FDA is rumored to face significant budget cuts proposed by the White House that would shift 100 percent of the responsibility for routine food facility inspections to states. Additionally, due to layoffs, FDA has suspended its proficiency testing program for food testing laboratories and its efforts to bolster avian influenza testing in food products.
This episode of Food Safety Five discusses two scientific advancements related to Listeria monocytogenes control: 1) a study that showed the effectiveness of combining antimicrobial blue light with chemical sanitizers for pathogen inactivation, and 2) the development of a new growth prediction model for L. monocytogenes in artisanal cheeses.
Protecting Italian honey authenticity and combatting food fraud, the Italian Standards Body’s (UNI’s) new UNI 11972 standard introduces a new analytical method for detecting honey adulteration based in Nuclear Magnetic Resonance technology.
A paper authored by experts associated with ILSI Europe asserts that global food safety would benefit from the harmonization of risk assessment protocols for food contact materials used by different regulatory bodies, and suggests a path forward for working toward harmonization.
In this episode of Food Safety Matters, we speak to Dr. Edward Dudley, Director of the E. coli Reference Center and Professor of Food Science at Penn State University, about the potential for wastewater monitoring to aid foodborne pathogen surveillance and bolster foodborne illness reporting.
The European Commission published a FAQ document to clarify the requirements of Regulation (EU) 2025/179, which mandates whole genome sequencing (WGS) testing and data reporting for important foodborne pathogens when suspected to be associated with a foodborne illness outbreak.
Adding to its existing certification for corn, ImagoAI’s Galaxy Mycotoxins Test has received the AOAC Performance Tested Methods (PTM) certification for aflatoxins, deoxynivalenol, fumonisins, and zearalenone in Wheat, Dried Distillers Grains With Solubles (DDGS), and Corn Gluten Meal (CGM).
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
This episode of Food Safety Five discusses two recent scientific studies that are advancing the food industry’s understanding of and ability to address Listeria monocytogenes, including new findings about the pathogen’s behavior in biofilms and a developing rapid detection method.
A new study by USDA researchers has shown that long-read whole genome sequencing (WGS) could detect Salmonella attachment to food-contact surfaces earlier than traditional culture-based methods, allowing for sanitation interventions to be applied before the maturation of robust and difficult-to-remove biofilms.
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