Czech Journal of Food Sciences, Volume (43), No (1), Year (2025-2) , Pages (8-16)

Title : ( Application predictive modelling of Penicillium roqueforti germination in environmental conditions in cake )

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Abstract

This study aimed to predict the germination of Penicillium roqueforti as one of the most important moulds in cake in certain environmental conditions that lead to cake spoilage. The germination rate of P. roqueforti was evalu- ated by culturing in the Yeast Extract Glucose Chloramphenicol Agar medium with different pH, water activity (aw), and inoculum size at three levels of temperature (15, 25, 30 °C) during 60 days by the factorial experiment. The re- sults of analysis of variance (ANOVA) proved that environmental conditions affect germination significantly (P < 0.05). Predictive modelling illustrated that the temperature did not affect germination significantly, while no germination was seen at aw = 0.65. The minimum lag phase of germination was observed at aw = 0.9, pH = 6.5, and inoculum size of 1 000 spores per mL. The logistic model was found to be more precise for fitting the data of P. roqueforti in cakes.

Keywords

mould germination; modelling; NeuroSolutions
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@article{paperid:1102131,
author = {},
title = {Application predictive modelling of Penicillium roqueforti germination in environmental conditions in cake},
journal = {Czech Journal of Food Sciences},
year = {2025},
volume = {43},
number = {1},
month = {February},
issn = {1212-1800},
pages = {8--16},
numpages = {8},
keywords = {mould germination; modelling; NeuroSolutions},
}

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%0 Journal Article
%T Application predictive modelling of Penicillium roqueforti germination in environmental conditions in cake
%A
%J Czech Journal of Food Sciences
%@ 1212-1800
%D 2025

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