Food Safety is of paramount concern to the consumer. We work with our clients and partners to help ensure food is safe to eat, and to prevent illness due to food-borne disease.

We carry out a range of research related to improving the safety of fresh and processed foods; including fungal and bacterial spoilage, safer postharvest storage systems and rapid sensing and diagnostics in food.

Our research addresses the demand for safe food with a longer shelf-life, without preservatives and additives, but which retains good nutritional value, taste and appearance.  

Our work has a considerable impact in the real-world. Our experimental and modelling approaches allow us to control the growth of economically important microbes (eg. mycotoxin producers, food spoilage agents, food pathogens, bioremediation and bio-control agents and algae for biofuel production) which leads to increased food safety, reduces waste and enhances sustainability.

Our integration of rapid experimental procedures and bio-mathematics has allowed us to develop new models which can predict mycotoxin growth in the presence of multiple hurdles in food (i.e. mild heat, mild acidity, low salt levels, refridgeration). These models have allowed us to create a large database of microbial growth (in excess of 500 million data points) for 20 different spoilage and pathogenic organisms under a multitude of different interacting environmental factors – this is now the basis of Nestle’s predictive microbiological modelling capability. With funding from the Food Standards Agency (FSA) we are now developing new stochastic models of microbial injury to investigate the effect of mild thermal processing on the survival and growth of pathogenic organisms.

We have developed predictive capabilities and software that will allow us to model the growth of food spoilage organisms. Such research can be used to control mycotoxin production and assist with risk analysis and product development.

Integration of molecular, ecological and phenotypic factors used by mycotoxin producing strains has enabled us to develop new models to examine the relative risk of contamination of food commodities, especially under changing climate conditions and different climate change scenarios.

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