Search Results (86)

This paper provides a systematic review of the progress in encoded microsphere suspension array technology and its application in the multiplex detection of mycotoxins. Mycotoxins are diverse and frequently coexist in food matrices, leading to synergistic toxic effects. This poses significant challenges to existing risk assessment systems. Current multiplex detection methods still face technical bottlenecks such as target loss, matrix interference, and reliance on large-scale instruments. Suspension array technology based on encoded microspheres, combined with efficient signal amplification strategies, offers an ideal platform for achieving highly sensitive and high-throughput analysis of mycotoxins. This paper systematically reviews the core aspects of this technology, including encoding strategies such as physical, optical, and multi-dimensional approaches, along with new encoding materials like aggregation-induced emission materials and fluorescent proteins. It further covers matrix materials and preparation methods with an emphasis on green, biocompatible options and integrated fabrication techniques, as well as signal amplification mechanisms based on nucleic acid amplification, enzyme catalysis, and nanomaterials. The integration of magnetic separation techniques and the combination with portable, smartphone-based platforms for intelligent on-site detection are also highlighted. Finally, this review outlines future development trends such as the incorporation of artificial intelligence, 3D printing, and smart algorithms, aiming to provide theoretical references and technical support for research and applications in related fields. Full article

This study evaluated 65 commercially available pet feed samples, including 33 cat feeds and 32 dog feeds (dry and wet formulations), for the presence of organic contaminants. These included mycotoxins, pesticides, pharmaceutical residues/veterinary drugs, and plant-based bioactive compounds. A suspect screening strategy was employed using QuEChERS extraction followed by LC-LTQ/Orbitrap HRMS analysis. A total of 29 compounds were tentatively identified within 186 detections. In total, 76.9% of the samples were contaminated with mycotoxins. Aflatoxins (B1, B2, G1, and G2), T2 toxins, and HT2 toxins were dominant, with Aflatoxin B1 occurring in 33.8% of the samples and exhibiting a higher prevalence in dry feeds than in wet feeds. Pesticides were present in 72.0% of the dry formulations, including aclonifen and pirimiphos-methyl, but were present in only 11% of the wet formulations. Plant-based bioactive compounds, including phytoestrogens, were identified in 51% of the samples, highlighting toxicologically relevant candidates that merit prioritization for targeted confirmation, particularly in cat feeds. Pharmaceuticals were found in 23.8% of dry feeds (sparfloxacin and fumagillin). Overall, the HRMS-based, standard-free suspect screening workflow provides an early-warning overview of multi-class co-occurrence patterns in complex pet feed matrices and supports the prioritization of candidates for subsequent confirmatory analysis. Full article

Exocarpium Citri Grandis (ECG) is a distinctive medicinal and edible product originating from southern China and is often covered with a layer of characteristic “white frost” (WF). This study investigated the composition, formation mechanism, microbial safety, and anti-inflammatory activity of the WF. Multi-technique analyses revealed that WF mainly consisted of crystalline naringin (~80% of total mass). Drying-induced shrinkage and rupture of oil glands on ECG suggested metabolite migration and surface crystallization as the key mechanisms for WF formation. Microbial profiling revealed no significant differences in fungal and bacterial communities between WF and non-frost (NF) samples, and none of eight common mycotoxins was detected, confirming its microbial safety. Brewing tests demonstrated that water boiling for 30 min achieved efficient extraction of naringin, with higher yields in WF samples than in NF samples. In RAW264.7 cells, both WF and NF extract significantly inhibited lipopolysaccharide-induced NO production as well as the secretion and transcription of TNF-α, IL-6, IL-1β, iNOS, and NF-κB, with WF extract showing a stronger effect. Overall, these findings indicate that WF originates from endogenous flavonoid crystallization rather than microbial contamination and enhances the anti-inflammatory activity. This study provides a scientific basis for quality evaluation, processing optimization, and standardization of ECG products. Full article

