Detection of Mycotoxins in Food Using Surface-Enhanced Raman Spectroscopy: A Review

A comparative study of aptasensor vs. immunosensor for ultrasensitive detection of aflatoxin B1 using Ag-pSi SERS substrate

Numerous SERS based platforms have been designed to address the emerging need for detecting fungal metabolite contamination in foodstuffs, and specifically the Group 1 carcinogen aflatoxin B1. Herein, 4-aminothiophenol modified silver-coated porous silicon was used as the SERS substrate. Two ratiometric responses were individually assessed upon direct target capture using specific aptamers or antibodies. Under optimized physical features, elevated enhancement factor, wide dynamic range, low detection limits and pronounced recycling capabilities were achieved (7.39 × 107, 0.2-200 ppb, 0.0085 and 0.0110 ppb, 7 and 1 regeneration cycles without impairing the performances for aptasensor and immunosensor, respectively). The accuracy and anti-interference responses in several intricate matrices (maize, peanut, wheat, oats and rice) were compared to a routine HPLC method with equivalent recoveries. Overall, the comparative assessment revealed preferable features of reusability, durability and accuracy of the aptasensor over the immunosensor. Furthermore, the results demonstrate the substantial potential of the proposed SERS substrate for diverse on-site analytical applications using simple and portable monitoring instrumentation.

Recent Plasmonic Gold- and Silver-Assisted Raman Spectra for Advanced SARS-CoV-2 Detection

COVID-19 has become one of the deadliest epidemics in the past years. In efforts to combat the deadly disease besides vaccines, drug therapies, and facemasks, significant focus has been on designing specific methods for the sensitive and accurate detection of SARS-CoV-2. Of these, surface-enhanced Raman scattering (SERS) is an attractive analytical tool for the identification of SARS-CoV-2. SERS is the phenomenon of enhancement of Raman intensity signals from molecular analytes anchored onto the surfaces of roughened plasmonic nanomaterials. This work gives an updated summary of plasmonic gold nanomaterials (AuNMs) and silver nanomaterials (AgNMs)-based SERS technologies to identify SARS-CoV-2. Due to extreme "hot spots" promoting higher electromagnetic fields on their surfaces, different shapes of AuNMs and AgNMs combined with Raman probes have been reviewed for enhancing Raman signals of probe molecules for quantifying the virus. It also reviews progress made recently in the design of certain specific Raman probe molecules capable of imparting characteristic SERS response/tags for SARS-CoV-2 detection.

Progress of machine learning-based biosensors for the monitoring of food safety: A review

Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessing food safety due to selectivity, and sensitivity but poor stability inherently limits their application. The emergence of machine learning (ML) has enhanced the efficiency of different sensors for food safety assessment. The ML combined with various noninvasive biosensors has been implemented efficiently to monitor food safety by considering the stability of bio-recognition molecules. This review comprehensively summarizes the application of ML-powered biosensors to investigate food safety. Initially, different detector-based biosensors using biological molecules with their advantages and disadvantages and biosensor-related various ML algorithms for food safety monitoring have been discussed. Next, the application of ML-powered biosensors to detect antibiotics, foodborne microorganisms, mycotoxins, pesticides, heavy metals, anions, and persistent organic pollutants has been highlighted for the last five years. The challenges and prospects have also been deliberated. This review provides a new prospect in developing various biosensors for multi-food contaminants powered by suitable ML algorithms to monitor in-situ food safety.

Reports of tropane alkaloid poisonings and analytical techniques for their determination in food crops and products from 2013 to 2023

