Comparing Nonsynergistic Gamma Models with Interaction Models To Predict Growth of Emetic Bacillus cereus when Using Combinations of pH and Individual Undissociated Acids as Growth-Limiting Factors

A combination of multiple hurdles to limit microbial growth is frequently applied in foods to achieve an overall level of protection. Quantification of hurdle technology aims at identifying synergistic or multiplicative effects and is still being developed. The gamma hypothesis states that inhibitory environmental factors aiming at limiting microbial growth rates combine in a multiplicative manner rather than synergistically. Its validity was tested here with respect to the use of pH and various concentrations of undissociated acids, i.e., acetic, lactic, propionic, and formic acids, to control growth of Bacillus cereus in brain heart infusion broth. The key growth parameter considered was the maximum specific growth rate, mu(max), as observed by determination of optical density. A variety of models from the literature describing the effects of various pH values and undissociated acid concentrations on mu(max) were fitted to experimental data sets and compared based on a predefined set of selection criteria, and the best models were selected. The cardinal model developed by Rosso (for pH dependency) and the model developed by Luong (for undissociated acid) were found to provide the best fit and were combined in a gamma model with good predictive performance. The introduction of synergy factors into the models was not able to improve the quality of the prediction. On the contrary, inclusion of synergy factors led to an overestimation of the growth boundary, with the inherent possibility of leading to underestimation of the risk under the conditions tested in this research.