Ambient mass spectrometry employing direct analysis in real time (DART) ion source for olive oil quality and authenticity assessment

Rapid Assessment of Metabolomic Fingerprinting of Recycled Sunflower By-Products via DART-HRMS

To comply with a more circular and environmentally friendly European common agricultural policy, while also valorising sunflower by-products, an ultrasound assisted extraction (UAE) was tested to optimise ethanol-wash solutes (EWS). Furthermore, the capabilities of DART-HRMS as a rapid and cost-effective tool for determining the biochemical changes after valorisation of these defatted sunflower EWS were investigated. Three batches of EWS were doubly processed into optimised EWS (OEWS) samples, which were analysed via DART-HRMS. Then, the metabolic profiles were submitted to a univariate analysis followed by a partial least square discriminant analysis (PLS-DA) allowing the identification of the 15 most informative ions. The assessment of the metabolomic fingerprinting characterising EWS and OEWS resulted in an accurate and well-defined spatial clusterization based on the retrieved pool of informative ions. The outcomes highlighted a significantly higher relative abundance of phenolipid hydroxycinnamoyl-glyceric acid and a lower incidence of free fatty acids and diglycerides due to the ultrasound treatment. These resulting biochemical changes might turn OEWS into a natural antioxidant supplement useful for controlling lipid oxidation and to prolong the shelf-life of foods and feeds. A standardised processing leading to a selective concentration of the desirable bioactive compounds is also advisable.

Direct analysis in real time of high-quality extra virgin olive oils for the rapid and automatic identification of origin trademark

BACKGROUND

Following our previous research on the differentiation of Italian extra virgin olive oils (EVOOs) by rapid evaporative ionization mass spectrometry coupled to a tandem high resolution mass analyser, the present study deals with the evaluation of another direct mass spectrometry (direct-MS) approach for the rapid and automatic discrimination of EVOOs. In particular, direct analysis in real time (DART-MS) was explored as an ambient MS (AMS) source for the building of a top-quality Italian EVOOs database and fast identification of unknown samples. A single quadrupole detector (QDa) was coupled with DART, taking advantage of a cost-saving, user-friendly and less sophisticated instrumental setup. Particularly, quickstrip cards, located on a moving rail holder, were employed, allowing for the direct analysis of 12 EVOO spots in a total analysis time of 6 min. The aim was to develop a reliable statistical model by applying principal component and linear discriminant analyses to clusterize and classify EVOOs according to geographical origin and cultivar, as main factors determining their nutritional and sensory profiles.

RESULTS

Satisfactory results were achieved in terms of identification reliability of unknown EVOOs, as well as false positive risk, thus confirming that the use of AMS combined with chemometrics is a powerful tool against fraudulent activities, without the need for mass accuracy data, which would increase the analysis cost.

CONCLUSION

A DART ionization source with a compact and reliable QDa MS analyser allowed for rapid fingerprinting analysis. Furthermore, MS spectra provided quali-quantitative information successfully related to EVOO differentiation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A dedicated electronic nose combined with chemometric methods for detection of adulteration in sesame oil

Sesame oil (SO), one of the most popular and expensive edible oils, is prone to adulteration. In this study, the fatty acid profiles of pure sesame seed oil and samples adulterated with two less expensive edible oils (canola and sunflower) were analyzed using Gas Chromatography. A dedicated e-nose system was developed and tested on 15 mixtures of sesame-canola and sesame-sunflower samples. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Multi-Layered Perceptron (MLP) methods were utilized to identify adulteration through the evaluation of Volatile Organic Compound. Result of chromatography showed that most samples of sesame oil containing impurities at levels less than 30% were recognized incorrectly in the standard range of SO fatty acids. This is while the developed e-nose system was able to detect adulteration at much lower levels. According to the results, PCA and LDA methods can describe the data set variance with precision of 95.6% and 97%, respectively. The MLP model had better results compared to PCA and LDA, with high determination coefficient (R2 = 0.981) and low RMSE (0.0178). Results indicate that the e-nose system provided an effective non-destructive method to detect SO adulteration at levels as low as 5%, which GC was unable to detect.

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.