Food safety is crucial to attaining food security and sustainability. Unsafe foods for human and animal consumption lead to product recalls and rejection, negatively impacting the global economy and trade. Similarly, climate change can adversely affect the availability of safe and nutritious food at the table. The changing climatic conditions and global food trade and transport can make the movement of toxic plants possible, resulting in food crops being increasingly invaded by some species of plants that produce toxic secondary metabolites, such as tropane alkaloids (TAs). Datura stramonium from the Solanaceae plant family is an invasive and virulent plant that produces high amounts of two TAs, atropine and scopolamine. Various food poisoning events following accidental or deliberate ingestion of foods contaminated by atropine and scopolamine from seeds of D. stramonium have been recorded in different locations globally. Due to these incidents, regulatory agencies require the development of plant toxin detection methods that can be used in the food chain as early as possible. This systematic review thus focuses on the TA determination techniques in food and feeds published between 2013 and 2023. A particular focus was given to the sample preparation methods, the improvements of each technique claimed, and data to support the performance of each method, especially the ability to measure at or below the maximum level. The review concludes with other technological advancements, including rapid spectroscopy, electrophoresis, and colorimetric methods, as well as the possibility of coupling with smartphones for use in on-farm detection and the challenges in applying them.

Recent Progress in Nanomaterial-Based Surface-Enhanced Raman Spectroscopy for Food Safety Detection

Food safety has recently become a widespread concern among consumers. Surface-enhanced Raman scattering (SERS) is a rapidly developing novel spectroscopic analysis technique with high sensitivity, an ability to provide molecular fingerprint spectra, and resistance to photobleaching, offering broad application prospects in rapid trace detection. With the interdisciplinary development of nanomaterials and biotechnology, the detection performance of SERS biosensors has improved significantly. This review describes the advantages of nanomaterial-based SERS detection technology and SERS's latest applications in the detection of biological and chemical contaminants, the identification of foodborne pathogens, the authentication and quality control of food, and the safety assessment of food packaging materials. Finally, the challenges and prospects of constructing and applying nanomaterial-based SERS sensing platforms in the field of food safety detection are discussed with the aim of early detection and ultimate control of foodborne diseases.

Signal-enhanced electrochemical sensor employing MWCNTs/CMK-3/AuNPs and Au@Pd core-shell structure for sensitive determination of AFB1 in complex matrix

A sandwich electrochemical sensor was fabricated based on multi-walled carbon nanotubes/ordered mesoporous carbon/AuNP (MWCNTs/CMK-3/AuNP) nanocomposites and porous core-shell nanoparticles Au@PdNPs to achieve rapid and sensitive detection of AFB1 in complex matrices. MWCNTs/CMK-3/AuNP nanocomposite, which was prepared by self-assembly method, served as a substrate material to increase the aptamer loading and improve the conductivity and electrocatalytic activity of the electrode for the first signal amplification. Then, Au@PdNPs, which were synthesized by one-pot aqueous phase method, were applied as nanocarriers loaded with plenty of capture probe antibody (Ab) and signal molecule toluidine blue (Tb) to form the Au@PdNPs-Ab-Tb bioconjugates for secondary signal amplification. The sensing system could still significantly improve the signal output intensity even in the presence of ultra-low concentration target compound due to the dual signal amplification of MWCNTs/CMK-3/AuNP nanocomposites and Au@PdNPs-Ab-Tb. The method exhibited high selectivity, low detection limit (9.13 fg/mL), and strong stability to differentiate AFB1 from other mycotoxins. Furthermore, the sensor has been successfully applied to the quantitative determination of AFB1 in corn, malt, and six herbs, which has potential applications in food safety, quality control, and environmental monitoring.

A Surface-Enhanced Raman Spectroscopy-Based Aptasensor for the Detection of Deoxynivalenol and T-2 Mycotoxins

The quality of food is one of the emergent points worldwide. Many microorganisms produce toxins that are harmful for human and animal health. In particular, mycotoxins from Fusarium fungi are strictly controlled in cereals. Simple and robust biosensors are necessary for 'in field' control of the crops and processed products. Nucleic acid-based sensors (aptasensors) offer a new era of point-of-care devices with excellent stability and limits of detection for a variety of analytes. Here we report the development of a surface-enhanced Raman spectroscopy (SERS)-based aptasensor for the detection of T-2 and deoxynivalenol in wheat grains. The aptasensor was able to detect as low as 0.17% of pathogen fungi in the wheat grains. The portable devices, inexpensive SERS substrate, and short analysis time encourage further implementation of the aptasensors outside of highly equipped laboratories.

