Development of stable and sensitive strip biosensors for the rapid detection of organophosphates and aflatoxin B1 in agricultural samples

In this study, we present a facile and efficient method for fabricating silk fibroin hydrogel films encapsulating the acetylcholinesterase enzyme (AChE) and pH test strips (biosensor strips) for detecting organophosphorus pesticides (OPs) and aflatoxin B1 (AFB1). These biosensor strips possess several unique properties: flexibility, time efficiency, and high stability. Upon exposure to OPs or AFB1, AChE activity is inhibited, leading to a discernible color change on the pH test strip, enabling rapid and sensitive visual detection of these contaminants. The strips were effectively utilized as a practical and sensitive platform for the visual detection of OPs and AFB1. The limits of detection for paraoxon, aldicarb, and AFB1 were determined to be 6.57, 8.92, and 0.274 ng mL-1, respectively. Furthermore, the applicability of these biosensors for detecting OPs or AFB1 in real samples of Chinese cabbage and peanuts was successfully demonstrated. Additionally, the performance of these novel strip composites was validated through comparison with commercial pesticide rapid test papers. Notably, the encapsulated AChE enzymes retained significant sensitivity for over 18 months, even when stored at 37 °C, and the biosensor strips exhibited remarkable resistance to sensitivity loss caused by inhibitors. This work presents a highly sensitive and stable enzyme-based visual detection paper for agricultural and food safety applications. In addition to its outstanding resistance to interference, the developed biosensor ensures reliable reproducibility and maintains stability over long-term use. This new approach to OP analysis in ecological samples has also been effectively used in the determination of OPs in lake water.

Integrating different detection techniques and data analysis methods for comprehensive food authenticity verification

Traditional food testing methods, primarily confined to laboratory settings, are increasingly inadequate to detect covert food adulteration techniques. Hence, a crucial review of recent technological strides to combat food fraud is essential. This comprehensive analysis explores state-of-the-art technologies in food analysis, accentuating the pivotal role of sophisticated data processing methods and the amalgamation of diverse technologies in enhancing food authenticity testing. The paper assesses the merits and drawbacks of distinct data processing techniques and explores their potential synergies. The future of food authentication hinges on the integration of portable smart detection devices with mobile applications for real-time food analysis, including miniaturized spectrometers and portable sensors. This integration, coupled with advanced machine learning and deep learning for robust model construction, promises to achieve real-time, on-site food detection. Moreover, effective data processing, encompassing preprocessing, chemometrics, and regression analysis, remains indispensable for precise food authentication.

Simultaneous detection of mixed colorants adulterated in black tea based on various morphological SERS sensors

Colorant adulteration is a common problem in tea safety control; thus, a rapid identification method is required. In this study, we optimized the fabrication parameters of various sensors to enhance their performance. R6G was used as a probe molecule, demonstrating that the sensnor remained stable for 120 days. Based on surface-enhanced Raman spectroscopy, the optimized sensors were used to identify and quantify mixed colorants (sunset yellow, lemon yellow, carmine, and erythrosine). Partial least squares prediction models were developed for each colorant (0.5-300 μg/mL), with R2 > 0.900 and RPD > 2.27; these indicated the accuracy of the sensors. The results also revealed a model recovery range of 95.9 % to 116 %, with RSD < 3.94 %, indicating the universality of our proposed method. Overall, the proposed method enables the detection of mixed-colorant adulteration in black tea within 3 min, thereby representing a novel method for the assessment of tea quality.

Retention time-independent strategy for screening pesticide residues in herbs based on a fingerprint database and all ion fragmentation acquisition with LC-QTOF MS

