Potential and limitations of non-targeted fingerprinting for authentication of food in official control

Freeze-Drying for the Reduction of Fruit and Vegetable Chain Losses: A Sustainable Solution to Produce Potential Health-Promoting Food Applications

Freeze-drying fresh vegetables and fruits may not only prevent post-harvest losses but also provide a concentrated source of nutrients and phytochemicals. This study focused on the phenolic composition of different freeze-dried products derived from horticultural crop remains (HCRs) in the vegetable and fruit production chain. These products may be considered as a potential health-promoting solution for preventing post-harvest fruit spoiling and losses. The total polyphenolic content (TPC) and the main phenolics were studied using high-performance liquid chromatography (HPLC) with a diode array detector (DAD). Additionally, an in vitro chemical screening of the antioxidant capacity was carried out using the Ferric Reducing Antioxidant Power (FRAP) assay. These analyses were performed together with an investigation of the correlations among phenolics and their antioxidant properties, and a bioinformatic approach was used to estimate the main potential bio-targets in human beings. Furthermore, a statistical approach using Principal Component Analysis (PCA) was carried out for a multivariate characterization of these products. Catechins, flavonols, and phenolic acids were the predominant and most discriminating classes in different products. The TPC values obtained in this study ranged from 366.86 ± 71.30 mg GAE/100 g DW (apple, MD) to 1077.13 ± 35.47 mg GAE/100 g DW (blueberry, MID) and 1102.25 ± 219.71 mg GAE/100 g DW (kaki, KD). The FRAP values ranged from 49.28 ± 2.88 mmol Fe2+/kg DW (apple, MD) to 80.43 ± 0.02 mmol Fe2+/kg DW (blueberry, MID) and 79.05 ± 0.21 mmol Fe2+/kg DW (kaki, KD). The proposed approach may be an effective tool for quality control and valorization of these products. This study showed that the utilization of crop remains can potentially lead to the development of new functional foods, providing additional economic benefits for farmers. Finally, the use of freeze-drying may potentially be a sustainable and beneficial solution for growers who may directly utilize this technology to produce dried products from the crop remains of their fruit productions.

Comparison of Multiple NIR Instruments for the Quantitative Evaluation of Grape Seed and Other Polyphenolic Extracts with High Chemical Similarities

Grape seed extract (GSE), one of the world's bestselling dietary supplements, is prone to frequent adulteration with chemically similar compounds. These frauds can go unnoticed within the supply chain due to the use of unspecific standard analytical methods for quality control. This research aims to develop a near-infrared spectroscopy (NIRS) method for the rapid and non-destructive quantitative evaluation of GSE powder in the presence of multiple additives. Samples were prepared by mixing GSE with pine bark extract (PBE) and green tea extract (GTE) on different levels between 0.5 and 13% in singular and dual combinations. Measurements were performed with a desktop and three different handheld devices for performance comparison. Following spectral pretreatment, partial least squares regression (PLSR) and support vector regression (SVR)-based quantitative models were built to predict extract concentrations and various chemical parameters. Cross- and external-validated models could reach a minimum R2p value of 0.99 and maximum RMSEP of 0.27% for the prediction of extract concentrations using benchtop data, while models based on handheld data could reach comparably good results, especially for GTE, caffeic acid and procyanidin content prediction. This research shows the potential applicability of NIRS coupled with chemometrics as an alternate, rapid and accurate quality evaluation tool for GSE-based supplement mixtures.

Detection of Sugar Syrups in Honey Using Untargeted Liquid Chromatography-Mass Spectrometry and Chemometrics

Background: Honey is one of the most adulterated foods worldwide, and several analytical methods have been developed over the last decade to detect syrup additions to honey. These include approaches based on stable isotopes and the specific detection of individual marker compounds or foreign enzymes. Proton nuclear magnetic resonance (1H-NMR) spectroscopy is applied as a rapid and comprehensive screening method, which also enables the detection of quality parameters and the analysis of the geographical and botanical origin. However, especially for the detection of foreign sugars, 1H-NMR has insufficient sensitivity. Methods: Since untargeted liquid chromatography-mass spectrometry (LC-MS) is more sensitive, we used this approach for the detection of positive and negative ions in combination with a recently developed data processing workflow for routine laboratories based on bucketing and random forest for the detection of rice, beet and high-fructose corn syrup in honey. Results: We show that the distinction between pure and adulterated honey is possible for all three syrups, with classification accuracies ranging from 98 to 100%, while the accuracy of the syrup content estimation depends on the respective syrup. For rice and beet syrup, the deviations from the true proportion were in the single-digit percentage range, while for high-fructose corn syrup they were much higher, in some cases exceeding 20%. Conclusions: The approach presented here is very promising for the robust and sensitive detection of syrup in honey applied in routine laboratories.