Raman Hyperspectral Imaging as a Potential Tool for Rapid and Nondestructive Identification of Aflatoxin Contamination in Corn Kernels

The potential of Raman hyperspectral imaging with a 785 nm excitation line laser was examined for the detection of aflatoxin contamination in corn kernels. Nine-hundred kernels were artificially inoculated in the laboratory, with 300 kernels each inoculated with AF13 (aflatoxigenic) fungus, AF36 (nonaflatoxigenic) fungus, and sterile distilled water (control). One-hundred kernels from each treatment were subsequently incubated for 3, 5, and 8 days. The mean spectra of single kernels were extracted from the endosperm side and the embryo area of the germ side, and local Raman peaks were identified based upon the calculated reference spectra of aflatoxin-negative and -positive categories separately. The principal component analysis-linear discriminant analysis models were established using different types of variable inputs including original full spectra, preprocessed full spectra, and identified local peaks over kernel endosperm-side, germ-side, and both sides. The results of the established discriminant models showed that the germ-side spectra performed better than the endosperm-side spectra. Based upon the 20 ppb-threshold, the best mean prediction accuracy of 82.6% was achieved for the aflatoxin-negative category using the original spectra in the combined form of both kernel sides, and the best mean prediction accuracy of 86.7% was obtained for the -positive category using the preprocessed germ-side spectra. Based upon the 100 ppb-threshold, the best mean prediction accuracies of 85.0% and 89.6% were achieved for the aflatoxin-negative and -positive categories separately, using the same type of variable inputs for the 20 ppb-threshold. In terms of overall prediction accuracy, the models established upon the original spectra in the combined form of both kernel sides achieved the best predictive performance, regardless of the threshold. The mean overall prediction accuracies of 81.8% and 84.5% were achieved with the 20 ppb- and 100 ppb-thresholds, respectively.

A Sensitive SERS Sensor Combined with Intelligent Variable Selection Models for Detecting Chlorpyrifos Residue in Tea

Chlorpyrifos is one of the most widely used broad-spectrum insecticides in agriculture. Given its potential toxicity and residue in food (e.g., tea), establishing a rapid and reliable method for the determination of chlorpyrifos residue is crucial. In this study, a strategy combining surface-enhanced Raman spectroscopy (SERS) and intelligent variable selection models for detecting chlorpyrifos residue in tea was established. First, gold nanostars were fabricated as a SERS sensor for measuring the SERS spectra. Second, the raw SERS spectra were preprocessed to facilitate the quantitative analysis. Third, a partial least squares model and four outstanding intelligent variable selection models, Monte Carlo-based uninformative variable elimination, competitive adaptive reweighted sampling, iteratively retaining informative variables, and variable iterative space shrinkage approach, were developed for detecting chlorpyrifos residue in a comparative study. The repeatability and reproducibility tests demonstrated the excellent stability of the proposed strategy. Furthermore, the sensitivity of the proposed strategy was assessed by estimating limit of detection values of the various models. Finally, two-tailed paired t-tests confirmed that the accuracy of the proposed strategy was equivalent to that of gas chromatography-mass spectrometry. Hence, the proposed method provides a promising strategy for detecting chlorpyrifos residue in tea.

Surface-enhanced Raman spectroscopy for studying the interaction of organometallic compound bis(1,3-dihexylimidazole-2-yl) silver(i) hexafluorophosphate (v) with the biofilm of Escherichia coli

