Basso Lab Introduces New System to Improve U.S. Cropland Nitrous Oxide Predictions

March 5, 2026

Dr. Bruno Basso, a Hannah Distinguished Professor in the Department of Earth and Environmental Sciences, co-led a research team that developed a new machine learning–based system capable of predicting nitrous oxide emissions from U.S. croplands with more than 80% accuracy. Working with former MSU graduate student—and current Basso Lab postdoctoral researcher—Prateek Sharma, as well as University Distinguished Professor G. Philip Robertson, Basso helped create a hybrid modeling approach that combines machine learning with ecosystem models to better capture daily emissions influenced by weather, soil conditions and crop management. Built using more than 12,000 field measurements across 17 sites in the Midwest and Great Plains, the model significantly improves on traditional prediction methods and could support field-specific strategies to reduce agricultural greenhouse gas emissions while improving national emissions accounting. The Basso Lab research team included: Aditya Manuraj, Neville Millar, Tommaso Tadiello, Mukta Sharma, and Mathieu Delandmeter. The study was published in Proceedings of the National Academy of Sciences.

Read the full article at MSU AgBioResearch