The Combined ICP-MS, ESEM-EDX, and HAADF-STEM-EDX Approach for the Assessment of Metal Sub-Micro- and Nanoparticles in Wheat Grain.

Metal sub-microparticles (SMPs) and nanoparticles (NPs) presence in food is attributable to increasing pollution from the environment in raw materials and finished products. In the present study, a multifaceted analytical strategy based on Environmental Scanning Electron Microscopy and High-Angle Annular Dark-Field-Scanning Transmission Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDX, HAADF-STEM-EDX) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was proposed for the detection and characterization of metal and metal-containing SMPs and NPs in durum wheat samples, covering a size measurement range from 1 nm to multiple µm. ESEM-EDX and ICP-MS techniques were applied for the assessment of SMP and NP contamination on the surface of wheat grains collected from seven geographical areas characterized by different natural and anthropic conditions, namely Italy, the USA, Australia, Slovakia, Mexico, Austria, and Russia. ICP-MS showed significant differences among the mean concentration levels of metals, with the USA and Italy having the highest level. ESEM-EDX analysis confirmed ICP-MS concentration measurements and measured the highest presence of particles < 0.8 µm in size in samples from Italy, followed by the USA. Less marked differences were observed when particles < 0.15 µm were considered. HAADF-STEM-EDX was applied to a selected number of samples for a preliminary assessment of internal contamination by metal SMPs and NPs, and to expand the measurable particle size range. The multifaceted approach provided similar results for Fe-containing SMPs and NPs. ICP-MS and ESEM-EDX also highlighted the presence of a significant abundance of Ti- and Al-containing particles, while for STEM-EDX, sample preparation artifacts complicated the interpretation. Finally, HAADF-STEM-EDX results provided relevant information about particles in the low nm range, since, by applying this technique, no particles smaller than 50 nm were observed in accordance with ESEM-EDX.

Isotopic, mycotoxin, and pesticide analysis for organic authentication along the production chain of wheat-derived products.

Wheat-based products are staples in diets worldwide. Organic food frauds continuously threaten consumer trust in the agri-food system. A multi-method approach was conducted for the organic authentication and safety assessment of pasta and bakery products along their production chain. Bulk and Compound-Specific (CS) Isotope Ratio Mass Spectrometry (IRMS) suggested the δ15Nbulk, δ15Nleucine and δ15Nproline as promising organic markers, with CS able to distinguish between pairs which bulk analysis could not. Processing significantly affected the values of δ15Nleucine, δ13Cproline and δ13Cleucine. Multi-mycotoxin analysis (HT-2, T-2, DON, ZEN, OTA, AFB1) revealed higher contamination in conventional than organic samples, while both milling and baking significantly reduced mycotoxin content. Lastly, from the evaluation of 400 residues, isopyrazam was present at the highest concentration (0.12 mg/kg) in conventional wheat, exhibiting a 0.12 Processing Factor (PF), while tebuconazole levels remained unchanged in pasta production (90 °C) and reduced below LOQ in biscuits and crackers (180-250 °C).

Authenticity assessment of ground black pepper by combining headspace gas-chromatography ion mobility spectrometry and machine learning.