A retention time (RT)-independent strategy for nontargeted screening of pesticide residues in herbs was exploited using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF MS). The core of this strategy is a fingerprint database coupled with a data-independent acquisition (DIA) scan mode of all ion fragmentation (AIF). In the fingerprint database, a total of 150 pesticides with quasimolecular ions and fragment ions at five-level collision energies were collected as qualified ions for screening. During the data acquisition, the AIF scan was performed via real unbiased full-spectrum MS/MS acquisition. Six herb matrices spiked with 30 banned pesticides were used to evaluate the applicability of the strategy in real samples. The use of the narrow ion mass extraction window (10 mDa) and the narrow RT window (0.1 min) enabled the effective extraction of spectra from noisy backgrounds and the discovery of suspected pesticides via similarity matching of filtered qualified ions. On average, more than 11/30 of pesticides at 1 ng mL-1 and more than 23/30 of pesticides at 10 ng mL-1 or lower could be screened out in each matrix using at least two qualified ions. In addition, the AIF mode exhibited superior anti-interference capability compared to data-dependent acquisition (DDA) and sequential window acquisition of all theoretical mass spectra (SWATH), as determined by comparing the limits of screening (LOSs) of 30 banned pesticides spiked into Isatidis Folium. Finally, the developed strategy was applied to screen pesticide residues in extracts of Ganoderma and Foeniculi Fructus. Phorate-sulfone and phorate-sulfoxide were found in Ganoderma, as well as terbufos-sulfone and terbufos-sulfoxide were found in Foeniculi Fructus. In conclusion, the developed RT-independent strategy based on a fingerprint database and AIF acquisition with LC-QTOF MS seems to be one of the most efficient tools for the analysis of nontargeted pesticide residues in complicated matrices.

Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging

This study investigated and comprehensively compared the performance of spectra (950-1660 nm) acquired respectively from NIR and HSI in the rapid and non-destructive quantification of azodicarbonamide (ADA) content (0-100 mg/kg) in WF and simultaneously identified WF containing excessive ADA (>45 mg/kg). The raw spectra were preprocessed using 14 methods and then mined by the partial least squares (PLS) algorithm to fit ADA levels using different numbers of WF samples for training and validation in five datasets (NTraining/Validation = 189/21, 168/42, 147/63, 126/84, 105/105), yielding better abilities of NIR Savitzky-Golay 1st derivative (SG1D) spectra-based PLS models and raw HSI spectra-based PLS models in quantifying ADA with higher determination coefficients and lower root-mean-square errors in validation (R2V & RMSEV), as well as establishing 100% accuracy in PLS discriminant analysis (PLS-DA) models for identifying excessive ADA-contained WF in each dataset. Twenty-four wavelengths selected from a NIR SG1D spectra in a 168/42 dataset and 23 from a raw HSI spectra in a 147/63 dataset allowed for the better performance of quantitative models in ADA determination with higher R2V and RMSEV in validation (R2V > 0.98, RMSEV < 3.87 mg/kg) and for discriminant models in WF classification with 100% accuracy. In summary, NIR technology may be sufficient if visualization is not required.

Multi-pesticide residue screening, identification, and quantification analysis in various fruits and vegetables by UHPLC-Q Exactive HRMS

A general strategy for qualitative screening and quantitative analysis of 403 pesticides in various fruits and vegetables was developed using ultrahigh-performance liquid chromatography (UHPLC) in conjunction with a Thermo Q Exactive Focus high-resolution mass spectrometer, relying on an executable compound database comprised of the exacted mass of precursor ions, retention times, and fragment ions. Taking advantage of the powerful separation capacity of UHPLC, an Orbitrap analyzer with high sensitivity in full scan mode and elevated mass resolution of product ions in the MS/MS mode, eight pairs of isomers and fifty-seven groups of isobaric compounds were selectively identified. The method was then systematically assessed and validated for eight fruits and vegetables, in terms of screening detection limit (SDL), matrix effects, recovery, and precision over 400 pesticides. The results showed that the SDLs of 68.0-84.4% for the pesticides were less than or equal to 10 μg kg-1 in the representative matrices, recoveries in the range of 60-120% accounting for 48.6-84.4% of all the targets at three lower fortified levels of 5, 20, and 50 μg kg-1 with a precision of less than 20% while the range of overall average recoveries for the majority of the pesticides were from 82.4% to 105.1% in the as-selected matrices with RSDs between 3.9% and 7.7%. Using this method, screening data from a survey of pesticide residues in 68 practical samples across 32 different matrix types provides scientific data for the inspection and supervision of pesticide residue safety of fruits and vegetables.

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Direct infusion-multiple reaction monitoring cubed (DI-MRM3) enables widely targeted bi-omics of Colla Corii Asini (Chinese name: Ejiao)

Food authenticity is extremely important and widely targeted bi-omics is a promising pipeline attributing to incorporating metabolomics and peptidomics. Colla Corii Asini (CCA, Ejiao) is one of the most popular tonic edible materials, with counterfeit and adulterated products being widespread. An attempt was devoted to develop a high-throughput and reliable DI-MRM3 program facilitating widely targeted bi-omics of CCA. Firstly, predictive MRM program captured metabolites and peptides in trypsin-digestive gelatins. After data alignment and structure annotation, primary parameters such as Q1 → Q3 → QLIT, CE, and EE were optimized for all 17 metabolites and 34 peptides by online ER-MS. Though a single run merely consumed 6.5 min, great selectivity was reached for each analyte. Statistical results showed that nine peptides contributed to distinguish CCA from other gelatins. After cross-validation with LC-MRM, DI-MRM3 was justified to be reproducible and high-throughput for widely targeted bi-omics of CCA, suggesting a meaningful tool for food authenticity.

