Characterisation of the surface growth of in cheese agar media using predictive mathematical models.

The main objective of this work was to characterise the mycelial growth of , one of the fungal contaminants that appear frequently in the artisan cheese production environment. The study uses primary Baranyi and Huang models to compare their parameters and predict on cheese-based medium (CBA) under diverse environmental conditions (temperature range from 6 to 37 °C and 0 and 1 % NaCl concentration). However, the Baranyi model consistently estimated longer lag phases and higher surface growth rates () than the Huang model; both models showed adequate best-fit performance (exactly with the mean coefficient of determination = (0.993 ± 0.020 × 10). The groups of primary growth parameters were analysed against temperature using the cardinal model (CM) with the following main outputs. The optimal surface growth rates () on CBA were 6.8 and 6.5 mm/d calculated with the Baranyi and Huang models, respectively. They were reduced by approximately 46 % on the surface of the agar medium when 1 % NaCl was added. was estimated in a very narrow range of 32.1-32.5 °C from both primary data sets (0 % and 1 % NaCl). Similarly, values of 37.2 °C and 37.3 °C were estimated for the Baranyi and Huang models, respectively; however, they decreased at 2 °C in CBA with 1 % NaCl ( = 35.1 °C). The application of CM for sgr provided an estimation of the parameter with negative values that are considered only as a theoretical output. The results provide insight into the modelling and prediction of fungi growth as a function of time and salt concentration, including the times to detect visible mycelial growth of . The mere quantification of this phenomenon can be useful for practice. Adjusting the frequency of the cheese surface washing step with a salt solution at the early stage of ripening properly can prevent the growth of not only fast fungal growers.