Application of Sorbent-Based Extraction Techniques in Food Analysis

This review presents an outline of the application of the most popular sorbent-based methods in food analysis. Solid-phase extraction (SPE) is discussed based on the analyses of lipids, mycotoxins, pesticide residues, processing contaminants and flavor compounds, whereas solid-phase microextraction (SPME) is discussed having volatile and flavor compounds but also processing contaminants in mind. Apart from these two most popular methods, other techniques, such as stir bar sorptive extraction (SBSE), molecularly imprinted polymers (MIPs), high-capacity sorbent extraction (HCSE), and needle-trap devices (NTD), are outlined. Additionally, novel forms of sorbent-based extraction methods such as thin-film solid-phase microextraction (TF-SPME) are presented. The utility and challenges related to these techniques are discussed in this review. Finally, the directions and need for future studies are addressed.

Revealing adulterated olive oils by triacylglycerol screening methods: Beyond the official method

Official control methods to detect olive oil (OO) adulteration fail to provide satisfactory consumer protection. Thus, faster and more sensitive screening tools are needed to increase their effectiveness. Here, the official method for adulterant detection in OO was compared with three untargeted screening methods based on triacylglycerol analysis using high-throughput (FIA-HESI-HRMS; HT-GC-MS; HPLC-RID) and pattern recognition techniques (PLS-DA). They were assayed on a set of genuine and adulterated samples with a high natural variability (n = 143). The sensitivity of the official method was 1 for high linoleic (HL) blends at ≥2 % but only 0.39 for high oleic (HO) blends at ≥5 %, while specificity was 0.96. The sensitivity of the screening methods in external validation was 0.90-0.99 for the detection of HL and 0.82-0.88 for HO blends. Among them, HT-GC-MS offered the highest sensitivity (0.94) and specificity (0.76), proving to be the most suitable screening tool for OO authentication.

Magnetic amino-rich hyper-crosslinked polymers for fat-rich foodstuffs pretreatment in nontargeted analysis of chemical hazards

Nontargeted analysis for chemical hazards is highly desirable in controlling food safety to ensure human health. As the dominating interference in fat-rich foodstuffs, lipids removal is a great challenge in sample pretreatment. Herein, diverse lipids from both animal and vegetable oils are effectively removed and 565 chemical hazards with various physicochemical properties are used for method validation. These benefits are from the designed magnetic amino-rich hyper-crosslinked core-shell polymeric composites (Fe₃O₄@poly(MAAM-co-EGDMA)) and the application of an auto extraction system. Among them, the amino groups are the key factors for lipid removal. Theoretical calculations, isothermal titration calorimetry (ITC), and functional monomer replacement demonstrated that the mechanisms to universally capture free fatty acids (FFAs) and triglycerides (TGs) are electrostatic interaction and supplemented by hydrogen bonding. Overall, this work highlights the great application potentials of polymeric adsorbents as sample pretreatment materials for nontargeted analysis in food safety.

Multidimensional Chromatographic Fingerprinting Combined with Chemometrics for the Identification of Regulated Plants in Suspicious Plant Food Supplements

The popularity of plant food supplements has seen explosive growth all over the world, making them susceptible to adulteration and fraud. This necessitates a screening approach for the detection of regulated plants in plant food supplements, which are usually composed of complex plant mixtures, thus making the approach not so straightforward. This paper aims to tackle this problem by developing a multidimensional chromatographic fingerprinting method aided by chemometrics. To render more specificity to the chromatogram, a multidimensional fingerprint (absorbance × wavelength × retention time) was considered. This was achieved by selecting several wavelengths through a correlation analysis. The data were recorded using ultra-high-performance liquid chromatography (UHPLC) coupled with diode array detection (DAD). Chemometric modelling was performed by partial least squares-discriminant analysis (PLS-DA) through (a) binary modelling and (b) multiclass modelling. The correct classification rates (ccr%) by cross-validation, modelling, and external test set validation were satisfactory for both approaches, but upon further comparison, binary models were preferred. As a proof of concept, the models were applied to twelve samples for the detection of four regulated plants. Overall, it was revealed that the combination of multidimensional fingerprinting data with chemometrics was feasible for the identification of regulated plants in complex botanical matrices.