Screening method for the characterization of anabolic steroids seized in Brazil using paper spray mass spectrometry and chemometric tools

This paper reports the use of paper spray mass spectrometry (PS-MS) combined with chemometric models to analyze seized samples of anabolic steroids. Because many forensic laboratories typically demand high-throughput analysis for this type of sample, we developed a quicker and simpler alternative analytical method for routine analysis with minimal sample preparation. Oily samples (n = 39) resulting from seizures carried out by Brazilian Federal and State Police units were selected for this study. These samples were analyzed by PS-MS in the positive ion mode and full scan (50-1000 m/z), providing spectra containing patterns of the respective active ingredients present in each product. A principal component analysis (PCA) model was built, which discriminated samples mainly according to their active ingredients and allowed to detect and characterize some cases of product counterfeiting. The variable selection method ordered predictors selection was employed jointly with PCA to improve sample cluster separation and to provide model simplification. The final PCA model was built with three principal components and using only 28 spectral variables. This model accounted for 69.82% of the variance and discriminated samples according to their specific active ingredients.

Comparison of LC-ESI, DART, and ASAP for the analysis of oligomers migration from biopolymer food packaging materials in food (simulants)

Biopolymers based on polylactic acid (PLA) and starch have numerous advantages, such as coming from renewable sources or being compostable, though they can have deficiencies in mechanical properties, and for this reason, polyester resins are occasionally added to them in order to improve their properties. In this work, migration from a PLA sample and from another starch-based biopolymer to three different food simulants was studied. Attention was focused on the determination of oligomers. The analysis was first performed by ultraperformance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF–MS), which allowed the identification of the oligomers present in migration. Then, the samples were analyzed by two ambient desorption/ionization techniques directly coupled to mass spectrometry (ADI), direct analysis in real-time coupled to standardized voltage and pressure (DART-MS) and atmospheric pressure solids analysis probe (ASAP-MS). These methodologies were able to detect simultaneously the main oligomers migrants and their adducts in a very rapid and effective way. Nineteen different polyester oligomers, fourteen linear and five cyclic, composed of different combinations of adipic acid [AA], propylene glycol [PG], dipropylene glycol [DPG], 2,2-dibutyl-1,3-propanediol [DBPG], or isobutanol [i-BuOH] were detected in migration samples from PLA. In migration samples from starch-based biopolymer, fourteen oligomers from poly(butylene adipate co-terephthalate) polyester (PBAT) were identified, twelve cyclic and two linear. The results from ADI techniques showed that they are a very promising alternative tool to assess the safety and legal compliance of food packaging materials.

High-throughput and trace analysis of diazepam in plasma using DART-MS/MS and its pharmacokinetic application

A high-throughput quantitative analytical method based on Direct Analysis in Real Time tandem mass spectrometry (DART-MS/MS) has been developed and validated for the determination of diazepam in rat plasma, whereby analyzing of each sample needs merely 25 μL plasma, simple solid phase extraction sample preparation and 15 s acquisition time. The multiple reaction monitoring (MRM) transitions at m/z 285.2 → 193.1 and 316.0 → 270.0 were selected for the monitoring of diazepam and its internal standard clonazepam respectively. A good linearity within the range of 10-2000 ng/mL, an intra- and inter-day precisions within <7.78% as to an accuracy ranging from 1.04% to 7.92% have been achieved. The method has been successfully applied to the pharmacokinetic study of diazepam in rats' plasma after a single intragastric administration at a dose of 10 mg/kg. The results indicate that this method fulfills the requirements of the bioanalysis in sensitivity and accuracy. It shows considerable promise for application of DART-MS to the quantitative investigation of other drugs.

