Rate is one of the most crucial decisions in the nitrogen management process. Our on-farm research has shown that the most profitable N rate varies widely from field to field, and from place to place within a field. (See more: Field-Scale Variability in Optimal Nitrogen Fertilizer Rate for Corn)
In order to manage this variability, producers need to have a way to reliably diagnose where to put more N and where to put less. Diagnosis has, unfortunately, turned out to be difficult. Recent research has shown that crop color is a more accurate way to diagnose N need than other methods.
Diagnosis needs to not only be accurate but convenient. A hand-held meter can accurately diagnose nitrogen need, but is too slow to be convenient over large acreage. Aerial photos can also predict nitrogen need, and can be acquired quickly over large areas. However, weather may delay acquisition of photos from airplanes or drones. Large fleets of small satellites are helping to overcome this obstacle since they are capturing many images of a field each week and you can look back in time for a clear day instead of waiting for one in the future. Another limitation is that images are difficult to use successfully until a crop has reached full canopy (due to interference by soil color).
Reflectance (color) sensors mounted on a fertilizer applicator allow diagnosis and application of the appropriate fertilizer rate in a single trip through the field. This technology offers great promise to reduce nitrogen rates and minimize nitrogen loss to the environment while maintaining full productivity. Sensor-guided nitrogen management for corn (PDF) and cotton (PDF) is one of the main components of our research and extension programming on nitrogen management. Scharf has developed a manual to help producers, retailers and consultants who are interested in adopting crop sensor technology to guide variable-rate N applications. Managing nitrogen with crop sensors: Why and how (PDF) is based on six years of on-farm demonstrations, which followed seven years of research to set the foundation for why and how sensors can help to manage nitrogen fertilizer better.