The researchers positioned the machine learning model as a low-cost complement to traditional testing workflows, helping dairy processors enhance food safety while targeting laboratory resources.
This episode of Food Safety Five discusses expert perspectives on the Healthy Florida First food contaminant testing program, including information gaps about the testing and risk assessment methodology and why this missing information matters.
The scientists will isolate and identify pathogens like Salmonella enterica and Listeria monocytogenes from Pennsylvania wastewater using whole genome sequencing (WGS), then work with the State Department of Health to connect isolates to foodborne illness outbreaks.
The researchers conducted environmental sampling throughout a controlled environment agriculture (CEA) operation and tested swabs for L. monocytogenes. Boot covers proved to be a useful tool for evaluating the effectiveness of cleaning and sanitation.
MagnaFlow is a new automated inline washwater analyzer that provides continuous, real-time visibility into the microbial loads present in post-harvest wash systems.
The SMARTBIOME platform combines high‑resolution DNA sequencing with bioinformatics and data science, an exclusive spoilage knowledge base, and expert consulting services to translate microbiological data into actionable insights.
The extended agreement between FDA’s Human Foods Program and Simulations Plus allows scientists to continue research involving computational models to support chemical safety assessments for food and food-contact substances.
The detection system was able to detect the presence of foodborne pathogens in complex food matrices as little as three hours with 0 percent false positives, 94 percent recall, and 100 percent precision.
Like the Healthy Florida First initiative’s previous reports on toxic heavy metals in candy and infant formula, details that would help contextualize the findings have not been disclosed, such as the sampling and testing methodology or relevant safety thresholds
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