under Frying Conditions: Multivariate Fingerprinting Approach

The stability of highly consumed vegetable refined oils after discontinuous frying of potatoes was compared. Both those vegetable oils containing additives and those that did not were considered. Vegetable oil samples were evaluated using refractive index, anisidine and peroxide values, UV absorbance and dielectric constant-based determination of the content of total polar compounds. Chemical changes caused over the frying time were monitored and multivariate modelling of the data was carried out. A new gas chromatographic-mass spectroscopy method was intended to record a fingerprint of both polar and non-polar compound fractions. Multivariate models of chromatographic fingerprints were also developed, and the results obtained from both approaches were verified to be statistically similar. In addition, multivariate modelling also allows to differentiate among vegetable oils according to oxidation performance. Indeed, it was initially observed that olive oils presented the highest natural thermo-oxidative stability compared to other seed oils, although it should be noted that these differences were not significant when regarding olive pomace oils and seed oils containing synthetic additives.

Reflecting the Quality Degradation of Engine Oil by the Thermal Diffusivity: Radiative and Nonradiative Analyses

Ageing of engine oil is an important issue determining the engine life and performance. The present work attempts to delineate the ageing-induced changes in engine oil through the mode-mismatched dual-beam thermal lens (MMDBTL) technique and other conventional spectroscopic techniques. For the analyses, engine oil samples were collected after every 200 km of runtime. As the thermal diffusivity is related to the nonradiative deexcitation upon optical absorption, comprehensive radiative and nonradiative analyses were carried out. The Ultraviolet-Visible, Fourier transform infrared, and Nuclear magnetic resonance spectroscopic analyses point to the structural modification as a result of the breaking of the long-chain hydrocarbons into ketones, aldehydes, esters, and other compounds. This modifies the absorption pattern, which can also be understood from the nonlinear refractive index study using the Z-scan technique. The compositional variations associated with the degradation upon ageing, the length of the hydrocarbon chain, and the formation of newer molecules account for the enhancement of the thermal diffusivity revealed through the MMBDTL techniques. The complementary nature of the radiative and nonradiative emission is understood from the fluorescence study. Thus, the study reveals the possibility of thermal diffusivity measurement as an effective tool for the quality monitoring of engine oil.

Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review

Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.

Phenolic Extract from Extra Virgin Olive Oil Induces Different Anti-Proliferative Pathways in Human Bladder Cancer Cell Lines

Regular consumption of olive oil is associated with protection against chronic-degenerative diseases, such as cancer. Epidemiological evidence indicates an inverse association between olive oil intake and bladder cancer risk. Bladder cancer is among the most common forms of cancer; in particular, the transitional cell carcinoma histotype shows aggressive behavior. We investigated the anti-proliferative effects of a phenolic extract prepared from an extra virgin olive oil (EVOOE) on two human bladder cancer cell lines, namely RT112 and J82, representing the progression from low-grade to high-grade tumors, respectively. In RT112, the EVOOE reduced cell viability (IC50 = 240 μg/mL at 24 h), triggering a non-protective form of autophagy, evidenced by the autophagosome formation and the increase in LC-3 lipidation. In J82, EVOOE induced a strong decrease in cell viability after 24 h of treatment (IC50 = 65.8 μg/mL) through rapid and massive apoptosis, assessed by Annexin V positivity and caspase-3 and -9 activation. Moreover, in both bladder cancer cell lines, EVOOE reduced intracellular reactive oxygen species, but this antioxidant effect was not correlated with its anti-proliferative outcomes. Data obtained suggest that the mixture of phenolic compounds in extra virgin olive oil activates different anti-proliferative pathways.

