Improve accuracy of predictive microbiology.

Understanding the risk of foodborne illness depends on knowing how environmental conditions can affect the behavior, i.e., growth, survival and decline, of a pathogen. This knowledge can then be translated into mathematical models that allow us to estimate the behavior of a specific pathogen under unique environmental conditions.

Such models are used by food companies to define critical control points (CCPs) in food processing operations, and in the subsequent development and implementation of HACCP food safety systems. In addition, these models can be used by risk assessors to define management decisions that may reduce the risk of foodborne disease.

Food poisoning caused by pathogens is still on the increase throughout Europe and elsewhere, despite general improvements in hygiene and food safety. More than 60% of outbreaks are associated with meat, fresh fruit and salads. The contaminating pathogens are mostly located on the surface of foods. So, controlling surface pasteurization processes is a very important issue.

An E.U.-funded research project is underway to develop more accurate predictive models involving the surface pasteurization of foods. The overall objective of scientists is to improve safety by optimizing thermal processing control, in particular by using high-temperature short-time (HTST) processing, heating and cooling cycles. The researchers would also like to improve slow thermal processing control. They hope to reach their objectives by establishing more accurate models of microbial death.

To date, researchers have:

* Constructed an accurate and very flexible apparatus which may heat or cool food between 5 C and 120 C in both wet and dry environments. The temperature cycles are repeatable within more or less 2 C, and the accuracy of measuring food surface temperatures is better than within 1 C.

* Introduced a lux-gene into the test pathogens, allowing these to glow only when they are alive. Scientists can quickly measure the effect of thermal cycles as the bioluminescence fades when the treatment is effective.

* Created heat transfer and microbial death models, to be verified against data obtained by the ongoing research. The data will be combined to create a model to predict how temperature changes impact microbial death on food surfaces.

Further information. Judith Evans, University of Bristol, Food Refrigeration and Process Engineering Research Center, Churchill Building, Langford North Somerset, BS40 5DU Bristol, England, U.K.; phone: [phone]; fax: [phone]; URL: www.bristol.ac.uk.