Toward the Non-Targeted Detection of Adulterated Virgin Olive Oil with Edible Oils via FTIR Spectroscopy & Chemometrics: Research Methodology Trends, Gaps and Future Perspectives

Fourier-Transform mid-infrared (FTIR) spectroscopy offers a strong candidate screening tool for rapid, non-destructive and early detection of unauthorized virgin olive oil blends with other edible oils. Potential applications to the official anti-fraud control are supported by dozens of research articles with a "proof-of-concept" study approach through different chemometric workflows for comprehensive spectral analysis. It may also assist non-targeted authenticity testing, an emerging goal for modern food fraud inspection systems. Hence, FTIR-based methods need to be standardized and validated to be accepted by the olive industry and official regulators. Thus far, several literature reviews evaluated the competence of FTIR standalone or compared with other vibrational techniques only in view of the chemometric methodology, regardless of the inherent characteristics of the product spectra or the application scope. Regarding authenticity testing, every step of the methodology workflow, and not only the post-acquisition steps, need thorough validation. In this context, the present review investigates the progress in the research methodology on FTIR-based detection of virgin olive oil adulteration over a period of more than 25 years with the aim to capture the trends, identify gaps or misuses in the existing literature and highlight intriguing topics for future studies. An extensive search in Scopus, Web of Science and Google Scholar, combined with bibliometric analysis, helped to extract qualitative and quantitative information from publication sources. Our findings verified that intercomparison of literature results is often impossible; sampling design, FTIR spectral acquisition and performance evaluation are critical methodological issues that need more specific guidance and criteria for application to product authenticity testing.

An Overview on the Application of Chemometrics Tools in Food Authenticity and Traceability

The use of advanced chemometrics tools in food authenticity research is crucial for managing the huge amount of data that is generated by applying state-of-the-art analytical methods such as chromatographic, spectroscopic, and non-targeted fingerprinting approaches. Thus, this review article provides description, classification, and comparison of the most important statistical techniques that are commonly employed in food authentication and traceability, including methods for exploratory data analysis, discrimination, and classification, as well as for regression and prediction. This literature revision is not intended to be exhaustive, but rather to provide a general overview to non-expert readers in the use of chemometrics in food science. Overall, the available literature suggests that the selection of the most appropriate statistical technique is dependent on the characteristics of the data matrix, but combining complementary tools is usually needed for properly handling data complexity. In that way, chemometrics has become a powerful ally in facilitating the detection of frauds and ensuring the authenticity and traceability of foods.

Characterization and Classification of Spanish Honey by Non-Targeted LC-HRMS (Orbitrap) Fingerprinting and Multivariate Chemometric Methods

A non-targeted LC-HRMS fingerprinting methodology based on a C18 reversed-phase mode under universal gradient elution using an Orbitrap mass analyzer was developed to characterize and classify Spanish honey samples. A simple sample treatment consisting of honey dissolution with water and a 1:1 dilution with methanol was proposed. A total of 136 honey samples belonging to different blossom and honeydew honeys from different botanical varieties produced in different Spanish geographical regions were analyzed. The obtained LC-HRMS fingerprints were employed as sample chemical descriptors for honey pattern recognition by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The results demonstrated a superior honey classification and discrimination capability with respect to previous non-targeted HPLC-UV fingerprinting approaches, with them being able to discriminate and authenticate the honey samples according to their botanical origins. Overall, noteworthy cross-validation multiclass predictions were accomplished with sensitivity and specificity values higher than 96.2%, except for orange/lemon blossom (BL) and rosemary (RO) blossom-honeys. The proposed methodology was also able to classify and authenticate the climatic geographical production region of the analyzed honey samples, with cross-validation sensitivity and specificity values higher than 87.1% and classification errors below 10.5%.

Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives

Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.

Advances in the Application of Liquid Chromatography in the Detection of Pollutants

Food is easy to be contaminated because of its complex composition. Therefore, in order to protect people from potential food contaminants, it is very necessary to test for various contaminants in food. Liquid chromatography is widely used in the field of food safety detection. In addition, with the development of liquid chromatography technology, more and more new instruments are combined with liquid chromatography. Compared with traditional liquid chromatography, combined liquid chromatography has great advantages in efficiency and operation. Therefore, it is rapidly promoted in the field of food safety testing. In this paper, the results of the determination of three kinds of food pollutants by different liquid chromatography methods are reviewed, and the indexes are compared and analyzed.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

Metabolite Fingerprinting Based on 1H-NMR Spectroscopy and Liquid Chromatography for the Authentication of Herbal Products