Escherichia coli biofilms are a major cause of gastrointestinal tract diseases, such as esophageal, stomach and intestinal diseases. Nowadays, these are the most commonly occurring diseases caused by consuming contaminated food. In this study, we evaluated the efficacy of probiotics in controlling multidrug-resistant E. coli and reducing its ability to form biofilms. Our results substantiate the effective use of probiotics as antimicrobial alternatives and to eradicate biofilms formed by multidrug-resistant E. coli. In this research, surface enhanced Raman spectroscopy (SERS) was utilized to identify and evaluate Escherichia coli biofilms and their response to the varying concentrations of the organometallic compound bis(1,3-dihexylimidazole-2-yl) silver(i) hexafluorophosphate (v). Given the escalating challenge of antibiotic resistance in bacteria that form biofilms, understanding the impact of potential antibiotic agents is crucial for the healthcare sector. The combination of SERS with principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) enabled the detection and characterization of the biofilm, providing insights into the biochemical changes induced by the antibiotic candidate. The identified SERS spectral features served as indicators for elucidating the mode of action of the potential drug on the biofilm. Through PCA and PLS-DA, metabolic variations allowing the differentiation and classification of unexposed biofilms and biofilms exposed to different concentrations of the synthesized antibiotic were successfully identified, with 95% specificity, 96% sensitivity, and a 0.75 area under the curve (AUC). This research underscores the efficiency of surface enhanced Raman spectroscopy in differentiating the impact of potential antibiotic agents on E. coli biofilms.

Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman)

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.

Biosensors based on core-shell nanoparticles for detecting mycotoxins in food: A review

Mycotoxins are toxic metabolites produced by fungi in the process of infecting agricultural products, posing serious threat to the health of human and animals. Thus, sensitive and reliable analytical techniques for mycotoxin detection are needed. Biosensors equipped with antibodies or aptamers as recognition elements and core-shell nanoparticles (NPs) for the pre-treatment and detection of mycotoxins have been extensively studied. By comparison with monocomponent NPs, core-shell nanostructures exhibit unique optical, electric, magnetic, plasmonic, and catalytic properties due to the combination of functionalities and synergistic effects, resulting in significant improvement of sensing capacities in various platforms, such as surface-enhanced Raman spectroscopy, fluorescence, lateral flow immunoassay and electrochemical sensors. This review focused on the development of core-shell NPs based biosensors for the sensitive and accurate detection of mycotoxins in food samples. Recent developments were categorised and summarised, along with detailed discussion of advantages and shortcomings. The future potential of utilising core-shell NPs in food safety testing was also highlighted.

Nanorod reassembling on a sprayed SERS substrate under confined evaporation inducing ultrasensitive TPhT detection

Triphenyltin is an estrogen like pollutant that poses significant environmental threats due to its highly accumulative toxicity. To improve regulation, a fast and sensitive detection method is urgently needed. SERS can capture fingerprint information and is capable of trace detection, making it an ideal solution. Here, we present a sprayed substrate comprised of lightconfining structures and gold nanorod assemblies that are easy to prepare, low-cost, and can form dense hotspots under confined evaporation. The substrates are three-layered: initially, a gold nanorod layer is sprayed as a support, then sputter Ag film on the surface to form a lightconfining structure, followed by another gold nanorod layer sprayed on the Ag film. The coupling of nanorod assembly with lightconfining Ag films leads to 10-fold sensitivity. In addition, sample droplet evaporation in a limited area called confined evaporation contributes to nanorod migration and reassembly on the corner of the substrate, enhancing analytes absorption, and substantially lowered the detection limits. By systematically evaluating the substrate performance, we were able to obtain an average enhancement factor of 3.31 × 106. After confined evaporation, the detection limit reached 10-18 M for R6G and for triphenyltin, it achieved 10-9 M. This novel method represents a significant advancement toward SERS application in detecting trace pollutants.

Advancing Mycotoxin Detection: Multivariate Rapid Analysis on Corn Using Surface Enhanced Raman Spectroscopy (SERS)

Mycotoxin contamination on food and feed can have deleterious effect on human and animal health. Agricultural crops may contain one or more mycotoxin compounds; therefore, a good multiplex detection method is desirable to ensure food safety. In this study, we developed a rapid method using label-free surface-enhanced Raman spectroscopy (SERS) to simultaneously detect three common types of mycotoxins found on corn, namely aflatoxin B1 (AFB1), zearalenone (ZEN), and ochratoxin A (OTA). The intrinsic chemical fingerprint from each mycotoxin was characterized by their unique Raman spectra, enabling clear discrimination between them. The limit of detection (LOD) of AFB1, ZEN, and OTA on corn were 10 ppb (32 nM), 20 ppb (64 nM), and 100 ppb (248 nM), respectively. Multivariate statistical analysis was used to predict concentrations of AFB1, ZEN, and OTA up to 1.5 ppm (4.8 µM) based on the SERS spectra of known concentrations, resulting in a correlation coefficient of 0.74, 0.89, and 0.72, respectively. The sampling time was less than 30 min per sample. The application of label-free SERS and multivariate analysis is a promising method for rapid and simultaneous detection of mycotoxins in corn and may be extended to other types of mycotoxins and crops.

