New research funded in part by the Arlington, Virginia-based Frozen Food Foundation reveals a possible solution for controlling Listeria monocytogenes (Lm) in food manufacturing facilities. The findings were published in the January 24, 2019 issue of Scientific Reports.
The Cornell University study focused on developing and testing a computer model that has the potential to pinpoint locations in a food manufacturing facility where Lm might be found. The model – which Cornell researchers named “Environmental monitoring with an Agent-Based Model of Listeria,” or (EnABLe) – would allow food production safety managers to then test these designated areas for the bacteria’s presence.
“Our organization and industry are focused on better understanding potential entry points for Listeria in frozen food facilities, ultimately leading to specific food safety protocols,” said Frozen Food Foundation Executive Vice President Dr. Donna Garren. “Lm is a challenge because of its ubiquity and ability to survive freezing temperatures. Cornell’s innovative work opens a new, predictive model for the frozen food industry to better understand and develop more robust food safety programs for detecting and minimizing the presence of Lm.”
“Illness stemming from frozen foods is extremely rare. But we want to do our part to prevent a listeriosis event from occurring,” Garren added. “That’s why we invest in scientific research to guide Lm-monitoring best practices, from the frozen food facility to fork. We are excited for the food safety advances Cornell has presented with this research.”
During the study, researchers entered all relevant food production data into EnABLe, including historical perspectives, expert feedback, details of food manufacturing equipment used, and its cleaning schedules, the job functions, and movement of materials and people within and from outside the facility.
Dr. Donna Garren“The goal is to build a decision-support tool for control of any pathogen in any complex environment,” said Renata Ivanek, Cornell University associate professor in the Department of Population Medicine and Diagnostic Sciences and senior author of the paper. “While a single person could never keep track of all this information, EnABLe connects data and potential sources of Lm contamination with approaches for risk mitigation and management.”
While the study describes Listeria spp. on equipment and surfaces in a cold-smoked salmon facility, insights gained from seeing patterns in the areas where Listeria spp. is predicted can inform the design of any food manufacturing facilities and Lm-monitoring programs.
“This is a novel tool to simulate and design food safety systems to trace Lm on equipment and food manufacturing facilities,” said Garren. “This research allows Lm to be traced in ways that haven’t been done before that will allow frozen food manufacturers to make science-based decisions when developing environmental monitoring programs and managing food safety risks in a complex environment.”
Garren added that the Cornell study will continue into 2019. The model will now be applied to and tested in select frozen food facilities as the next step in a potential industry-wide rollout.