High-throughput bioanalysis of sitagliptin in plasma using direct analysis in real time mass spectrometry and its application in the pharmacokinetic study thereof

Sitagliptin is a dipeptidyl peptidase-IV inhibitor for the treatment of type 2 diabetes mellitus. In the present study, a sensitive and high-throughput quantitative method based on the direct analysis in real time tandem mass spectrometry has been developed and validated for the bioanalysis of sitagliptin in rat plasma without chromatographic separation. Sitagliptin and its internal standard retagliptin were detected in positive ion mode by multiple reaction monitoring transitions at m/z 408.2→235.0 and 465.2→260.1, respectively. The method includes a simple solid-phase extraction sample preparation procedure, through which appropriate and reproducible analytical results within the linear concentration range of 20-2000 ng/mL have been achieved. The intra- and interday precisions were <10.6% and the accuracies were ranging from -8.17 to 2.60%. This method has been successfully applied to the pharmacokinetic study of sitagliptin after single intravenous administration in rats. This approach shows considerable promise of direct analysis in real time tandem mass spectrometry method in the high-throughput bioanalysis.

Diacylglycerols ions as novel marker indicators for the classification of edible oils using ultrahigh resolution mass spectrometry

Diacylglycerols (DAGs) ions, instead of triacylglycerols (TAGs) ions, were established as marker indicators for an improved classification of edible oils using ultrahigh resolution mass spectrometry (UHRMS). DAGs ions can be used not only to identify triacylglycerols (TAGs) and their embedded fatty acids (FAs), but also to distinguish positional isomers of TAGs. In this work, DAGs ions were determined in edible oils by direct infusion atmospheric pressure chemical ionization-ultrahigh resolution mass spectrometry (APCI-UHRMS), where the ultrahigh resolving power up to 500,000 FWHM (full width at half maximum) can provide accurate molecular compositions and detailed fingerprints MS spectra in a minute. A total of 146 samples belonging to 22 species of plant oils and animal fats, were characterized. Chemometric analyses were performed using principal component analysis, partial least square-discriminant analysis and orthogonal partial least squares-discriminant analysis. DAGs ions were proved to be better than TAGs ions as marker indicators in the chemometric analyses. An overall correct rate of 93.40% was achieved for the classification of tested samples. In addition, blend oils and gutter oils were also characterized by this developed method.

Optimization of an Untargeted DART-HRMS Method Envisaging Identification of Potential Markers for Saffron Authenticity Assessment

Saffron is one of the most expensive agricultural products in the world and as such, the most commonly adulterated spice, with undeclared plant-based surrogates or synthetic components simulating color and morphology. Currently, saffron quality is certificated in the international trade market according to specific ISO guidelines, which test aroma, flavor, and color strength. However, it has been demonstrated that specific adulterants such as safflower, marigold, or turmeric up to 20% (w/w) cannot be detected under the prescribed approach; therefore, there is still a need for advanced and sensitive screening methods to cope with this open issue. The current investigation aims to develop a rapid and sensitive untargeted method based on an ambient mass spectrometry ionization source (DART) and an Orbitrap™high-resolution mass analyzer to discriminate pure and adulterated saffron samples with either safflower or turmeric. The metabolic profiles of pure and adulterated model samples prepared at different inclusion levels were acquired. Unsupervised multivariate analysis was carried out based on hierarchical cluster analysis and principal component analysis as first confirmation of the discriminating potential of the metabolic profile acquired under optimized DART-HRMS conditions. In addition, a preliminary selection of potential markers for saffron authenticity was accomplished, identifying compounds able to discriminate the type of adulteration down to a concentration level of 5%.

Role of analytical testing for food fraud risk mitigation - A commentary on implementation of analytical fraud testing: Role of analytical testing for food fraud mitigation

Food fraud is of high concern to the food industry. A multitude of analytical technologies exist to detect fraud. However, this testing is often expensive. Available databases detailing fraud occurrences were systematically examined to determine how frequently analytical testing triggered fraud detection. A conceptual framework was developed for deciding when to implement analytical testing programmes for fraud and a framework to consider the economic costs of fraud and the benefits of its early detection. Factors associated with statistical sampling for fraud detection were considered. Choice of sampling location on the overall food-chain may influence the likelihood of fraud detection.

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A conceptual framework was developed for deciding when to implement analytical testing programmes for fraud.

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A conceptual framework for the economic impact damage of food fraud is presented.

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Sampling for fraudulent activity poses several unique challenges compared to other food safety related sampling activities.

