Geographical origin classification of olive oils by PTR-MS

Rapid Identification of Adulteration in Extra Virgin Olive Oil via Dynamic Headspace Sampling and High-Pressure Photoionization Time-of-Flight Mass Spectrometry

High-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) combined with dynamic headspace sampling was developed for rapid identification of adulteration in extra virgin olive oil (EVOO). The volatile organic compound (VOC) fingerprints of EVOO, refined rapeseed oil (r-RO), peanut oil (PO), corn oil (CO), fragrant rapeseed oil (f-RO), and sunflower oil (SO) were obtained in just 1.5 min, which enabled satisfactory classification of different edible oils. 1,4-Bis(methylene)cyclohexane and dimethyl disulfide were unique VOCs in r-RO and f-RO, respectively, while 2,5-dimethylpyrazine and 2-methylpyrazine were distinctive VOCs in PO. Percentages as low as 3% r-RO, 1% PO, and 1% f-RO in r-RO-EVOO, PO-EVOO, and f-RO-EVOO mixtures, respectively, were successfully identified based on the characteristic VOCs. Linear regression equations of these VOCs were established and utilized for predicting the adulteration proportions. The good agreements between the actual adulteration proportions and the predicted ones demonstrated that HPPI-TOFMS was reliable for the quantification of EVOO adulteration.

Geographical authentication of virgin olive oil by GC-MS sesquiterpene hydrocarbon fingerprint: Verifying EU and single country label-declaration

According to the last report from the European Union (EU) Food Fraud Network, olive oil tops the list of the most notified products. Current EU regulation states geographical origin as mandatory for virgin olive oils, even though an official analytical method is still lacking. Verifying the compliance of label-declared EU oils should be addressed with the highest priority level. Hence, the present work tackles this issue by developing a classification model (PLS-DA) based on the sesquiterpene hydrocarbon fingerprint of 400 samples obtained by HS-SPME-GC-MS to discriminate between EU and non-EU olive oils, obtaining an 89.6% of correct classification for the external validation (three iterations), with a sensitivity of 0.81 and a specificity of 0.95. Subsequently, multi-class discrimination models for EU and non-EU countries were developed and externally validated (with three different validation sets) with successful results (average of 92.2% of correct classification for EU and 96.0% for non-EU countries).

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.

Revealing dynamic changes of the volatile profile of food samples using PTR-MS

Volatile compounds carry valuable information regarding the properties of foodstuffs. Volatiles emitted from food can be used as, for example, indicators of quality, shelf-life, or authenticity. A better understanding of the multitude of transformations which occur during food processing could facilitate the optimisation of production, increase the desirability of food products, and also their wholesomeness. However, as some of these transformations are fast-paced, it is necessary to monitor them using techniques which enable real-time determination of volatiles, such as proton transfer reaction-mass spectrometry (PTR-MS). Recent years have seen a marked increase in its use in food analysis, since it can be used to obtain insight into the dynamics of the monitored processes and can be the basis for precise quality control methods for food processing. This review highlights recent works in which PTR-MS was used in monitoring during foodstuffs production, preparation and storage.

Release Kinetics Studies of Early-Stage Volatile Secondary Oxidation Products of Rapeseed Oil Emitted during the Deep-Frying Process

The research concerns the use of proton transfer reaction mass spectrometer to track real-time emissions of volatile secondary oxidation products released from rapeseed oil as a result of deep-frying of potato cubes. Therefore, it was possible to observe a sudden increase of volatile organic compound (VOC) emissions caused by immersion of the food, accompanied by a sudden release of steam from a potato cube and a decrease of the oil temperature by more than 20 °C. It was possible to identify and monitor the emission of major secondary oxidation products such as saturated and unsaturated aldehydes, namely acrolein, pentanal, 2-hexenal, hexanal, 2-nonenal and 2-decenal. Each of them has an individual release characteristic. Moreover, the impact of different initial frying temperatures on release kinetics was investigated. Subsequently, it was possible to approximate the cumulative emission by a second-degree polynomial (R² ≥ 0.994). Using the proposed solution made it possible for the first time to observe the impact of the immersion of food in vegetable oil on the early emission of thermal degradation products oil.

