AI suggested options to reduce global ammonia emissions from 3 major crops by 38 percent

Artificial intelligence has been taught to calculate ammonia emissions in agricultural systems. Researchers have developed an artificial intelligence-enabled model to help reduce global ammonia emissions from cropland wheat, rice and corn. An international research team led by the Hong Kong University of Science and Technology (HKUST) has created an artificial intelligence (AI) model that could help mitigate global ammonia (NH 3) emissions from agriculture. The study, titled “Managing Fertilizer Use to Reduce Global Ammonia Emissions,” was published in the journal Nature. Using the power of machine learning, this pioneering study not only found that global NH 3 emissions from cropland are lower than previously estimated, but also demonstrated how optimizing fertilizer management can effectively reduce emissions by an additional 38% without compromising overall crop yields . Ammonia emissions from various agricultural and industrial processes can cause air and water pollution, ...