Analytical Methods for the Characterization of Vegetable Oils

The determination of the authenticity of extra virgin olive oils (EVOOs) has become more interesting in recent years. Italy is the first country in Europe in terms of number of Protected Designation of Origin (PDO) oils, which connects consumers to a feeling of tradition and thus to higher quality standards. This work focused on the consideration of the inorganic content as a possible marker of EVOOs. Ten vegetable oils (VOs), eight Italian EVOOs and seven not Italian EVOOs were analyzed. After pretreatment by acid mineralization, Al, Ba, Ca, Cu, Fe, K, Li, Mg, Mn, Na, P, Sb, Se and Zn were determined by ICP-OES. The electrochemical properties of a selected group of EVOOs and other vegetal oils of different botanical origin were investigated by voltammetry. Carbon paste electrodes (CPEs) were prepared. The features observed in the voltammograms reflect the reactions of electroactive compounds, which are present in the oils. A chemometric treatment of the results was performed to assess the possibility to distinguish (i) the region of provenience considering the inorganic profile; and (ii) the plant species from which each oil was obtained on the basis of the current profile registered during voltammetric analysis. Inorganic composition seems to be a useful marker for the assessment of the geographical origin of an EVOO. The EVOO-CPEs voltammetry seems to have a good ability to distinguish the plant species of origin. This method could be useful to monitor the conservation status of the oils, as the redox profile is linked to the oxidative degradation state.

Magnetic thermo-responsive branched polymer for fast extraction and enrichment of phenolic acids in olive oil with tunable and enhanced performance

Magnetic thermo-responsive branched polymer (Fe₃O₄@poly(glycidyl methacrylate)@poly(N-isopropylacrylamide)) was fabricated for the first time and applied for microwave-assisted magnetic solid phase extraction of phenolic acids in olive oil samples followed by ultra-high performance liquid chromatography-tandem mass spectrometry analysis in multiple reaction monitoring mode. Owing to the controllable molecular weight of poly(glycidyl methacrylate) synthesized by atom transfer radical polymerization and the thermo-responsive characteristic of poly(N-isopropylacrylamide), extraction performance could be efficiently tuned and enhanced. The whole sample pretreatment process was accomplished within 1 min with the help of the microwave. The nanocomposites were characterized by transmission electron microscope, scanning electron microscope, Fourier transform infrared spectroscopy, thermogravimetric analysis, vibrating sample magnetometer, water contact angles and dynamic light scattering. The adsorption experimental data fitted well with the Freundlich isotherm model and followed the pseudo-second-order kinetic model. The factors affecting the extraction process including adsorbent amount, adsorption time, sample volume, desorption conditions and interferents were investigated and optimized. Under the most favorable conditions, the developed method showed good linearity (R² ≥ 97.98%) in the range of 0.2-30 μg L^-1, low limits of detection (0.005-0.030 μg L^-1) and limits of quantification (0.016-0.098 μg L^-1) as well as satisfactory precision (RSDs≤4.85%). Our proposed method was successfully used for determination of phenolic acids in olive oil samples and satisfactory recoveries at three spiked concentration levels were in the range of 84.6-108.1% with RSDs less than 9.20%. Coupled with principal component analysis, our developed method proved promising for fast and convenient differentiation between extra virgin olive oils and refined olive oils.

Oxidized Forms of Olive Oil Secoiridoids: Semisynthesis, Identification and Correlation with Quality Parameters

Secoiridoids is the prominent chemical class of olive oil polar constituents and are characterized by significant biological properties. They are abundant in different chemical forms and relatively high concentrations compared to other components, while prone to oxidation due to their chemical motif. In recent years, oxidized derivatives of secoiridoids have been reported, either as natural constituents of olive oil or as components which are gradually formed in all stages of its production and storage. The mono-oxidized forms of oleocanthal and oleacein named as the respective acids have been recently isolated from olive oil and unambiguously structurally characterized. Other oxidized forms of elenolic acid or more complex secoiridoids, such as those of oleuropein and ligstroside aglycones are also sporadically mentioned in the literature. No further information is provided since they have not been isolated in pure form in order to be accurately identified. Most of the time, they are generally referred as oxidized forms of the parent compounds and commonly identified based on mass spectrometric data. In the current study, the semi-synthesis of the main oxidized olive oil secoiridoids, i.e., oleocanthalic acid, oleaceinic acid, EDA acid, carboxylic form of elenolic acid, carboxylic form of ligstroside aglycon, and carboxylic form of oleuropein aglycon is described starting from the corresponding aldehydic derivatives, using SeO₂/H₂O₂ as oxidative agents. Furthermore, their presence in a number of Greek olive oils was investigated as well, as possible correlation thereof with quality parameters.

