Ohio State University scientists develop early detection tool for beech leaf disease
Diseases of trees can profoundly impact forest ecosystems. Beech is one of the dominant tree species in beech-maple forests, a major component of terrestrial ecosystems in the eastern United States. Beech leaf disease (BLD) was discovered on American beech trees in northeast Ohio in 2012 and it has now spread across nine states in the northeastern U.S. and the Canadian province of Ontario. The disease affects the leaves and buds. Eventually no new leaves are produced, and the buds desiccate and wither on the infected branches, leading to tree death. The cause of the disease isn’t known, so it is important to find a way manage it. Early detection and rapid response via either treatment or tree removal are the most cost-effective measures. Until now, however, we had no real way to detect beech leaf disease in the early stages of new outbreaks.
In response, researchers at the Ohio State University are investigating and testing the use of artificial intelligence technology to detect BLD in early stages. The scientists developed an early in-field detection for BLD using near-infrared spectroscopy.
The result of this new technology could prove valuable for early detection of BLD as well as other forest diseases. This new advanced tool gives managers a leg up on the disease by allowing them to carefully map its true distribution and implementing management strategies ahead of the moving disease front.
Link to full statement on website: http://landgrantimpacts.tamu.edu/impacts/show/5801