This research project aims to investigate the physiological and environmental factors controlling the response of selected bacterial foodborne pathogens to stress.
<p>The project has six objectives:<ol>
<li>To identify which factors enable a small fraction of a cell population to survive a stress treatment (such as osmotic stress).
<li>To measure the range of lag times that can be reasonably expected within unadapted cell populations.
<li>To determine the extent to which survival rates can be increased and lag times reduced by deliberate preadaption and selection of cells within the population.
<li>To develop a complex probability distribution for predicting survival rates within a cell population and the distribution of lag times.
<li>To apply the principles to a spray-drying operation.
<li>To transfer these principles to industry.
The Ministry of Agriculture, Fisheries and Food (MAFF) Micromodel has proved valuable to the industry by allowing companies to reduce the number of studies necessary to ensure the safety of products.
<p>In some products it has been possible to allow longer shelf lives, based on model predictions, resulting in substantial financial benefit.
<p>However, there are situations, mainly related to survival rather than growth rates, where the predictions are less reliable. For example, there are circumstances where a small fraction of bacterial pathogens such as salmonella survive an industrial process, such as drying.
These can cause food poisoning when the dried food (such as an instant soup powder) is rehydrated by consumers at low temperatures.
<p>Other examples exist where manufacturers feel that safety margins based on the model's predictions of survival rates may be over cautious.
This is because they are based on the responses obtained with physiologically active cells that may not apply to all food situations.
<p>Micromodel predictions are based on data obtained from cells that were not exposed to stress and so there is the possibility that lag times could be dangerously overestimated in some circumstances.
<p>These three situations are an example of our current inability to reliably predict the factors involved in microbial survival (such as survival rates, lag times, resuscitation or death rates) in foods.
This study aims to improve our ability to predict these survival factors by taking an account of the statistical distribution of the responses within a cell population.
<p>Find more about this project and other FSA food safety-related projects at the <a href="http://www.food.gov.uk/science/research/" target="_blank">Food Standards Agency Research webpage</a>.