Advances, challenges, and opportunities for food safety analysis in the isothermal nucleic acid amplification/CRISPR-Cas12a era

Global food safety stands out as a prominent public concern, affecting populations worldwide. The recurrent challenge of food safety incidents reveals the need for a robust inspection framework. In recent years, the integration of isothermal nucleic acid amplification with CRISPR-Cas12a techniques has emerged as a promising tool for molecular detection of food hazards, presenting next generation of biosensing for food safety detection. This paper provides a comprehensive review of the current state of research on the synergistic application of isothermal nucleic acid amplification and CRISPR-Cas12a technology in the field of food safety. This innovative combination not only enriches the analytical tools, but also improving assay performance such as sensitivity and specificity, addressing the limitations of traditional methods. The review summarized various detection methodologies by the integration of isothermal nucleic acid amplification and CRISPR-Cas12a technology for diverse food safety concerns, including pathogenic bacterium, viruses, mycotoxins, food adulteration, and genetically modified foods. Each section elucidates the specific strategies employed and highlights the advantages conferred. Furthermore, the paper discussed the challenges faced by this technology in the context of food safety, offering insightful discussions on potential solutions and future prospects.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Nanomaterials based sensors for analysis of food safety

The freshnessof the food is a major issue because spoiled food lacks critical nutrients for growth and could be harmful to human health if consumed directly. Nanomaterials are captivating due to their unique properties like large surface area, high selectivity, small dimension, great biocompatibility and conductivity, real-time onsite analysis, etc. which give them an advantage over conventional evaluation techniques. Despite these advantages of nanomaterials used in food safety and their preservation, food products can still get affected by various environmental factors (like pH, temperature, etc.), making the use of time-temperature indicators more condescending. This review is a comprehensive study on food safety, its causes, the responsible analytes, their remedies by various nanomaterials, the development of various nanosensors, and the various challenges faced in maintaining food safety standards to reduce the risk of contaminants.

MSdeCIpher: A Tool to Link Data from Complementary Ionization Techniques in High-Resolution GC-MS to Identify Molecular Ions

Electron ionization (EI) and molecular ion-generating techniques like chemical ionization (CI) are complementary ionization methods in gas chromatography (GC)-mass spectrometry (MS). However, manual curation effort and expert knowledge are required to correctly assign molecular ions to fragment spectra. MSdeCIpher is a software tool that enables the combination of two separate datasets from fragment-rich spectra, like EI-spectra, and soft ionization spectra containing molecular ion candidates. Using high-resolution GC-MS data, it identifies and assigns molecular ions based on retention time matching, user-defined adduct/neutral loss criteria, and sum formula matching. To our knowledge, no other freely available or vendor tool is currently capable of combining fragment-rich and soft ionization datasets in this manner. The tool's performance was evaluated on three test datasets. When molecular ions are present, MSdeCIpher consistently ranks the correct molecular ion for each fragment spectrum in one of the top positions, with average ranks of 1.5, 1, and 1.2 in the three datasets, respectively. MSdeCIpher effectively reduces candidate molecular ions for each fragment spectrum and thus enables the usage of compound identification tools that require molecular masses as input. It paves the way towards rapid annotations in untargeted analysis with high-resolution GC-MS.

Recent Advances in Design and Application of Nanomaterials-Based Colorimetric Biosensors for Agri-food Safety Analysis

A colorimetric sensor detects an analyte by utilizing the optical properties of the sensor unit, such as absorption or reflection, to generate a structural color that serves as the output signal to detect an analyte. Detecting the refractive index of an analyte by recording the color change of the sensor structure on its surface has several advantages, including simple operation, low cost, suitability for onsite analysis, and real-time detection. Colorimetric sensors have drawn much attention owing to their rapidity, simplicity, high sensitivity and selectivity. This Review discusses the use of colorimetric sensors in the food industry, including their applications for detecting food contaminants. The Review also provides insight into the scope of future research in this area.

