Modelling and predicting growth of psycrotolerant pseudomonads in milk and cottage cheese

Introduction: Predictive food microbiology models have the potential to evaluate the effect of temperature on microbial growth during distribution as well as be used to determine how product characteristics can be modified to reduce growth to an acceptable level.
Methods: Growth kinetics of psychrotolerant pseudomonads were determined using Bioscreen C experiments, challenge tests, storage trial and literature data. The effect of storage temperature and product characteristics on growth rates (μmax) were described using a simplified cardinal parameter model and the gamma concept. The developed broth/Bioscreen C model included the effect of temperature, pH, NaCl/aw, lactic, sorbic acid and their interaction (Le Marc et al., 2002). Then, the reference growth rate parameter (μref) was fitted to a total of 35 μmax-values from cottage cheese with cultured cream dressing.
Results: The new models were successfully validated, based on bias and accuracy factor, for 59 growth curves of psychrotolerant pseudomonads in dairy products. The acceptable simulation zone method showed the new model for cottage cheese to successfully predict growth of psychrotolerant pseudomonads at both constant and dynamic temperature storage conditions.
Conclusions: The present study developed and validated mathematical models to predict growth of psychrotolerant pseudomonads in chilled milk and cottage cheese with cultured cream dressing. The cottage cheese model can be used to evaluate the effect of product reformulations on growth.