Analytical and Structural Tools of Lipid Hydroperoxides: Present State and Future Perspectives

Mono- and polyunsaturated lipids are particularly susceptible to peroxidation, which results in the formation of lipid hydroperoxides (LOOHs) as primary nonradical-reaction products. LOOHs may undergo degradation to various products that have been implicated in vital biological reactions, and thus in the pathogenesis of various diseases. The structure elucidation and qualitative and quantitative analysis of lipid hydroperoxides are therefore of great importance. The objectives of the present review are to provide a critical analysis of various methods that have been widely applied, and more specifically on volumetric methods, applications of UV-visible, infrared, Raman/surface-enhanced Raman, fluorescence and chemiluminescence spectroscopies, chromatographic methods, hyphenated MS techniques, NMR and chromatographic methods, NMR spectroscopy in mixture analysis, structural investigations based on quantum chemical calculations of NMR parameters, applications in living cells, and metabolomics. Emphasis will be given to analytical and structural methods that can contribute significantly to the molecular basis of the chemical process involved in the formation of lipid hydroperoxides without the need for the isolation of the individual components. Furthermore, future developments in the field will be discussed.

Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches

Geographical origin assessment of extra virgin olive oil (EVOO) is recognised worldwide as raising consumers’ awareness of product authenticity and the need to protect top-quality products. The need for geographical origin assessment is also related to mandatory legislation and/or the obligations of true labelling in some countries. Nevertheless, official methods for such specific authentication of EVOOs are still missing. Among the analytical techniques useful for certification of geographical origin, nuclear magnetic resonance (NMR) and mass spectroscopy (MS), combined with chemometrics, have been widely used. This review considers published works describing the use of these analytical methods, supported by statistical protocols such as multivariate analysis (MVA), for EVOO origin assessment. The research has shown that some specific countries, generally corresponding to the main worldwide producers, are more interested than others in origin assessment and certification. Some specific producers such as Italian EVOO producers may have been focused on this area because of consumers’ interest and/or intrinsic economical value, as testified also by the national concern on the topic. Both NMR- and MS-based approaches represent a mature field where a general validation method for EVOOs geographic origin assessment could be established as a reference recognised procedure.

Mechanism, indexes, methods, challenges, and perspectives of edible oil oxidation analysis

Edible oils are indispensable food components, because they are used for cooking or frying. However, during processing, transport, storage, and consumption, edible oils are susceptible to oxidation, during which various primary and secondary oxidative products are generated. These products may reduce the nutritional value and safety of edible oils and even harm human health. Therefore, analyzing the oxidation of edible oil is essential to ensure the quality and safety of oil. Oxidation is a complex process with various oxidative products, and the content of these products can be evaluated by corresponding indexes. According to the structure and properties of the oxidative products, analytical methods have been employed to quantify these products to analyze the oxidation of oil. Combined with proper chemometric analytical methods, qualitative identification has been performed to discriminate oxidized and nonoxidized oils. Oxidative products are complex and diverse. Thus, proper indexes and analytical methods should be selected depending on specific research objectives. Expanding the mechanism of the correspondence between oxidative products and analytical methods is crucial. The underlying mechanism, conventional indexes, and applications of analytical methods are summarized in this review. The challenges and perspectives for future applications of several methods in determining oxidation are also discussed. This review may serve as a reference in the selection, establishment, and improvement of methods for analyzing the oxidation of edible oil. HighlightsThe mechanism of edible oil oxidation analysis was elaborated.Conventional oxidation indexes and their limited values were discussed.Analytical methods for the determination of oxidative products and qualitative identification of oxidized and non-oxidized oils were reviewed.

Sensitivity of Proton NMR Relaxation and Proton NMR Diffusion Measurements to Olive Oil Adulterations with Vegetable Oils

Olive oils and, in particular, extra-virgin olive oils (EVOOs) are one of the most frauded food. Among the different adulterations of EVOOs, the mixture of high-quality olive oils with vegetable oils is one of the most common in the market. The need for fast and cheap techniques able to detect extra-virgin olive oil adulterations was the main motivation for the present research work based on ¹H NMR relaxation and diffusion measurements. In particular, the ¹H NMR relaxation times, T₁ and T₂, measured at 2 and 100 MHz on about 60 EVOO samples produced in Italy are compared with those measured on four different vegetable oils, produced from macadamia nuts, linseeds, sunflower seeds, and soybeans. Self-diffusion coefficients on this set of olive oils and vegetable oil samples were measured by means of the ¹H NMR diffusion ordered spectroscopy (DOSY) technique, showing that, except for the macadamia oil, other vegetable oils are characterized by an average diffusion coefficient sensibly different from extra-virgin olive oils. Preliminary tests based on both NMR relaxation and diffusometry methods indicate that eventual adulterations of EVOO with linseed oil and macadamia oil are the easiest and the most difficult frauds to be detected, respectively.