T-2 and HT-2 Toxins: Toxicity, Occurrence and Analysis: A Review

One of the major classes of mycotoxins posing serious hazards to humans and animals and potentially causing severe economic impact to the cereal industry are the trichothecenes, produced by many fungal genera. As such, indicative limits for the sum of T-2 and HT-2 were introduced in the European Union in 2013 and discussions are ongoing as to the establishment of maximum levels. This review provides a concise assessment of the existing understanding concerning the toxicological effects of T-2 and HT-2 in humans and animals, their biosynthetic pathways, occurrence, impact of climate change on their production and an evaluation of the analytical methods applied to their detection. This study highlights that the ecology of F. sporotrichioides and F. langsethiae as well as the influence of interacting environmental factors on their growth and activation of biosynthetic genes are still not fully understood. Predictive models of Fusarium growth and subsequent mycotoxin production would be beneficial in predicting the risk of contamination and thus aid early mitigation. With the likelihood of regulatory maximum limits being introduced, increased surveillance using rapid, on-site tests in addition to confirmatory methods will be required. allowing the industry to be proactive rather than reactive.

Design, Fabrication, and Applications of SERS Substrates for Food Safety Detection: Review

Sustainable and safe food is an important issue worldwide, and it depends on cost-effective analysis tools with good sensitivity and reality. However, traditional standard chemical methods of food safety detection, such as high-performance liquid chromatography (HPLC), gas chromatography (GC), and tandem mass spectrometry (MS), have the disadvantages of high cost and long testing time. Those disadvantages have prevented people from obtaining sufficient risk information to confirm the safety of their products. In addition, food safety testing, such as the bioassay method, often results in false positives or false negatives due to little rigor preprocessing of samples. So far, food safety analysis currently relies on the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), HPLC, GC, UV-visible spectrophotometry, and MS, all of which require significant time to train qualified food safety testing laboratory operators. These factors have hindered the development of rapid food safety monitoring systems, especially in remote areas or areas with a relative lack of testing resources. Surface-enhanced Raman spectroscopy (SERS) has emerged as one of the tools of choice for food safety testing that can overcome these dilemmas over the past decades. SERS offers advantages over chromatographic mass spectrometry analysis due to its portability, non-destructive nature, and lower cost implications. However, as it currently stands, Raman spectroscopy is a supplemental tool in chemical analysis, reinforcing and enhancing the completeness and coverage of the food safety analysis system. SERS combines portability with non-destructive and cheaper detection costs to gain an advantage over chromatographic mass spectrometry analysis. SERS has encountered many challenges in moving toward regulatory applications in food safety, such as quantitative accuracy, poor reproducibility, and instability of large molecule detection. As a result, the reality of SERS, as a screening tool for regulatory announcements worldwide, is still uncommon. In this review article, we have compiled the current designs and fabrications of SERS substrates for food safety detection to unify all the requirements and the opportunities to overcome these challenges. This review is expected to improve the interest in the sensing field of SERS and facilitate the SERS applications in food safety detection in the future.

Applications of Delayed Luminescence for tomato fruit quality assessment across varied Sicilian cultivation zones

