Browsing Articles publicats (Tecnologia, Enginyeria i Ciència dels Aliments) by Author "Aldars García, Laila"
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- ItemOpen AccessAn attempt to model the probability of growth and aflatoxin B1 production of Aspergillus flavus under non-isothermal conditions in pistachio nuts(Elsevier, 2015) Aldars García, Laila; Ramos Girona, Antonio J.; Sanchís Almenar, Vicente; Marín Sillué, SòniaHuman exposure to aflatoxins in foods is of great concern. The aim of this work was to use predictive mycology as a strategy to mitigate the aflatoxin burden in pistachio nuts postharvest. The probability of growth and aflatoxin B1 (AFB1) production of aflatoxigenic Aspergillus flavus, isolated from pistachio nuts, under static and non-isothermal conditions was studied. Four theoretical temperature scenarios, including temperature levels observed in pistachio nuts during shipping and storage, were used. Two types of inoculum were included: a cocktail of 25 A. flavus isolates and a single isolate inoculum. Initial water activity was adjusted to 0.87. Logistic models, with temperature and time as explanatory variables, were fitted to the probability of growth and AFB1 production under a constant temperature. Subsequently, they were used to predict probabilities under non-isothermal scenarios, with levels of concordance from 90 to 100% in most of the cases. Furthermore, the presence of AFB1 in pistachio nuts could be correctly predicted in 70-81 % of the cases from a growth model developed in pistachio nuts, and in 67-81% of the cases from an AFB1 model developed in pistachio agar. The information obtained in the present work could be used by producers and processors to predict the time for AFB1 production by A. flavus on pistachio nuts during transport and storage.
- ItemOpen AccessAssessment 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(Elsevier, 2018) Aldars García, Laila; Marín Sillué, Sònia; Sanchís Almenar, Vicente; Magan, Naresh; Medina, AngelIntraspecies 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 aw 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.
- ItemOpen AccessModeling postharvest mycotoxins in foods: recent research(Elsevier, 2016) Aldars García, Laila; Ramos Girona, Antonio J.; Sanchís Almenar, Vicente; Marín Sillué, SòniaAvailable information on the prediction of postharvest production of mycotoxins in recent years is reviewed. Predictive mycology has been focused mainly on fungal growth whereas studies on prediction of mycotoxins in foods are scarce. Modeling mycotoxin production is challenging due to the high variability in mycotoxigenic potential among species and isolates. Besides mycotoxin biosynthesis pathways and factors influencing them are still poorly understood. Baranyi and Luedeking-Piret models have been recently used as primary models for mycotoxin prediction, while for secondary modeling, polynomial approaches have been used. Furthermore, probability models can be a different alternative. In any case, media for data generation, intraspecies variability, and microbial interactions should not be disregarded before model application in food safety management systems.
- ItemOpen AccessModelling the Probability of Growth and Aflatoxin B1 Production of Aspergillus Flavus under Changing Temperature Conditions in Pistachio Nuts(Elsevier, 2016) Aldars García, Laila; Ramos Girona, Antonio J.; Sanchís Almenar, Vicente; Marín Sillué, SòniaThe aim of this work was to use probability models for the prediction of growth and aflatoxin production by Aspergillus flavus as a strategy to mitigate the aflatoxin presence in pistachio nuts during postharvest. Logistic models, with temperature and time as explanatory variables, were fitted to the probability of growth and aflatoxin B1 (AFB1) production under constant temperature levels, afterwards they were used to predict probabilities under non-isothermal scenarios. The models obtained showed levels of concordance from 80 to 100% in most of the cases. Moreover, the presence of AFB1 in pistachio nuts could be correctly predicted through AFB1 models developed in agar medium or through growth models in pistachio nuts. These findings can support decision making, at transport and storage level, and could be used by producers and processors to predict the time for AFB1 production by A. flavus in pistachio nuts in postharvest.
- ItemOpen AccessProbability models for growth and aflatoxin B1 production as affected by intraspecies variability in Aspergillus flavus(Elsevier, 2018) Aldars García, Laila; Berman, María; Ortiz Solà, Jordi; Ramos Girona, Antonio J.; Marín Sillué, SòniaThe 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 (0.84e0.98 aw) and six temperature levels (15e40 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.
- ItemRestrictedSingle 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(Elsevier, 2017) Aldars García, Laila; Sanchís Almenar, Vicente; Ramos Girona, Antonio J.; Marín Sillué, SòniaThe 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 colonywas 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 3–5 days 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 9 days). 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.
- ItemRestrictedTime-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(Elsevier, 2017) Aldars García, Laila; Sanchís Almenar, Vicente; Ramos Girona, Antonio J.; Marín Sillué, SòniaThe 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.