Determination of the Small-Scale Physical Model Parameters of Pavement Structure

A large amount of the local and first-class road infrastructures in Central Europe lead through settled areas, such as villages or even historical cities and town centers. The vibrations generated by passing vehicles around the pavement spread to the subgrade to the environment and also affect civil engineering structures and buildings. We have decided to adopt the approach of small-scale modeling of the pavement with the subgrade. Small-scale physical modeling brings benefits, such as size reduction, simplification, or controlled conditions during the test. To study the effect of static and dynamic behavior during the occurrence, a simulation mass physical model is used for testing. A static plate load test is used to determine the bearing capacity and settlement and consistency of measurement of the plate’s vertical movement at a given load acting on the plate. The aim of the mass surface simulation’s dynamic testing was to measure the response in time acceleration forms. Based on the performed experimental measurements undertaken on the physical model as well as the numerical simulation performed in FEM, we can state that the gelatin-based simulation mass is usable for the simulation of the earth environment in contact with building structures.

The Use of Stable Isotope Ratio Analysis to Trace European Sea Bass (D. labrax) Originating from Different Farming Systems

Simple Summary

European sea bass is one of the most economically important fish species in the Mediterranean area. The potential effects of farming systems on the final quality of this product and the recent popular demand for labels to certify the animal rearing origin, which is increasingly used as a marketing tool, have raised the use of analytical techniques that make it possible to differentiate this fish product according to the rearing farming system and authenticate their geographical origin. The aim of this study was to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) and geographic origins (different locations scattered throughout Italy). The results of this study showed the viability of δ¹³C and δ¹⁵N to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Meanwhile, the measurement of δ¹⁸O and δ²H made it possible to distinguish the geographical origin of the sea bass farmed extensively and intensively (in cages).

Abstract

This study aimed to determine whether isotopic ratio mass spectrometry (IRMS) can discriminate farmed European sea bass according to different farming systems and geographic origins. Dicentrarchus labrax of commercial size from three different rearing systems (concrete tank inland, sea cages, and extensive methods in valleys or salt works) were collected at the trading period (autumn–winter). For each farming type, different locations spread over Italy were monitored. Once the fish were harvested, the muscle and feed were sampled. For both muscle and feed, δ¹³C and δ¹⁵N were measured by continuous flow elemental analyzer isotope ratio mass spectrometry (CF-EA-IRMS) with the goal of discriminating samples based on the rearing system. Additional δ²H and δ¹⁸O measurements of fish samples were performed by continuous flow total combustion elemental analyzer isotope ratio mass spectrometry (CF-TC/EA-IRMS) to track the geographical origin. The measurements of δ¹³C and δ¹⁵N made it possible to discriminate cultured sea bass from different farming systems (extensive vs. intensive) reared at different geographical sites in Italy. Additional information was obtained from δ¹⁸O and δ²H, which enabled the geographical areas of origin of the sea bass farmed extensively and intensively (in cages) to be distinguished.

Verifying the Geographical Origin and Authenticity of Greek Olive Oils by Means of Optical Spectroscopy and Multivariate Analysis

Olive oil samples from three different Greek regions (Crete, Peloponnese and Lesvos) were examined by optical spectroscopy in a wide spectral region from ultraviolet to near infrared using absorption, fluorescence and Raman spectroscopies. With the aid of machine learning methods, such as multivariate partial least squares discriminant analysis, a clear classification of samples originating from the different Greek geographical regions was revealed. Moreover, samples produced in different subareas of Crete and Peloponnese were also well discriminated. Furthermore, mixtures of olive oils from different geographical origins were studied employing partial least squares as a tool to establish a model between the actual and predicted compositions of the mixtures. The results demonstrated that optical spectroscopy combined with multivariate statistical analysis can be used as an emerging innovative alternative to the classical analytical methods for the identification of the origin and authenticity of olive oils.

