Cornell University develops tool for controlling foodborne pathogens in food manufacturing facilities
The 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.
New research funded in part by the Frozen Food Foundation, a non-profit arm of American Frozen Food Institute, Arlington, Va., reveals a possible solution for controlling Listeria monocytogenes (Lm) in food manufacturing facilities.
The study, conducted by Cornell University, Ithaca, N.Y., 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 (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,” says Dr. Donna Garren, executive vice president of Frozen Food Foundation. “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,” adds Garren. “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.
“The goal is to build a decision-support tool for control of any pathogen in any complex environment,” says Renata Ivanek, associate professor in Cornell University’s 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,” says 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.”