Currently, the authentication of ground black pepper is a major concern, creating a need for a rapid, highly sensitive and specific detection tool to prevent the introduction of adulterated batches into the food chain. To this aim, head space gas-chromatography ion mobility spectrometry (HS-GC-IMS), combined with machine learning, is tested in this initial, proof-of-concept study. A broad variety of authentic samples originating from eight countries and three continents were collected and spiked with a range of adulterants, both endogenous sub-products and an assortment of exogenous materials. The method is characterized by no sample preparation and requires 20 min for chromatographic separation and ion mobility data acquisition. After an explorative analysis of the data, those were submitted to two different machine learning algorithms (partial least squared discriminant analysis-PLS-DA and support vector machine-SVM). While the PLS-DA model did not provide fully satisfactory performances, the combination of HS-GC-IMS and SVM successfully classified the samples as authentic, exogenously-adulterated or endogenously-adulterated with an overall accuracy of 90 % and 96 % on withheld test set 1 and withheld test set 2, respectively (at a 95 % confidence level). Some limitations, expected to be mitigated by further research, were encountered in the correct classification of endogenously adulterated ground black pepper. Correct categorization of the ground black pepper samples was not adversely affected by the operator or the time span of data collection (the method development and model challenge were carried out by two operators over 6 months of the study, using ground black pepper harvested between 2015 and 2019). Therefore, HS-GC-IMS, coupled to an intelligent tool, is proposed to: (i) aid in industrial decision-making before utilization of a new batch of ground black pepper in the production chain; (ii) reduce the use of time-consuming conventional analyses and; (iii) increase the number of ground black pepper samples analyzed within an industrial quality control frame.

Tailor-made fermentation of sourdough reduces the acrylamide content in rye crispbread and improves its sensory and nutritional characteristics.

Thirty strains of lactic acid bacteria (LAB) and Saccharomyces cerevisiae E8.9 (wild type) were used to formulate fifteen combinations of starters by mixing two or three LAB with the yeast (ratio LAB: yeast, 10: 1). Such combinations were used to prepare rye sourdough and their performance in term of acidification and biochemical characteristics during fermentation at two temperatures (30 and 37 °C) and duration (4 and 8 h) were screened. The best thirteen sourdough formulations were selected and used for rye crispbread making. The analysis of acrylamide concentration demonstrated that 11 out 13 formulations resulted in significant decreases of concentration compared to the baker's yeast (control), with reductions up to 79.6 %. The rye sourdough crispbreads showed also higher amount of volatile organic compounds (VOCs) compared to the baker's yeast control. Two rye sourdough crispbreads, selected to represent the opposite extremes within the thirteen formulations in term of VOC profiles and fermentation performances, demonstrated better sensory and nutritional features, such as phytic acid reduction (up to 47.3 %), and enhanced total free amino acid compared to the control. These evidences suggest the potential of tailored sourdough fermentations as alternative and suitable biotechnological strategy for lowering acrylamide levels in rye crispbread.

Untargeted metabolomics liquid chromatography-high resolution mass spectrometry approach for the geographical origin assessment of Italian dehydrated apples.

Geographical provenience is nowadays a relevant aspect of the authenticity and the quality of many food commodities. Dehydrated apple cubes/slices represent an ingredient commonly used by food companies for bakery products. However, this apple-based matrix is not so known and studied from an analytical point of view. In the present work, seven compounds were identified as key molecules to distinguish between Italian and non-Italian samples, through an untargeted ultrahigh-pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) approach. This methodology was merged with multivariate statistical analysis, and the principal features were studied and identified considering several identification steps. Samples from 2020 and 2021 harvesting campaigns, with partial and total dehydration rates, with or without peel, and from different apple varieties were considered for the study, for a total of 91 samples. Afterward, the same analysis protocol was applied to an external set (n = 12 samples), included in the statistical models, searching for the key compounds identified in the training set. Interesting and significant results underlined the potentiality of the UHPLC-HRMS technology as a confirmatory strategy for the geographical origin assessment of dehydrated apple commodities.

QuEChERS method combined to liquid chromatography high-resolution mass spectrometry for the accurate and sensitive simultaneous determination of pyrrolizidine and tropane alkaloids in cereals and spices.