Mechanism behind the paper spray chemical ionization phenomenon and the choice of solvent

Paper spray chemical ionization (PSCI) combined with mass spectrometry has been proposed as a sensitive method for the analysis of nonpolar aromatic compounds; however, the mechanism behind PSCI is not well understood. In the present study, the evidence for the occurrence of corona discharge is provided and its mechanism is proposed. Photographs taken with a highly sensitive camera evidently demonstrate the occurrence of corona discharge at the end of the triangular shape tip when a nonpolar solvent such as hexane was used at an applied potential of 6-7 kV. Nevertheless, corona discharge was not observed in the presence of a polar solvent. The occurrence of the corona discharge was attributed to charge accumulation in the dielectric layer generated by the nonpolar solvent on the fibers of the paper tip. Specifically, corona discharge was generated at the tip end when the charge approached a critical threshold. In the presence of a polar solvent, however, the dielectric layer was not generated and, hence, corona discharge was not observed. Based on this information, three nonpolar solvents were selected and their sensitivity for analyzing the phenanthrene and maltene fractions of crude oil was evaluated. Chlorobenzene provided the highest signal abundance; therefore, it was suggested as the optimum solvent for PSCI. Notably, the fundamental understanding of corona discharge in PSCI acquired in this study provides a basis for further improvement of this technique by way of surface modification.

Applications of direct analysis in real time mass spectrometry in food analysis: A review

RATIONALE

Direct analysis in real time (DART) combined with mass spectrometry (MS) detection has become one of the most broadly used analytical approaches for the direct molecular characterization of food samples with regard to their chemical quality, safety, origin, and authentication. The major advantages of DART-MS for food analysis include high chemical sensitivity and specificity, high speed and throughput of analysis, simplicity, and the obviation of tedious sample preparation and solvents.

METHODS

The recent applications of DART coupled with different mass analyzers, including quadrupole, ion trap, Orbitrap, and time of flight, are discussed. In addition, sample pretreatment methods that have been coupled with DART-MS are discussed.

RESULTS

We summarize the applications of DART-MS in food science and industry published in the period from 2005 to this date. The applications and analytical characteristics are systematically categorized across the three major types of foods: solid foods, liquid foods, and viscous foods.

CONCLUSIONS

DART-MS has proved its high suitability for the direct, rapid, and high-throughput molecular analysis of very different food samples with minimal or no sample preparation, thus offering a high-speed alternative to liquid chromatography/mass spectrometry (LC/MS) and gas chromatography/mass spectrometry (GC/MS) approaches that are traditionally employed in food analysis.

Two-Photon Fluorescence Study of Olive Oils at Different Excitation Wavelengths

Two-photon fluorescence (TPF) of olive oils is discovered and observed experimentally for the first time. Variations of the single-photon fluorescence (SPF) and TPF with the excitation wavelength are investigated for four different olive oils. The results show that fluorescence of the cosmetic olive oils (COO) is very weak and exhibits only one spectral peak around 490 nm. While for the ordinary edible oils (OEO) whether they are during their shelf life or not, their fluorescence spectra may exhibit multiple peak structures. The short-term natural expiration only slightly weakens TPF of OEO. Moreover, the excitation wavelength affects the OEO spectra considerably in terms of the spectral peak number, the spectral peak position, and spectral shapes. When the excitation wavelength decreases from 700 nm, the whole TPF of the OEO also decreases. Relatively, however, the short wave band will decrease and disappear more quickly. While for the SPF, the long wave band will decrease and disappear first. The optimal excitation wavelengths to make the TPF strongest are around 700 nm and 640 nm for OEOs and COO, respectively. And effects of temperature on SPF and TPF of extra virgin olive oil are also explored. This work may be of significance for its potential applications in TPF detection and two-photon laser.

Building robust models for identification of adulteration in olive oil using FT-NIR, PLS-DA and variable selection

Being a product with a high market value, olive oil undergoes adulterations. Therefore, studies that make the verification of the authenticity of olive oil more efficient are necessary. The aim of this study was to develop a robust model using FT-NIR and PLS-DA to discriminate extra virgin olive oil samples and build individual models to differentiate adulterated extra virgin olive oil samples. The best PLS-DA-OPS classification model for olive oils showed specificity (Spe) and accuracy (Acc) values higher than 99.7% and 99.9%. For the classification of adulterants, PLS-DA-OPS models presented values of Spe at 96.0% and Acc above 95.5% for varieties. For the blend, the best PLS-DA-GA model presented Acc and Spe values greater than 98.2% and 98.8%. Reliable and robust models have been built, allowing differentiation from seven adulterants to genuine extra virgin olive oils.