The detection of environmental toxicants is transitioning from centralized laboratory methods to decentralized, point-of-care (POC) monitoring. A highly innovative approach in this field is the repurposing of commercially available, low-cost, and portable personal glucose meters (PGMs) as universal biosensing platforms. This strategy leverages the widespread availability and ease of use of PGMs to develop rapid, on-site detection methods for a wide array of non-glucose targets, significantly reducing both cost and development time. This systematic review comprehensively examines the various strategies employed to adapt PGMs for the detection of a wide array of ecotoxicants, including chemical targets (antibiotics, mycotoxins, pesticides, heavy metals, persistent organic pollutants) and biological ones (pathogenic bacteria, and viruses). The systematic review critically evaluates different sensor designs, highlighting that while aptamer-based and non-enzymatic biosensors offer advantages in stability and cost, antibody-based sensors provide high specificity. A significant finding is the persistent trade-off between analytical sensitivity and practical field deployment; many of the most sensitive assays require multi-step procedures, precise temperature control, magnetic separation, centrifugation, and the use of additional equipment, factors that undermine true POC utility. To address this gap, we propose four essential criteria for POC readiness: (i) ambient-temperature operation, (ii) no reliance on magnetic or centrifugal separation, (iii) total assay time, and (iv) robustness in complex environmental matrices. This systematic review confirms the feasibility of this approach across a broad spectrum of targets. However, the key challenge for future research lies in simplifying the assay protocols, eliminating cumbersome sample preparation steps, and enhancing robustness to make these biosensors truly practical for routine, on-site environmental monitoring. Full article

Aflatoxins are carcinogenic secondary metabolites produced by Aspergillus species and are common contaminants of many crops including maize. Atoxigenic Aspergillus flavus strains, formulated as biocontrol products such as Aflasafe^® TZ01, that comprises a mixture of four native atoxigenic strains, are used as pre-harvest agents to suppress toxigenic strains and reduce aflatoxin levels. This study assessed the intended and potential unintended impacts of Aflasafe^® TZ01 on mycotoxin contamination in maize. A total of 158 samples 79 from treated and 79 from untreated fields were collected from Chemba and Kiteto districts in Tanzania. Multi-mycotoxin analysis was conducted using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Detected toxins included aflatoxins (AFB1, AFB2, AFG1, AFG2), trichothecenes, and fumonisins (FB1, FB2, FB3). Non-parametric paired t-test analysis showed significant reductions in AFB1 (62%, p = 0.024) in treated samples. The mean concentrations of Fusarium mycotoxins such as NIV, T2, and ZEN were higher in treated maize. However, statistical analysis showed that these differences were only numerical trends, and were not significant (p > 0.05). These findings confirm the efficacy of Aflasafe^® TZ01 in reducing aflatoxins, while underscoring the importance of continued monitoring for other mycotoxins as part of integrated mycotoxin management strategies to mitigate both aflatoxins and co-occurring toxins. Full article

Deoxynivalenol (DON) and zearalenone (ZEN) are common mycotoxins in animal feeds, and their metabolites can be detected in exposed animals. Traditional methods focus on mycotoxin detection in feed, whereas biomarker-based approaches are used for evaluating individual exposure. This study aimed to develop and validate a multi-analyte method for the detection of biomarkers of ZEN, DON, and their metabolites α-zearalanol (α-ZAL), zearalanone (ZAN), deepoxy-DON (DOM-1), and 3-acetyl-DON (3-ADON) in swine using dried blood spots (DBSs) on qualitative filter paper. Analysis was performed using high-performance liquid chromatography–tandem mass spectrometry. Blank blood samples from three male pigs were fortified with 20, 40, and 60 μg/L of each analyte. Aliquots of 40 μL were spotted onto filter paper and then extracted and analyzed. Method validation included evaluating limits of detection and quantification, linearity, matrix effects, recovery, repeatability, intermediate precision, and selectivity. All analytes were detectable in DBS. Also, ZEN, ZAN, DON, and DOM-1 met all validation criteria, with recovery values of 89.10%, 79.79%, 101.50%, and 79.50%, respectively. Both α-ZAL and 3-ADON showed lower recoveries (74.66% and 58.66%). The method was successfully validated for simultaneous analysis of ZEN, ZAN, DON, and DOM-1 in swine DBS, offering a practical and minimally invasive tool for biomonitoring mycotoxin exposure. Full article