Within the last decades, in the EU, there has been an increasing interest in toxic plant alkaloids as food contaminants, especially after the continuous and growing consumption of plant-based foods compared with food of animal origin. In this regard, the once neglected presence of these tropane alkaloids (TAs) and pyrrolizidine alkaloids (PAs) has recently been reconsidered by the European Food Safety Authority, highlighting the lack of data and the need to develop risk assessment strategies. For this reason, the emphasis has been placed on detecting their occurrence in food through the development of accurate and sensitive analytical methods to achieve the determination of these compounds. The present study aims to elaborate and validate an analytical method based on QuEChERS sample preparation approach, exploiting the UHPLC coupled to the HRMS to simultaneously identify and quantify 21 PAs and two TAs in cereals and spices. For TAs, the obtained limit of detection (LOD) is 0.1 µg·kg-1 and the limit of quantification (LOQ) is 0.4 µg·kg-1 , while for PAs, the LODs values ranging between 0.2 to 0.3 µg·kg-1 and the LOQ, between 0.4 and 0.8 µg·kg-1 , ensuring compliance with the recently established European Regulations. Several commercial samples were analysed to further verify the applicability of this comprehensive analytical approach.

Thermal desorption direct analysis in real-time high-resolution mass spectrometry and machine learning allow the rapid authentication of ground black pepper and dried oregano: A proof-of-concept study.

Thermal desorption direct analysis in real-time high-resolution mass spectrometry (TD-DART-HRMS) approaches have gained popularity for fast screening of a variety of samples. With rapid volatilization of the sample at increasing temperatures outside the mass spectrometer, this technique can provide a direct readout of the sample content with no sample preparation. In this study, TD-DART-HRMS's utility for establishing spice authenticity was examined. To this aim, we directly analyzed authentic (typical) and adulterated (atypical) samples of ground black pepper and dried oregano in positive and negative ion modes. We analyzed a set of authentic ground black pepper samples (n = 14) originating from Brazil, Sri Lanka, Madagascar, Ecuador, Vietnam, Costa Rica, Indonesia, Cambodia, and adulterated samples (n = 25) consisting of mixtures of ground black pepper with this spice's nonfunctional by-products (pinheads or spent) or with different exogenous materials (olive kernel, green lentils, black mustard seeds, red beans, gypsum plaster, garlic, papaya seeds, chili, green aniseed, or coriander seeds). TD-DART-HRMS facilitated the capture of informative fingerprinting of authentic dried oregano (n = 12) originating from Albania, Turkey, and Italy and those spiked (n = 12) with increasing percentages of olive leaves, sumac, strawberry tree leaves, myrtle, and rock rose. A predictive LASSO classifier was built, after merging by low-level data fusion, the positive and negative datasets for ground black pepper. Fusing multimodal data allowed retrieval of more comprehensive information from both datasets. The resultant classifier achieved on the withheld test set accuracy, sensitivity, and specificity of 100%, 75%, and 90%, respectively. On the contrary, the sole TD-(+)DART-HRMS spectra of the oregano samples allowed construction of a LASSO classifier that predicted the adulteration of the oregano with excellent statistical indicators. This classifier achieved, on the withheld test set, 100% each for accuracy, sensitivity, and specificity.

A geographical origin assessment of Italian hazelnuts: Gas chromatography-ion mobility spectrometry coupled with multivariate statistical analysis and data fusion approach.

Hazelnut is a commodity that has gained interest in the food science community concerning its authenticity. The quality of the Italian hazelnuts is guaranteed by Protected Designation of Origin and Protected Geographical Indication certificates. However, due to their modest availability and the high price, fraudulent producers/suppliers blend, or even substitute, Italian hazelnuts with others from different countries, having a lower price, and often a lower quality. To contrast or prevent these illegal activities, the present work investigated the application of the Gas Chromatography-Ion mobility spectrometry (GC-IMS) technique on the hazelnut chain (fresh, roasted, and paste of hazelnuts). The raw data obtained were handled and elaborated using two different ways, software for statistical analysis, and a programming language. In both cases, Principal Component Analysis and Partial Least Squares-Discriminant Analysis models were exploited, to study how the Volatile Organic Profiles of Italian, Turkish, Georgian, and Azerbaijani products differ. A prediction set was extrapolated from the training set, for a preliminary models' evaluation, then an external validation set, containing blended samples, was analysed. Both approaches highlighted an interesting class separation and good model parameters (accuracy, precision, sensitivity, specificity, F1-score). Moreover, a data fusion approach with a complementary methodology, sensory analysis, was achieved, to estimate the performance enhancement of the statistical models, considering more discriminant variables and integrating at the same time further information correlated to quality aspects. GC-IMS could be a key player as a rapid, direct, cost-effective strategy to face authenticity issues regarding the hazelnut chain.