Analysis of Extra Virgin Olive Oils from Two Italian Regions by Means of Proton Nuclear Magnetic Resonance Relaxation and Relaxometry Measurements

The interest in development of new non-destructive methods for characterization of extra virgin olive oils (EVOOs) has been increasing in the recent years. Among different experimental techniques, nuclear magnetic resonance (NMR) relaxation measurements are very promising in the field of food characterization and authentication. In this study, we focused on relaxation times T1 and T2 measured at different magnetic field strengths (namely, 2, 100, and 400 MHz) and 1H NMR T1 relaxometry dispersions directly on olive oil samples without any chemical/physical treatments. A large set of EVOO samples produced in two regions of Italy, Tuscany and Apulia, were investigated by means of 1H NMR relaxation techniques. The relaxation studies reported here show several common features between the two sets of EVOO samples, thus indicating that relaxation properties, namely, the ranges of values of T1 and T2 at 2 and 100 MHz, are characteristic of EVOOs, independently from the cultivars, climate, and geographic origin. This is a promising result in view of quality control and monitoring.

Fast 1H-NMR Species Differentiation Method for Camellia Seed Oils Applied to Spanish Ornamentals Plants. Comparison with Traditional Gas Chromatography

Camellia genus (Theaceae) is comprised of world famous ornamental flowering plants. C. japonica L. and C. sasanqua Thunb are the most cultivated species due to their good adaptation. The commercial interest in this plant linked to its seed oil increased in the last few years due to its health attributes, which significantly depend on different aspects such as species and environmental conditions. Therefore, it is essential to develop fast and reliable methods to distinguish between different varieties and ensure the quality of Camellia seed oils. The present work explores the study of Camellia seed oils by species and location. Two standardized gas chromatography methods were applied and compared with that of data obtained from proton nuclear magnetic resonance spectroscopy (¹H-NMR) for fatty acids profiling. The principal component analysis indicated that the proposed ¹H-NMR methodology can be quickly and reliably applied to separate specific Camellia species, which could be extended to other species in future works.

Geographical origin discrimination of "Ntopia" olive oil cultivar from Ionian islands using volatile compounds analysis and computational statistics

The aim of the present study was to characterize the aroma profile of olive oil of the "Ntopia" (local) cultivar from the Ionian islands (Zakynthos, Kefalonia, Leukada, and Kerkyra) (Greece), and investigate whether specific volatile compounds could be considered as indicators of olive oil geographical origin, using computational statistics. In this context, 137 olive oil samples were subjected to headspace solid phase microextraction coupled to gas chromatography/mass spectrometry using the internal standard method. Computational statistics on the semi-quantitative data of olive oil samples, as rapid machine learning algorithms, showed that specific volatile compounds could be used as indicators of geographical origin of olive oil of the "Ntopia" cultivar, among the four main Ionian islands. Volatile compounds such as ethanol, pentanal, 2,4-dimethylheptane, 3,7-dimethyl-1,3,6-octatriene (E), 2,5-dimethylnonane, 1-hexanol, 6-methyl-5-hepten-2-one, octanal, dl-Limonene, acetic acid hexyl ester and dodecane could aid to the geographical origin discrimination of "Ntopia" olive oil cultivar when two (Zakynthos and Kefalonia) or four (Zakynthos, Kefalonia, Leukada and Kerkyra) Ionian islands are subjected to statistical analysis. The discrimination rate using the cross-validation method was 100% and 85.7%, respectively. These results were further evaluated using training and holdout partitions, during which a comparable classification rate was obtained.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00217-021-03863-2.

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.

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.