Agricultural nondestructive testing technology is pivotal in safeguarding food quality assurance, safety monitoring, and supply chain transparency. While conventional optical methods such as near-infrared spectroscopy and hyperspectral imaging demonstrate proficiency in surface composition analysis, their constrained penetration depth and environmental sensitivity limit effectiveness in dynamic agricultural inspections. This review highlights the transformative potential of microwave technologies, systematically examining their operational principles, current implementations, and developmental trajectories for agricultural quality control. Microwave technology leverages dielectric response mechanisms to overcome traditional limitations, such as low-frequency penetration for grain silo moisture testing and high-frequency multi-parameter analysis, enabling simultaneous detection of moisture gradients, density variations, and foreign contaminants. Established applications span moisture quantification in cereal grains, oilseed crops, and plant tissues, while emerging implementations address storage condition monitoring, mycotoxin detection, and adulteration screening. The high-frequency branch of the microwave–millimeter wave systems enhances analytical precision through molecular resonance effects and sub-millimeter spatial resolution, achieving trace-level contaminant identification. Current challenges focus on three areas: excessive absorption of low-frequency microwaves by high-moisture agricultural products, significant path loss of microwave high-frequency signals in complex environments, and the lack of a standardized dielectric database. In the future, it is essential to develop low-cost, highly sensitive, and portable systems based on solid-state microelectronics and metamaterials, and to utilize IoT and 6G communications to enable dynamic monitoring. This review not only consolidates the state-of-the-art but also identifies future innovation pathways, providing a roadmap for scalable deployment of next-generation agricultural NDT systems. Full article

The rapid evolution of deep learning (DL) has fundamentally transformed the paradigm for detecting special components in agricultural products, addressing critical challenges in food safety, quality control, and precision agriculture. This comprehensive review systematically analyzes many seminal studies to evaluate cutting-edge DL applications across three core domains: contaminant surveillance (heavy metals, pesticides, and mycotoxins), nutritional component quantification (soluble solids, polyphenols, and pigments), and structural/biomarker assessment (disease symptoms, gel properties, and physiological traits). Emerging hybrid architectures—including attention-enhanced convolutional neural networks (CNNs) for lesion localization, wavelet-coupled autoencoders for spectral denoising, and multi-task learning frameworks for joint parameter prediction—demonstrate unprecedented accuracy in decoding complex agricultural matrices. Particularly noteworthy are sensor fusion strategies integrating hyperspectral imaging (HSI), Raman spectroscopy, and microwave detection with deep feature extraction, achieving industrial-grade performance ($RPD$ > 3.0) while reducing detection time by 30–100× versus conventional methods. Nevertheless, persistent barriers in the “black-box” nature of complex models, severe lack of standardized data and protocols, computational inefficiency, and poor field robustness hinder the reliable deployment and adoption of DL for detecting special components in agricultural products. This review provides an essential foundation and roadmap for future research to bridge the gap between laboratory DL models and their effective, trusted application in real-world agricultural settings. Full article

This work proposes an insight into the mycotoxins detected in wheat from the 2023 and 2024 harvests in Belgium and highlights the link between agronomic conditions and mycotoxin contamination. The study utilized samples from a Belgian trial network, covering nine locations in 2023 and eight in 2024, ensuring diverse pedoclimatic contexts and including 11 different varieties. Sowing and harvest dates, previous crops and meteorological data were collected for these locations. A validated UPLC-MS/MS multi-mycotoxin method able to detect 20 mycotoxins, regulated or not, was used. Deoxynivalenol, zearalenone, and enniatins B and B1 were detected in the 2023 and 2024 samples. Enniatin A1 was only detected in the 2024 samples. Mycotoxin contamination was higher in 2024 compared to 2023, in terms of both the number of contaminated samples and the contamination levels. Enniatins B and B1, non-regulated mycotoxins, were widely detected in the 2024 wheat samples, with enniatin B detected in 68 out 88 samples ranging from 12 to 488 µg/kg. Differences between the wheat varieties were observed, with some varieties showing significantly higher contamination. Additionally, geographic location appeared to influence contamination levels, which could be related to previous crops or meteorological events. In conclusion, this research provides a comprehensive analysis of mycotoxin co-contamination in wheat samples from diverse pedoclimatic contexts in Belgium based over 2 years. It shows the importance of weather conditions on mycotoxin contamination. It also emphasizes the importance of variety selection to manage mycotoxin contamination. Full article

