A team of Michigan State University researchers has developed a groundbreaking machine learning system capable of predicting nitrous oxide emissions from U.S. croplands with unprecedented accuracy, a finding with valuable implications for national greenhouse gas accounting and mitigation.
The study was published in the journal Proceedings of the U.S. National Academy of Sciences.
Nitrous oxide is a greenhouse gas emitted in agricultural operations primarily through the use of nitrogen fertilizers. Accurately predicting emissions has eluded scientists due to the complex interplay of weather, soil conditions and crop management practices that influence the microbes responsible for producing the gas.