Statistical Analysis of the Profitability of Fungicide Applications on Corn Crops in the North Central United States and Canada
Project collaborators
Damon Smith, Plant Pathology
Isaac Baumann and Maria Oros, Data Science Institute
Project start and end dates
October 2023-Jan 2024
Project Summary
This project aimed to describe fungicide use in corn crops by developing a decision-support tool using inference modeling based on historical and geographical data on crop yields from 19 states in the North Central US and Ontario, Canada. The project quantified the return on investment (ROI) for various fungicide treatments. By inputting corn prices and disease severity, the resulting model provides farmers with a tool to estimate the profitability of different fungicide applications based on real-time crop conditions, ultimately enhancing decision-making.
Key Elements of the Work
- Statistical Modeling: Advanced statistical techniques were employed to quantify the efficacy of each fungicide treatment in mitigating disease severity. This model incorporated agronomic data and economic factors to project yield increases attributable to fungicide treatments.
- Decision Support Tool: A user-friendly dashboard was created to visualize model outputs and facilitate data-driven decision-making for farmers and agricultural stakeholders.
Intended Beneficiaries
The primary beneficiaries are researchers, agronomists, farmers, and policymakers involved in corn production. These stakeholders will gain insights to improve agricultural practices and decision-making related to crop management.
Impact
Our analysis clarified the ROI for each fungicide treatment, identifying the most cost-effective options for specific input such as cost of the fungicide, corn commodity price, the expected yield, and the disease severity level. This enables stakeholders to make better-informed decisions. We also provided break-even probabilities, helping farmers and policymakers evaluate financial risks associated with different treatments and crop conditions.
Project Deliverables
- GitHub Repository: Contains the modeling approach and code.
- ROI Calculator App: Supports decision-making by providing an interactive tool for stakeholders.
- Scientific Paper: Currently in progress, detailing the methodology and insights derived from these analytical tools. The paper aims to offer the scientific community a thorough understanding of the statistical approaches used and their applications in enhancing agricultural research outcomes.