Development of accurate predictive models for the assessment of the survival of Campylobacter jejuni and C. coli under food-relevant conditions.
New predictive models are urgently needed to inform the food industry about treatments to eliminate Campylobacter from food products.
Data used in current models does not:
- Take into account the interactions between food and Campylobacter.
- Recognise the population biology or prior ‘environmental experience’ of Campylobacter. For example, Campylobacter (Figure 1) responds to heat exposure (Hughes et al., 2009 and 2010) differently than Salmonella (Figure 2) following pre-chilling (Humphrey, 1990).
Figure 1: Campylobacter heated at 52°C- effect of pre-chill (blue), and without prior treatment (red)
Figure 2: Salmonella heated at 52°C- effect of pre-chill (blue), and without prior treatment (red)
- Allow recovery of injured cells, with studies often using media containing antimicrobials which may prevent the recovery of sub-lethally injured bacteria.
- To use laboratory techniques, which take account of the biology and physiology of Campylobacter.
- To examine survival of Campylobacter at high temperature in laboratory media.
- To investigate the interaction of Campylobacter with food matrices and its influence of survival at high temperatures.
- To investigate the survival and growth of Campylobacter in food interiors after non-lethal heat treatments.
- To use the data generated to model and predict the growth (where relevant) and survival of Campylobacter in food and food-related environments, with associated confidence intervals.
This project is funded by the Food Standards Agency (FSA).