Production of photochromic nanocomposite film via spray-coating of rare-earth strontium aluminate for anti-counterfeit applications

New photochromic film was developed toward the preparation of anti-counterfeiting documents utilizing inorganic/organic nanocomposite enclosing a photoluminescent inorganic pigment and a polyacrylic binder polymer. To generate a translucent film from pigment/polyacrylic nanocomposite, the phosphorescent strontium aluminum oxide pigment should be well-dispersed in the solution of the polyacrylic-based binder without agglomeration. The photochromic nanocomposite was applied efficiently onto commercial cellulose paper documents utilizing the effective and economical spray-coating technology followed with thermofixation. A homogeneous photochromic film was immobilized onto cellulose paper surface to introduce a transparent film changing to greenish-yellow upon exposure to ultraviolet light as depicted by CIE coloration measurements. The photochromic effect was monitored at lowest pigment concentration (0.25 wt%). The spray-coated paper documents exhibit two absorbance bands at 256 and 358 nm, and two fluorescence peaks at 433 and 511 nm. The morphologies of the spray-coated documents were explored. The spray-coated paper sheets showed a reversible photochromic effect without fatigue under ultraviolet irradiation. The rheology of the produced photochromic composites as well as the mechanical properties and photostability of the spray-coated documents were studied.

Chemometric Discrimination of the Varietal Origin of Extra Virgin Olive Oils: Usefulness of 13C Distortionless Enhancement by Polarization Transfer Pulse Sequence and 1H Nuclear Magnetic Resonance Data and Effectiveness of Fusion with Mid-Infrared Spectroscopy Data

The label authentication of monovarietal extra virgin olives is of great relevance from a socio-economical point of view. This work aims to gain insights into the prediction of the varietal origin of extra virgin olive oil (EVOO) samples obtained from single olive cultivars, French cultivars Olivière, Salonenque, and Tanche and Portuguese cultivars Blanqueta, Carrasquenha, and Galega Vulgar, collected in 2016-2017 and 2017-2018 harvest seasons. To pursue this study, spectroscopic approaches based on one-dimensional nuclear magnetic resonance (1D NMR) spectroscopy, namely, ¹H and ¹³C NMR distortionless enhancement by polarization transfer (DEPT) 45 pulse sequence, and Fourier transform mid-infrared spectroscopy (FT-MIR) are used in combination with partial least square discriminant analysis (PLS1-DA). The results obtained by PLS1-DA models using ¹H and ¹³C NMR DEPT 45 data are compared to those of PLS1-DA models using MIR data. The application of a control chart method allows for the optimization of the interpretation of the PLS1-DA results, and an efficient two-step strategy is proposed to improve the discrimination of the six studied cultivars. Then, NMR and MIR data are combined by either a mid- or high-level data fusion approach to further improve the discrimination. The models are also tested on samples from other cultivars to check their ability to reject varieties that were not considered in the calibration process.

Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy

In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided by machine learning algorithms, were employed for the discrimination/classification of olive oils regarding their geographical origin. Both emission and absorption spectra were initially preprocessed by means of Principal Component Analysis (PCA) and were subsequently used for the construction of predictive models, employing Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). All data analysis methodologies were validated by both “k-fold” cross-validation and external validation methods. In all cases, very high classification accuracies were found, up to 100%. The present results demonstrate the advantages of machine learning implementation for improving the capabilities of these spectroscopic techniques as tools for efficient olive oil quality monitoring and control.

Seeking a Fast Screening Method of the Varietal Origin of Olive Oil: The Usefulness of an NMR-Based Approach

This work encompasses the use of 1D multinuclear NMR spectroscopy, namely, ¹H NMR and ¹³C NMR DEPT 45, combined with a multivariate statistical analysis to characterize olive oils produced from nine different varieties: Galega Vulgar, Cobrançosa, Cordovil de Serpa, Blanqueta, Madural, Verdeal Alentejana, Arbequina, Picual and Carrasquenha. Thus, the suitability of an NMR-based spectroscopic tool to discriminate olive oils according to their varietal origin is addressed. The results obtained show that the model based on ¹³C NMR DEPT 45 data has a stronger performance than the model based on ¹H NMR data, proving to be promising in the discrimination of the olive oils under study based on their varietal origin, being particularly relevant for olive oils of the Galega Vulgar variety.

