Improving infant formula safety checks: research
Producers of infant formula employ comprehensive food safety systems and use product testing to ensure the systems are working. A study from the University of Illinois Urbana-Champaign found that some testing methods are more powerful than others at catching contaminants.
To catch risky pathogens like Cronobacter, the researchers found that it is better to space out samples over time than to randomly sample from the product as it is being produced. Furthermore, while taking more samples of a product increases the chance to catch a pathogen, there is a point after which it is unlikely to increase safety.
Matthew J Stasiewicz, project lead and associate professor in the Department of Food Science and Human Nutrition (FSHM), said existing sample and testing guidance is powerful, but more research is needed into patterns of contamination in infant formula production.
Safety systems for infant formula production include control points such as milk pasteurisation and steps to prevent contamination. Product testing is an additional tool that producers are using to verify safety and it must be powerful enough to detect risks before a product is released on the market.
The study used computer models to simulate sampling and testing finished formula to gauge the power of current national and international guidelines for testing programs and suggest ways to do better.
The process was based on detecting a realistic hazard, defined by what was observed in samples from Cronobacter-contaminated batches produced in Europe in the 2010s, the most current data available.
Safety plans with 30 or more grab samples had a very high probability of detecting hazards; however, there was a point of diminishing returns, where very high sample numbers would not be meaningfully more powerful, such as testing every can produced. The researchers concluded that systematic or stratified random sampling patterns are more effective than simple random sampling for bulk powder testing.
“In addition to analysing relevant scenarios, we built a web app that allows industry stakeholders to simulate various sampling scenarios and gain a deeper understanding of the effectiveness of sampling plans specific to their plants. With this knowledge, producers can proactively address risks and optimise current sampling practices,” said Minho Kim, lead author and a doctoral student in FSHN.
The paper, “Simulation Evaluation of Power of Sampling Plans to Detect Cronobacter in Powdered Infant Formula Production”, is published in the Journal of Food Protection.
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