Algorithm Development for Nitrogen Recommendations Based on Aerial Imagery: An Agronomist Approach.

Nitrogen (N) management is one of the most complex and expensive aspects of crop production.  Changes in plant genetics, earlier planting dates, larger farm size which compresses time available for field work per acre, equipment innovations, increasing fuel and N costs, as well as concerns with potential environmental contamination all contribute to this increased complexity. Balancing time and financial resources in an effort to maximize yield and profitability, while still being a good environmental steward has become difficult for producers.  Producers need tools to assist them in optimizing their N management program by removing the year to year uncertainty in identifying the right time and rate for N applications. 

Many attempts have been made to develop new tools and methodologies for optimizing site-specific N management.  Previous efforts with active optical sensor technology, however promising, has been meet with poor adoption.  The rise of small unmanned aircraft systems (sUAS) has led to a flourish in research and development for utilizing aerial imagery for N management.  However, availability of algorithms for properly converting the spectral data into accurate crop specific N recommendations is sparse.  The development of crop specific N recommendation algorithms require more than an understanding of remote sensing, it requires in-depth knowledge of crop physiology and soil fertility in order to properly interpret the meaning of crop spectral data for identifying the presence of N stress.  By utilizing sound agronomic and remote sensing principles, many approaches can be used for developing N recommendation algorithms for aerial imagery.