New Risk Maps Empower Soybean Farmers to Tackle Charcoal Rot Early.

A groundbreaking study published in Phytopathology has introduced a powerful new tool to help soybean farmers predict and manage the destructive soilborne disease charcoal rot before it impacts their crops. The disease, caused by the fungus Macrophomina phaseolina (Mp), thrives under hot and dry conditions, often going undetected until significant damage has occurred. Now, researchers have developed high-resolution risk maps that forecast disease-prone areas based on underlying soil properties.

The study was led by Horacio Lopez-Nicora, Assistant Professor of Soybean Pathology and Nematology at The Ohio State University, alongside postdoctoral researcher Sandip Mondal. The research team collected soil samples from 297 soybean fields across seven departments in Paraguay—one of South America’s key soybean-producing regions.

Their analysis found that Mp is most abundant in the southeastern part of the country, where soils tend to be more acidic and rich in clay. These conditions were identified as critical factors influencing the proliferation of the fungus. Using geostatistical techniques such as ordinary kriging and co-kriging, the team generated interpolated maps showing colony-forming unit (CFU) densities of Mp across the landscape. These methods allowed them to accurately predict disease hotspots based on soil characteristics, even in unsampled areas.

“By using geostatistical mapping and predictive modeling, we're giving farmers the ability to forecast disease risk before it becomes a problem,” said Lopez-Nicora.

The innovation lies in its proactive approach. Rather than relying on visible symptoms that often appear too late, the risk maps incorporate measurable soil attributes—such as pH, clay content, and cation exchange capacity—that are strongly correlated with the presence of Mp. Among these, lower pH showed a notably strong negative correlation with fungal abundance, helping to pinpoint where the pathogen is most likely to thrive.

To assess the spatial distribution of Mp, the researchers employed Moran’s I statistic, which confirmed that the fungus clusters in specific areas instead of spreading uniformly. This discovery underscores the importance of precision in disease scouting, as traditional methods may overlook localized hotspots.

“Charcoal rot doesn't spread evenly across a field. It pops up in the right conditions, and those conditions are often hiding in the soil,” Mondal explained. “This tool helps uncover those high-risk zones.”

These findings pave the way for more targeted disease management strategies. By identifying vulnerable areas, farmers can adopt more efficient agricultural practices—such as adjusting planting dates, rotating crops, or applying soil treatments—only where they’re most needed. This not only helps conserve resources and cut input costs, but also supports higher crop yields under increasingly unpredictable climate conditions.

Beyond individual farms, the research holds promise for broader agricultural policy and planning. “The implications go beyond individual growers,” said Mondal. “For policymakers, the study offers a scalable strategy to support food security by integrating soil data and disease forecasting into national crop protection programs.”

With contributions from scientists at the University of Wisconsin–Madison, Universidad Nacional de Asunción, and Universidad Católica in Paraguay, the project exemplifies how international collaboration and smart data application can lead to transformative change in agriculture.

“This isn’t just about soybeans or one disease,” Lopez-Nicora emphasized. “It’s about showing how spatial data and soil science can help make farming more predictive, efficient, and sustainable.”

Source:https://phys.org/news/2025-04-soybean-farmers-charcoal.html

This is non-financial/medical advice and made using AI so could be wrong.