Cardinal models to describe the effect of temperature and pH on the growth of Anoxybacillus flavithermus & Bacillus licheniformis.

Anoxybacillus flavithermus and Bacillus licheniformis are among the predominant spore-formers of heat-processed foods. To our knowledge, no systematic analysis of growth kinetic data of A. flavithermus or B. licheniformis is currently available. In the present study, the growth kinetics of A. flavithermus and B. licheniformis in broth at various temperature and pH conditions were studied. Cardinal models were used to model the effect of the above-mentioned factors on the growth rates. The estimated values for the cardinal parameters Tmin,Topt,Tmax,pHmin and pH1/2 for A. flavithermus were 28.70 ± 0.26, 61.23 ± 0.16 and 71.52 ± 0.32 °C, 5.52 ± 0.01 and 5.73 ± 0.01, respectively, while for B. licheniformis they were 11.68 ± 0.03, 48.05 ± 0.15, 57.14 ± 0.01 °C, 4.71 ± 0.01 and 5.670 ± 0.08, respectively. The growth behaviour of these spoilers was also investigated in a pea beverage at 62 and 49 °C, respectively, to adjust the models to this product. The adjusted models were further validated at static and dynamic conditions and demonstrated good performance with 85.7 and 97.4% of predicted populations for A. flavithermus and B. licheniformis, respectively, being within the -10%-10% relative error (RE) zone. The developed models can be useful tools in assessing the potential of spoilage of heat-processed foods including plant-based milk alternatives.

Modelling the Radial Growth of Geotrichum candidum: Effects of Temperature and Water Activity.

Modelling the growth of microorganisms in relation to environmental factors provides quantitative knowledge that can be used to predict their behaviour in foods. For this reason, the effects of temperature and water activity (aw) adjusted with NaCl on the surface growth of two isolates and one culture strain of Geotrichum candidum were studied. A dataset of growth parameters obtained from almost 600 growth curves was employed for secondary modelling with cardinal models (CMs). The theoretical minimal temperature resulting from the modelling of the mycelium proliferation rate ranged from -5.2 to -0.4 °C. Optimal and maximal temperatures were calculated and found to have narrow ranges of 25.4 to 28.0 °C and 34.2 to 37.6 °C, respectively. Cardinal aw values associated with radial growth (awmin from 0.948-0.960 and awopt from 0.992-0.993) confirmed the salt sensitivity of the species. Model goodness-of-fit was evaluated by the coefficient of determination R2, which ranged from 0.954 to 0.985, and RMSE, which ranged from 0.28 to 0.42. Substantially higher variability accompanied the lag time for growth modelling than the radial growth rate modelling despite the square root transformation of the reciprocal lag phase data (R2 = 0.685 to 0.808). Nevertheless, the findings demonstrate that the outputs of growth modelling can be applied to the quantitative evaluation of the roles of G. candidum in fresh cheese spoilage as well as the ripening of Camembert-type cheeses or various artisanal cheeses. Along with validation, the interactions with lactic acid bacteria can be included to improve the predictions of G. candidum in the future.

Effects of temperature, pH and water activity on the growth and the sporulation abilities of Bacillus subtilis BSB1.

Spore-forming bacteria are implicated in cases of food spoilage or food poisoning. In their sporulated form, they are resistant to physical and chemical treatments applied in the food industry and can persist throughout the food chain. The sporulation leads to an increase in the concentration of resistant forms in final products or food processing equipment. In order to identify sporulation environments in the food industry, it is necessary to be able to predict bacterial sporulation according to environmental factors. As sporulation occurs after bacterial growth, a kinetic model of growth-sporulation was used to describe the evolution of vegetative cells and spores through time. The effects of temperature, pH and water activity on the growth and the sporulation abilities of Bacillus subtilis BSB1 were modelled. The values of the growth boundaries were used as inputs to predict these effects. The good description of the sporulation kinetics by growth parameters suggests that the impact of the studied environmental factors is the same on both physiological process. Suboptimal conditions for growth delay the appearance of the first spores, and spores appear more synchronously in suboptimal conditions for growth. The developed model was also applicable to describe the growth and sporulation curves in changing temperature and pH conditions over time.

Development and validation of a predictive model for the effect of temperature, pH and water activity on the growth kinetics of Bacillus coagulans in non-refrigerated ready-to-eat food products.

A cardinal model (CM) for the effects of temperature (range: 32-59 °C), pH (range: 5.0-8.5) and water activity (aw) (range: 0.980-0.995) on Bacillus coagulans DSM 1 growth rate was developed in brain heart infusion broth (BHI), using the Bioscreen C method and further validated in selected food products. The estimated values for the cardinal parameters Tmin, Topt, Tmax, pHmin, pHopt, pHmax, [Formula: see text] and [Formula: see text] were 23.77 ± 0.19 °C, 52.89 ± 0.01 °C, 59.37 ± 0.07 °C, 4.70 ± 0.02, 6.43 ± 0.02, 8.56 ± 0.01, 0.969 ± 0.0007 and 0.998 ± 0.0011, respectively. The growth behaviour of B. coagulans was studied in five commercial non-refrigerated ready-to-eat food products under static conditions at 53 °C in order to estimate the optimum specific growth rate for each tested food product. The developed models were validated in the five selected food products under four different dynamic temperature profiles by comparing predicted and observed growth behaviour of B. coagulans. The validation results indicated a good performance of the model for all tested products with the overall Bias factor (Bf) and Accuracy factor (Af) estimated at 1.00 and 1.12, respectively. The developed model can be considered an effective tool in predicting B. coagulans growth and spoilage risks of non-refrigerated ready-to-eat food products during distribution and storage.