A Non-Targeted High-Resolution Mass Spectrometry Study for Extra Virgin Olive Oil Adulteration with Soft Refined Oils: Preliminary Findings from Two Different Laboratories

This work presents a non-targeted high-resolution mass spectrometry inter-laboratory study for the detection of new chemical markers responsible of soft refined oils addition to extra virgin olive oils. Refined oils (soft deodorized and soft deacidified) were prepared on a laboratory scale starting from low-quality olive oils and analyzed together with a set of pure extra virgin olive oil (EVOO) samples and with mixtures of adulterated and pure EVOO at different percentages. The same analytical workflow was applied in two different laboratories equipped with two types of instrumentation (Q-Orbitrap and Q-TOF); a group of discriminant molecules was selected, and a tentative identification of compounds was also proposed. In summary, 12 molecules were identified as markers of this specific adulteration, and seven of them were selected as discriminative in both the laboratories, with a similar trend throughout the samples (i.e., propylene glycol 1 stearate). The results obtained in the two laboratories are comparable, concretely demonstrating the inter-laboratory repeatability of non-targeted studies. As a confirmation, the same markers were detected also in "in-house" mixtures and in suspect commercial deodorized mixtures, reinforcing the robustness of the results obtained and proving that, thanks to these molecules, mixtures containing at least 40% of adulterated oils can be detected.

Geographical Origin Discrimination of Monofloral Honeys by Direct Analysis in Real Time Ionization-High Resolution Mass Spectrometry (DART-HRMS)

An untargeted method using direct analysis in real time and high resolution mass spectrometry (DART-HRMS) combined to multivariate statistical analysis was developed for the discrimination of two monofloral (chestnut and acacia) honeys for their geographical origins-i.e., Italy and Portugal for chestnut honey and Italy and China for acacia honey. Principal Component Analysis, used as an unsupervised approach, showed samples of clusterization for chestnut honey samples, while overlapping regions were observed for acacia honeys. Three supervised statistical approaches, such as Principal Components-Linear Discriminant Analysis, Partial Least Squares-Discriminant Analysis and k-nearest neighbors, were tested on the dataset gathered and relevant performances were compared. All tested statistical approaches provided comparable prediction abilities in cross-validation and external validation with mean values falling between 89.2-98.4% for chestnut and between 85.8-95.0% for acacia honey. The results obtained herein indicate the feasibility of the DART-HRMS approach in combination with chemometrics for the rapid authentication of honey's geographical origin.

Application of High Resolution Mass Spectrometric methods coupled with chemometric techniques in olive oil authenticity studies - A review

Extra Virgin Olive Oil (EVOO), the emblematic food of the Mediterranean diet, is recognized for its nutritional value and beneficial health effects. The main authenticity issues associated with EVOO's quality involve the organoleptic properties (EVOO or defective), mislabeling of production type (organic or conventional), variety and geographical origin, and adulteration. Currently, there is an emerging need to characterize EVOOs and evaluate their genuineness. This can be achieved through the development of analytical methodologies applying advanced "omics" technologies and the investigation of EVOOs chemical fingerprints. The objective of this review is to demonstrate the analytical performance of High Resolution Mass Spectrometry (HRMS) in the field of food authenticity assessment, allowing the determination of a wide range of food constituents with exceptional identification capabilities. HRMS-based workflows used for the investigation of critical olive oil authenticity issues are presented and discussed, combined with advanced data processing, comprehensive data mining and chemometric tools. The use of unsupervised classification tools, such as Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA), as well as supervised classification techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Partial Least Square Discriminant Analysis (PLS-DA), Orthogonal Projection to Latent Structure-Discriminant Analysis (OPLS-DA), Counter Propagation Artificial Neural Networks (CP-ANNs), Self-Organizing Maps (SOMs) and Random Forest (RF) is summarized. The combination of HRMS methodologies with chemometrics improves the quality and reliability of the conclusions from experimental data (profile or fingerprints), provides valuable information suggesting potential authenticity markers and is widely applied in food authenticity studies.