Sustainable Palm Oil-The Role of Screening and Advanced Analytical Techniques for Geographical Traceability and Authenticity Verification

Palm oil production from oil palm (Elaeis guineensis Jacq.) is vital for the economy of Malaysia. As of late, sustainable production of palm oil has been a key focus due to demand by consumer groups, and important progress has been made in establishing standards that promote good agricultural practices that minimize impact on the environment. In line with the industrial goal to build a traceable supply chain, several measures have been implemented to ensure that traceability can be monitored. Although the palm oil supply chain can be highly complex, and achieving full traceability is not an easy task, the industry has to be proactive in developing improved systems that support the existing methods, which rely on recorded information in the supply chain. The Malaysian Palm Oil Board (MPOB) as the custodian of the palm oil industry in Malaysia has taken the initiative to assess and develop technologies that can ensure authenticity and traceability of palm oil in the major supply chains from the point of harvesting all the way to key downstream applications. This review describes the underlying framework related to palm oil geographical traceability using various state-of-the-art analytical techniques, which are also being explored to address adulteration in the global palm oil supply chain.

From Extra Virgin Olive Oil to Refined Products: Intensity and Balance Shifts of the Volatile Compounds versus Odor

To explore relationships between the volatile organic compounds (VOCs) of different grades of olive oils (OOs) (extra virgin olive oil (EVOO), refined olive oil (ROO), and pomace olive oil (POO)) and odor quality, VOCs were measured in the headspace of the oils by proton transfer reaction quadrupole ion guide time-of-flight mass spectrometry. The concentrations of most VOCs differed significantly between the grades (EVOO > ROO > POO), whereas the abundance of m/z 47.012 (formic acid), m/z 49.016 (fragments), m/z 49.027 (fragments), and m/z 115.111 (heptanal/heptanone) increased in that order. Although the refined oils had considerably lower VOC abundance, the extent of the decline varied with the VOCs. This results in differences in VOCs proportions. The high VOC abundance in the EVOO headspace in comparison to ROO and POO results in a richer and more complex odor. The identified C5–C6 compounds are expected to contribute mainly to the green odor notes, while the identified C1–C4 and C7–C15 are mainly responsible for odor defects of OOs. Current results reveal that processing strongly affects both the quantitative and relative abundance of the VOCs and, therefore, the odor quality of the various grades of OOs.

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.

Fast discrimination of bacteria using a filter paper-based SERS platform and PLS-DA with uncertainty estimation

Rapid and reliable identification of bacteria is an important issue in food, medical, forensic, and environmental sciences; however, conventional procedures are time-consuming and often require extensive financial and human resources. Herein, we present a label-free method for bacterial discrimination using surface-enhanced Raman spectroscopy (SERS) and partial least squares discriminant analysis (PLS-DA). Filter paper decorated with gold nanoparticles was fabricated by the dip-coating method and it was utilized as a flexible and highly efficient SERS substrate. Suspensions of bacterial samples from three genera and six species were directly deposited on the filter paper-based SERS substrates before measurements. PLS-DA was successfully employed as a multivariate supervised model to classify and identify bacteria with efficiency, sensitivity, and specificity rates of 100% for all test samples. Variable importance in projection was associated with the presence/absence of some purine metabolites, whereas confidence intervals for each sample in the PLS-DA model were calculated using a resampling bootstrap procedure. Additionally, a potential new species of bacteria was analyzed by the proposed method and the result was in agreement with that obtained via 16S rRNA gene sequence analysis, thereby indicating that the SERS/PLS-DA approach has the potential to be a valuable tool for the discovery of novel bacteria. Graphical abstract This paper describes the discrimination of bacteria at the genus and species levels, after minimal sample preparation, using paper-based SERS substrates and PLS-DA with uncertainty estimation.

A new method for real-time monitoring of volatiles in frying fumes using proton transfer reaction mass spectrometry with time-of-flight analyser

Abstract

To safeguard the consumers’ well-being, it is necessary to develop novel methods for determination of carcinogens in food, including volatiles generated during frying. The currently used procedures for analysis of volatile fraction of vegetable oils are not based on real-time measurements and thus do not enable the determination of carcinogenic compounds in frying fumes; instead, only the headspace or liquid fraction is sampled. In this article, described is an approach in which proton transfer reaction mass spectrometry with time-of-flight analyser (PTR-TOFMS) was used for real-time monitoring of carcinogenic compounds generated during thermal degradation of rapeseed oil. Using PTR-MS, it was possible to monitor the concentration of known volatile carcinogens according to the International Agency for Research on Cancer (IARC), alongside BTEX compounds, acrolein, and selected aldehydes. Moreover, the applicability of several supervised data analysis methods for the classification of oil samples according to their degree of thermal degradation was presented, with best results obtained using the k-nearest neighbours algorithm. Proton transfer reaction mass spectrometry is a powerful technique for the determination of carcinogenic compounds generated during thermal degradation of edible oils. Further investigation of the chemical processes which occur during frying can lead to improvement of food safety.

