Leveraging Machine Learning to Improve Soil Greenhouse Gas Predictions.

Agricultural soils are large sources of greenhouse gas emissions, particularly the potent nitrous oxide (N2O). While N2O emissions can be predicted by traditional biogeochemical models, these forecasts contain a lot of uncertainty. New efforts, including research (https://doi.org/10.1002/agj2.21185) published in the recent Agronomy Journal special section "Machine Learning in Agriculture," use machine learning to improve N2O flux predictions and guide management interventions. [ABSTRACT FROM AUTHOR]