An attempt to model the probability of growth and aflatoxin B1 production of Aspergillus flavus under non-isothermal conditions in pistachio nuts

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.

Mycotoxins in Pistachios (Pistacia vera L.): Methods for Determination, Occurrence, Decontamination

The consumption of pistachios (Pistacia vera L.) has been increasing, given their important benefit to human health. In addition to being an excellent nutritional source, they have been associated with chemical hazards, such as mycotoxins, resulting in fungal contamination and its secondary metabolism. Aflatoxins (AFs) are the most common mycotoxins in pistachio and the most toxic to humans, with hepatotoxic effects. More mycotoxins such as ochratoxin A (OTA), fumonisins (FBs), zearalenone (ZEA) and trichothecenes (T2, HT2 and DON) and emerging mycotoxins have been involved in nuts. Because of the low levels of concentration and the complexity of the matrix, the determination techniques must be very sensitive. The present paper carries out an extensive review of the state of the art of the determination of mycotoxins in pistachios, concerning the trends in analytical methodologies for their determination and the levels detected as a result of its contamination. Screening methods based on immunoassays are useful due to their simplicity and rapid response. Liquid chromatography (LC) is the gold standard with new improvements to enhance accuracy, precision and sensitivity and a lower detection limit. The reduction of Aspergillus' and aflatoxins' contamination is important to minimize the public health risks. While prevention, mostly in pre-harvest, is the most effective and preferable measure to avoid mycotoxin contamination, there is an increased number of decontamination processes which will also be addressed in this review.

Impact of granite irradiation on aflatoxin reduction in pistachio

In this research with the effect of radioactive granite gamma radiation, the reduction of aflatoxin B1 in pistachios was examined in three steps. In the first step, the aflatoxin reduction in small packets by granite bed was tested. In this step, the aflatoxin level of 300 g pistachios packets was reduced up to 81.3 ± 1.5 percent by 4 kg granite bed after 4 days. After observation of aflatoxin reduction by granite bed, the second step was done with increasing the granite and pistachio mass and irradiation time. In this step, the aflatoxin level of 1 kg pistachios was reduced up to 4949 ± 2.6 percent by 6 kg granite after 9 days. According to the results, the aflatoxin reduction of 1 kg pistachios by 1 kg granite after 1 days (as aflatoxin Reduction Coefficient (ARC)) was calculated as ARC = 0.0090 ± 0.0025 (kg. day)^-1. The aflatoxin types of detected in this research were B1 and B2 types that AFB2 level was much less than one. Therefore the effect of granite irradiation on AFB2 reduction wasn't considered. The final step was designed for testing the aflatoxin Reduction Coefficient (ARC). This step was shown that the confidence level between practical result and aflatoxin Reduction Coefficient (ARC) result is about 97 percent. The results indicated that the level of fat and protein of pistachios by granite gamma radiation did not change after 9 days. Therefore the granite irradiation can be used for aflatoxin reduction of pistachios.

Interacting Abiotic Factors Affect Growth and Aflatoxin B1 Production Profiles of Aspergillus flavus Strains on Pistachio-Based Matrices and Pistachio Nuts

Pistachio nuts are an economically important commodity produced by many countries. They can be colonized by mycotoxigenic fungi, especially Aspergillus flavus, resulting in contamination with aflatoxins (AFs), especially aflatoxin B₁ (AFB₁), a Class 1a carcinogen. The objectives were to examine the effect of interactions between the two key abiotic factors, temperature and water activity (a _w ) on (a) in vitro growth and AFB₁ production by four strains of A. flavus isolated from pistachio nuts, on a milled pistachio nut medium modified ionically (NaCl) and non-ionically (glycerol) in the range 20-35°C and 0.995-0.85 a _w , (b) colonization of layers of raw pistachio nuts stored at different interacting temperature x a _w conditions and on relative AFB₁ production and (c) develop models to produce contour maps of the optimal and marginal boundary conditions for growth and AFB₁ production by up to 4 strains of this species. On pistachio nut-based media, optimum growth of four strains of A. flavus was at 0.98-0.95 a _w and 30-35°C. Optimum AFB₁ production was at 30-35°C and 0.98 a _w . No significant differences in growth was found on ionic and non-ionically modified media. Colonization of layers of raw pistachio nuts was slower and contamination with AFB₁ significantly less than in in vitro studies. Contour maps based on the pooled data for up to four strains (in vitro, in situ) showed the optimum and marginal conditions for growth and AFB₁ production. These data can be used to identify those conditions which represent a high, intermediate or low risk of colonization and AFB₁ contamination in the pistachio nut processing chain. These results are discussed in the context of the development of appropriate intervention strategies to minimize AFB₁ contamination of this economically important commodity.