Graphical abstract

Proton-transfer reaction mass spectrometry (PTR-MS) for the authentication of regionally unique South African lamb

The volatile fingerprints of South African lamb meat and fat were measured by proton-transfer mass spectrometry (PTR-MS) to evaluate it as an authentication tool. Meat and fat of the Longissimus lumborum (LL) of lambs from six different regions were assessed. Analysis showed that the volatile fingerprints were affected by the origin of the meat. The classification of the origin of the lamb was achieved by examining the calculated and recorded fingerprints in combination with chemometrics. Four different partial least squares discriminant analysis (PLS-DA) models were fitted to the data to classify lamb meat and fat samples into "region of origin" (six different regions) and "origin" (Karoo vs. Non-Karoo). The estimation models classified samples 100% correctly. Validation of the first two models gave 42% (fat) and 58% (meat) correct classification of region, while the second two models performed better with 92% (fat) and 83% (meat) correct classification of origin.

Sensory, spectrometric (PTR-ToF-MS) and chemometric analyses to distinguish extra virgin from virgin olive oils

Olive oil samples were obtained from six cultivars grown in different environments, and graded by chemical analyses as extra virgin (EVOOs). These were evaluated for flavors and off-flavors, and relative VOCs spectrum as determined by PTR-ToF-MS. A hierarchical clustering of Panel test data separated olive oil in three groups, one including the samples with perceived off-flavor (VOOs), regardless of cultivar and environment. The Pearson's correlation coefficients between the mass data from PTR-ToF-MS and the sensory characteristics perceived by the Panel test were determined. A mass-to-sensory attributes correlation index was calculated. A color-coded card was built up based on the intensities (ncps) of five selected protonated mass data that was able to distinguish EVOOs from VOOs olive oil samples.

Analysis of Volatile Compounds by Advanced Analytical Techniques and Multivariate Chemometrics

Smelling is one of the five senses, which plays an important role in our everyday lives. Volatile compounds are, for example, characteristics of food where some of them can be perceivable by humans because of their aroma. They have a great influence on the decision making of consumers when they choose to use a product or not. In the case where a product has an offensive and strong aroma, many consumers might not appreciate it. On the contrary, soft and fresh natural aromas definitely increase the acceptance of a given product. These properties can drastically influence the economy; thus, it has been of great importance to manufacturers that the aroma of their food product is characterized by analytical means to provide a basis for further optimization processes. A lot of research has been devoted to this domain in order to link the quality of, e.g., a food to its aroma. By knowing the aromatic profile of a food, one can understand the nature of a given product leading to developing new products, which are more acceptable by consumers. There are two ways to analyze volatiles: one is to use human senses and/or sensory instruments, and the other is based on advanced analytical techniques. This work focuses on the latter. Although requirements are simple, low-cost technology is an attractive research target in this domain; most of the data are generated with very high-resolution analytical instruments. Such data gathered based on different analytical instruments normally have broad, overlapping sensitivity profiles and require substantial data analysis. In this review, we have addressed not only the question of the application of chemometrics for aroma analysis but also of the use of different analytical instruments in this field, highlighting the research needed for future focus.