Three types of solid waste are produced during beer fermentation: spent grain, hot trub, and residual yeast. While the first is used as livestock feed, the seconds has not yet found any real reapplication in the field of circular economy. The aim of this work is to study and characterize these two brewing wastes, i.e., hot trub and residual yeast, to evaluate their potential reuse in the agricultural field. Samples from top-fermented and bottom-fermented beers were chemically investigated. Initially, the safety was assessed via multi-detection analysis of 57 mycotoxins, and all samples were deemed safe. Subsequently, the chemical and elemental composition was examined via ICP-MS and microanalysis, along with phenolic compounds and antioxidant activity via HPLC and spectrophotometric determinations, to achieve a thorough characterization of these waste samples. The C/N ratio of residual yeast from top-fermented beer and hot trub of the bottom-fermented one were near the optimal one (10:1). This research marks an initial step towards repurposing brewery waste materials as fertilizers. The subsequent steps will involve the formulation and field trials. Full article

A total of 98 samples of spices, herbs, and mixtures commercialized in Italy were analyzed for 11 mycotoxins, regulated and non-regulated. The occurrence of 1–4 mycotoxins was found in 84% and 60% of spice samples and herb samples, respectively. Spices were the most contaminated matrix. Total aflatoxins were detected in 5% and 9% of herbs and spices, respectively, and ochratoxin A was detected in 14% of spices and not at all in herbs. Only one sample of spices (cloves) showed an AFB₁ value (9.0 µg/kg) higher than the limit. No sample of herbs and spices had an OTA content beyond the limit. Within the non-regulated mycotoxins, ZEA was the most commonly occurring, and its mean levels in positive samples of spices ranged from 4.6 µg/kg (ZEA) to 1813.9 µg/kg (FB₁). The mean levels of FB₂ and ZEA in positive samples of herbs were 131.4 µg/kg and 2.5 µg/kg, respectively. The mean levels of non-regulated mycotoxins in positive samples of herbs-and-spices mixtures ranged from 2.6 µg/kg (ZEA) to 1071.7 µg/kg (FB₁). The most contaminated herbs and spices were garlic and basil, respectively. This study provides a significant amount of information on the natural occurrence of multi-mycotoxins in herbs and spices consumed in Italy, which will be useful for the future regulation of some mycotoxins, in particular, FBs. Full article

Contamination by multi-mycotoxins in cattle feed can lead to increased susceptibility to diseases and loss of performance. The present study aimed to investigate the occurrence of multiple mycotoxins present in the diet of beef cattle feedlots in Brazil. Chromatographic analyses were performed on 152 TMR samples from seven states, representing the diet provided to 1,246,522 animals. Contamination by mycotoxins was found in 100% of the TMR samples analyzed, with the most frequent being fumonisins, present in 100% of the samples, followed by zearalenone, which contaminated 79.6% of the samples, and subsequently by aflatoxins, deoxynivalenol, and T-2, while HT-2 was not detected in any of the samples. Furthermore, 2.6% of samples showed co-occurrence of five different types of mycotoxins, 23.7% presented four mycotoxins, 41.4% three mycotoxins, 22.4% two mycotoxins, and 9.9% of the samples showed contamination by only one mycotoxin. The significant prevalence of mycotoxins of the Fusarium and Aspergillus genera in the samples of the present study indicates a notable degree of pre- and post-harvest contamination in these beef cattle diets. Further studies are needed to define methods for monitoring cattle exposure to clarify its effects, even at low levels, and reduce the impacts on beef cattle production in Brazil. Full article

