Development and validation of predictive models for the effect of storage temperature and pH on the growth boundaries and kinetics of Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks.

This study was undertaken to provide quantitative tools for predicting the behavior of the spoilage bacterium Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks. In the first part of the study, a growth/no growth interface model was developed, predicting the probability of growth as a function of temperature and pH. For this purpose, the growth ability of A. acidoterrestris was studied at different combinations of temperature (15-45 °C) and pH (2.02-5.05). The minimum pH and temperature where growth was observed was 2.52 (at 35 and 45 °C) and 25 °C (at pH ≥ 3.32), respectively. Then a logistic polynomial regression model was fitted to the binary data (0: no growth, 1: growth) and, based on the concordance index (98.8%) and the Hosmer-Lemeshow statistic (6.226, P = 0.622), a satisfactory goodness of fit was demonstrated. In the second part of the study, the effects of temperature (25-55 °C) and pH (3.03-5.53) on A. acidoterrestris growth rate were investigated and quantitatively described using the cardinal temperature model with inflection and the cardinal pH model, respectively. The estimated values for the cardinal parameters Tmin, Tmax, Topt and pHmin, pHmax, pHopt were 18.11, 55.68, 48.60 °C and 2.93, 5.90, 4.22, respectively. The developed models were validated against growth data of A. acidoterrestris obtained in eight commercial pasteurized fruit drinks. The validation results showed a good performance of both models. In all cases where the growth/no growth interface model predicted a probability lower than 0.5, A. acidoterrestris was, indeed, not able to grow in the tested fruit drinks; similarly, when the model predicted a probability above 0.9, growth was observed in all cases. A good agreement was also observed between growth predicted by the kinetic model and the observed kinetics of A. acidoterrestris in fruit drinks at both static and dynamic temperature conditions.

Development and application of predictive models for fungal growth as tools to improve quality control in yogurt production.

The effect of storage temperature (0-40 °C) and inoculum size (10¹-105 spores) on the mycelium growth kinetics of 12 fungal species on yogurt were monitored. A cardinal model with inflection (CMI) was used to describe the effect of temperature on the growth rate (µ) and the lag time (λ) of each isolate. Significant differences on the temperature dependence of the mycelium growth between the tested species were observed. Depending on the strain, the estimated minimum, optimum and maximum temperature parameters for µ (T(min), T(opt), T(max)) ranged from -7.6 to 9.6, 19.5 to 37.8 and 29.8 to 46.9 °C, respectively. Only λ was found to be affected by the inoculum size and a linear relation between Ln (λ) and Log (inoculum size) was revealed. The inoculum level did not influence the values of T(min), T(opt) and T(max) for λ. Based on the above observations, the combined effect of inoculum size and temperature on λ was modeled using a modified CMI. The parameter λ(opt) (λ at optimum conditions) was expressed as a function of the inoculum size. Validation studies showed a good performance of the developed models. The application scheme of the models for improving fungi control in yogurt productions is discussed.