Project collaborators
Richard Webster and Hope Becton, North Dakota State University
Damon Smith, UW–Madison
Maria Oros, Data Science Institute
Project start and end dates
March 2025-June 2025
Project summary
“We have been working on the development of a new economic decision tool for farmers and ag professionals to help guide which pesticide products would be most economically viable on their operations. By combining years of field data from across the North Central region of the U.S., we have been able to develop models that are being integrated into this new tool that will help farmers remain profitable, especially in uncertain times.”
–Richard Webster, Assistant Professor of Plant Pathology, NDSU
Sclerotinia stem rot, also known as white mold, is ranked third among the top soybean diseases in the northern United States, causing over 26.1 million bushels of yield loss (CPN). In this meta-analysis, we evaluated the efficacy of fungicide treatments on disease reduction and their subsequent impact on grain yield. The data derive from seven years of uniform protocols applied across the northern U.S.
Our project covered three research opportunities:
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- Meta-analysis to analyze large, multi-site year datasets: Our goal was to infer mean estimates of treatment effects, incorporating heterogeneous variance structures and random effects to account for between-study variability.
- Mechanistic modeling to characterize soybean yield loss in terms of disease dynamics.
- A hybrid modeling approach that combines a probabilistic framework with the mechanistic model described above to characterize treatment profitability on a per-unit basis.
- This analysis resulted in a custom website for farmers and an API for agricultural practitioners to integrate these findings into their workflows.
Project deliverables
- Statistical consulting and reports of the analysis
- Paper publication (in progress)
- APP and API to deploy the inference results
“This project is being led by a great team of researchers from across the University of Wisconsin–Madison in the Plant Pathology Department and Data Science Institute, and North Dakota State University.”
–Richard Webster, Assistant Professor of Plant Pathology, NDSU