Advancing food safety risk assessment in China: development of new approach methodologies (NAMs)

Novel techniques and methodologies are being developed to advance food safety risk assessment into the next-generation. Considering the shortcomings of traditional animal testing, new approach methodologies (NAMs) will be the main tools for the next-generation risk assessment (NGRA), using non-animal methodologies such as in vitro and in silico approaches. The United States Environmental Protection Agency and the European Food Safety Authority have established work plans to encourage the development and application of NAMs in NGRA. Currently, NAMs are more commonly used in research than in regulatory risk assessment. China is also developing NAMs for NGRA but without a comprehensive review of the current work. This review summarizes major NAM-related research articles from China and highlights the China National Center for Food Safety Risk Assessment (CFSA) as the primary institution leading the implementation of NAMs in NGRA in China. The projects of CFSA on NAMs such as the Food Toxicology Program and the strategies for implementing NAMs in NGRA are outlined. Key issues and recommendations, such as discipline development and team building, are also presented to promote NAMs development in China and worldwide.

Recent Advances in Personal Glucose Meter-Based Biosensors for Food Safety Hazard Detection

Food safety has emerged as a significant concern for global public health and sustainable development. The development of analytical tools capable of rapidly, conveniently, and sensitively detecting food safety hazards is imperative. Over the past few decades, personal glucose meters (PGMs), characterized by their rapid response, low cost, and high degree of commercialization, have served as portable signal output devices extensively utilized in the construction of biosensors. This paper provides a comprehensive overview of the mechanism underlying the construction of PGM-based biosensors, which consists of three fundamental components: recognition, signal transduction, and signal output. It also detailedly enumerates available recognition and signal transduction elements, and their modes of integration. Then, a multitude of instances is examined to present the latest advancements in the application of PGMs in food safety detection, including targets such as pathogenic bacteria, mycotoxins, agricultural and veterinary drug residues, heavy metal ions, and illegal additives. Finally, the challenges and prospects of PGM-based biosensors are highlighted, aiming to offer valuable references for the iterative refinement of detection techniques and provide a comprehensive framework and inspiration for further investigations.

Application and prospect of metabolomics-related technologies in food inspection

BACKGROUND

Food inspection covers a broad range of topics, including nutrient analysis, food pollutants, food auxiliary materials, additives, and food sensory identification. The foundation of diverse subjects like food science, nutrition, health research, and the food industry, as well as the desired reference for drafting trade and food legislation, makes food inspection highly significant. Because of their high efficiency, sensitivity, and accuracy, instrumental analysis methods have gradually replaced conventional analytical methods as the primary means of food hygiene inspection.

SCOPE AND APPROACH

Metabolomics-based analysis technology, such as nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), has become a widely used analytics platform. This research provides a bird's eye view of the application and future of metabolomics-related technologies in food inspection.

KEY FINDINGS AND CONCLUSIONS

We have provided a summary of the features and the application range of various metabolomics techniques, the strengths and weaknesses of different metabolomics platforms, and their implementation in specific inspection procedures. These procedures encompass the identification of endogenous metabolites, the detection of exogenous toxins and food additives, analysis of metabolite alterations during processing and storage, as well as the recognition of food adulteration. Despite the widespread utilization and significant contributions of metabolomics-based food inspection technologies, numerous challenges persist as the food industry advances and technology continues to improve. Thus, we anticipate addressing these potential issues in the future.

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.

Untargeted Metabolomics to Characterize the Urinary Chemical Landscape of E-Cigarette Users

