Data Efficiency and AI Integration Projects

Data Efficiency and AI Integration Projects is sponsored by Department of Agriculture (USDA). Encourages projects that integrate AI to improve data efficiency in agricultural research.

Data Science for Food and Agricultural Systems (DSFAS) | NIFA The lifecycle of grants and cooperative agreements consists of four phases: Pre-Award, Award, Post-Award, and Close Out. The National Institute of Food and Agriculture is committed to serving its stakeholders, Congress, and the public by using new technologies to advance greater openness.

The Data Gateway enables users to find funding data, metrics, and information about research, education, and Extension projects that have received grant awards from NIFA. This website houses a large volume of supporting materials. In this section, you can search the wide range of documents, videos, and other resources.

Technical Assistance Webinar: The Equipment Grants Program (EGP) The Equipment Grants Program seeks to provide eligible institutions with the opportunity to acquire a shared-use piece of equipment/instrument that supports their research, research training, and extension goals. The National Institute of Food and Agriculture provides leadership and funding for programs that advance agriculture-related sciences.

Data Science for Food and Agricultural Systems (DSFAS) The A1541 Data Science for Food and Agricultural Systems (DSFAS) program area priority, within the USDA NIFA Agriculture and Food Research Initiative (AFRI), focuses on the intersections of data science or artificial intelligence (AI) with agriculture.

The goal of A1541 DSFAS is to enable systems and communities to effectively utilize data, improve resource management, and integrate new technologies, automation, mechanization, and approaches to advance the U.S. food and agriculture enterprises.

The Agriculture and Food Research Initiative (AFRI) A1541 Data Science for Food and Agricultural Systems (DSFAS) program solicits applications that focus on data science to enable systems and communities to effectively utilize data, improve resource management, and integrate new technologies, automation, mechanization and approaches to advance the U.S. food and agricultural enterprises.

The program welcomes university-based research as well as public and private partnerships.

Projects funded through DSFAS include the examination of the value of data for small and large farms, agricultural and food industries; and the understanding of how data science or AI can be leveraged to impact the agricultural supply chain, improve consumer health, environmental and natural resource management, affect the structure of U.S. food and agriculture sectors, and increase U.S. competitiveness.

DSFAS projects should be equally well-grounded in agricultural sciences and in data science or AI, with high relevance and novelty in both areas. DSFAS applications must fall under one of the following project types: Regular DSFAS applications for project periods of three to five years. DSFAS Coordinated Innovation Networks (CIN) research or integrated applications for project periods of three to five years.

All CIN projects must address the following: Synergy: There should be a demonstrable benefit to the existence of a multidisciplinary, multi-sector, or multifunctional CIN that would not otherwise be possible by the participating entities and individuals operating independently.

Contribution: Each participating individual or entity should have a unique, meaningful, and active contribution to the network that is critical to the network's functioning, performance, and success in addressing bottlenecks in critical areas.

Continuity: There should be a sustainability plan for network persistence beyond the duration of initial grant support (e.g., identification of additional funding sources and/or more formal organizational arrangements). Management: There should be a plan for coordination and oversight including, but not limited to, communication, leadership, advisory boards, milestones, and evolution over time (e.g., new objectives or new participants).

DSFAS Coordinated Innovation Networks (CIN) applications for projects meeting the criteria in the DSFAS research priorities section and the additional CIN criteria above. DSFAS Coordinated Innovation Networks Food Supply Modeling (CIN-FM) applications in the special focus area of food supply chain modeling.

Creative, novel projects that meet the overall goals of advancing modeling on examining transitions to robust, resilient, and cooperative food supply networks are welcome. For more information, please read the DSFAS program area priority description in Part I, C of the AFRI Foundational and Applied Science (FAS) NOFO .

AFRI FAS Funding Opportunity Page Competitive Grant Programs Data Science for Food and Agricultural Systems FAQ A1541 DSFAS Awards (previously funded projects) DSFAS Technical Assistance Webinar Page last updated: December 17, 2025 Your feedback is important to us.