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.

Natural Product Discovery by Direct Analysis in Real Time Mass Spectrometry

Direct analysis in real time mass spectrometry (DART MS) is one of the first ambient ionization methods to be introduced and commercialized. Analysis by DART MS requires minimal sample preparation, produces nearly instantaneous results, and provides detection over a broad range of compounds. These advantageous features are particularly well-suited for the inherent complexity of natural product analysis. This review highlights recent applications of DART MS for species identification by chemotaxonomy, chemical profiling, genetic screening, and chemical spatial analysis from plants, insects, microbes, and metabolites from living systems.

Atmospheric Pressure Dark-Current Argon Discharge Ionization with Comparable Performance to Direct Analysis in Real Time Mass Spectrometry

Herein, a dark-current discharge state created by combining argon flow with a needle electrode in ambient air is described that has an ionization efficiency and mechanism comparable to those of conventional helium direct analysis in real time (DART), without requiring dopants and DART glow discharge. Using this method, polar compounds such as α-amino acids were ionized in the dark-current argon discharge via (de)protonation, molecular anion formation, fragmentation, (de)protonation with the attachment of oxygen, deprotonation with hydrogen loss and negative ion attachment. In contrast, nonpolar compounds (e.g., n-alkanes) were detected as positive ions via hydride abstraction and oxidation. Major background ions observed were H₃O⁺(H₂O)_n, O₂^·+, O₂^·−(H₂O)_n and CO₃^·−. These results indicate that the present dark-current discharge efficiently generates resonance-state argon with an internal energy of ∼14.2 eV, higher than that of the well-known metastable state (∼11.6 eV). It is therefore suggested that ionization reactions occurring there can be attributed to the Penning ionization of atmospheric H₂O and O₂ by resonance-state argon, analogous to helium DART.

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Typings of Edible Oils through Spectral Networking of Triacylglycerol Fingerprints

Adulteration of edible oils by the manufacturers has been found frequently in modern societies. Due to the complexity of the chemical contents in edible oils, it is challenging to quantitatively determine the extent of adulteration and prove the authenticity of edible oils. In this study, a robust and simple MALDI-TOF-MS platform for rapid fingerprinting of triacylglycerols (TAGs) in edible oils was developed, where spectral similarity analysis was performed to quantitatively reveal correlations among edible oils in the chemical level. Specifically, we proposed oil networking, a spectral similarity-based illustration, which enabled reliable classifications of tens of commercial edible oils from vegetable and animal origins. The strategy was superior to traditional multivariate statistics due to its high sensitivity in probing subtle changes in TAG profiles, as further demonstrated by the success in determination of the adulterated lard in a food fraud in Taiwan. Finally, we showed that the platform allowed quantitative assessment of the binary mixture of olive oil and canola oil, which is a common type of olive oil adulteration in the market. Overall, these results suggested a novel strategy for chemical fingerprint-based quality control and authentication of oils in the food industry.

Assessing fish authenticity by direct analysis in real time-high resolution mass spectrometry and multivariate analysis: discrimination between wild-type and farmed salmon

