NSF Award
2420647
Designing and deploying artificial intelligence (AI) tools in agriculture represents an exciting opportunity for international collaboration, uniting diverse expertise and resources to tackle global challenges. Our project aims to impact agriculture by developing, deploying, and democratizing AI tools to help farmers manage pests and stressors more effectively, making farming less risky, more profitable, and more sustainable. We plan to create AI-driven tools that provide personalized management advice, enhance crop yields, and support sustainable farming practices. This initiative will bring together scientists and practitioners from the US, India, and Japan, fostering international collaboration and innovation. The AI-driven approaches will benefit small and medium-sized farmers, offering easy-to-use, accessible technology to help them pursue climate-smart agriculture. The project also includes educational components and multilateral engagements to inspire the next generation of agricultural and AI experts.<br/><br/>This EAGER project seeks to pursue multilateral research partnerships between the US, India, and Japan to develop and deploy AI-driven tools to enhance agricultural productivity. This team will work across two areas of collaborative effort: (i) developing hybrid machine learning models that combine sensor (proximal and remote) data with biophysical knowledge for yield and stress prediction, and (ii) utilizing agronomic data -- both biotic (insects, weeds, diseases) and abiotic (nutrient deficiencies, herbicide injury) -- to fine-tune and deploy large vision and language models developed by AIIRA (one of the five NIFA-funded National AI Institutes) in the US, led by Iowa State University (ISU). By collaborating with international partners that span diverse environments, we aim to develop and validate a robust, scalable framework for agricultural management that supports real-time decision-making and fosters sustainable agricultural practices globally. The initiative also emphasizes educational outreach, promoting interdisciplinary learning and broadening participation in AI-driven agriculture. <br/><br/>This project is funded as part of the Quad AI-ENGAGE initiative, a collaboration of the National Science Foundation, Commonwealth Scientific and Industrial Research Organization of Australia, Indian Council of Agricultural Research, and Japan Science and Technology Agency to advance innovation to empower next generation agriculture.<br/><br/>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.
