Cornell summit showcases AI innovation in agriculture – Cornell Chronicle

Report on the Cornell Institute for Digital Agriculture (CIDA) Annual Workshop

1.0 Executive Summary

The Cornell Institute for Digital Agriculture (CIDA) held its annual workshop on October 21 at Cornell University. The event convened a multi-disciplinary group of academics, students, and industry stakeholders to review progress and foster collaboration in digital agriculture. The workshop’s central theme was the application of data, technology, and artificial intelligence (AI) to address global challenges in food systems, with a significant focus on advancing the United Nations Sustainable Development Goals (SDGs).

2.0 Workshop Objectives and Alignment with SDGs

The primary goal of the summit was to create an ecosystem for innovation by integrating expertise from veterinary medicine, computer science, agriculture, and ethics. This collaborative approach directly supports several key SDGs.

• SDG 2 (Zero Hunger): The workshop focused on developing technologies to create more efficient, sustainable, and resilient food systems to enhance global food security.
• SDG 9 (Industry, Innovation, and Infrastructure): The event showcased cutting-edge research and initiatives designed to build resilient infrastructure and foster innovation in the agricultural sector.
• SDG 17 (Partnerships for the Goals): The gathering itself exemplified this goal by bringing together academia, industry partners, and researchers from diverse fields to accelerate progress through collaboration.

3.0 Keynote Address: AI’s Transformative Impact on Sustainable Production

Keynote speaker Aidan Connolly outlined a future where AI fundamentally reshapes agriculture. His address highlighted how an “AI revolution” could optimize production, supply chains, and resource management.

1. Enhanced Food Security (SDG 2): Connolly envisioned AI-designed and operated farms that replicate natural systems with enhanced precision, strengthening global food security.
2. Responsible Consumption and Production (SDG 12): The application of AI is projected to improve resource use efficiency, minimizing waste and promoting sustainable production patterns in line with SDG 12.

4.0 Cornell Initiatives Driving Progress on SDGs

The workshop spotlighted several Cornell-led initiatives that leverage digital technology to advance agricultural sustainability and climate resilience.

• Cornell Agricultural Systems Testbed (CAST) and AI4AG: These programs develop “farm-ready” AI tools by integrating data from field and livestock systems, directly contributing to SDG 2 (Zero Hunger) by improving farm productivity and sustainability.
• Center for Research on Programmable Plant Systems (CROPPS): By enabling plants to signal their own needs, this research supports precision agriculture, which is critical for SDG 12 (Responsible Consumption and Production).
• NASA ACRES: This initiative uses remote sensing to improve soil and crop modeling, providing data essential for sustainable land management and contributing to SDG 2 and SDG 13 (Climate Action).
• AI LEAF Institute: The development of decision-support tools for climate-smart farming directly addresses the targets of SDG 13 (Climate Action).
• Grow-NY: By catalyzing ag-tech startups, this program fosters economic growth and technological innovation, aligning with SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure).

5.0 Research Innovation Fund Projects

Presentations from the CIDA Research Innovation Fund showcased projects targeting specific sustainability challenges.

• Integrated System Modeling for Valorizing Agricultural and Food Waste: This project explores creating a sustainable circular bioeconomy by repurposing agricultural byproducts, directly supporting SDG 12 (Responsible Consumption and Production).
• Scaling up Digital Agriculture in Africa: This research focuses on expanding digital agriculture through small and medium-sized enterprises, advancing SDG 2 (Zero Hunger) and SDG 9 (Industry, Innovation, and Infrastructure) on the African continent.
• Delay-Sensitive Edge Intelligence for Digital Agriculture: This investigation into advanced computing for real-time decision-making promotes technological upgrades and innovation within the agricultural industry, a key component of SDG 9.

