A High-throughput Automated Platform for Rapid Isolation and Enumeration of Salmonella

In the United States, Salmonella infection is a leading cause of hospitalizations and deaths from foodborne illness, with poultry products being a dominant source.The current methods used to detect, isolate and enumerateSalmonella are slow, labor-intensive, and expensive, which creates a major bottleneck in ensuring food safety.This research aims to solve this critical problem by developing MagiCyte MB, a fully automated, high-speed, and cost-effective system for the rapid detection, enumeration and isolation of Salmonella. Our approach leverages novel biological methods, advanced robotics, computer vision, and artificial intelligence to replace traditional manual processes.In this phase I research, we will validate our new technology by testing its ability to quickly and accurately isolate and enumerateSalmonella from chicken carcass rinse samples. The ultimate goal is to introduce a paradigm-shifting technology for pathogen testing that fundamentally changes how the food industry ensures public safety.