Nutritional Properties and In Vitro Antidiabetic Activities of Blue and Yellow Corn Extracts: A Comparative Study

The objective of this research was to designate and identify the profile of fatty acids, sterols, and polyphenol compounds and to demonstrate the antidiabetic activity, in blue corn extracts (BCE) in comparison with the yellow variant of this raw material. All of the maize lines, including the blue corn, were grown in Europe (southwestern part of Poland) and not in the place of origin (South America). In the extracts of the blue corn variety, eight anthocyanin compounds were isolated. The compound found in the largest amount was pelargonidin, followed by cyanidin-3-glucoside and other glycoside derivatives. Unsaturated fatty acids were the main ones found in the lipid fraction of blue and yellow corn, including linoleic acid and oleic acid. Saturated fatty acids, such as stearic and palmitic acid, were present in smaller amounts. The blue corn’s sterol profile was similar to other varieties of this corn, with β-sitosterol and campesterol occurring in the largest amount, alongside smaller amounts of stigmastanol and stigmasterol. The blue corn variety was characterized by a high content of polyphenolic compounds, which show several biological activities, including antidiabetic activity. The strongest in vitro antidiabetic effect was found in the blue corn lines. Among the polyphenolic compounds in both the blue and yellow corn varieties, in the largest amounts, were caffeic acid, procyanidin B2, and gallic acid. Despite the known and proven biological activity of polyphenolic compounds, the fat fraction showed the highest in vitro antidiabetic activity in the BCE studied.

Mixture Analyses of Air-sampled Pollen Extracts Can Accurately Differentiate Pollen Taxa

The daily pollen forecast provides crucial information for allergic patients to avoid exposure to specific pollen. Pollen counts are typically measured with air samplers and analyzed with microscopy by trained experts. In contrast, this study evaluated the effectiveness of identifying the component pollens using the metabolites extracted from an air-sampled pollen mixture. Ambient air-sampled pollen from Munich in 2016 and 2017 was visually identified from reference pollens and extracts were prepared. The extracts were lyophilized, rehydrated in optimal NMR buffers, and filtered to remove large proteins. NMR spectra were analyzed for pollen associated metabolites. Regression and decision-tree based algorithms using the concentration of metabolites, calculated from the NMR spectra outperformed algorithms using the NMR spectra themselves as input data for pollen identification. Categorical prediction algorithms trained for low, medium, high, and very high pollen count groups had accuracies of 74% for the tree, 82% for the grass, and 93% for the weed pollen count. Deep learning models using convolutional neural networks performed better than regression models using NMR spectral input, and were the overall best method in terms of relative error and classification accuracy (86% for tree, 89% for grass, and 93% for weed pollen count). This study demonstrates that NMR spectra of air-sampled pollen extracts can be used in an automated fashion to provide taxa and type-specific measures of the daily pollen count.

Near UV-Vis and NMR Spectroscopic Methods for Rapid Screening of Antioxidant Molecules in Extra-Virgin Olive Oil

Several spectroscopic techniques have been optimized to check extra-virgin olive oil quality and authenticity, as well as to detect eventual adulterations. These methods are usually complementary and can give information about different olive oil chemical components with bioactive and antioxidant properties. In the present work, a well-characterized set of extra-virgin olive oil (cultivar Frantoio) samples from a specific area of Tuscany (Italy) were investigated by combining near UV-Vis absorption spectroscopy, ¹H and ¹³C nuclear magnetic resonance (NMR) to identify and quantify different chemical components, such as pigments, secoiridoids and squalene, related to the nutritional and quality properties of olive oils. Moreover, the pigmentation index of olives, organoleptic and sensory properties, total phenolic compound contents and the lipidic fractions of olive oils were investigated. The results obtained are, finally, compared and discussed in order to correlate several properties of both olives and olive oils with specific features of the cultivation area.

The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples

In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Volatile compound data were combined with chemometric methods (Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA)) with the aim not only to differentiate olive oils but also to identify characteristic volatile compounds that would enable differentiation of botanical origin (marker compounds). The application of Stepwise LDA (SLDA) effectively reduced the large number of statistically significant volatile compounds involved in the differentiation process, and thus, led to a set of parameters, the majority of which belong to compounds that are highly dependent on variety. In addition, the use of these marker compounds resulted in an increased correct classification rate (85.6%) using the cross-validation method indicating the validity of the model developed despite the use of a large number of dependent variables (cultivars).