The food industry places significant emphasis on ensuring quality and traceability as key components of a healthy diet. To cater to consumer demands, researchers have prioritized the development of analytical techniques that can rapidly and non-invasively provide data on quality parameters. In this study, we propose to use the Delayed Luminescence (DL), an ultra-weak and photo-induced emission of optical photons, as a tool for a rapid evaluation of quality profile associated with fruit ripening, in support of traditional analysis methods. Delayed Luminescence measurements have been performed on cherry tomatoes, with and without the PGI "Pomodoro di Pachino" certification, harvested from two different growing areas of south-eastern Sicily (Italy). Then, DL emissions were correlated with soluble solid content and titratable acidity values, which are known to affect the flavor, the commerciality and the maturity degree of tomato fruits. In addition, we evaluated the changes in the DL parameters with respect to the geographical origin of the cherry tomatoes, with the aim of testing the possibility of applying the technique for identification purposes. The signals of Delayed Luminescence appeared to be good indicators of the macromolecular structure of the biological system, revealing structural changes related to the content of total soluble solids present in the juice of tomatoes analyzed, and they appeared unsuitable for authenticating vegetable crops, since the differences in the photon yields emitted by tomato Lots were not related to territory of origin. Thus, our results suggest that DL can be used as a nondestructive indicator of important parameters linked to tomato fruit quality.

Raman spectroscopy in crop quality assessment: focusing on sensing secondary metabolites: a review

As a crop quality sensor, Raman spectroscopy has been consistently proposed as one of the most promising and non-destructive methods for qualitative and quantitative analysis of plant substances, because it can measure molecular structures in a short time without requiring pretreatment along with simple usage. The sensitivity of the Raman spectrum to target chemicals depends largely on the wavelength, intensity of the laser power, and exposure time. Especially for plant samples, it is very likely that the peak of the target material is covered by strong fluorescence effects. Therefore, methods using lasers with low energy causing less fluorescence, such as 785 nm or near-infrared, are vigorously discussed. Furthermore, advanced techniques for obtaining more sensitive and clear spectra, like surface-enhanced Raman spectroscopy, time-gated Raman spectroscopy or combination with thin-layer chromatography, are being investigated. Numerous interpretations of plant quality can be represented not only by the measurement conditions but also by the spectral analysis methods. Up to date, there have been attempted to optimize and generalize analysis methods. This review summarizes the state of the art of micro-Raman spectroscopy in crop quality assessment focusing on secondary metabolites, from in vitro to in vivo and even in situ, and suggests future research to achieve universal application.

Recent advances in simultaneous detection strategies for multi-mycotoxins in foods

Mycotoxin contamination has become a challenge in the field of food safety testing, given the increasing emphasis on food safety in recent years. Mycotoxins are widely distributed, in heavily polluted areas. Food contamination with these toxins is difficult to prevent and control. Mycotoxins, as are small-molecule toxic metabolites produced by several species belonging to the genera Aspergillus, Fusarium, and Penicillium growing in food. They are considered teratogenic, carcinogenic, and mutagenic to humans and animals. Food systems are often simultaneously contaminated with multiple mycotoxins. Due to the additive or synergistic toxicological effects caused by the co-existence of multiple mycotoxins, their individual detection requires reliable, accurate, and high-throughput techniques. Currently available, methods for the detection of multiple mycotoxins are mainly based on chromatography, spectroscopy (colorimetry, fluorescence, and surface-enhanced Raman scattering), and electrochemistry. This review provides a comprehensive overview of advances in the multiple detection methods of mycotoxins during the recent 5 years. The principles and features of these techniques are described. The practical applications and challenges associated with assays for multiple detection methods of mycotoxins are summarized. The potential for future development and application is discussed in an effort, to provide standards of references for further research.

Application of Nanomaterials for Coping with Mycotoxin Contamination in Food Safety: From Detection to Control

Mycotoxins, which are toxic secondary metabolites produced by fungi, are harmful to humans. Mycotoxin-induced contamination has drawn attention worldwide. Consequently, the development of reliable and sensitive detection methods and high-efficiency control strategies for mycotoxins is important to safeguard food industry safety and public health. With the rapid development of nanotechnology, many novel nanomaterials that provide tremendous opportunities for greatly improving the detection and control performance of mycotoxins because of their unique properties have emerged. This review comprehensively summarizes recent trends in the application of nanomaterials for detecting mycotoxins (fluorescence, colorimetric, surface-enhanced Raman scattering, electrochemical, and point-of-care testing) and controlling mycotoxins (inhibition of fungal growth, mycotoxin absorption, and degradation). These detection methods possess the advantages of high sensitivity and selectivity, operational simplicity, and rapidity. With research attention on the control of mycotoxins and the gradual excavation of the properties of nanomaterials, nanomaterials are also employed for the inhibition of fungal growth, mycotoxin absorption, and mycotoxin degradation, and impressive controlling effects are obtained. This review is expected to provide the readers insight into this state-of-the-art area and a reference to design nanomaterials-based schemes for the detection and control of mycotoxins.