Smartphone-based magneto-immunosensor on carbon black modified screen-printed electrodes for point-of-need detection of aflatoxin B1 in cereals.

Considering the complexities and speed of modern food chains, there is an increasing demand for point-of-need detection of food contaminants, particularly highly regulated chemicals and carcinogens such as aflatoxin B1. We report a user-friendly smartphone-based magneto-immunosensor on carbon black modified electrodes for point-of-need detection of aflatoxin B1 in cereals. For buffered analyte solutions and a corn extract sample, the assay demonstrated a low limit of detection of 13 and 24 pg/mL, respectively. The assay was also highly reproducible, exhibiting mean relative standard deviations of 3.7% and 4.0% for the buffered analyte and corn extract samples. The applicability of the assay was validated on the basis of EU guidelines and the detection capability was lower than or equal to 2 µg/kg, which is the EU maximum residue limit for aflatoxin B1 in cereals. False-positive and false-negative rates were less than 5%. Additionally, an open-source android application, AflaESense, was designed to provide a simple interface that displays the result in a traffic-light-type format, thus minimizing user training and time for data analysis. AflaESense was used for smartphone-based screening of spiked corn samples containing aflatoxin B1 (0.1, 2, and 10 ng/mL), and naturally contaminated corn containing 0.15 ng aflatoxin B1/mL. The measured values were in close agreement with spiked concentrations (r2 = 0.99), with recovery values ranging between 80 and 120%. Finally, contaminated samples correctly triggered a red alert while the non-contaminated samples led to the display of a green color of AflaESense. To the best of our knowledge, this is the first smartphone-based electrochemical system effective for screening samples for contamination with aflatoxin B1.

A DNA Metabarcoding Workflow to Identify Species in Spices and Herbs.

BACKGROUND: Spices and herbs are food categories regularly cited as highly susceptible to be adulterated. To detect potential adulteration with undeclared species, DNA-based methods are considered the most suitable tools. OBJECTIVE: In this study, the performance of the ready-to-use Thermo Scientific™ NGS Food Authenticity Workflow (Thermo Fisher Scientific)-a commercial DNA metabarcoding approach-is described. The tool was further applied to analyze 272 commercial samples of spices and herbs. METHOD: Pure samples of spices and herbs were analyzed with the Thermo Scientific NGS Food Authenticity Workflow to assess its specificity, and spikings down to 1% (w/w) allowed evaluation of its sensitivity. Commercial samples, 62 and 210, were collected in Asian and European markets, respectively. RESULTS: All tested species were correctly identified often down to the species level, while spikings at 1% (w/w) confirmed a limit of detection at this level, including in complex mixtures composed of five different spices and/or herbs. The analysis of 272 commercial samples showed that 78% were compliant with the declared content, whereas the rest were shown to contain undeclared species that were in a few cases allergenic or potentially toxic. CONCLUSIONS: The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable to identify food plant species in herbs and spices, not only when tested on pure samples, but also in mixtures down to 1% (w/w). The overall workflow is user-friendly and straightforward, which makes it simple to use and facilitates data interpretation. HIGHLIGHTS: The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable for species identification in herbs and spices, and it allowed the detection of undeclared species in commercial samples. Its ease of use facilitates its implementation in testing laboratories.

Non-targeted high-resolution mass spectrometry study for evaluation of milk freshness.

