Developing Proximal and Remote Sensing-based Precision Sulfur Management Strategies

Study author(s): Yuxin Miao, University of Minnesota
Growing season(s): 2024, 2025, 2026
Minnesota location(s): Various

Note: Reports, including figures and tables, are available for download below.

2025 Growing Season

What is this study about?

Farmers across Minnesota commonly spread sulfur (S) fertilizers at a blanket, uniform rate across entire fields (typically 20–30 lb/ac). However, soil conditions fluctuate within a single field, and ongoing field trials show that the actual amount of sulfur corn needs ranges anywhere from 0 to 40 lb/ac. Applying a flat rate leads to either under-fertilizing parts of the field (reducing crop yields) or over-fertilizing (wasting money and risking nutrient runoff). Traditional soil tests are notoriously unreliable for predicting sulfur needs, so a new, rapid way to measure crop sulfur levels directly in the field is necessary.

What will be addressed?

  • Lack of precise sulfur diagnostics: Conventional lab testing of plant tissue takes days or weeks, making in-season crop management difficult.
  • Uniform application waste: Applying the same fertilizer rate across varying soils causes profit losses from both under-application and over-application.

Goals, and Farmer Benefits

  • Increased Profitability & Resource Efficiency: By applying sulfur only where and when corn needs it, farmers can cut unnecessary fertilizer costs and optimize yield potential.
  • Real-time Crop Health Insights: Rapid diagnosis allows growers to make informed, site-specific fertilizer adjustments during the growing season.
  • Environmental Protection: Preventing over-application minimizes nutrient runoff into local waters.

What Specifically Will Be Studied?

Researchers will test three advanced sensing technologies to non-destructively measure sulfur and other nutrients in growing corn:

  1. Portable Sensors: Handheld devices that scan living corn leaves directly in the field to give instant plant sulfur readings.
  2. UAV (Drone) Hyperspectral Imaging: Drones fitted with specialized cameras to map corn sulfur levels across whole fields.
  3. PlanetScope Satellite Imaging: High-resolution satellite data to monitor overall crop growth and health throughout the season.

How the Study Will Be Conducted

  • Field Trials (Years 1–2): Experiments will run on university research plots and on working farms using five sulfur application rates (0, 10, 20, 30, and 40 lb S/ac).
  • Data & Sample Collection: Researchers will take drone footage, satellite images, and handheld leaf and canopy scans during the V6–V9 corn growth stages, then cross-reference those scans with traditional laboratory tissue tests.
  • Model Development: Scientists will build machine learning models that translate drone, satellite, and portable sensing readings into accurate map-based fertilizer recommendations.
  • On-Farm Strip Trials (Year 3): Promising variable-rate strategies will be tested directly on partner farms using randomized strip trials to measure real-world performance, overall yield improvement, sulfur use efficiency, and economic returns. Participating farmers receive compensation for hosting the trial plots.
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