Using EU Rapid Alert System for Food and Feed (RASFF) data, researchers have developed an integrated artificial intelligence (AI) framework for conducting food safety risk assessments, and demonstrated its usefulness in decreasing the ambiguity of risk management decisions.
This episode of Food Safety Five discusses newly published CDC data about the pathogens causing foodborne illness and contributing factors of outbreaks, as well as research by CDC, USDA, and FDA scientists exploring the use of AI analysis of whole genome sequencing data for foodborne illness source attribution.
A project funded by the Center for Produce Safety is developing an identification and deterrent system for high-risk birds in produce fields based on sound surveillance and artificial intelligence (AI). The tool would automatically deploy interventions to drive away birds that are more likely to spread foodborne pathogens.
Researchers from CDC, FDA, and USDA trained an artificial intelligence (AI) machine learning model to conduct food source attribution for human cases of salmonellosis by analyzing whole genome sequencing (WGS) data for Salmonella isolates. The model showed promise, estimating that the majority of salmonellosis cases are caused by chicken and vegetables
In a new study, the UK Health Security Agency (UKHSA) evaluated the ability of artificial intelligence (AI) to detect foodborne illness outbreaks by analyzing online restaurant reviews. Although several challenges were identified that must be overcome before AI can be used routinely in epidemiological investigations, UKHSA believes the approach shows promise.
An expanded range of jointly developed pest traps from BrightAI and Pelsis bring new artificial intelligence (AI) -powered pest detection devices to a wider range of food facilities.
A researcher from Southern Illinois University Carbondale has received a $150,000 grant from USDA-NIFA to develop an AI-based rapid detection method for Salmonella on onions.
Trustwell recently added an Allergen Identification feature to its Genesis Foods platform, which uses artificial intelligence (AI) to recognize and alert users of potential allergens for submitted ingredients, helping inform accurate labeling and potential corrective actions.
On November 6, the Food and Agriculture Organization of the United Nations (FAO) will hold a technical seminar on artificial intelligence (AI) for food safety, a virtual livestream of which will be available for public viewing.
Combining genomic sequencing data and artificial intelligence (AI), researchers have demonstrated the efficacy of a new approach for the untargeted detection of contaminants, antibiotics, and other food safety anomalies in bulk milk samples.
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