Overview
Scientists have employed a combination of machine learning and a high-resolution imaging robot to measure and map extensive underground fungal networks. The research focused on quantifying the Earth's carbon circulatory system, specifically the vast fungal webs present beneath the surface.
Approach
The methodology involved the application of machine learning algorithms in conjunction with data acquired from a high-resolution imaging robot. This dual approach was instrumental in enabling the measurement and mapping of subterranean fungal structures. The objective was to characterize the extent of these fungal webs, which are described as a component of the Earth's carbon circulatory system.