Herbal medicines (HMs) are regarded as one of the traditional medicines in health care to prevent and treat some diseases. Some herbal components such as turmeric and ginger are used as HMs, therefore the identification and confirmation of herbal use are very necessary. In addition, the adulteration practice, mainly motivated to gain economical profits, may occur by substituting the high price of HMs with lower-priced ones or by addition of certain chemical constituents known as Bahan Kimia Obat (chemical drug ingredients) in Indonesia. Some analytical methods based on spectroscopic and chromatographic methods are developed for the authenticity and confirmation of the HMs used. Some approaches are explored during HMs authentication including single-component analysis, fingerprinting profiles, and metabolomics studies. The absence of reference standards for certain chemical markers has led to exploring the fingerprinting approach as a tool for the authentication of HMs. During fingerprinting-based spectroscopic and chromatographic methods, the data obtained were big, therefore the use of chemometrics is a must. This review highlights the application of fingerprinting profiles using variables of spectral and chromatogram data for authentication in HMs. Indeed, some chemometrics techniques, mainly pattern recognition either unsupervised or supervised, were applied for this purpose.

Honey authenticity: the opacity of analytical reports-part 2, forensic evaluative reporting as a potential solution

The analytical techniques applied to verify honey authenticity are multifaceted and often result in complex data rich certificates of analysis that are open to interpretation and may be opaque to stakeholders without specialist knowledge. In these cases, the drawing of an independent overarching opinion is challenging. Two questions arise: (Q1) Is it acceptable to report interpretation, particularly if it is adverse, without exhibiting the supporting data? (Q2) How may a valid overarching opinion on authenticity be derived from a large, partially conflicting, dataset? To Q1, it is demonstrated that full disclosure of the data used in interpretation is mandatory. To Q2 it is proposed, with worked examples, to adopt ‘evaluative reporting’; a formalised likelihood ratio thought process used in forensic science for evaluation of findings and their strength assessment. In the absence of consensus on techniques for honey authenticity adoption of reporting conventions will allow objective assessments of reports, with equity to all and provide a better basis to identify and address fraud.

Detecting adulteration of stingless bee honey using untargeted 1H NMR metabolomics with chemometrics

As stingless bee honey (SBH) is gaining in popularity in the Malaysian market, it is now prone to adulteration. The higher price of SBH compared to floral honey has led to the use of unusual adulterants such as vinegar and even floral honey to mimic the unique taste and appearance of SBH. Since the current AOAC 998.12 method fails to detect these adulterants as their δ13C values are in the range for C3 plants, untargeted 1H NMR metabolomics was proposed. Principal component analysis of SBH 1H NMR fingerprints was able to distinguish authentic SBHs from adulterated ones down to 1% adulteration level for selected adulterants. Discriminant analysis showed promising results in distinguishing the preliminary datasets of authentic SBHs from the adulterated ones, including discriminating SBHs adulterated with different adulterants derived from C3 and C4 plants. Hence, to assure any emerging adulterant can be detected, all 1H NMR regions should be considered.

Chromatographic Fingerprinting and Food Identity/Quality: Potentials and Challenges

Chromatograms are a valuable source of information about the chemical composition of the food being analyzed. Sometimes, this information is not explicit and appears in a hidden or not obvious way. Thus, the use of chemometric tools and data-mining methods to extract it is required. The fingerprint provided by a chromatogram offers the possibility to perform both identity and quality testing of foodstuffs. This perspective is aimed at providing an updated opinion of chromatographic fingerprinting methodology in the field of food authentication. Furthermore, the limitations, its absence in official analytical methods, and the future directions of this methodology are discussed.

Enterprise Food Fraud in China: Key Factors Identification From Social Co-governance Perspective

Food fraud not only exacerbates human public health risks but also threatens the business development of food and related industries. Therefore, how to curb food fraud effectively becomes a crucial issue for governments, industries, and consumers. Previous studies have demonstrated that enterprise food fraud is subject to joint influences of factor at various hierarchical levels within a complex system of stakeholders. To address enterprise food fraud, it is necessary to identify the key such factors and elucidate the functional mechanisms, as well as systematic analysis of the interrelationships among clusters and factors. Hence, we grounded on a social co-governance perspective and investigated the food fraud key influencing factors and their interrelationships in an emerging food market – China, by using the DEMATEL-based analytic network process (DANP). Results showed that the identified key cluster was government regulation, social governance, and detection techniques. Four other key factors were also identified, including government regulatory capability and penalty intensity, expected economic benefits, maturity of market reputation mechanism, and transparency of supply chain. Policy implications from the social co-governance perspective for China and similar economies are discussed finally.