Compositional Signatures of Conventional, Free Range, and Organic Pork Meat Using Fingerprint Techniques

Consumers’ interest in the way meat is produced is increasing in Europe. The resulting free range and organic meat products retail at a higher price, but are difficult to differentiate from their counterparts. To ascertain authenticity and prevent fraud, relevant markers need to be identified and new analytical methodology developed. The objective of this pilot study was to characterize pork belly meats of different animal welfare classes by their fatty acid (Fatty Acid Methyl Ester—FAME), non-volatile compound (electrospray ionization-tandem mass spectrometry—ESI-MS/MS), and volatile compound (proton-transfer-reaction mass spectrometry—PTR-MS) fingerprints. Well-defined pork belly meat samples (13 conventional, 15 free range, and 13 organic) originating from the Netherlands were subjected to analysis. Fingerprints appeared to be specific for the three categories, and resulted in 100%, 95.3%, and 95.3% correct identity predictions of training set samples for FAME, ESI-MS/MS, and PTR-MS respectively and slightly lower scores for the validation set. Organic meat was also well discriminated from the other two categories with 100% success rates for the training set for all three analytical approaches. Ten out of 25 FAs showed significant differences in abundance between organic meat and the other categories, free range meat differed significantly for 6 out of the 25 FAs. Overall, FAME fingerprinting presented highest discrimination power.

Origin authentication of distillers' dried grains and solubles (DDGS)--application and comparison of different analytical strategies

In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.

Authentication of dried distilled grain with solubles (DDGS) by fatty acid and volatile profiling

Demand for ethanol substituted fuels from the utilisation of cereal based biofuel has resulted in an over production of dried distillers grains with solubles (DDGS) that are now readily available on the animal feed market. With this rapid emerging availability comes potential variability in the nutritional value of DDGS and possible risks of feed contaminants. Subsequently, the authentication and traceability of alternative animal feed sources is of high priority. In this study and as part of the EU research project “Quality and Safety of Feeds and Food for Europe (QSAFFE FP7-KBBE-2010-4) an attempt was made to classify the geographical origin of cereal grains used in the production of DDGS material. DDGS material of wheat and corn origin were obtained from Europe, China, and the USA. Fatty acid profiles and volatile fingerprints were assessed by gas chromatography flame ionisation (GC-FID) and rapid proton transfer reaction mass spectrometry (PTR-MS) respectively. Chemometric analysis of fatty acid profiles and volatile fingerprints allowed for promising classifications of cereals used in DDGS material by geographical and botanical origin and enabled visual representation of the data. This objective analytical approach could be adapted for routine verification of cereal grains used in the production of DDGS material.

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Fatty acid and volatile composition of dried distillers grains were analysed.

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Fatty acid and volatile fingerprints of samples were studied by chemometric models.

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Models showed good classifications for botanical, geographical origin and process.

PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins

Characterisation of coffees according to their origins is of utmost importance for commercial qualification. In this study, the aroma profiles of different batches of three monoorigin roasted Coffea arabica coffees (Brazil, Ethiopia and Guatemala) were analysed by Proton-Transfer-Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS). The measurements were performed with the aid of a multipurpose autosampler. Unsupervised and supervised multivariate data analysis techniques were applied in order to visualise data and classify the coffees according to origin. Significant differences were found in volatile profiles of coffees. Principal component analysis allowed visualising a separation of the three coffees according to geographic origin and further partial least square regression-discriminant analysis classification showed completely correct predictions. Remarkably, the samples of one batch could be used as training set to predict geographic origin of the samples of the other batch, suggesting the possibility to predict further batches in coffee production by means of the same approach. Tentative identification of mass peaks aided characterisation of aroma fractions. Classification pinpointed some volatile compounds important for discrimination of coffees.

Effect of the pig rearing system on the final volatile profile of Iberian dry-cured ham as detected by PTR-ToF-MS

The volatile compound profile of dry-cured Iberian ham lean and subcutaneous fat from pigs fattened outdoors on acorn and pasture (Montanera) or on high-oleic concentrated feed (Campo) was investigated by proton transfer reaction time-of-flight mass spectrometry. In addition to the usual proton transfer ionization the novel switchable reagent ions system was implemented which allows the use of different precursor ions (H(3)O(+), NO(+) and O(2)(+)). The analysis of the lean and subcutaneous fat volatile compounds allowed a good sample discrimination according to the diet. Differences were evident for several classes of compounds: in particular, Montanera hams showed higher concentrations of aldehydes and ketones and lower concentrations of sulfur-containing compounds compared to Campo hams. The use of NO(+) as precursor ion confirmed the results obtained with H(3)O(+) in terms of classification capability and provides additional analytical insights.