Modeling postharvest mycotoxins in foods: recent research

A Portable Automated Microfluidic Platform for Point-of-Care Testing for Multiple Mycotoxins in Wine

Food safety requires point-of-care testing (POCT) for mycotoxins, since their presence in wine significantly impacts the wine industry and poses a severe threat to human life. Traditional detection methods are usually limited to detecting one mycotoxin and cannot achieve high-throughput, automated, and rapid quantitative analysis of multiple mycotoxins in real samples. Here, we propose a portable automated microfluidic platform (PAMP) integrating a chemiluminescence (CL) imaging system and a microfluidic chip to realize POCT for multiple mycotoxins in real samples, simplifying complex manual operations, shortening the detection time, and improving the detection sensitivity. Specially, silicone films were used as substrates on microfluidic chips to incubate mycotoxin conjugations, and the streptavidin-biotin (SA-B) system and an indirect immunoassay were implemented on silicone films to improve the sensitivity of reaction results. Interestingly, these methods significantly improved detection results, resulting in sensitive detection of mycotoxins, including zearalenone (ZEA) ranging from 1 to 32 ng/mL, aflatoxin B1 (AFB1) ranging from 0.2 to 6.4 ng/mL, and ochratoxin A (OTA) ranging from 2 to 64 ng/mL. The recovery of samples reached 91.39-109.14%, which verified the reliability and practicability of the PAMP. This PAMP enables sensitive and rapid detection of multiple mycotoxins in markets or wineries that lack advanced laboratory facilities. Therefore, it is essential to develop a portable microfluidic platform for POCT to detect mycotoxins in real samples.

Recent advances and challenges in the analysis of natural toxins

Natural toxins (NTs) are poisonous secondary metabolites produced by living organisms developed to ward off predators. Especially low molecular weight NTs (MW<∼1 kDa), such as mycotoxins, phycotoxins, and plant toxins, are considered an important and growing food safety concern. Therefore, accurate risk assessment of food and feed for the presence of NTs is crucial. Currently, the analysis of NTs is predominantly performed with targeted high pressure liquid chromatography tandem mass spectrometry (HPLC-MS/MS) methods. Although these methods are highly sensitive and accurate, they are relatively expensive and time-consuming, while unknown or unexpected NTs will be missed. To overcome this, novel on-site screening methods and non-targeted HPLC high resolution mass spectrometry (HRMS) methods have been developed. On-site screening methods can give non-specialists the possibility for broad "scanning" of potential geographical regions of interest, while also providing sensitive and specific analysis at the point-of-need. Non-targeted chromatography-HRMS methods can detect unexpected as well as unknown NTs and their metabolites in a lab-based approach. The aim of this chapter is to provide an insight in the recent advances, challenges, and perspectives in the field of NTs analysis both from the on-site and the laboratory perspective.

Mitigating aflatoxin B1 in high-moisture sorghum silage: Aspergillus flavus growth and aflatoxin B1 prediction

Aspergillus flavus (A. flavus), a frequent contaminant in silage, is a significant producer of aflatoxins, notably the potent carcinogen aflatoxin B1. This contaminant poses a potential risk during the initial aerobic phase of ensiling. The present work studied the impact of temperature on A. flavus growth and aflatoxin B1 production in laboratory-scale sorghum silos during the initial aerobic phase. Growth curves of A. flavus were generated at various temperatures and modeled with the Gompertz model. Results indicated that the optimal temperature range for the maximum growth rate in sorghum mini-silos is between 25 and 30°C. Mold biomass and aflatoxin B1 levels were quantified using qPCR and HPLC, respectively. A predictive model for aflatoxin B1 synthesis in the initial ensiling phase was established, in function of grain moisture, external temperature, and time. Within the studied range, A. flavus's initial concentration did not significantly influence aflatoxin B1 production. According to the model maximum aflatoxin production is expected at 30% moisture and 25°C temperature, after 6 days in the aerobic phase. Aflatoxin B1 production in such conditions was corroborated experimentally. Growth curves and aflatoxin B1 production highlighted that at 48 h of incubation under optimal conditions, aflatoxin B1 concentrations in mini-silos exceeded national legislation limits, reaching values close to 100 ppb. These results underscore the risk associated with A. flavus presence in ensiling material, emphasizing the importance of controlling its development in sorghum silos.

Predictive growth kinetic parameters and modelled probabilities of deoxynivalenol production by Fusarium graminearum on wheat during simulated storing conditions

AIMS

Mathematical models were employed to predict the growth kinetic parameters of F. graminearum and the accumulation of deoxynivalenol (DON) during wheat storage as a function of different moisture contents (MCs) and temperatures.

