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Researchers develop botulism prediction model

2021-06-03 foodsafetynews

Tag: botulism prediction model

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A mathematical model has been developed by scientists in Denmark to control the risk from Clostridium botulinum in certain foods.

The tool could be used in development or reformulation of fresh and lightly preserved seafood and poultry products that do not support the growth of Clostridium botulinum. Botulism poisoning is a serious but rare illness caused by toxins produced by Clostridium botulinum bacteria.

Researchers at the National Food Institute, Technical University of Denmark developed and evaluated the model for non-proteolytic Clostridium botulinum to predict the effect of temperature, salt/water activity (aw), pH, acetic, benzoic, citric, lactic and sorbic acids on growth responses.

For refrigerated products, guidelines for controlling Clostridium botulinum indicate that water in them should have a salt content of at least 3.5 percent but this hampers efforts to develop products with reduced salt.

Salt reduction challenge
If food producers want to launch items that contain less salt, they have to do laboratory experiments to document that a change in recipe will not compromise food safety.

Predictive food microbiology models can simulate the combined effect of different product characteristics and storage conditions as previously shown with Listeria monocytogenes.

The developed model can predict whether a particular recipe for chilled products can prevent the growth of Clostridium botulinum and production of the toxin. This does not mean it can entirely substitute challenge testing, but the number of tests for product development or reformulation can be reduced.

Several mathematical models for the growth or toxin formation of Clostridium botulinum exist but they don’t include the preservatives acetic, benzoic, citric and sorbic acids which are important for lightly preserved seafood and various other products.

Researchers used four Clostridium botulinum isolates that cannot form the dangerous toxins as surrogates for predicting the absence of growth and of toxin formation in different recipes, according to the study published in the International Journal of Food Microbiology.

evaluation and potential expansion
For model evaluation, 40 challenge tests with fresh and lightly preserved seafood were performed. It was evaluated with 94 growth rates and 432 time to toxin formation data from scientific literature for seafood, poultry, meat, pasta and prepared meals.

The model correctly predicted 93.8 percent of the growth responses with 5.6 percent being fail-safe and less than 1 percent fail-dangerous. Fail-safe is when growth was predicted when none was observed and fail-dangerous is no growth predicted when growth was seen.

The study was supported by the Danish Food Industry Agency as part of a project between DTU Food and Royal Greenland Seafood A/S.

More data are needed to evaluate the model with meat, prepared meals and vegetable products. Future studies may extend the model with terms for smoke components/phenol, modified atmosphere/Carbon dioxide, nitrite and nisin to expand its applicability for smoked and modified atmosphere packed food, cured meat and processed cheese.

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