Effect of Drying Temperatures and Exposure Times on Aspergillus flavus Growth and Aflatoxin Production on Artificially Inoculated Hazelnuts

ABSTRACT

Aspergillus flavus may colonize hazelnuts and produce aflatoxins in the field and during storage. The main purpose of this study was to investigate the influence of drying temperature and exposure times on the viability of A. flavus and its ability to produce aflatoxins during the drying process and storage. Hazelnuts were inoculated with A. flavus and dried at different temperatures to reach 6% moisture content and a water activity (aw) of 0.71, a commercial requirement to avoid fungal development and aflatoxin contamination. Hazelnuts were dried at 30, 35, 40, 45, and 50°C and subsequently stored at 25°C for 14 days. After drying at 30, 35, and 40°C, increased amounts of A. flavus were evident, with the highest concentration occurring after drying at 35°C ([6.1 ± 2.4] × 106A. flavus CFU/g). At these temperatures, aflatoxins were detected only at 30 and 35°C. Aflatoxins, however, were present at higher levels after drying at 30°C, with concentrations of 1.93 ± 0.77 μg/g for aflatoxin B1 (AFB1) and 0.11 ± 0.04 μg/g for aflatoxin B2 (AFB2). After 14 days of storage, the highest A. flavus concentration and the highest levels of mycotoxins were detected in samples treated at 35°C ([8.2 ± 2.1] × 107A. flavus CFU/g and 9.30 ± 1.58 μg/g and 0.89 ± 0.08 μg/g for AFB1 and AFB2, respectively). In hazelnuts dried at 45 or 50°C, no aflatoxins were found either after drying or storage, and a reduction of A. flavus viable conidia was observed, suggesting that a shorter and warmer drying is essential to guarantee nut safety. The lowest temperature that guarantees the lack of aflatoxins should be selected to maintain the organoleptic quality of hazelnuts. Therefore, 45°C should be the recommended drying temperature to limit A. flavus growth and aflatoxin contamination on hazelnuts.

HIGHLIGHTS

Assessment of intraspecies variability in fungal growth initiation of Aspergillus flavus and aflatoxin B1 production under static and changing temperature levels using different initial conidial inoculum levels

Intraspecies variability in fungal growth and mycotoxin production has important implications for food safety. Using the Bioscreen C we have examined spectrophotometrically intraspecies variability of A. flavus using 10 isolates under different environments, including temperature shifts, in terms of growth and aflatoxin B₁ (AFB₁) production. Five high and five low AFB₁ producers were examined. The study was conducted at 5 isothermal conditions (from 15 to 37 °C) and 4 dynamic scenarios (between 15 and 30 °C). The experiments were carried out in a semisolid YES medium at 0.92 a_w and two inoculum levels, 10² and 10³ spores/mL. The Time to Detection (TTD) of growth initiation was determined and modelled as a function of temperature through a polynomial equation and the model was used to predict TTD under temperature upshifts conditions using a novel approach. The results obtained in this study have shown that a model can be developed to describe the effect of temperature upshifts on the TTD for all the studied isolates and inoculum levels. Isolate variability increased as the growth conditions became more stressful and with a lower inoculum level. Inoculum level affected the intraspecies variability but not the repeatability of the experiments. In dynamic conditions, isolate responses depended both on the temperature shift and, predominantly, the final temperature level. AFB₁ production was highly variable among the isolates and greatly depended on temperature (optimum temperature at 30-35 °C) and inoculum levels, with often higher production with lower inoculum. This suggests that, from an ecological point of view, the potential isolate variability and interaction with dynamic conditions should be taken into account in developing strategies to control growth and predicting mycotoxin risks by mycotoxigenic fungi.

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.