The constant increase in seafood consumption worldwide has led to a parallel growth of the incidence of products obtained by aquaculture on the market, but also of the fraudulent commercialization of farmed products as wild-type ones. A careful characterization of the lipid component of seafood products based on chromatography-mass spectrometry techniques has been reported as a promising approach to reliably differentiate farmed from wild-type products. In this context, a fast method based on Direct Analysis in Real Time (DART) coupled to High Resolution Mass Spectrometry (HRMS) based on a single stage Orbitrap mass analyzer, integrated by Principal Component Analysis (PCA), was developed in the present study and applied to scout for spectral features useful to discriminate wild-type from farmed salmon of Salmo salar species. In particular, normalized intensities obtained for the 30 most intense signals (all referred to fatty acids, FA) detected in negative ion DART-HRMS spectra of the lipid extracts of salmon fillets [26 wild-type from Canada, 74 farmed from Canada (25), Norway (25) and Chile (24)] were considered as the variables for PCA. The scatterplot referred to the first two principal components showed a clear distinction between wild-type and farmed salmon, which gathered as a unique cluster, despite the remarkable differences in their geographical origin. In accordance with previous studies based on more complex and time-demanding analytical approaches, three saturated (14:0, 16:0 and 18:0) FA, along with unsaturated ones having 20 or 22 carbon atoms, were found as the main discriminating variables for wild-type salmons, whereas FA with compositions 18:1, 18:2, 18:3 and several oxidized forms arising from them were found to have a significantly higher incidence in farmed salmon. The method was further validated by Discriminant Analysis (DA) performed on the same dataset used for PCA integrated by data obtained from 6 commercial samples, putatively referred to farmed Norwegian salmon. Results showed that 100% of the latter were correctly classified as farmed type. Relative abundances of DART-HRMS signals related to specific FA appear then very promising for the differentiation of wild-type salmon from farmed ones, a very relevant issue in the context of consumers' protection from seafood frauds.

Direct analysis in real time coupled to high resolution mass spectrometry as a rapid tool to assess salmon (Salmo salar) freshness

Direct analysis in real time-high resolution mass spectrometry (DART-HRMS) was applied to the detection of lipid species in the lipid extracts of farmed salmon samples collected from a local retailer and analyzed right after the purchase and after storage for 4 and 6 days under refrigerated conditions. The recognition of type and composition of lipids detected in DART-HRMS spectra was performed by using the relevant accurate m/z data (accuracy better than 5 ppm) as input for a search on the LipidMaps database. As a result, several fatty acids (FA), either saturated or mono-/poly-unsaturated, and triacylglycerols (TAG) were recognized in the three types of samples from the corresponding negative and positive ion DART-HRMS spectra, respectively. Following, spectral intensities were exploited to monitor the evolution of selected FA and TAG during the refrigeration of salmon meat. In particular, after 4 days of refrigeration, a statistically significant increase was recorded for FA with side chain compositions 18:2, 18:1, 20:5, and 22:6 despite a significant decrease found for TAG with overall side chain compositions 50:4, 52:5, 52:4, and 52:3 after the same time. These evolutions were consistent with a general model already proposed for the effect of low temperature treatments on seafood, implying the action of endogenous lipases, with consequent increase of the free FA amount and decrease in glycerophospholipids and triglycerides contents. The described results indicate DART-HRMS as a promising MS-based rapid tool for the assessment of fish, or other seafood, freshness.

Metabolomic Approach for the Authentication of Berry Fruit Juice by Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry Coupled to Chemometrics

Berry fruit juice, which is represented by blueberry and cranberry juice, has become increasingly popular due to its reported nutritional and health benefits. However, in markets, adulteration of berry fruit juice with cheaper substitutes is frequent. In the present study, a metabolomic approach for authentication of berry fruit juices by liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) was established. The global characterization of the berry fruit metabolome by information dependent acquisition directed LC-MS/MS coupled to a peak mining workflow by isotope pattern matching was reported. Targeted metabolomics analysis of known juice biomarkers, such as flavonoids, anthocyanins, etc. exhibited a good separation of berry fruit juices from adulterant juices. Moreover, untargeted metabolomics analysis was carried out and subjected to chemometrics analysis. Discrimination of blueberry juice, cranberry juice, and its adulterant apple juice and grape juice was obtained by principal component analysis-discriminant analysis. Eighteen characteristic markers discriminating berry fruit juice and its adulterants were selected by comparison of marker abundances in different juice samples. Identification of characteristic markers was accomplished by elemental formula prediction and online database searches based on accurate MS information. These results suggested that the combination of untargeted and targeted metabolomics approach has great potential for authentication of berry fruit juice.

