Abstract
AbstractAgricultural 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.
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