Olive Oil Quality and Authenticity Assessment Aspects Employing FIA-MRMS and LC-Orbitrap MS Metabolomic Approaches

Edible vegetable oils comprise integral components of humans' daily diet during the lifetime. Therefore, they constitute a central part of dietary-exposome, which among other factors regulates human health. In particular, the regular consumption of olive oil (OO) has been largely accepted as a healthy dietary pattern. Responsible for its recognition as a superior edible oil is its exceptional aroma and flavor. Its unique composition is characterized by high levels of monounsaturated fatty acids and the presence of minor constituents with important biological properties, such as the so-called OO polyphenols. Being a high added value product, OO suffers from extensive fraud and adulteration phenomena. However, its great chemical complexity, variability, and the plethora of parameters affecting OO composition hamper significantly the selection of the absolute criteria defining quality and authenticity, and a reliable and robust methodology is still unavailable. In the current study, Flow Injection Analysis-Magnetic Resonance Mass Spectrometry (FIA-MRMS) was investigated under a metabolic profiling concept for the analysis of Greek Extra Virgin Olive Oils (EVOO). More than 200 monovarietal (Koroneiki) EVOO samples were collected from the main Greek OO producing regions and investigated. Both intact oil and the corresponding polyphenols were analyzed in fast analysis time of 2 and 8 min, respectively. In parallel, an LC-Orbitrap MS platform was used to verify the efficiency of the method as well as a tool to increase the identification confidence of the proposed markers. Based on the results, with FIA-MRMS, comparable and improved projection and prediction models were generated in comparison to those of the more established LC-MS methodology. With FIA-MRMS more statistically significant compounds and chemical classes were identified as quality and authenticity markers, associated with specific parameters, i.e. geographical region, cultivation practice, and production procedure. Furthermore, it was possible to monitor both lipophilic and hydrophilic compounds with a single analysis. To our knowledge, this approach is among the few studies in which two FT-MS platforms combining LC and FIA methods were integrated to provide solutions to quality control aspects of OO. Moreover, both lipophilic and hydrophilic components are analyzed together, providing a holistic quality control workflow for OO.

The Application of Molecular Spectroscopy in Combination with Chemometrics for Halal Authentication Analysis: A Review

Halal is an Arabic term used to describe any components allowed to be used in any products by Muslim communities. Halal food and halal pharmaceuticals are any food and pharmaceuticals which are safe and allowed to be consumed according to Islamic law (Shariah). Currently, in line with halal awareness, some Muslim countries such as Indonesia, Malaysia, and Middle East regions have developed some standards and regulations on halal products and halal certification. Among non-halal components, the presence of pig derivatives (lard, pork, and porcine gelatin) along with other non-halal meats (rat meat, wild boar meat, and dog meat) is typically found in food and pharmaceutical products. This review updates the recent application of molecular spectroscopy, including ultraviolet-visible, infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies, in combination with chemometrics of multivariate analysis, for analysis of non-halal components in food and pharmaceutical products. The combination of molecular spectroscopic-based techniques and chemometrics offers fast and reliable methods for screening the presence of non-halal components of pig derivatives and non-halal meats in food and pharmaceutical products.

Rapid Analytical Method to Characterize the Freshness of Olive Oils Using Fluorescence Spectroscopy and Chemometric Algorithms

One of the most important issues in the field of quality assurance of olive oils is the detection of the freshness of olive oil. In this study, 400 nm laser-induced fluorescence spectroscopy was used with supervised and unsupervised multivariate analysis methods to develop a rapid method able to discriminate between freshly produced olive oils and oil that has been stored for a period of time ranging from 12 to 24 months. The fluorescence spectral data were firstly processed by the PCA. This method shows strong discrimination of the three oil classes using the first three components which present 96% of the total variability of the initial data, and then supervised classification models were constructed using the discriminant partial least square regression PLS-DA, support vector machine SVM, and linear discriminant analysis LDA. These methods show a high capacity in the classification of the three classes of olive oil. The validation of these classification models by external samples shows a high capacity of classification of the samples in their class with an accuracy of 100%. This study demonstrated the feasibility of the fluorescence spectroscopy fingerprint (routine technique) for the classification of olive oils according to their freshness and storage time.

