Predicting Listeria’s Resistance to Disinfectants Using AI – U.S. Correspondence by Jay Lee (151)

Frequent Detection in U.S. Exports… Found in Processed and RTE Foods

Biofilm Formation Makes It Resistant to Disinfectants, Surviving Cleaning

Danish Researchers Predict Pathogen Elimination Within Minutes

Applicable to Smart Factories, Cold Chains, and Foodservice Facilities

△ Jay Lee, CEO of J&B Food Consulting

Listeria monocytogenes is a deadly bacterium frequently detected not only in Korean refrigerated and frozen processed foods but also in agricultural products exported to the U.S. While it may not be a major issue in Korea, it is considered one of the most dangerous pathogens in the United States. Korean fish cake products, salted seafood, frozen ready-to-eat (RTE) items, and enoki mushrooms are typical examples that have tested positive for Listeria during U.S. import inspections.

Listeria monocytogenes thrives in cold, damp environments and is often found in food processing facilities. Its primary threat lies in its ability to form biofilms on surfaces. Over time, these biofilms can develop resistance to disinfectants, making the bacteria much harder to eliminate.

Until now, detecting such resistance required lengthy laboratory tests. Even when surfaces appear clean, resistant bacteria can hide in crevices and corners, posing an ongoing risk. Routine environmental monitoring and Listeria testing are essential, but if cleaning and sanitizing are ineffective, they are of little use. Reliance on disinfectants alone may fail if the bacteria form biofilms, as this can render the bacteria impervious to the chemicals.

Recently, researchers from the DTU National Food Institute in Denmark and other institutions developed a method using artificial intelligence (AI) and DNA analysis to predict how well pathogenic bacteria like Listeria can withstand disinfectants.

Published in Scientific Reports, a Nature research journal, the study demonstrated that machine learning can predict whether specific bacterial strains will survive sanitation processes. The AI model achieved up to 97% accuracy and was able to determine resistance not only to pure chemical substances but also to commercial disinfectant products. The researchers also identified several new resistance genes, beyond those already known, improving prediction accuracy and expanding our understanding of bacterial resistance mechanisms. Unlike traditional lab tests, which can take days, this AI-based method can deliver accurate predictions within minutes using only DNA data.

Such technology aligns closely with prevention-focused regulations like the U.S. Food Safety Modernization Act (FSMA). It can also be applied immediately to HACCP-based smart factories, cold chain distribution networks, high-risk foodservice facilities, and hospital catering systems.

The food industry continues to create innovations by integrating AI, and its role is expanding across many sectors.

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