The health and safety of using e-cigarette products (vaping) have been challenging to assess and further regulate due to their complexity. Inhaled e-cigarette aerosols contain chemicals with under-recognized toxicological profiles, which could influence endogenous processes once inhaled. We urgently need more understanding on the metabolic effects of e-cigarette exposure and how they compare to combustible cigarettes. To date, the metabolic landscape of inhaled e-cigarette aerosols, including chemicals originated from vaping and perturbed endogenous metabolites in vapers, is poorly characterized. To better understand the metabolic landscape and potential health consequences of vaping, we applied liquid chromatography-mass spectrometry (LC-MS) based nontargeted metabolomics to analyze compounds in the urine of vapers, cigarette smokers, and nonusers. Urine from vapers (n = 34), smokers (n = 38), and nonusers (n = 45) was collected for verified LC-HRMS nontargeted chemical analysis. The altered features (839, 396, and 426 when compared smoker and control, vaper and control, and smoker and vaper, respectively) among exposure groups were deciphered for their structural identities, chemical similarities, and biochemical relationships. Chemicals originating from e-cigarettes and altered endogenous metabolites were characterized. There were similar levels of nicotine biomarkers of exposure among vapers and smokers. Vapers had higher urinary levels of diethyl phthalate and flavoring agents (e.g., delta-decalactone). The metabolic profiles featured clusters of acylcarnitines and fatty acid derivatives. More consistent trends of elevated acylcarnitines and acylglycines in vapers were observed, which may suggest higher lipid peroxidation. Our approach in monitoring shifts of the urinary chemical landscape captured distinctive alterations resulting from vaping. Our results suggest similar nicotine metabolites in vapers and cigarette smokers. Acylcarnitines are biomarkers of inflammatory status and fatty acid oxidation, which were dysregulated in vapers. With higher lipid peroxidation, radical-forming flavoring, and higher level of specific nitrosamine, we observed a trend of elevated cancer-related biomarkers in vapers as well. Together, these data present a comprehensive profiling of urinary biochemicals that were dysregulated due to vaping.

Easily operated COF-based monolithic sponges as matrix clean-up materials for non-targeted analysis of chemical hazards in oil-rich foods

Non-targeted analysis of chemical hazards in foods plays a crucial role in controlling food safety. However, because it brings forward high demand for sample pretreatment, materials suitable for the pretreatment of foods, especially animal foods, are rare. Herein, covalent organic frameworks (COF)-based monolithic materials were constructed by three successive steps: preparation of polydimethylsiloxane (PDMS) sponge using sugar cube as a sacrificial template, loading of a heteroporous COF on PDMS sponge via ultrasonic or in-situ growth method, coating of the obtained PDMS@COF by polydopamine (PDA) network. As-prepared PDMS@COF@PDA sponges were demonstrated to work well in sample pretreatment of animal foods for non-targeted analysis of chemical hazards. After a simple vortex treatment for about 2 min, more than 98% triglycerides, the main interfering matrix components in animal foods, could be removed from lard and pork samples, accompanied by "full recovery" (recovery efficiencies: ≥63%) of 44 chemical hazards with different physicochemical properties. Besides providing promising sample pretreatment materials for non-targeted food safety analysis, this work also paves a feasible way to improve COF-based monolithic materials and thus promote their practical applications, because we found that the introduction of PDA network on COF-based monolithic material surface could play a role in "killing three birds with one stone": enhancing the stability of the materials by overcoming the detachment of COF during operations; controllably adjusting hydrophobic and hydrogen-bonding interactions on the material surface to promote the removal of triglycerides; weakening the hydrophobic and π-π interactions between COF and chemical hazards to increase the recoveries of chemical hazards.

Glutathione-Capped CdTe Quantum Dots Based Sensors for Detection of H2O2 and Enrofloxacin in Foods Samples

Additives and antibiotic abuse during food production and processing are among the key factors affecting food safety. The efficient and rapid detection of hazardous substances in food is of crucial relevance to ensure food safety. In this study, a water-soluble quantum dot with glutathione as a ligand was synthesized as a fluorescent probe by hydrothermal method to achieve the detection and analysis of H₂O₂. The detection limits were 0.61 μM in water and 68 μM in milk. Meanwhile, it was used as a fluorescent donor probe and manganese dioxide nanosheets were used as a fluorescent acceptor probe in combination with an immunoassay platform to achieve the rapid detection and analysis of enrofloxacin (ENR) in a variety of foods with detection limits of 0.05-0.25 ng/mL in foods. The proposed systems provided new ideas for the construction of fluorescence sensors with high sensitivity.

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.

Tetrodotoxin and Its Analogues in Food: Recent Updates on Sample Preparation and Analytical Methods Since 2012

Tetrodotoxin (TTX), found in various organisms including pufferfish, is an extremely potent marine toxin responsible for numerous food poisoning accidents. Due to its serious toxicity and public health threat, detecting TTX and its analogues in diverse food matrices with a simple, fast, efficient method has become a worldwide concern. This review summarizes the advances in sample preparation and analytical methods for the determination of TTX and its analogues, focusing on the latest development over the past five years. Current state-of-the-art technologies, such as solid-phase microextraction, online technology, novel injection technology, two-dimensional liquid chromatography, high-resolution mass spectrometry, newly developed lateral flow immunochromatographic strips, immunosensors, dual-mode aptasensors, and nanomaterials-based approaches, are thoroughly discussed. The advantages and limitations of different techniques, critical comments, and future perspectives are also proposed. This review is expected to provide rewarding insights to the future development and broad application of pretreatment and detection methods for TTX and its analogues.

