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2344877

Cooperative Agreement

Overview

Grant Description
Convergence Accelerator Track J Phase 2: Rapid Detection Technologies and Decision-Support Systems for Safe, Equitable Food Systems -Salmonella is a leading cause of foodborne illness, resulting in 1.35 million infections, 26,500 hospitalizations, 420 deaths, and costs the US economy $4.1 billion annually.

Despite nationwide efforts, the infection rates have been unchanged for three decades, disproportionately affecting vulnerable populations, making it a ?One Health? issue. To cope with this challenge, this project establishes diverse partnerships with the poultry industry, end-to-end supply chains, food banks, and extension educators.

The objective is to create a transformative sensor-enabled decision support system (DSS; termed as SENS-D), which incorporates multiple rapid sensing technologies and sensing systems prototypes, along with visualization, prediction, and optimization capabilities to detect and mitigate Salmonella contamination throughout the poultry supply chain. SENS-D is envisioned to provide data-driven solutions that significantly improve food safety, equity, efficiency, and resilience, particularly among disadvantaged populations.

The sensing systems are portable, easy-to-use, accurate, and cost-effective. By integrating sensor results with the DSS, this technology will ensure an equitable and secure food supply, facilitated through collaborations with food safety stakeholders. SENS-D can be adapted to detect various pathogens in other food products including beef, pork, dairy, and produce, ultimately reducing the $152 billion economic burden of foodborne illness in the U.S.

To promote inclusivity and maximizing social impact, the project will engage underrepresented and vulnerable groups, stakeholders, students and postdoctoral researchers. Additionally, this initiative will train the workforce to tackle equitable food safety by creating new educational and training opportunities for convergence science approaches at the intersection of public health, poultry science, food and animal science, supply chain, engineering, and analytics/AI.

This project develops three innovative sensing technologies and user-centric prototypes for portable systems, transforming poultry testing by enabling rapid, multiplex, and quantitative detection and surveillance of Salmonella serovars within 10-60 minutes. The surface enhanced Raman spectroscopy sensor integrates metal nanoantennas on a side-polished multimode optical fiber core, enabling rapid, quantitative detection of Salmonella serovars.

The impedance-based biosensor concentrates Salmonella to a detectable threshold, capturing and identifying the pathogen, while the nanopore-facilitated, multi-locus checkpoint sequencing sensor differentiates Salmonella serovars through single-nucleotide variations. The DSS employs advanced analytics and AI to monitor, predict, and mitigate Salmonella risks, both spatially and temporally, in a sensor-enabled poultry supply chain.

It utilizes a cloud-based One Health data environment for real-time data integration from the sensing system. Advanced statistical and machine learning techniques will predict Salmonella levels and product shelf-life. Optimization will be used for sensor placement, intelligent distribution of food, and workforce planning to facilitate implementation of sensors, while achieving multiple performance metrics of safety, equity, efficiency, and resilience.

An analytical toolkit will determine the efficacy of policies and interventions for Salmonella mitigation. Through stakeholder and end-user engagement, SENS-D has the potential to transform Salmonella mitigation and significantly enhance food safety. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

- Subawards are planned for this award.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF CONVERGENCE ACCELERATOR PHASES 1 AND 2 FOR THE 2022 COHORT - TRACKS H, I, J", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22583
Awarding / Funding Agency
Place of Performance
Columbia, Missouri 65211-0001 United States
Geographic Scope
Single Zip Code
Analysis Notes
Amendment Since initial award the total obligations have increased 100% from $2,000,000 to $4,000,000.
University Of Missouri System was awarded Rapid Salmonella Detection System for Safe and Equitable Food Systems Cooperative Agreement 2344877 worth $4,000,000 from National Science Foundation in December 2023 with work to be completed primarily in Columbia Missouri United States. The grant has a duration of 3 years and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships. The Cooperative Agreement was awarded through grant opportunity NSF Convergence Accelerator Phases 1 and 2 for the 2022 Cohort - Tracks H, I, J.

Status
(Ongoing)

Last Modified 1/14/25

Period of Performance
12/15/23
Start Date
11/30/26
End Date
57.0% Complete

Funding Split
$4.0M
Federal Obligation
$0.0
Non-Federal Obligation
$4.0M
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2344877

Subgrant Awards

Disclosed subgrants for 2344877

Transaction History

Modifications to 2344877

Additional Detail

Award ID FAIN
2344877
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
491502 INNOVATION AND TECHNOLOGY ECOSYSTEMS
Funding Office
491502 INNOVATION AND TECHNOLOGY ECOSYSTEMS
Awardee UEI
SZPJL5ZRCLF4
Awardee CAGE
9C156
Performance District
MO-03
Senators
Joshua Hawley
Eric Schmitt
Modified: 1/14/25