Open Access Bacillus cereus Cocktail Secondary Growth Model for the Food Industry

A cost-effective algorithm is presented, using a virtual dataset of growth rates from a cocktail of <i>Bacillus cereus</i> strains, for developing an open access, extended-range secondary growth model. Extended-range growth models can span the range of processing conditions typically used in food manufacturing and are therefore more relevant for industry. The open access extended-range secondary growth model for a cocktail of <i>B. cereus</i> strains was created using publicly available data, and the methodology can be adapted for modelling growth of other pathogens. An extended-range model can help manage <i>B. cereus</i> hazards in novel food categories with non-traditional formulations as estimations of <i>B. cereus</i> risks in these foods become more precise. This open access model, however, needs to be validated using data from <i>B. cereus</i> strain cocktails isolated from production facilities. Once validated, these independent factor models are valuable tools, in a pathogen decision support platform, which are tuned to local production environments. Such a platform can address the needs of current and future food product portfolios, effectively mitigating risks associated with <i>B. cereus</i> and other relevant pathogens.