论文和技术资料

Predictive food microbiology currently first requires experimental data for growth on fresh produce and then fitting an empirical or semi-empirical model to the data, making extrapolation to other conditions (temperature, type of produce) difficult. Herein, we develop a mechanistic model for the growth of human pathogenic bacteria (Escherichia coli O157:H7 and Salmonella spp.) on spinach using geometry acquired from µCT. By knowing the initial substrate profile on the leaf and number of bacteria, we show how you can predict the number of bacteria at any time, predict the colony morphologies and migration, and conduct what-if scenarios that will improve food safety mitigation strategies.