Application of modelling techniques in the food industry: determination of shelf-life for chilled foods

Microbiological modelling techniques (predictive microbiology, the Bayesian Markov Chain Monte Carlo method and a probability risk assessment approach) were combined to assess the shelf-life of an in-pack heat-treated, low-acid sauce intended to be marketed under chilled conditions. From a safety perspective, the product and process design for the chilled sauce was focused on the spore forming micro-organism Bacillus cereus. Different scenarios of time/temperature profiles in the food supply chain from manufacture up to the consumer were analysed in terms of growth of B. cereus (growth rate and lag phase) and of the consequence of this on the shelf-life. The end of the shelf-life was considered to be the time at which B. cereus reaches a concentration of 10 5 cfu g -1 . For example, we have found equivalence in term of model output between scenarios in which the temperature in both retail and at the consumer home was below 6°C for 60 days, below 8°C for 28 days, and below 10°C for 17 days. These results can be used to support decisions relating to new product design, such as maximum shelf-life, target markets and labelling.