Unsymmetrical dimethylhydrazine and related compounds in the environment: Recent updates on pretreatment, analysis, and removal techniques

Unsymmetrical dimethylhydrazine (1,1-Dimethylhydrazine, UDMH) has been widely used as aerospace fuel in many countries. The launch of space vehicles can cause the release and leakage of UDMH into the environment, posing serious threats to ecology system and human population. Even worse, the health risks are also pertinent to its numerous classes of transformation products including N-Nitrosodimethylamine (NDMA), because most of them display carcinogenic and mutagenic properties. Recently, there has been an intense ongoing development of simple, fast, green, and effective techniques for determining and removing these hazardous substances. This review summarizes the latest research progress regarding the sources, fates, pretreatment, analysis, and removal techniques of UDMH and related products in the environment. Sample preparation methods mainly include pressurized liquid extraction, liquid-phase microextraction techniques, solid-phase extraction, headspace-solid-phase microextraction, and supercritical fluid extraction. Detection and identification methods mainly include high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS), gas chromatography coupled with tandem mass spectrometry (GC-MS/MS), and sensors. Removal methods mainly include advanced oxidation processes, adsorption, biodegradation techniques. The advantages/disadvantages, applications, and trends of the proposed approaches are thoroughly discussed to provide a valuable reference for further studies.

Background ions into exclusion list: A new strategy to enhance the efficiency of DDA data collection for high-throughput screening of chemical contaminations in food

Foods contaminated with hazardous compounds, could pose potential risks for human health. To date, there is still a big challenge in accurate identification. In this study, a novel data-dependent acquisition (DDA) approach, based on a combination of inclusion list and exclusion list, was proposed to acquire more effective MS/MS spectra. This strategy was successfully applied in a large-scale screening survey to detect 50 mycotoxins in oats, 155 veterinary drugs in dairy milk, and 200 pesticides in tomatoes. Compared with traditional acquisition modes, this new strategy has higher detection rate, particularly at ultra-low concentration by eliminating background influence, thereby generating the MS/MS spectra for more potential hazardous materials instead of matrix interference. Additionally, the obtained MS/MS spectra are simpler and more likely to be traced back than DIA. Moreover, this new strategy would be more comprehensively applied in food safety monitoring with the improvement of HRMS and post-acquisition techniques.

Nontargeted screening method for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry

Nontargeted screening of both veterinary drugs and their metabolites is important for comprehensive safety evaluation of animal-derived foods. In this study, a novel nontargeted screening strategy was developed for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry. First, an in-house database of mass spectra including 3,710 veterinary drugs and their metabolites was constructed. Second, fragmentation characteristics of parent drugs and their metabolites in mass spectrometry were investigated and summarized. Then, a nontargeted screening procedure was established based on fragmentation characteristics to screen unknown parent drugs and their metabolites. Finally, the strategy was applied to 33 egg samples, and four veterinary drugs and three drug metabolites were determined and identified. These results showed that the developed strategy can realize suspect and nontargeted screening of veterinary drugs and their metabolites, and can also be applied to other animal-derived foods.

Controllable synthesis of uniform large-sized spherical covalent organic frameworks for facile sample pretreatment and as naked-eye indicator

The successful application of covalent organic frameworks (COFs) depends on not only their unique chemical structures but also their morphology, size, and architecture. Spherical COFs (SCOFs) are attracted special attention due to the superiority of spherical materials in many applications. However, the synthesis of uniform large-sized SCOFs remains a challenge. Herein, by carefully optimizing the synthesis of a heteropore COF, we find that solvent type and catalyst concentration play important roles in determining the morphology and size of COFs, and eventually achieve the controllable synthesis of large SCOFs with uniform sizes ranging from 200 μm to 5 mm. The obtained SCOFs keep the dual-pore feature of the heteropore COF and show good stability and high crystallinity. To exhibit the superior application potential of SCOFs, the SCOFs with a size range of 200-300 μm were demonstrated to be promising solid-phase extraction (SPE) fillers. As-prepared SCOFs-packed SPE column could effectively remove ≥99% phytochrome matrix from 6 different vegetable samples in 10 s, accompanied by 72.56-112.37% recoveries of 33 chemical hazards with different physicochemical properties, thus showing greatly promising application prospects in sample pretreatment of nontargeted food safety analysis. By utilizing acid/base-adjusted reversible color change, millimeter-sized SCOFs were developed as an easy-to-operate and reusable naked-eye indicator of acids.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers

