PubMed · 2026-07-02
Scientists have reviewed and compared a range of tools, from old-school manual counting to modern AI, for measuring how well beneficial soil fungi colonize plant roots. The review helps researchers pick the right method for their needs, with machine learning approaches showing the most promise for fast, accurate, consistent results.
The review synthesizes studies on AMF colonization quantification published from 2001 to 2026, covering both traditional and emerging image-based methods.
Deep learning tools such as AMFinder, TAIM, and Mask R-CNN represent the cutting edge, offering automated, high-throughput root colonization assessment compared to manual gridline intersection counting.
Comprehensive reviews specifically focused on image-based AMF quantification methods remain scarce, leaving a guidance gap that this paper directly addresses for non-expert researchers.