Basis of predictive mycology

University of Burgundy, Dijon, Bourgogne, France
International Journal of Food Microbiology (Impact Factor: 3.08). 05/2005; 100(1-3):187-96. DOI: 10.1016/j.ijfoodmicro.2004.10.013
Source: PubMed


For over 20 years, predictive microbiology focused on food-pathogenic bacteria. Few studies concerned modelling fungal development. On one hand, most of food mycologists are not familiar with modelling techniques; on the other hand, people involved in modelling are developing tools dedicated to bacteria. Therefore, there is a tendency to extend the use of models that were developed for bacteria to moulds. However, some mould specificities should be taken into account. The use of specific models for predicting germination and growth of fungi was advocated previously []. This paper provides a short review of fungal modelling studies.

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Available from: Philippe Dantigny
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    • "Predictive microbiology is a useful tool to estimate microbial growth parameters under experimental as well as in food system. For fungi a simple and direct method to evaluate mycelium growth on the surface of solid substrate is to measure colony diameter over period of time (Dantigny et al., 2005b). There are detailed reports about different models for predicting fungal growth and toxin production under different treatment conditions (Garcia et al., 2009). "
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    ABSTRACT: The current study aimed at characterizing the chemical components of betel leaf (Piper betle L. var. Tamluk Mitha) essential oil (BLEO) and modelling its effect on growth of Penicillium expansum on semi-synthetic medium. Gas chromatography-mass spectrophotometry (GC-MS) analysis of BLEO revealed the presence of different bioactive phenolic compounds in significant amounts. Among 46 different components identified, chavibetol (22.0%), estragole (15.8%), β-cubebene (13.6%), chavicol (11.8%), and caryophyllene (11.3%) were found to be the major compounds of BLEO. A disc diffusion and disc volatilization method were used to evaluate antifungal activity of the oil against a selected food spoilage mould. The logistic model was used to study the kinetics of spore germination. Prediction and validation of antifungal effect of BLEO was performed on semi-synthetic medium (apple juice agar) using predictive microbiological tools. The Baranyi and Roberts model was used to estimate maximum growth rate (μmax in mm/day) and apparent lag time (λ in days) of the mould. Secondary modelling was performed using a re-parameterized Monod-type equation based on cardinal values to study the effect of different BLEO concentration on estimated growth parameters. Emax (minimum concentration of oil at which mould growth was inhibited) and MIC (minimum inhibitory concentration of BLEO at which lag time is infinite) value of BLEO against P. expansum was estimated to be 0.56 and 0.74 μl/ml, respectively, which was found to be similar on potato dextrose agar (PDA) as well as apple juice agar (AJA) medium. The correlation between estimated growth parameters of the mould on both the media was obtained with satisfactory statistical indices (R2 and RMSE). This study revealed inhibitory efficacy of BLEO on spore germination, mycelial growth and apparent lag time of P. expansum in a dose-dependent manner. Hence, BLEO has potential to be used as a natural food preservative.
    Full-text · Article · Oct 2015 · International Journal of Food Microbiology
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    • "Secondary models normally used for modeling growth parameters of bacteria have been used for parameters of moulds (Dantigny et al. 2005), like the Square Root and Arrhenius-Davey models. The dependence of µ max and λ parameters on the temperature were described by the Square Root model (Ratkowsky et al. 1982) "
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    ABSTRACT: The aim of this study was to establish primary and secondary models to describe the growth kinetics of Byssochlamys fulva on solidified apple juice at different temperatures. B. fulva was inoculated on solidified apple juice at 10, 15, 20, 25 and 30 °C. Linear-with-breakpoint, Baranyi and Roberts, and Huang primary models (without upper asymptote) were fitted to the data, and they showed good ability to describe the growth kinetics. B. fulva showed longer adaptation time on apple juice than on culture medium, but growth rates were similar as reported in the literature. The dependence of µmax and λ parameters on temperature was described with Square Root and Arrhenius-Davey secondary models, respectively. These models were important to establish process/storage conditions and apple juice shelf life.
    Full-text · Article · Aug 2014 · Brazilian Archives of Biology and Technology
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    • "Many available data confirm high biocompatibility of silica nanotubes with human cells, especially at lower concentrations (0.05–0.005 μg/ml) (Dantigny et al. 2005). Likewise, TiO2 alone has no effect on cell proliferation, but it becomes cytotoxic after UV irradiation (Nan et al. 2008; Kubota et al. 1994). "
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