For the first time, scientists have achieved a groundbreaking advancement in the accurate prediction of carbon cycles using Artificial Intelligence (AI) and supercomputers, enabling precise measurement of greenhouse gas (GHG) emissions from individual farms on a national scale. The ability to monitor these emissions is crucial for creating effective measurement, reporting, and verification systems in agriculture. This technology could drive the adoption of climate-smart farming practices and significantly contribute to global efforts in mitigating climate change.
The study, led by experts from the University of Illinois Urbana-Champaign and the University of Minnesota, was recently published in Nature Communications. It was developed with support from key funding agencies, including the U.S. Department of Energy and the U.S. National Science Foundation. The team’s solution integrates AI and advanced supercomputing to monitor changes in GHG emissions as farms implement climate-friendly practices such as cover cropping and precision nitrogen management.
The predictive modeling tool, built using Knowledge-Guided Machine Learning (KGML), combines satellite remote sensing, computational models, and AI to deliver highly accurate results. The KGML model for agriculture (KGML-Ag) is able to produce results over 10,000 times faster than traditional models, making it a powerful tool for the agricultural sector. By providing accurate carbon flux predictions at the farm level, this system allows farmers, companies, and policymakers to assess and reduce emissions throughout the agricultural supply chain.
One of the key advantages of this AI-powered system is its scalability. While initially tested in the Midwest (USA), the technology can be applied on a national and even global level, offering significant potential for reducing agricultural emissions worldwide. The model’s ability to work across different agricultural systems in various regions makes it an indispensable tool for advancing climate-smart agriculture.
This research sets a new benchmark for how farming practices can be measured uniformly, fostering better communication among stakeholders about GHG emissions.
By enabling the agriculture industry to monitor and reduce its carbon footprint, the study presents a pathway for global efforts to lower emissions, particularly in regions facing economic and environmental challenges in agriculture.
(Source: University of Illinois Urbana-Champaign)
