AI Model Boosts Food Contamination Detection Accuracy

Researchers develop deep learning tool to rapidly identify bacterial contamination in food

Published on Feb. 10, 2026

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Researchers have developed an artificial intelligence tool that can rapidly detect bacterial contamination in foods like leafy greens, meat, and cheese. The deep learning-based model can reliably identify live bacteria within three hours, a significant improvement over current methods that can take days. The key breakthrough was training the model to distinguish bacteria from microscopic food debris, eliminating over 24% of previous misclassifications.

Why it matters

Bacterial contamination in food production is a major public health issue, leading to millions of cases of foodborne illness annually in the U.S. Early detection of pathogens before products reach consumers is critical to prevent outbreaks, protect public health, and reduce costly product recalls.

The details

The AI model, developed by researchers at Oregon State University, UC Davis, Korea University, and Florida State University, was trained on images of three bacterial strains (E. coli, listeria, and Bacillus subtilis) as well as food debris from chicken, spinach, and Cotija cheese. Previous models that were only trained on bacteria misclassified food debris as bacteria over 24% of the time. The enhanced model, trained on both bacteria and debris, eliminated these misclassifications, enabling reliable detection within three hours.

  • The study was published in February 2026.

The players

Luyao Ma

An assistant professor at Oregon State University who led the research team.

Hyeon Work Park

A co-author from Korea University.

Zhengao Li

A co-author from Florida State University.

Nitin Nitin

A co-author from the University of California, Davis.

U.S. Department of Agriculture-National Institute of Food and Agriculture

The agency that supported the research.

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What they’re saying

“Early detection of foodborne pathogens before products reach the market is essential to prevent outbreaks, protect consumer health and reduce costly recalls.”

— Luyao Ma, Assistant Professor, Oregon State University (Mirage News)

What’s next

Researchers are now working to optimize the AI system for industry adoption.

The takeaway

This breakthrough in rapid, accurate detection of food contamination using AI could have significant public health and economic benefits by preventing foodborne illness outbreaks and reducing costly product recalls.