Collaborations

The Environmental Microbial & Food Safety Laboratory has a long and productive history of collaborative research involving stakeholders.

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Current collaborators and projects:

ARMY, UNITED STATES DEPARTMENT OF, THE, NATICK, MA

Spectral Sensing Technologies for Safety and Quality Assessment of Food, Food Contact Surfaces, and Controlled-Environment Food Production Systems

FOUNDATION OF RESEARCH AND BUSINESS, CHUNGNAM

Spectral Sensing and Instrumentation for Automated Food Integrity Assessment

GYEONGSANG NATIONAL UNIVERSITY

Image-Fusion Methods for Monitoring Safety and Health of Plants in Space Crop Production Environment

MONTANA STATE UNIVERSITY, BOZEMAN

Monitoring and Managing Microbial Water Quality for Food Safety

NASA KENNEDY SPACE FLIGHT CENTER, Alachua

Multi-modal Imaging for Monitoring Plant Health and Crop Growth Remotely in Spacecraft

SAFETYSPECT, INC., GRAND FORKS, CA

Integration of Multimodal UAV Sensors for Preharvest Food Safety Monitoring Applications

SHERPA SPACE INC.

AI-enhanced Vertical Farming Platforms for Efficient and Sustainable Specialty Crop Production

THE CENTER FOR PRODUCE SAFETY, WOODLAND

Assessing Romaine Lettuce “Forward Processing” for Potential Impacts on EHEC Growth, Antimicrobial Susceptibility, and Infectivity

Development of an Infrared-Functionalized Microbalance Sensor for Cyclospora Cayetanensis Detection and Differentiation

UNIVERSITY OF CALIFORNIA, DAVIS, DAVIS, CA

Precision Solutions for Pathogen Carriage on Dairy Farms Using Machine Learning

UNIVERSITY OF CONNECTICUT, STORRS, CT

From Seed to Plate: Improving Produce Safety for Organic Production Using Natural Biocontrol Strategies

UNIVERSITY OF DELAWARE, NEWARK, DE

Factors Affect the Transfer of Bacterial Pathogens to Leafy Greens from Soils

Factors Affect the Transfer of Bacterial Pathogens to Leafy Greens from Soils

Factors Affecting the Transfer of Bacterial and Viral Pathogens to Produce to Protect Food Safety and Security

UNIVERSITY OF FLORIDA, GAINESVILLE, FL

Hybrid Edge-Cloud AI Platforms for Optical Detection of Citrus HLB, Black Spot, and Emerging Diseases

UNIVERSITY OF MARYLAND BALTIMORE COUNTY, BALTIMORE

Automated non-invasive Detection of Surface Contamination and Optimizing Surface Biofilm Removal Conditions in Large-Scale Food Processing Equipment

UNIVERSITY OF MARYLAND, COLLEGE PARK, COLLEGE PARK, MD

Development of AI-Machine Vision Based Automated Robotics Technologies for Microbial Food Safety and Agricultural Applications

Modeling Fate and Transport of Indicator and Pathogenic Organisms to Assess Microbial Water Quality of Irrigation Water Sources