Enabling Adoption of Regenerative Agriculture through Soil Carbon Copilots
Margaret Capetz, Swati Sharma, Rafael Padilha, Peder Olsen, and Jessica Wolk, Emre Kiciman, Ranveer Chandra

TL;DR
This paper introduces an AI-driven Soil Organic Carbon Copilot that automates data integration to analyze and promote regenerative agriculture practices, helping mitigate climate change impacts on soil health.
Contribution
It presents a novel AI system that automates complex data ingestion for large-scale soil health analysis, enabling evidence-based sustainable agriculture strategies.
Findings
Diverse agricultural activity may reduce tillage effects.
Extreme weather significantly impacts soil carbon levels.
Composting can mitigate soil organic carbon loss.
Abstract
Mitigating climate change requires transforming agriculture to minimize environ mental impact and build climate resilience. Regenerative agricultural practices enhance soil organic carbon (SOC) levels, thus improving soil health and sequestering carbon. A challenge to increasing regenerative agriculture practices is cheaply measuring SOC over time and understanding how SOC is affected by regenerative agricultural practices and other environmental factors and farm management practices. To address this challenge, we introduce an AI-driven Soil Organic Carbon Copilot that automates the ingestion of complex multi-resolution, multi-modal data to provide large-scale insights into soil health and regenerative practices. Our data includes extreme weather event data (e.g., drought and wildfire incidents), farm management data (e.g., cropland information and tillage predictions), and SOC…
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Taxonomy
TopicsPhotovoltaic Systems and Sustainability · Agriculture, Land Use, Rural Development · Agricultural Systems and Practices