METHODS AND RESULTS

The colony counting method was used to quantify F. graminearum growth under different environmental conditions, and kinetic and probability models were developed to describe the effect of different MCs and temperatures on fungal growth and DON production during wheat storage. Among the employed secondary models (Arrhenius-Davey, Gibson, and Cardinal), the general polynomial best predicted the fungal growth rate under varying temperature and MC during wheat storage. According to the logistic model, DON contamination was correctly predicted in 96.5% of cases.

CONCLUSIONS

The maximum growth rate of fungi was 0.4889±0.092 Log CFU g^-1 d^-1 at 25°C and 30% moisture according to the polynomial model. At below 17°C and ≤15% moisture, no fungal growth was observed. The probability model of toxin production showed no toxin production at less than 15% moisture (a_w ≤ 0.76) and below 15°C.

SIGNIFICANCE AND IMPACT OF THE STUDY

This is the first application of a probability model of DON production during wheat storage, providing a reference for preventing fungal growth and mycotoxin accumulation by F. graminearum during wheat storage and guaranteeing food product safety.

Metal-Organic Frameworks-Based Sensors for Food Safety

Food contains a variety of poisonous and harmful substances that have an impact on human health. Therefore, food safety is a worldwide public concern. Food detection approaches must ensure the safety of food at every step of the food supply chain by monitoring and evaluating all hazards from every single step of food production. Therefore, early detection and determination of trace-level contaminants in food are one of the most crucial measures for ensuring food safety and safeguarding consumers’ health. In recent years, various methods have been introduced for food safety analysis, including classical methods and biomolecules-based sensing methods. However, most of these methods are laboratory-dependent, time-consuming, costly, and require well-trained technicians. To overcome such problems, developing rapid, simple, accurate, low-cost, and portable food sensing techniques is essential. Metal-organic frameworks (MOFs), a type of porous materials that present high porosity, abundant functional groups, and tunable physical and chemical properties, demonstrates promise in large-number applications. In this regard, MOF-based sensing techniques provide a novel approach in rapid and efficient sensing of pathogenic bacteria, heavy metals, food illegal additives, toxins, persistent organic pollutants (POPs), veterinary drugs, and pesticide residues. This review focused on the rapid screening of MOF-based sensors for food safety analysis. Challenges and future perspectives of MOF-based sensors were discussed. MOF-based sensing techniques would be useful tools for food safety evaluation owing to their portability, affordability, reliability, sensibility, and stability. The present review focused on research published up to 7 years ago. We believe that this work will help readers understand the effects of food hazard exposure, the effects on humans, and the use of MOFs in the detection and sensing of food hazards.

Essential Oil Nanoemulsion as Eco-Friendly and Safe Preservative: Bioefficacy Against Microbial Food Deterioration and Toxin Secretion, Mode of Action, and Future Opportunities

Microbes are the biggest shareholder for the quantitative and qualitative deterioration of food commodities at different stages of production, transportation, and storage, along with the secretion of toxic secondary metabolites. Indiscriminate application of synthetic preservatives may develop resistance in microbial strains and associated complications in human health with broad-spectrum environmental non-sustainability. The application of essential oils (EOs) as a natural antimicrobial and their efficacy for the preservation of foods has been of present interest and growing consumer demand in the current generation. However, the loss in bioactivity of EOs from fluctuating environmental conditions is a major limitation during their practical application, which could be overcome by encapsulating them in a suitable biodegradable and biocompatible polymer matrix with enhancement to their efficacy and stability. Among different nanoencapsulated systems, nanoemulsions effectively contribute to the practical applications of EOs by expanding their dispersibility and foster their controlled delivery in food systems. In line with the above background, this review aims to present the practical application of nanoemulsions (a) by addressing their direct and indirect (EO nanoemulsion coating leading to active packaging) consistent support in a real food system, (b) biochemical actions related to antimicrobial mechanisms, (c) effectiveness of nanoemulsion as bio-nanosensor with large scale practical applicability, (d) critical evaluation of toxicity, safety, and regulatory issues, and (e) market demand of nanoemulsion in pharmaceuticals and nutraceuticals along with the current challenges and future opportunities.