Liquid chromatographic methods coupled to chemometrics: a short review to present the key workflow for the investigation of wine phenolic composition as it is affected by environmental factors

The guarantee of wine authenticity arises great concern because of its nutritional and economic importance. Phenolic fingerprints have been used as a source of chemical information for various authentication issues, including botanical and geographical origin, as well as vintage age. The local environment affects wine production and especially its phenolic metabolites. Integrated analytical methodologies combined with chemometrics can be applied in wine fingerprinting studies for the determination and establishment of phenolic markers that contain comprehensive and standardized information about the wine profile and how it can be affected by various environmental factors. This review summarizes all the recent trends in the generation of chemometric models that have been developed for treating chromatographic data and have been used for the investigation of critical wine authenticity issues, revealing phenolic markers responsible for the botanical, geographical, and vintage age classification of wines. Overall, the current review suggests that chromatographic methodologies are promising and powerful techniques that can be used for the accurate determination of phenolic compounds in difficult matrices like wine, highlighting the advantages of the applications of supervised chemometric tools over unsupervised for the construction of prediction models that have been successfully used for the classification based on their territorial and botanical origin.

A combined metabolomics and peptidomics approach to discriminate anomalous rind inclusion levels in Parmigiano Reggiano PDO grated hard cheese from different ripening stages

Parmigiano Reggiano is a hard cheese with a Protected Designation of Origin (PDO) certification that also applies to the grated product. The percentage of rind in grated Parmigiano Reggiano is regulated by the PDO production Specification and must not exceed the limit of 18% (w/w). The present study evaluates the potential of an untargeted foodomics approach to detect anomalous inclusions of rind in grated Parmigiano Reggiano cheese. In particular, a combined metabolomics and peptidomics approach was used to detect potential markers of counterfeits (rind > 18%). In the framework of realistic food integrity purposes, non-Parmigiano Reggiano grated samples and different ripening times were also considered. Untargeted metabolomics allowed detecting 347 compounds, with a prevalence of amino acids and peptide derivatives, followed by fatty acyls and other compounds (such as lactones, ketones, and aldehydes) typically related to proteolysis and lipolysis events. Overall, the unsupervised multivariate statistics showed that the ripening time plays a hierarchically higher impact than rind inclusion in determining the main differences in the chemical profiles detected. Interestingly, supervised statistics highlighted distinctive markers for ripening time and rind inclusion, with only 16 common discriminant compounds being shared between the two conditions. The best markers of rind inclusion > 18% were 2-hydroxyadenine (VIP score = 1.937; AUC value = 0.83) and the amino acid derivatives argininic acid (VIP score = 1.462; AUC value = 0.75) and 5-hydroxyindole acetaldehyde (VIP score = 1.710; AUC value = 0.86). Interestingly, the medium-chain aldehyde 4-hydroperoxy-2-nonenal was a common marker of both ripening time and anomalous rind inclusion (>18%), likely arising from the lipid oxidation processes. Finally, among potential marker peptides of rind inclusion, the alpha-S1 casein proteolytic product (F)FVAPFPEVFGK(E) could be identified.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.

Non-Targeted LC-MS Metabolomics Approach towards an Authentication of the Geographical Origin of Grain Maize (Zea mays L.) Samples

Safety along the food and feed supply chain is an emerging topic and closely linked to the ability to analytical trace the geographical origin of food or feed. In this study, ultra-performance liquid chromatography coupled with electrospray ionization quadrupole-time-of-flight mass spectrometry was used to trace back the geographical origin of 151 grain maize (Zea mays L.) samples from seven countries using a high resolution non-targeted metabolomics approach. Multivariate data analysis and univariate statistics were used to identify promising marker features related to geographical origin. Classification using only 20 selected markers with the Random Forest algorithm led to 90.5% correctly classified samples with 100 times repeated 10-fold cross-validation. The selected markers were assigned to the class of triglycerides, diglycerides and phospholipids. The marker set was further evaluated for its ability to separate between one sample class and the rest of the dataset, yielding accuracies above 89%. This demonstrates the high potential of the non-polar metabolome to authenticate the geographic origin of grain maize samples. Furthermore, this suggests that focusing on only a few lipids with high potential for grain maize authentication could be a promising approach for later transfer of the method to routine analysis.

