Returning organic nutrient sources (for example, straw and manure) to
rice fields is inevitable for coupling crop–livestock production. However,
an accurate estimate of net carbon (C) emissions and strategies to
mitigate the abundant methane (CH4) emission from rice fields supplied
with organic sources remain unclear. Here, using machine learning and a
global dataset, we scaled the field findings up to worldwide rice fields to
reconcile rice yields and net C emissions. An optimal organic nitrogen (N)
management was developed considering total N input, type of organic
N source and organic N proportion. A combination of optimal organic N
management with intermittent flooding achieved a 21% reduction in net
global warming potential and a 9% rise in global rice production compared
with the business-as-usual scenario. Our study provides a solution for
recycling organic N sources towards a more productive, carbon-neutral and
sustainable rice–livestock production system on a global scale.