Solid-phase extraction techniques based on nanomaterials for mycotoxin analysis: An overview for food and agricultural products

Mycotoxin contamination is a globally concerned problem for food and agricultural products since it may directly or indirectly induce severe threats to human health. Sensitive and selective screening is an efficient strategy to prevent or reduce human and animal exposure to mycotoxins. However, enormous challenges exist in the determination of mycotoxins, arising from complex sample matrices, trace-level analytes, and the co-occurrence of diverse mycotoxins. Appropriate sample preparation is essential to isolate, purify, and enrich mycotoxins from complicated matrices, thus decreasing sample matrix effects and lowering detection limits. With the cross-disciplinary development, new solid-phase extraction strategies have been exploited and integrated with nanotechnology to meet the challenges of mycotoxin analysis. This review summarizes the advance and progress of solid-phase extraction techniques as the methodological solutions for mycotoxin analysis. Emphases are paid on nanomaterials fabricated as trapping media of SPE techniques, including carbonaceous nanoparticles, metal/metal oxide-based nanoparticles, and nanoporous materials. Advantages and limitations are discussed, along with the potential prospects. This article is protected by copyright. All rights reserved.

Hydrophilic-Hydrophobic Nanohybrids of AuNP-Immobilized Two-Dimensional Nanomica Platelets as Flexible Substrates for High-Efficiency and High-Selectivity Surface-Enhanced Raman Scattering Microbe Detection

A flexible hybrid substrate was developed by affixing gold nanoparticles (AuNPs) onto the surface of two-dimensional nanomica platelets (NMPs). The substrate was successfully used in biosensors with high efficiency and high selectivity through surface-enhanced Raman scattering (SERS). By controlling the amphiphilicity of the hybrid substrate, the flexible substrate was made highly selective toward biomolecules. Four different SERS substrate systems were constructed, including intercalated mica, exfoliated NMPs, hydrophilic exfoliated NMPs, and hydrophobic exfoliated NMPs. NMPs were only 1 nm thick. AuNPs adsorbed on both sides of NMPs and thus created excellent three-dimensional hot junction effects in the z-axis direction. For the detection of adenine in DNA, a satisfactory Raman enhancement factor (EF) of up to 8.9 × 10⁶ was achieved with the detection limit as low as 10^-8 M. Subsequently, the AuNP/NMP hybrids were adopted to rapidly detect hydrophilic Staphylococcus hominis and hydrophobic Escherichia coli. The AuNP/PIB-POE-PIB/NMP nanohybrid was concurrently hydrophilic and hydrophobic. This amphiphilic property greatly enhanced the detection selectivity and signal intensity for hydrophilic or hydrophobic bacteria. Overall, AuNPs/PIB-POE-PIB/NMPs developed as SERS substrates enable rapid, sensitive biodetection.

Mimotope-Based Immunoassays for the Rapid Analysis of Mycotoxin: A Review

Mycotoxins are toxic contaminants in foods and feeds that are naturally occurring and largely unavoidable. Determining their contents in these products is essential to protect humans from harm. Immunoassays of mycotoxins have been well-established because they are fast, sensitive, simple, and cost-effective. However, a major limitation of immunoassays is the requirement of toxic mycotoxins as competing antigens, standards, or competing tracers. Mimotopes are peptides or proteins that can specifically bind to antibodies and compete with analytes for binding sites by mimicking antigenic epitopes. They can be employed as substitutes for competing antigens, standards, or competing tracers to avoid use of mycotoxins. This review summarizes the production and functionalization of the two main kinds of mimotopes, mimic peptides and anti-idiotypic antibodies (Ab2), and their applications in rapid analysis of mycotoxins.