An Authentication Study on Grappa Spirit: The Use of Chemometrics to Detect a Food Fraud

An authenticity study on Italian grape marc spirit was carried out by gas chromatography (GC) and chemometrics. A grape marc spirit produced in Italy takes the particular name of “grappa”, a product which has peculiar tradition and production in its country of origin. Therefore, the evaluation of its authenticity plays an important role for its consumption in Italy, as well as for its exportation all around the world. For the present work, 123 samples of grappa and several kinds of spirits were analyzed in their alcohol content by electronic densimetry, and in their volatile fraction by gas-chromatography with a flame-ionization detector. Part of these samples (94) was employed as a training set to compute a chemometric model (by linear discriminant analysis, LDA) and the other part (29 samples) was used as a test set to validate it. Finally, two grappa samples seized from the market by the Italian Customs and Monopolies Agency and considered suspicious due to their aroma reported as non-compliant were projected onto the LDA model to evaluate the compliance with the “grappa” class. A further one-class classification method by principal component analysis (PCA) was carried out to evaluate the compliance with other classes. Results showed that the suspicious samples were not recognized as belonging to any of the analyzed spirit classes, confirming the starting hypothesis that they could be grappa samples adulterated in some way.

Detecting Admixture to Mango Purée of the Alphonso Cultivar (Mangifera indica L. cv. Alphonso) by 1H-NMR Spectroscopy

Food authenticity is becoming increasingly important but challenges existing analytical methods. In this study, we analyze the mango cultivar Alphonso with regard to authenticity using 1H-NMR spectroscopy. This cultivar has been termed “the king of mangoes” due to its unique flavor. Regarding its metabolites however, little is known about unique constellations that allow for differentiation of the Alphonso cultivar. We find that the Alphonso cultivar is distinguished by high levels of niacin, trigonelline, and histidine but features relatively low levels of alanine. Furthermore, we develop a model based on the local outlier factor algorithm that effectively detects admixture of non-Alphonso cultivars to Alphonso purée. This task is highly challenging because we identified no metabolites that are unique or uniquely absent in the Alphonso cultivar compared to other mango cultivars analyzed in this study. Our model shows promising results on a test set: Admixtures consisting of 35% non-Alphonso and 65% Alphonso mango purée were uncovered with a sensitivity of 88%. At the same time, our model verified Alphonso samples with a good specificity of 86%.

Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study

INTRODUCTION

The relationship between the chemical composition of food products and their sensory profile is a complex association confronting many challenges. However, new untargeted methodologies are helping correlate metabolites with sensory characteristics in a simpler manner. Nevertheless, in the pilot phase of a project, where only a small set of products are used to explore the relationships, choices have to be made about the most appropriate untargeted metabolomics methodology.

OBJECTIVE

To provide a framework for selecting a metabolite-sensory methodology based on: the quality of measurements, the relevance of the detected metabolites in terms of distinguishing between products or in terms of whether they can be related to the sensory attributes of the products.

METHODS

In this paper we introduce a systematic approach to explore all these different aspects driving the choice for the most appropriate metabolomics method.

RESULTS

As an example we have used a tomato soup project where the choice between two sampling methods (SPME and SBSE) had to be made. The results are not always consistently pointing to the same method as being the best. SPME was able to detect metabolites with a better precision, SBSE seemed to be able to provide a better distinction between the soups.

CONCLUSION

The three levels of comparison provide information on how the methods could perform in a follow up study and will help the researcher to make a final selection for the most appropriate method based on their strengths and weaknesses.

Authentication of tejocote (Crataegus mexicana) dietary supplements based on DNA barcoding and chemical profiling

Tejocote (Crataegus mexicana, Mexican hawthorn), known as a weight-loss supplement, has been marketed online and is easily available for overseas direct purchase. Alipotec (brand name) is known as one of the most popular products containing tejocote in Mexico and other countries. However, adverse effects have been reported by users of these supplements. Therefore it is necessary to find the reason for the side effect. Dietary supplement samples labelled as containing tejocote were analysed using mass spectrometry and DNA barcoding analysis. Our results demonstrate that Alipotec samples contained ingredients from different species, yellow oleander instead of tejocote. The rpoB barcode region was able to differentiate between tejocote and yellow oleander species. Moreover, it was also observed that three compounds, including thevetin B, neriifolin, and digitoxigenin, clearly distinguish between tejocote and yellow oleander samples. This is the first and preliminary investigation to use an integrated approach of both chemical and genomic profiling for the authentication of dietary supplement containing tejocote.