Decision support system for integrated management of mycotoxins in feed and food supply chains

Mycotoxins present a global food safety threat of our feed and food. Mycotoxins are toxic metabolites of certain fungi in agricultural products that are harmful to animal and human health. The presence of mycotoxins in these products depends on a variety of management and environmental factors in the field, during storage and/or processing of feed and food commodities. To date, information on mycotoxin management is available, but is not easy to access by supply chain actors. This study aimed to design, build and test a Decision Support System (DSS) that can help decision making on mycotoxin management by various actors along the feed and food supply chains. As part of this, available knowledge and data on mycotoxin prevention and control were collected and synthesised into easy to understand guidelines and tools for various groups of end-users. The DSS consists of four different modules: (a) static information module and (b) scenario analysis module, (c) dynamic module for forecasting mycotoxins, and (d) dynamic module for real-time monitoring of moulds/mycotoxins in grain silos. Intended end-users are all end-user groups for modules (a) and (b); growers and collectors for module (c) and; post-harvest storage managers for module (d). The DSS is user-friendly and accessible through PCs, tablets and smartphones (see https://mytoolbox-platform.com/ ). In various phases of the DSS development, the tool has been demonstrated to groups of end-users, and their suggestions have been taken into account, whenever possible. Also, a near final version has been tested with individual farmers on the easiness to use the system. In this way we aimed to maximise the DSS uptake by actors along the chain. Ultimately, this DSS will improve decision making on mycotoxin management; it will assist in reducing mycotoxin contamination in the key crops of Europe, thereby reducing economic losses and improving animal and human health.

Molecularly Imprinted Polymer as Selective Sorbent for the Extraction of Zearalenone in Edible Vegetable Oils

A method based on the selective extraction of zearalenone (ZON) from edible vegetable oils using molecularly imprinted polymer (MIP) has been developed and validated. Ultra-high-pressure liquid chromatography coupled with a fluorescence detection system was employed for the detection of zearalenone. The method was applied to the analysis of zearalenone in maize oil samples spiked at four concentration levels within the maximum permitted amount specified by the European Commission Regulation (EC) No. 1126/2007. As a result, the proposed methodology provided high recoveries (>72%) with good linearity (R2 > 0.999) in the range of 10-2000 μg/kg and a repeatability relative standard deviation below 1.8%. These findings meet the analytical performance criteria specified by the European Commission Regulation No. 401/2006 and reveal that the proposed methodology can be successfully applied for monitoring zearalenone at trace levels in different edible vegetable oils. A comparison of MIP behavior with the ones of QuEChERS and liquid-liquid extraction was also performed, showing higher extraction rates and precision of MIP. Finally, the evolution of ZON contamination during the maize oil refining process was also investigated, demonstrating how the process is unable to completely remove (60%) ZON from oil samples.

Interaction of water activity and temperature on the growth, gene expression and aflatoxin production by Aspergillus flavus on paddy and polished rice

Water activity (a_w) and temperature are two pivotal environmental factors affecting Aspergillus flavus growth and aflatoxin production. Here, we found that AFB₁ production on polished rice can occur over a wider range of temperature × a_w levels than that on paddies. For fungal growth on polished rice, the optimum conditions were a_w 0.92-0.96 and 28-37 °C. The maximum amounts of AFB₁ on polished rice was observed at 33 °C and a_w 0.96. Compared to 33 °C, all tested genes of A. flavus on polished rice were significantly up-regulated at 25 °C under a_w 0.96. The late structural genes of pathway were significantly down-regulated at 37 °C under a_w 0.96, although aflR and aflS and most of early structural genes were up-regulated. Compared to a_w 0.96, most of pathway genes were significantly down-regulated at a_w 0.90 and 0.99 under 33 °C, although two regulatory genes were up-regulated at a_w 0.90.

Probability models for growth and aflatoxin B1 production as affected by intraspecies variability in Aspergillus flavus

The probability of growth and aflatoxin B₁ (AFB₁) production of 20 isolates of Aspergillus flavus were studied using a full factorial design with eight water activity levels (0.84-0.98 a_w) and six temperature levels (15-40 °C). Binary data obtained from growth studies were modelled using linear logistic regression analysis as a function of temperature, water activity and time for each isolate. In parallel, AFB₁ was extracted at different times from newly formed colonies (up to 20 mm in diameter). Although a total of 950 AFB₁ values over time for all conditions studied were recorded, they were not considered to be enough to build probability models over time, and therefore, only models at 30 days were built. The confidence intervals of the regression coefficients of the probability of growth models showed some differences among the 20 growth models. Further, to assess the growth/no growth and AFB₁/no- AFB₁ production boundaries, 0.05 and 0.5 probabilities were plotted at 30 days for all of the isolates. The boundaries for growth and AFB₁ showed that, in general, the conditions for growth were wider than those for AFB₁ production. The probability of growth and AFB₁ production seemed to be less variable among isolates than AFB₁ accumulation. Apart from the AFB₁ production probability models, using growth probability models for AFB₁ probability predictions could be, although conservative, a suitable alternative. Predictive mycology should include a number of isolates to generate data to build predictive models and take into account the genetic diversity of the species and thus make predictions as similar as possible to real fungal food contamination.