Milk freshness is an important parameter for both consumers' health and quality of milk-based products. Up to now there have been neither analytical methods nor specific parameters to uniquely define milk freshness from a complete and univocal chemical perspective. In this study, 8 molecules were selected and identified as responsible for milk aging, using a liquid chromatography-high-resolution mass spectrometry approach followed by chemometric data elaboration. For model setup and marker selection, 30 high-quality pasteurized fresh milk samples were collected directly from the production site and analyzed immediately and after storage at 2 to 8°C for 7 d. The markers were then validated by challenging the model with a set of 10 milk samples, not previously analyzed. Our results demonstrated that the markers identified within this study can be successfully used for the correct classification of non-fresh milk samples, complementing and successfully enhancing parallel evaluations obtainable through sensory measures.

The MyToolbox EU-China Partnership-Progress and Future Directions in Mycotoxin Research and Management.

Affordable and practical tools for farmers and food processors along the chain are required to efficiently reduce the risk of mycotoxin contamination of crops, feeds and foods. Developing new tools and enhancing existing ones was the mission of MyToolBox-a four-year EU-project that included important Chinese partners and joint research efforts. To identify future directions in mycotoxin research and management in China and their role in China-EU relations, a unique stakeholder workshop including group discussions was organized in Beijing. Six related topics: biocontrol, forecasting, sampling and analysis, silo management, detoxification, and the development of safe use options for contaminated materials were covered. The discussions clearly identified a critical need for smart, integrated strategies to address mycotoxin issues to attain safer food and feed, and to minimize losses and export rejections. Managing data on when, where and the size of mycotoxin contamination events and identifying the institution(s) to manage them are complex issues in China. Studies of microbes and novel, genetically-altered enzymes to limit pre-harvest contamination and to manage post-harvest product detoxification and alternate uses of contaminated materials are in the early stages in China. Further efforts are needed to increase the visibility of mycotoxin problems beyond the scientific and research communities.

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.

Practical approach to develop a multi-group screening method for detection of mycotoxins, pesticides and veterinary drugs in food.

A multi-group screening method to detect residues of veterinary drugs in meat and environmental contaminants in wheat flour has been developed using liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry (LC-HRMS). The procedure was tested for over 300 representative compounds (173 veterinary drugs, 122 pesticides and 9 mycotoxins) analysing in parallel negative and positive (spiked) samples according to European validation rules. The Screening Target Concentrations (STCs) were chosen conservatively with respect to the method purposes. Interpretation of results was based on retention time, mass accuracy of precursor and MS2 spectral library. Evaluating the percentage of false negative results, 280 out of the 304 analytes were detectable at the STCs (false compliant rate ≤ 5%). In wheat flours, incurred levels of mycotoxins, deoxynivalenol and 3-acetyldeoxynivalenol, higher than STCs, were frequently found, whereas in meat, the most detected veterinary drugs were antibiotics generally at negligible concentrations (<10 µg kg-1 ). Finally, seven test materials from proficiency test schemes were successfully tested.

Fate of Free and Modified Forms of Mycotoxins during Food Processing.

International trade is highly affected by mycotoxin contaminations, which result in an annual 5% to 10% loss of global crop production [...].

A non-targeted high-resolution mass spectrometry approach for the assessment of the geographical origin of durum wheat.

The assessment of durum wheat geographical origin is an important and emerging challenge, due to the added value that a claim of origin could provide to the raw material itself, and subsequently to the final products (i.e. pasta). Up to now, the typical approach presented in literature is the evaluation of different isotopic ratios of the elements, but other techniques could represent an interesting and even more powerful alternative. In this study, using a non-targeted high-resolution mass spectrometry approach, a selection of chemical markers related to the geographical origin of durum wheat was provided. Samples of the 2016 wheat campaign were used to set up the model and to select the markers, while samples from the 2018 campaign were used for model and markers validation. Including in the samples set different geographies across different continents, a discrimination through Italian, European and Not European samples is now possible.

Investigating the in vitro catabolic fate of Enniatin B in a human gastrointestinal and colonic model.