Chemical Characterization of Recycled Consumer Products Using Suspect Screening Analysis

Recycled materials are found in many consumer products as part of a circular economy; however, the chemical content of recycled products is generally uncharacterized. A suspect screening analysis using two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) was applied to 210 products (154 recycled, 56 virgin) across seven categories. Chemicals in products were tentatively identified using a standard spectral library or confirmed using chemical standards. A total of 918 probable chemical structures identified (112 of which were confirmed) in recycled materials versus 587 (110 confirmed) in virgin materials. Identified chemicals were characterized in terms of their functional use and structural class. Recycled paper products and construction materials contained greater numbers of chemicals than virgin products; 733 identified chemicals had greater occurrence in recycled compared to virgin materials. Products made from recycled materials contained greater numbers of fragrances, flame retardants, solvents, biocides, and dyes. The results were clustered to identify groups of chemicals potentially associated with unique chemical sources, and identified chemicals were prioritized for further study using high-throughput hazard and exposure information. While occurrence is not necessarily indicative of risk, these results can be used to inform the expansion of existing models or identify exposure pathways currently neglected in exposure assessments.

Rapid geographical indication of peppercorn seeds using corona discharge mass spectrometry

With increasing demands for more rapid and practical analyses, various techniques of ambient ionization mass spectrometry have gained significant interest due to the speed of analysis and abundance of information provided. Herein, an ambient ionization technique that utilizes corona discharge was applied, for the first time, to analyze and categorize whole seeds of black and white peppers from different origins. This setup requires no solvent application nor gas flow, thus resulting in a very simple and rapid analysis that can be applied directly to the sample without any prior workup or preparation. Combined with robust data pre-processing and subsequent chemometric analyses, this analytical method was capable of indicating the geographical origin of each pepper source with up to 98% accuracies in all sub-studies. The simplicity and speed of this approach open up the exciting opportunity for onsite analysis without the need for a highly trained operator. Furthermore, this methodology can be applied to a variety of spices and herbs, whose geographical indication or similar intellectual properties are economically important, hence it is capable of creating tremendous impact in the food and agricultural industries.

Nandrolone and estradiol biomarkers identification in bovine urine applying a liquid chromatography high-resolution mass spectrometry metabolomics approach

With the aim of specifically investigating patterns associated with three steroid treatments (17β-nandrolone, 17β-estradiol, and 17β-nandrolone + 17β-estradiol) in bovine, an reversed phase liquid chromatography (RPLC)-electrospray ionization (ESI)(+/-)-high-resolution mass spectrometry (HRMS) study was conducted to characterize the urinary profiles of involved animals. Although specific fingerprints with strong differences could be highlighted between urinary metabolite profiles within urine samples collected on control and treated animals, it appeared further that significant discriminations could also be observed between steroid treatments, evidencing thus specific patterns and candidate biomarkers associated to each treatment. An MS-2 structural elucidation step enabled level-1 identification of two biomarkers mainly involved in energy pathways, in relation to skeletal muscle functioning. These results make it possible to envisage a global strategy for the detection of anabolic practices involving steroids, while at the same time providing clues as to the compounds used, which would facilitate the confirmation stage to follow.

Metabolomics as a marketing tool for geographical indication products: a literature review

Geographical indication (GI) is used to identify a product's origin when its characteristics or quality are a result of geographical origin, which includes agricultural products and foodstuff. Metabolomics is an “omics” technique that can support product authentication by providing a chemical fingerprint of a biological system, such as plant and plant-derived products. The main purpose of this article is to verify possible contributions of metabolomic studies to the marketing field, mainly for certified regions, through an integrative review of the literature and maps produced by VOSviewer software. The results indicate that studies based on metabolomics approaches can relate specific food attributes to the region’s terroir and know-how. The evidence of this connection, marketing of GIs and metabolomics methods, is viewed as potential tool for marketing purposes (e.g., to assist communication of positive aspects and quality), and legal protection. In addition, our results provide a taxonomic categorization that can guide future marketing research involving metabolomics. Moreover, the results are also useful to government agencies to improve GIs registration systems and promotion strategies.

Are the elemental fingerprints of organic and conventional food different? ED-XRF as screening technique

Research has been conducted the last years to assess whether organically grown food is chemically different from produce of conventional agriculture and which markers are appropriate to discriminate between them. Most articles focus on one single food commodity, produced under strict controlled organic farming conditions, leaving open the question whether the difference would be seen when applied to the same commodity under different growing conditions. In this work 118 organic and 151 conventional samples of commercially available paprika powder, cinnamon, coffee, tea, chocolate, rice, wheat flour, cane sugar, coconut water, honey and bovine milk were characterised for their elemental composition using energy dispersive X-ray fluorescence. Resulting profiles were analysed using univariate and multivariate statistical techniques. Organic samples of a given commodity clustered together and were separated from their conventional counterparts. Differences in the elemental composition of food, could be used to develop statistical models for verifying the agronomical production system.