Single vs multiple-spore inoculum effect on growth kinetic parameters and modeled probabilities of growth and aflatoxin B1 production of Aspergillus flavus on pistachio extract agar

The objective of the present study was to assess the differences in modeled growth/AFB1 production probability and kinetic growth parameters for Aspergillus flavus inoculated as single spores or in a concentrated inoculation point (~500 spores). The experiment was carried out at 25°C and at two water activities (0.85 and 0.87) on pistachio extract agar (3%). Binary data obtained from growth and AFB1 studies were modeled using linear logistic regression analysis. The radial growth curve for each colony was fitted to a linear model for the estimation of the lag phase for growth and the mycelial growth rate. In general, radial growth rate and lag phase for growth were not normally distributed and both of them were affected by the inoculation type, with the lag phase for growth being more affected. Changing from the multiple spore to the single spore inoculation led to a delay of approximately 3-5days on the lag phase and higher growth rates for the multiple spore experiment were found. The same trend was observed on the probability models, with lower predicted probabilities when colonies came up from single spores, for both growth and AFB1 production probabilities. Comparing both types of models, it was concluded that a clear overestimation of the lag phase for growth occurred using the linear model, but only in the multiple spore experiment. Multiple spore inoculum gave very similar estimated time to reach some set probabilities (t10, t50 and t100) for growth or AFB1 production due to the abruptness of the logistic curve developed. The observed differences suggest that inoculum concentration greatly affects the outcome of the predictive models, the estimated times to growth/AFB1 production being much earlier for the concentrated inoculum than for a single spore colony (up to 9days). Thus the number of spores used to generate data in predictive mycology experiments should be carefully controlled in order to predict as accurately as possible the fungal behavior in a foodstuff.

Time-course of germination, initiation of mycelium proliferation and probability of visible growth and detectable AFB1 production of an isolate of Aspergillus flavus on pistachio extract agar

The aim of this work was to assess the temporal relationship among quantified germination, mycelial growth and aflatoxin B₁ (AFB1) production from colonies coming from single spores, in order to find the best way to predict as accurately as possible the presence of AFB1 at the early stages of contamination. Germination, mycelial growth, probability of growth and probability of AFB1 production of an isolate of Aspergillus flavus were determined at 25 °C and two water activities (0.85 and 0.87) on 3% Pistachio Extract Agar (PEA). The percentage of germinated spores versus time was fitted to the modified Gompertz equation for the estimation of the germination parameters (geometrical germination time and germination rate). The radial growth curve for each colony was fitted to a linear model for the estimation of the apparent lag time for growth and the growth rate, and besides the time to visible growth was estimated. Binary data obtained from growth and AFB1 studies were modeled using logistic regression analysis. Both water activities led to a similar fungal growth and AFB1 production. In this study, given the suboptimal set conditions, it has been observed that germination is a stage far from the AFB1 production process. Once the probability of growth started to increase it took 6 days to produce AFB1, and when probability of growth was 100%, only a 40-57% probability of detection of AFB1 production was predicted. Moreover, colony sizes with a radius of 1-2 mm could be a helpful indicator of the possible AFB1 contamination in the commodity. Despite growth models may overestimate the presence of AFB1, their use would be a helpful tool for producers and manufacturers; from our data 5% probability of AFB1 production (initiation of production) would occur when a minimum of 60% probability of growth is observed. Legal restrictions are quite severe for these toxins, thus their control from the early stages of contamination throughout the food chain is of paramount importance.

Metabolites of Microbial Origin with an Impact on Health: Ochratoxin A and Biogenic Amines

Safety and quality are significant challenges for food; namely, safety represents a big threat all over the world and is one of the most important goal to be achieved in both Western Society and Developing Countries. Wine safety mainly relies upon some metabolites and many of them are of microbial origin. The main goal of this review is a focus on two kinds of compounds (biogenic amines and mycotoxins, mainly Ochratoxin A) for their deleterious effects on health. For each class of compounds, we will focus on two different traits: (a) synthesis of the compounds in wine, with a brief description of the most important microorganisms and factors leading this phenomenon; (b) prevention and/or correction strategies and new trends. In addition, there is a focus on a recent predictive tool able to predict toxin contamination of grape, in order to perform some prevention approaches and achieve safe wine.