Modeling the effect of temperature on the growth rate and lag phase of Penicillium expansum in apples.

TítuloModeling the effect of temperature on the growth rate and lag phase of Penicillium expansum in apples.
Publication TypeJournal Article
Year of Publication2007
AuthorsBaert, K, Valero, A, De Meulenaer, B, Samapundo, S, Ahmed, MM, Bo, L, Debevere, J, Devlieghere, F
JournalInt J Food Microbiol
Date Published2007 Sep 15
Palabras claveAgar, Colony Count, Microbial, Food Contamination, Food Microbiology, Kinetics, Linear Models, Malus, Mathematics, Models, Biological, Penicillium, Predictive Value of Tests, Reproducibility of Results, Risk Assessment, Sensitivity and Specificity, Temperature

The objective of the present study was to develop validated models that describe the effect of storage temperature on the growth rate and lag phase of six Penicillium expansum strains. The growth of the selected strains was therefore studied on Apple Puree Agar Medium (APAM) at 30, 25, 16, 10, 4 and 2 degrees C. Growth rates and lag phases were estimated using linear regression. Several secondary models were evaluated and for the growth rate, a modification of the extended Ratkowsky model was selected. Regarding the lag phase, the Arrhenius-Davey model provided the best adjustment to the observed data. Model validation was performed in two steps. Firstly, the developed models were validated on APAM. The obtained bias factors (Bf) ranged from 0.91 to 1.14 and the accuracy factors (Af) were <1.2 for the validation performed on APAM, indicating that the models were good predictors of the true mean colony growth rate and lag phase. Afterwards, an external validation was carried out in apples. For the growth rate, Bf ranged from 0.64 to 0.81 and Af<1.39, indicating conservative predictions. On the contrary for the lag phase, a clear deviation was observed between predictions and observed values on apples (0.35<Bf<0.7 and Af>1.6). These results highlight that the use of simulation or synthetic media for the development of predictive models for the lag phase of moulds can lead to inadequate predictions and that a validation on the real food matrix is necessary. Application of the developed models is possible in the framework of Quantitative Risk Assessment to develop control strategies against blue mould rot in apple and enables the inclusion of strain variability. However, possible underestimation of the lag phase should be taken into account.

Alternate JournalInt. J. Food Microbiol.