Enniatin B is an emerging mycotoxin known to present biological activity because of its ionophoric characteristics. This compound has demonstrated strong in vitro cytotoxicity against different cancer cells, also at low molecular concentrations. Its natural occurrence in food commodities and feed is highly reported world-wide, but few information is available about its stability in the human gastro-intestinal tract. The present work evaluates the catabolic fate of enniatin B upon in vitro simulated digestion and colonic fermentation. LC-MS target and untargeted analysis have been performed to quantify the extent of enniatin B degradation and the formation of catabolic products. The results obtained showed significant degradation of enniatin B (degradation rate 79 ± 5%) along the gastrointestinal tract and further degradation of residual enniatin B was observed during colonic fermentation after 24 h of incubation. Moreover, 5 catabolic metabolites of enniatin B were putatively identified after gastrointestinal digestion resulting from the oxidation and opening of the depsipeptide ring. As a final step, the pharmacokinetic properties of enniatin B degradation products were tested in silico revealing that some of them may be adsorbed at the gastrointestinal level more than the parent compound. Additionally, the smaller degradation products showed moderate blood-brain-barrier crossing.

Assessment of Enzymatic Improvers in Flours Using LC-MS/MS Detection of Marker Tryptic Peptides.

Enzymatic improvers are enzymes obtained from microbial or fungal cultures, added as technical adjuvants to flour, with the aim of improving the dough characteristics in bakery products. They are used in a low ppm range and, being technical adjuvants, can go undeclared on the label. Many types of enzymatic improvers are present on the market, such as amylases, lipases, proteases, xylanases, glucose oxidases, and others, each with a different function. Analytical methods capable of detecting these enzymes are needed, particularly for bakery companies, in order to monitor the quality of raw materials and to detect any undeclared presence. In the present work, specific peptide markers, obtained by enzymatic digestion, have been used to detect the presence of enzymatic improvers by LC-MS/MS techniques. Promising results were obtained for some enzymes acting on the carbohydrate fraction (glucoamylase, glucose oxidase, xylanase) in which amounts as low as 20 ppm could be identified in blind flour samples. For lipases and proteases the method proved to be very effective in terms of specific identification, even if less sensitive.

Thinking Out of the Box: On the Ability of Zea mays L. to Biotrasform Aflatoxin B1 Into Its Modified Forms.

While aflatoxin metabolism in animals has been clarified, very limited information is so far available on the possible biotransformation occurring in plants. Therefore, this work aimed at investigating whether AFB1 metabolites could occur in field-grown infected maize and the putative role of Zea mays L. metabolism in their production. For such scope, asymptomatic in vitro-grown plantlets and in silico evaluations of plant transforming enzymes were used to pinpoint how plants may handle these compounds. Our data demonstrated the role of maize plants in the production of Phase I hydroxylated aflatoxins, including, among others, AFM1, AFM2, and aflatoxicol, and suggest that plant cytochromes may be involved in this biotransformation of AFB1.

Novel analytical methods to study the fate of mycotoxins during thermal food processing.

Food processing can lead to a reduction of contaminants, such as mycotoxins. However, for food processing operations where thermal energy is employed, it is often not clear whether a reduction of mycotoxins also results in a mitigation of the toxicological impact. This is often due to the reason that the formed degradation products are not characterized and data on their toxicity is scarce. From the perspective of an analytical chemist, the elucidation of the fate of a contaminant in a complex food matrix is extremely challenging. An overview of the analytical approaches is given here, and the application and limitations are exemplified based on cases that can be found in recent literature. As most studies rely on targeted analysis, it is not clear whether the predetermined set of compounds differs from the degradation products that are actually formed during food processing. Although untargeted analysis allows for the elucidation of the complete spectrum of degradation products, only one such study is available so far. Further pitfalls include insufficient precision, natural contamination with masked forms of mycotoxins and interferences that are caused by the food matrix. One topic that is of paramount importance for both targeted and untargeted approaches is the availability of reference standards to identity and quantity the formed degradation products. Our vision is that more studies need to be published that characterize the formed degradation products, collect data on their toxicity and thereby complete the knowledge about the mycotoxin mitigating effect during food processing.