Rapid Analysis of Illegal Cationic Dyes in Foods and Surface Waters Using High Temperature Direct Analysis in Real Time High-Resolution Mass Spectrometry

A high temperature desorption (HTD) direct analysis in real time-high-resolution mass spectrometric (DART-HRMS) method was developed for the rapid analysis of four banned cationic dyes. Rhodamine B is used to dye foods, while malachite green, crystal violet, and methylene blue are added to fishponds as antimicrobials. A simple induced phase separation extraction was used to pretreat samples. The DART-HRMS method employed two temperature steps, i.e., 200 °C for drying, purification, and enrichment of sample solution and 500 °C for thermal desorption and ionization of analytes. The calibration curves of dyes in the range of 50-2000 ng/mL were linear using deuterated malachite green as an internal standard. The LODs vary for all analytes between 0.1 and 30 ppb depending on the matrix and experimental conditions. Through analyses of real samples, two chili powders and one chili oil were found to be contaminated by rhodamine B. The concentrations were comparable with those found by an HPLC-MS/MS method.

Improvement in ionization efficiency of direct analysis in real time-mass spectrometry (DART-MS) by corona discharge

Herein it is shown that a combination of direct analysis in real time (DART) with a corona discharge system consisting of only a needle electrode easily improves DART ionization efficiency. Positive and negative DC corona discharges led to a formation of abundant excited helium atoms as well as the reactant ions H3O(+)(H2O)n and O2˙(-) in the DART analyte ionization area. These phenomena resulted in an increase in the absolute intensities of (de)protonated analytes by a factor of 2-20 over conventional DART. The other analyte ions detected in this corona-DART system (i.e., molecular ions, fragment ions, oxygenated (de)protonated analytes, dehydrogenated deprotonated analytes, and negative ion adducts) were quite similar to those obtained from DART alone. This indicates a lack of side reactions due to the corona discharge. The change in the relative intensities of individual analyte-related ions due to the combination of a corona discharge system with DART suggests that there is no effect of the abundant excited helium in the analyte ionization area on the fragmentation processes or enhancement of oxidation due to hydroxyl radicals HO˙. Furthermore, it was found that the corona-DART combination can be applied to the highly sensitive analysis of n-alkanes, in which the alkanes are ionized as positive ions via hydride abstraction and oxidation, independent of the type of alkane or the mass spectrometer used.

A Practical Method to Estimate the Resolving Power of a Chemical Sensor Array: Application to Feature Selection

A methodology to calculate analytical figures of merit is not well established for detection systems that are based on sensor arrays with low sensor selectivity. In this work, we present a practical approach to estimate the Resolving Power of a sensory system, considering non-linear sensors and heteroscedastic sensor noise. We use the definition introduced by Shannon in the field of communication theory to quantify the number of symbols in a noisy environment, and its version adapted by Gardner and Barlett for chemical sensor systems. Our method combines dimensionality reduction and the use of algorithms to compute the convex hull of the empirical data to estimate the data volume in the sensor response space. We validate our methodology with synthetic data and with actual data captured with temperature-modulated MOX gas sensors. Unlike other methodologies, our method does not require the intrinsic dimensionality of the sensor response to be smaller than the dimensionality of the input space. Moreover, our method circumvents the problem to obtain the sensitivity matrix, which usually is not known. Hence, our method is able to successfully compute the Resolving Power of actual chemical sensor arrays. We provide a relevant figure of merit, and a methodology to calculate it, that was missing in the literature to benchmark broad-response gas sensor arrays.

Direct analysis in real time-Mass spectrometry (DART-MS) in forensic and security applications

Over the last decade, direct analysis in real time (DART) has emerged as a viable method for fast, easy, and reliable "ambient ionization" for forensic analysis. The ability of DART to generate ions from chemicals that might be present at the scene of a criminal activity, whether they are in the gas, liquid, or solid phase, with limited sample preparation has made the technology a useful analytical tool in numerous forensic applications. This review paper summarizes many of those applications, ranging from the analysis of trace evidence to security applications, with a focus on providing the forensic scientist with a resource for developing their own applications. The most common uses for DART in forensics are in studying seized drugs, drugs of abuse and their metabolites, bulk and detonated explosives, toxic chemicals, chemical warfare agents, inks and dyes, and commercial plant and animal products that have been adulterated for economic gain. This review is meant to complement recent reviews that have described the fundamentals of the ionization mechanism and the general use of DART. We describe a wide range of forensic applications beyond the field of analyzing drugs of abuse, which dominates the literature, including common experimental and data analysis methods. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:171-187, 2018.