USDA Scientist Demonstrates Food Safety Software

The USDA-ARS Pathogen Modeling Program assists food industry specialists in predicting pathogen growth during emergencies.

Updated on Oct. 28, 2026 in Nutrition

Isometric editorial illustration of laboratory beakers and stainless steel canisters, representing the precision of food pathogen modeling software. — USDA scientists are utilizing new predictive software to help food industry specialists assess pathogen growth and safety during equipment failures. AI Illustration. Upload story photo >

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USDA lead scientist Vijaya Juneja recently visited the Robert M. Kerr Food and Agricultural Products Center to demonstrate software designed for pathogen prediction. The visit highlighted how the tool helps industry professionals estimate food safety and shelf life.

Why it matters

The software provides critical decision-making support for specialists who must quickly assess food storage safety during unexpected electrical outages or equipment failures.

The USDA-ARS Pathogen Modeling Program allows specialists to input pathogen behavior data to estimate growth trajectories in food products. This predictive microbiology approach helps professionals calculate safety outcomes and product shelf life.

The players

Vijaya Juneja

She serves as a lead scientist at the USDA Agricultural Research Service and specializes in predictive microbiology.

Robert M. Kerr Food and Agricultural Products Center

This facility supports food and agricultural development through research, technology, and industry outreach.

The details

Industry specialists utilize this software to accurately predict how pathogens behave within various food environments. By modeling these growth patterns, experts can determine the viability of food storage during crises like equipment malfunctions.

October 2026: Vijaya Juneja visited the Food and Agricultural Products Center.

The Big Picture

This visit integrates the USDA-ARS Pathogen Modeling Program into modern industrial workflows by highlighting its role in critical safety assessments. The demonstration marks a shift toward utilizing automated software to replace reactive decision-making in food storage management.

While primarily for industry use, this technology ensures the food products consumers purchase meet higher safety standards during power or equipment interruptions. It ultimately strengthens the resilience of the local food supply against spoilage events.

The takeaway

Predictive microbiology software provides a data-driven approach to maintaining food quality during unforeseen facility disruptions. Industry members can implement these modeling techniques to ensure storage safety and minimize food waste.