Mass spectrometry (MS) is one of the most widely used analytical techniques in many fields. Recent developments in chemical and biological researches have drawn much attention to the measurement of substances with low abundances in samples. Continuous efforts have been made consequently to further improve the sensitivity of MS. Modifications on the mass analyzers of mass spectrometers offer a direct, universal and practical way to obtain higher sensitivity. This review provides a comprehensive overview of the latest developments in mass analyzers for the improvement of mass spectrometers' sensitivity, including quadrupole, ion trap, time-of-flight (TOF) and Fourier transform ion cyclotron (FT-ICR), as well as different combinations of these mass analyzers. The advantages and limitations of different mass analyzers and their combinations are compared and discussed. This review provides guidance to the selection of suitable mass spectrometers in chemical and biological analytical applications. It is also beneficial to the development of novel mass spectrometers.

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.

Functional Hybrid Micro/Nanoentities Promote Agro-Food Safety Inspection

The rapid development of nanomaterials has provided a good theoretical basis and technical support to solve the problems of food safety inspection. The combination of functionalized composite nanomaterials and well-known detection methods is gradually applied to detect hazardous substances, such as chemical residues and toxins, in agricultural food products. This review concentrates on the latest agro-food safety inspection techniques and methodologies constructed with the assistance of new hybrid micro/nanoentities, such as molecular imprinting polymers integrated with quantum dots (MIPs@QDs), molecular imprinting polymers integrated with upconversion luminescent nanoparticles (MIPs@UCNPs), upconversion luminescent nanoparticles combined with metal-organic frameworks (UCNPs@MOFs), magnetic metal-organic frameworks (MOFs@Fe₃O₄), magnetic covalent-organic frameworks (Fe₃O₄@COFs), covalent-organic frameworks doped with quantum dots (COFs@QDs), nanobody-involved immunoassay for fast inspection, etc. The presented summary and discussion favor a relevant outlook for further integrating various disciplines, like material science, nanotechnology, and analytical methodology, for addressing new challenges that emerge in agro-food research fields.

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.

What's in this drink? Classification and adulterant detection in Irish Whiskey samples using near infrared spectroscopy combined with chemometrics

BACKGROUND

Near-infrared (NIR) spectroscopy coupled with principal component analysis (PCA) and partial least squares (PLS) regression was used to analyse a series of different Irish Whiskey samples in order to define their spectral profile and to assess the capability of the NIR method to identify samples based on their origin and storage (e.g. distiller, method of maturation). The ability of NIR spectroscopy to quantify the level of potential chemical adulterants was also investigated. Samples were spiked with 0.1%, 0.5%, 1.0%, 1.5% and 2.0% v/v of each adulterant (e.g. methanol, ethyl acetate, etc.) prior to NIR analysis.

RESULTS

The results of this study demonstrated the capability of NIR spectroscopy combined with PLS regression to classify the whiskey samples and to determine the level of adulteration. Moreover, the potential of NIR coupled with chemometric analysis as a rapid, portable, and non-destructive screening tool for quality control, traceability, and food/beverage adulteration for customs and other regulatory agencies, to mitigate beverage fraud was illustrated.

CONCLUSION

Given the non-specificity of the NIR technique, these positive preliminary results indicated that this method of analysis has the potential to be applied to identify the level of adulteration in distilled spirits. The rapid nature of the technique and lack of consumables or sample preparation required allows for a far more time and cost-effective analysis per sample. © 2021 Society of Chemical Industry.

Polyphenol Exposure, Metabolism, and Analysis: A Global Exposomics Perspective

Polyphenols are generally known for their health benefits and estimating actual exposure levels in health-related studies can be improved by human biomonitoring. Here, the application of newly available exposomic and metabolomic technology, notably high-resolution mass spectrometry, in the context of polyphenols and their biotransformation products, is reviewed. Comprehensive workflows for investigating these important bioactives in biological fluids or microbiome-related experiments are scarce. Consequently, this new era of nontargeted analysis and omic-scale exposure assessment offers a unique chance for better assessing exposure to, as well as metabolism of, polyphenols. In clinical and nutritional trials, polyphenols can be investigated simultaneously with the plethora of other chemicals to which we are exposed, i.e., the exposome, which may interact abundantly and modulate bioactivity. This research direction aims at ultimately eluting into atrue systems biology/toxicology evaluation of health effects associated with polyphenol exposure, especially during early life, to unravel their potential for preventing chronic diseases.

