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AI Magazine
Article . 2024 . Peer-reviewed
License: CC BY NC
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DBLP
Article . 2024
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AIIRA: AI Institute for Resilient Agriculture

Authors: Baskar Ganapathysubramanian; Jessica M. P. Bell; George Kantor; Nirav C. Merchant; Soumik Sarkar; Patrick S. Schnable; Michelle Segovia; +2 Authors

AIIRA: AI Institute for Resilient Agriculture

Abstract

AbstractAIIRA seeks to transform agriculture by creating a new AI‐driven framework for modeling plants at various agronomically relevant scales. We accomplish this by designing and deploying AI‐driven predictive models that fuse diverse data with siloed domain knowledge.AIIRA's vision, illustrated in Figure 1, consists of four technical thrusts with cross‐cutting education, training, and outreach activities. Our activities are focused on theory, algorithms, and tools for the principled creation of goal‐oriented AI tools deployed at plant and field scales. Our use‐inspired AI developments are tightly integrated with USDA‐relevant challenges in crop improvement and sustainable crop production. Our strong social science focus ensures sustained AI adoption across the ag value chain. Our cyberinfrastructure (CI) efforts ensure cohesive, sustainable, and extensible CI to reproducibly share and manage data assets and analysis workflows to a diverse spectrum of the Ag community. Taken together, this will ensure long‐term payoffs in AI and agriculture.AIIRA has established a new field ofCyber Agricultural Systems at the intersection of plant science, agronomics, and AI. Our signature activities build the workforce for this new field through formal and informal educational activities. Through these activities,AIIRA creates accessible pathways for underrepresented groups, especially Native Americans and women.

Country
United States
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Keywords

DegreeDisciplines::Engineering::Mechanical Engineering::Computer-Aided Engineering and Design, 570, DegreeDisciplines::Life Sciences::Plant Sciences::Agronomy and Crop Sciences, 630

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Top 10%
hybrid