Скачать или смотреть Rapid Identification of Foodborne Pathogens Using Machine Learning - Kaidi Wang PhD Candidate

Rapid Identification of Foodborne Pathogens Using Machine Learning
The 2023 Lister Science Chats

Supported by the Lister Family Engaged Science Initiative, the Lister Science Chats connects members of the community through live science talks with researchers from the McGill Faculty of Agricultural and Environmental Sciences. These chats feature Macdonald Campus graduate students giving an engaging 6-minute talk on their research and concludes with a Q&A period.

Kaidi Wang, PhD Candidate, Food Science and Agricultural Chemistry

This study developed a rapid and reliable approach to identify 5 common foodborne bacteria using Raman spectroscopy at the single-cell level, providing a powerful tool for epidemiological surveillance of foodborne pathogens in the agri-food chain.