Critical evaluation of ambient mass spectrometry coupled with chemometrics for the early detection of adulteration scenarios in Origanum vulgare L

Nowadays, most of the screening methods in food manufacturing are based on spectroscopic techniques. Ambient Mass Spectrometry is a relatively new field of analytical chemistry which has proven to offer similar speed and ease-of-use when compared to other fingerprinting techniques, alongside the advantages of good selectivity, sensitivity and chemical information. Numerous applications have been explored in food authenticity, based either on the target detection of adulteration markers or, less frequently, on the development of multivariate classification models. The aim of the present work was to evaluate and compare the capabilities of Direct Analysis in Real Time (DART) and Atmospheric Solid Analysis Probe (ASAP) Mass Spectrometry (MS) for the high-throughput authenticity screening of commercial herbs and spices products. The gross addition of bulking material to dried Mediterranean oregano was taken as case study. First, a pilot sample set, constituted by authentic dried oregano, olive leaves (a frequently reported adulterant) and mixtures thereof at different levels (i.e. 10, 20, 30 and 50% w/w) was used. Each sample was fingerprinted by both ambient-MS techniques. After appropriate pre-processing, the whole mass spectra were used for the subsequent multivariate data analysis. Soft Independent Modelling of Class Analogy was adopted as classification algorithm and the model was challenged with both new authentic oregano and in-house prepared blends. To the best of our knowledge, this is the first report of DART-MS and ASAP-MS used in full scan mode and coupled to chemometric modelling as rapid fingerprinting approach for food authentication. Although both the techniques provided satisfactory results, ASAP-MS clearly showed greater potential, leading to reproducible, diagnostic feature-rich mass spectra. For this reason, ASAP-MS was further tested under a more convoluted scenario, where the training and validation sets were enlarged with additional authentic oregano samples and a wider range of adulterant species, respectively. Overall good results were achieved, with 93% model predictive accuracy, and screening detection capability estimated between 5-20% (w/w) addition, depending on the adulterant considered with the only exception of majorana. Investigation of Q residuals could highlight the statistically-relevant chemical markers which could be tentatively annotated by coupling the ASAP probe with a high resolution mass analyser. The results from the validation study confirmed the great potential of ASAP-MS in combination with chemometrics as fast MS-based screening solution and demonstrated its feasibility for classification model building.

Honey Phenolic Compound Profiling and Authenticity Assessment Using HRMS Targeted and Untargeted Metabolomics

Honey consumption is attributed to potentially advantageous effects on human health due to its antioxidant capacity as well as anti-inflammatory and antimicrobial activity, which are mainly related to phenolic compound content. Phenolic compounds are secondary metabolites of plants, and their content in honey is primarily affected by the botanical and geographical origin. In this study, a high-resolution mass spectrometry (HRMS) method was applied to determine the phenolic profile of various honey matrices and investigate authenticity markers. A fruitful sample set was collected, including honey from 10 different botanical sources (n = 51) originating from Greece and Poland. Generic liquid-liquid extraction using ethyl acetate as the extractant was used to apply targeted and non-targeted workflows simultaneously. The method was fully validated according to the Eurachem guidelines, and it demonstrated high accuracy, precision, and sensitivity resulting in the detection of 11 target analytes in the samples. Suspect screening identified 16 bioactive compounds in at least one sample, with abscisic acid isomers being the most abundant in arbutus honey. Importantly, 10 markers related to honey geographical origin were revealed through non-targeted screening and the application of advanced chemometric tools. In conclusion, authenticity markers and discrimination patterns were emerged using targeted and non-targeted workflows, indicating the impact of this study on food authenticity and metabolomic fields.

Breaking Through the Barrier: Regulatory Considerations Relevant to Ambient Mass Spectrometry at the Bedside

Rapid characterization of tissue disorder using ambient mass spectrometry (MS) techniques, requiring little to no preanalytical preparations of sampled tissues, has been shown using a variety of ion sources and with many disease classes. A brief overview of ambient MS in clinical applications, the state of the art in regulatory affairs, and recommendations to facilitate adoption for use at the bedside are presented. Unique challenges in the validation of untargeted MS methods and additional safety and compliance requirements for deployment within a clinical setting are further discussed. Development of a harmonized validation strategy for ambient MS methods is emphasized.