Food safety: New algorithm could help with environmental monitoring

In a food production or processing plant, the seek-and-destroy method is a technique for finding niches that harbor bacterial pathogens, like the particularly tricky Listeria monocytogenes (L. mono). If detected, the contaminated area can be totally cleaned and disinfected, eradicating the pathogen.

It’s an approach to environmental monitoring that has been increasingly encouraged as the years go by — a proactive tactic that helps producers protect their customers and their brands.

Now, students from New York’s Cornell University have developed a computer model that they believe can help food facilities know which parts of the production environment they should target for pathogen testing.

“The goal is to build a decision-support tool for control of any pathogen in any complex environment,” said associate professor Renata Ivanek.

The program, Environmental Monitoring with an Agent-Based Model of Listeria (EnABLe), computes the most likely locations in the facility where foodborne pathogens might lie. As it exists currently, the model focuses on L. mono, but the developers hope to expand its capabilities.

Based on what the model simulates, food safety experts at the facility can increase environmental monitoring at what are determined as high-risk areas, augmenting their already-existing Hazard Analysis Critical Control Point plan.

EnABLe does this by analyzing data about facility history, expert feedback, equipment used, cleaning schedules, tasks performed as part of the production process, materials used, and people who enter from outside the facility. It aims to consider more information than a single person could keep track of, predicting a range of possible outcomes.

“Whenever we have an environment that is complex, we always have to rely on expert opinion and general rules for this system, or this company, but what we’re trying to offer is a way to make this more quantitative and systematic by creating this digital reality,” Ivanek said.

The model’s development was funded by a grant given by the Frozen Food Foundation.

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