6.0 Conclusion: Fostering Collaborative Ecosystems for Global Impact

The workshop concluded with an Industry Thought Summit that reinforced the importance of cross-sector partnerships. CIDA’s unique ecosystem, which unites diverse research centers and industry leaders, was highlighted as a critical driver for accelerating innovations with both local and global impact. This collaborative model is a practical application of SDG 17 (Partnerships for the Goals), demonstrating that multi-stakeholder cooperation is essential to achieving a sustainable future in agriculture.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 2: Zero Hunger – The article focuses on strengthening global food security, sustainable agriculture, and improving farm productivity.
• SDG 9: Industry, Innovation and Infrastructure – The core theme is the application of advanced technology, AI, and research to innovate the agricultural sector.
• SDG 12: Responsible Consumption and Production – A specific project mentioned deals with repurposing agricultural waste, promoting a circular economy.
• SDG 13: Climate Action – The article discusses the development of climate-resilient and climate-smart farming practices.
• SDG 17: Partnerships for the Goals – The entire event described is a multi-stakeholder collaboration between academia, industry, and researchers to achieve common goals.

2. What specific targets under those SDGs can be identified based on the article’s content?

• SDG 2: Zero Hunger
  • Target 2.4: “By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change…”. The article directly addresses this by discussing initiatives for “sustainable agriculture,” “climate-resilient farming,” and technologies that “directly improve farm productivity and sustainability.”
• SDG 9: Industry, Innovation and Infrastructure
  • Target 9.5: “Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries…”. The article is centered on this target, highlighting CIDA’s mission to “build a dynamic community of researchers” and its Research Innovation Fund which provides “seed support for collaborative research that seeks to advance digital agriculture through novel and cutting-edge projects.” Initiatives like CROPPS, NASA ACRES, and AI LEAF are prime examples of enhancing scientific research and technology.
  • Target 9.b: “Support domestic technology development, research and innovation in developing countries…”. This is referenced in the discussion on “Scaling up Digital Agriculture in Africa: Role of Enabling Environments and Small and Medium-Sized Enterprises,” which focuses on expanding these technological advancements to developing regions.
• SDG 12: Responsible Consumption and Production
  • Target 12.5: “By 2030, substantially reduce waste generation through prevention, reduction, recycling and reuse.” This is directly addressed by Professor Jeff Tester’s presentation on “Integrated System Modeling for Valorizing Agricultural and Food Waste in a Sustainable Circular Bioeconomy with Energy and Nutrient Recovery,” which explores methods to repurpose agricultural byproducts.
• SDG 13: Climate Action
  • Target 13.1: “Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.” The article mentions the development of “climate-resilient farming” and the NSF-funded “AI LEAF institute,” which “develops decision-support tools for climate-smart farming,” directly contributing to this target.
• SDG 17: Partnerships for the Goals
  • Target 17.16: “Enhance the Global Partnership for Sustainable Development, complemented by multi-stakeholder partnerships…”. The CIDA workshop itself is an embodiment of this target, bringing together “faculty and students from across” multiple colleges, “as well as industry partners and stakeholders.” The article emphasizes that CIDA’s uniqueness is its “ecosystem” approach, “accelerating innovation” by bringing together diverse groups.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• For SDG 2 (Target 2.4):
  • Implied Indicator: Increased farm productivity and sustainability. The article mentions that initiatives like CAST are “testing innovations that can directly improve farm productivity and sustainability,” suggesting that changes in yield, resource efficiency, and environmental impact are key metrics.
• For SDG 9 (Target 9.5):
  • Implied Indicator: Number of research projects and innovations developed. The CIDA “Research Innovation Fund” which supports “cutting-edge projects” and the mention of ag-tech startups catalyzed by “Grow-NY” imply that the quantity and impact of these funded projects and new businesses are measures of progress.
• For SDG 12 (Target 12.5):
  • Implied Indicator: Amount of agricultural waste valorized. The project on “Valorizing Agricultural and Food Waste” implies that a key metric for success would be the volume or percentage of agricultural byproducts that are successfully repurposed into valuable resources like energy or nutrients.
• For SDG 13 (Target 13.1):
  • Implied Indicator: Adoption of climate-smart farming tools. The development of “decision-support tools for climate-smart farming” by the AI LEAF institute suggests that the number of farms or agricultural systems implementing these tools to enhance resilience would be a relevant indicator.
• For SDG 17 (Target 17.16):
  • Implied Indicator: Number and diversity of partnerships. The article describes the CIDA workshop as a gathering of experts from “veterinary medicine, computer science, law, and ethics” and “industry partners.” The success of this ecosystem can be measured by the number of active collaborations and joint projects between these different stakeholders.

4. Table of SDGs, Targets, and Indicators

Source: news.cornell.edu