Researchers have developed a new, farm-to-fork quantitative microbial risk assessment (QMRA) model to evaluate the risk of Listeria monocytogenes contamination in fresh-cut cantaloupe.
This episode of Food Safety Five discusses hoses as reservoirs for biofilms in food processing facilities, the presence of Listeria monocytogenes and Campylobacter on retail beef and chicken, a new Salmonella serovar database, and microplastics release from food contact materials.
An analysis conducted by Cornell University researchers sought to better understand the genomic characteristics associated with an important reoccurring, emerging, and persistent (REP) Salmonella strain, S. Infantis REPJFX01, to help inform targeted interventions.
The Cornell College of Agriculture and Life Sciences (CALS) Food Safety Laboratory has developed the Salmonella Serovar Wiki—a web resource for global food safety professionals to rapidly access information about a given Salmonella serovar.
A Center for Produce Safety (CPS) -funded study is investigating how different aspects of bulb onion production influence Salmonella and Escherichia coli risk, filling knowledge gaps about short- and intermediate-day varieties.
Consumer and regulatory demand for naturally derived alternatives to synthetic food colorants is on the rise. To meet that demand, Cornell University scientists have developed a new blue food dye made of algae protein.
Using a newly developed quantitative microbial risk assessment (QMRA) model, researchers have identified interventions along the U.S. romaine lettuce supply chain that would most effectively reduce E. coli contamination. The QMRA is publicly available for use.
According to a pre-publication version of a study conducted by Cornell University and backed by FDA, aging raw milk cheese may not be effective at eliminating the Highly Pathogenic Avian Influenza H5N1 virus. However, adequate heat treating or pH 5.0 conditions could be effective.
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.
To help predict and mitigate the presence of Escherichia coli and other foodborne pathogens on lettuce, a new weather-based model has been developed by USDA-ARS researchers and collaborators.