The detection and quantification of mycotoxins in beer are critical for ensuring consumer safety and regulatory compliance. These contaminants, originating from barley and other grains, persist and potentially transform during the brewing process. This study presents an innovative analytical protocol using liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC/ESI-MS/MS) for the simultaneous qualitative and quantitative analysis of nine mycotoxins, including aflatoxins (AFB1, AFB2, AFG1, AFG2), Ochratoxin A (OTA), Fumonisins (FB1, FB2), Deoxynivalenol (DON), and HT-2. The method leverages the efficiency of multi-mycotoxin immunoaffinity columns, providing streamlined sample preparation with high specificity and sensitivity. Validation was conducted using craft beers from Calabria, including freeze-dried samples to enhance analytical consistency and stability. The method’s accuracy was confirmed by using spiking samples with mycotoxins at concentrations compliant with the European Commission’s regulations (Recommendation 2024/1038/EU). The developed protocol delivers reliable results with minimized resource consumption, offering a robust tool for quality control and safety assessments in brewing. By addressing knowledge gaps in freeze-dried craft beer, this study contributes to advancing food safety standards in the brewing industry. Full article

Mycotoxins are secondary metabolites originating from several species of fungi that have proven to demonstrate high toxicity. In addition, potential contamination sources can promote increased human exposure to the adverse effects of these toxins. For this reason, it was necessary to develop several analytical methods that allow detection with the highest possible sensitivity for these toxic metabolites. Furthermore, since these methods involve high cost, are lengthy, and have sensitivity requirements, the development of multi-analyte detection methods is indispensable. The increasing consumption of groundnuts (legumes) as well as nuts (such as almonds, walnuts, and pistachios) and dried fruit (raisins and dried figs) has increased the risk of poisoning and the harmful effects of mycotoxins, which has encouraged studies for the creation of these methods. This review addresses the most representative methods applied to analyze and quantify mycotoxins in groundnuts (peanuts) together with decontamination techniques. The methodologies presented in this review are primarily based on analytical techniques for nuts and dried fruits. However, each of these methodologies can also be applied to peanut analysis for comparison and use. It is also relevant to highlight the importance of the development of multi-analyte methods in order to identify multiple mycotoxins using a single method, saving time, costs, and resources. Full article

The current status of multi-mycotoxin contamination in edible and medicinal plants demands urgent development of high-throughput analytical methods for mycotoxin detection. In this study, a reliable and sensitive method for the simultaneous analysis of 73 mycotoxins was established and successfully applied to detect mycotoxins in 260 samples of four dual-purpose plants (lotus seed, coix seed, licorice root, and dried tangerine peel). Sample preparation involved optimized QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) extraction combined with liquid–liquid extraction purification, and an enhanced ion pair library was established to reduce matrix interference and improve the method’s universality. Method validation demonstrated recovery rates ranging from 61.6% to 118.6% for all compounds, with relative standard deviations (RSDs) below 15%. The limits of detection (LODs) and quantification (LOQs) ranged from 0.25–12.25 μg/kg and 0.5–25 μg/kg, respectively. Based on the contamination analysis and health risk assessment using Margin of Exposure (MOE) and Hazard Index (HI) methods, we found that multi-mycotoxin contamination is highly prevalent in edible and medicinal plants, with different components being susceptible to invasion by distinct fungal genera. Seed-type plants showed high susceptibility to Aspergillus (53.3%) and Fusarium (22.2%) contamination, with MOE values below 10,000 for aflatoxins indicating potential health risks. Physical state and good storage conditions significantly influenced contamination levels, with fragmented samples showing substantially higher mycotoxin levels. Additionally, mycotoxins with associated biosynthetic metabolic pathways were frequently detected simultaneously in highly contaminated samples. Based on these findings, we recommend implementing strict moisture control during storage, maintaining intact product form where possible, and establishing comprehensive supplier qualification systems. This study provides valuable reference for monitoring mycotoxin contamination in similar plants. Full article