Virgin olive oil metabolomics: A review

Metabolomics involvement in the study of foods is steadily growing. Such a rise is a consequence of the increasing demand in the food sector to address challenges regarding the issues of food safety, quality, and authenticity in a more comprehensive way. Virgin olive oil (VOO) is a key product of the Mediterranean diet, with a globalized consumer interest as it may be associated with various nutritional and health benefits. Despite the strict legislation to protect this high added-value agricultural commodity and offer guarantees to consumers and honest producers, there are still analytical issues needing to be further addressed. Thus, this review aims to present the efforts made using targeted and untargeted metabolomics approaches, namely nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry-based techniques (mainly LC/GC-MS) combined with multivariate statistical analysis. Case-studies focusing on geographical/varietal classification and detection of adulteration are discussed with regards to the identification of possible markers. The advantages and limitations of each of the aforementioned techniques applied to VOO analysis are also highlighted.

Authentication of Turkish olive oils by using detailed pigment profile and spectroscopic techniques

BACKGROUND

Minor compounds of olive oil could have discriminatory characteristics in the authentication of this product. It was aimed to determine the detailed pigment profiles of Turkish olive oils and use them in differentiation of the samples in comparison to fast, reliable, and environmentally friendly Fourier-transform infrared (FTIR) and ultraviolet (UV)-visible spectroscopic techniques. Pigment contents of 91 olive oils obtained from different locations for two consecutive harvesting years were determined with chromatographic analysis and FTIR and UV-visible spectra of these samples were also obtained. All data were analyzed with orthogonal partial least-squares discriminant analysis to investigate the differentiation ability of these methods with regard to their detailed pigment and spectroscopic profiles.

RESULTS

Pheophytin a (2.78-8.98 mg kg^-1 ) and lutein (1.19-4.07 mg kg^-1 ) were the major pigments in all samples. Pigment profiles provided successful classification of olive oils with respect to their designated origins and harvesting year with average correct classification rates of 97%. UV-visible spectroscopy has quite similar results with pigment profiles in terms of its discriminatory power. In addition, FTIR and fused data were slightly better in discrimination of the samples, and the fused dataset has the highest correct classification rate of 100%.

CONCLUSION

Use of detailed pigment profiles is quite promising in authentication of olive oils. However, UV-visible and FTIR spectroscopic techniques could be reliable alternatives for the same purposes. All of the techniques studied have great potential in 'protected designation of origin' certification studies. © 2020 Society of Chemical Industry.

An Extract of Olive Mill Wastewater Downregulates Growth, Adhesion and Invasion Pathways in Lung Cancer Cells: Involvement of CXCR4

Several diet-derived compounds have been reported to exert antioxidant, anti-proliferative and anti-angiogenic effects in numerous cancers and could be beneficial in cancer prevention. Olive oil production involves the generation of an aqueous phase defined as olive mill wastewater (OMWW), a polluting effluent rich in soluble polyphenols. Here, we assessed the cancer preventive properties exerted by a purified extract of OMWW (A009) for its activity on lung cancer cell lines. Hydroxytyrosol, the most abundant polyphenol present in our A009 extracts, was used as reference molecule in the assays performed. Extracts from OMWW from two different olive oil cultivars were used. We found that the A009 extracts limit lung cancer cell proliferation in a dose and time dependent manner. These effects were associated with the induction of apoptosis. A009 extracts were effective in inhibiting adhesion capabilities on a fibronectin layer accompanied with a reduction in their ability to generate invasive sprouts in a Matrigel layer. The production of chemokine CXCL12 and CXCR4 receptor were reduced by treatment with the extracts. Also, A009 interfered with the production of proangiogenic and pro-inflammatory VEGF, CXCL8, and CCL2 (as detected by FACS analysis) in the lung cell lines. A009 extracts were able to decrease STAT3 phosphorylation in lung cancer cells. Our results show that A009 extracts reduced activities related to tumor cell behavior in lung cancer cell lines, suggesting that they could have a potential cancer preventive role.