An overview of chemical contaminants and other undesirable chemicals in alcoholic beverages and strategies for analysis

The presence of chemical contaminant in alcoholic beverages is a widespread and notable problem with potential implications for human health. With the complexity and wide variation in the raw materials, production processes, and contact materials involved, there are a multitude of opportunities for a diverse host of undesirable compounds to make their way into the final product-some of which may currently remain unidentified and undetected. This review provides an overview of the notable contaminants (including pesticides, environmental contaminants, mycotoxins, process-induced contaminants, residues of food contact material [FCM], and illegal additives) that have been detected in alcoholic products thus far based on prior reviews and findings in the literature, and will additionally consider the potential sources for contamination, and finally discuss and identify gaps in current analytical strategies. The findings of this review highlight a need for further investigation into unwanted substances in alcoholic beverages, particularly concerning chemical migrants from FCMs, as well as a need for comprehensive nontargeted analytical techniques capable of determining unanticipated contaminants.

Strategies for data reduction in non-targeted screening analysis: The impact of sample variability for food safety applications

While analytical methods targeting specific compounds are critical for food safety, analytes excluded from the targeted list will not be identified. Non-targeted analyses (NTA) using LC/HR-MS complement these approaches by producing information-rich data sets where molecular formula can be generated for each detected compound; however, data mining can be labor intensive. Thus, we examined different NTA approaches to reduce the number of compounds needing further investigation, without relying on a suspect list or MS/MS database, both in single ingredient foods (i.e., oats) and more complex, oat-containing samples. We investigated inherent sample variability and utilized this information to build in-house databases for removing food compounds from sample data. While food databases were useful for data reduction, differential analysis was the most promising approach for single ingredient foods because it substantially reduced the number of features while retaining spiked QC compounds; however, a combination of approaches was necessary with greater sample complexity.

A new PARAFAC-based algorithm for HPLC-MS data treatment: herbal extracts identification

INTRODUCTION

Role of highly informative high-performance liquid chromatography mass spectrometry (HPLC-MS) methods in quality control is increasing. Complex herbal products and formulations can simultaneously contain extracts from different plants. Therefore, due to the leads to lack of commercial standards it is important to develop novel approaches for comprehensive treatment of big datasets.

OBJECTIVE

The aim of this study is to create a straightforward and information-saving algorithm for the identification of plants extracts in commercial products.

MATERIAL AND METHODS

In total, 34 samples, including Glycyrrhiza glabra and Panax ginseng dried roots; and Abrus precatorius dried leaves, their double and triple mixtures and flavoured oolong tea samples were analysed by HPLC-MS and combined in a three-dimensional dataset (retention time-mass-to-charge ratio (m/z)-samples). This dataset was subjected to smoothing and denoising techniques and further decomposed using parallel factor analysis (PARAFAC).

RESULTS

Samples were divided into eight clusters; loading matrices were interpreted and the presence of the most characteristic triterpene glycoside groups was demonstrated and supported by the characteristic chromatogram approach. The occurrence of Abrus precatorius and G. glabra additives in flavoured tea was confirmed.

CONCLUSION

Developed HPLC-MS-PARAFAC method is potentially reliable and an efficient tool for handling untreated experimental data and its future development may lead to more comprehensive evaluation of chemical composition and quality control of food additives and other complex mixtures.

A review of pretreatment and analysis of macrolides in food (Update Since 2010)

Macrolides are versatile broad-spectrum antibiotics whose activity stems from the presence of a macrolide ring. They are widely used in veterinary medicine to prevent and treat disease. However, because of their improper use and the absence of effective regulation, these compounds pose a threat to human health and the environment. Consequently, simple, quick, economical, and effective techniques are required to analyze macrolides in animal-derived foods, biological samples, and environmental samples. This paper presents a comprehensive overview of the pretreatment and analytical methods used for macrolides in various sample matrices, focusing on the developments since 2010. Pretreatment methods mainly include liquid-liquid extraction, solid-phase extraction, matrix solid-phase dispersion, and microextraction methods. Detection and quantification methods mainly include liquid chromatography (coupled to mass spectrometry or other detectors), electrochemical methods, capillary electrophoresis, and immunoassays. Furthermore, a comparison between the pros and cons of these methods and prospects for future developments are also discussed.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.