Developing Infrastructure for Implementing Adaptive Nitrogen Management Practices for Corn on a Large Scale in Iowa.

Despite considerable amount of research, managing nitrogen (N) fertilization in corn production remains highly uncertain. This is mainly due to difficulty in predicting the processes that regulate nitrogen (N) transformation in the soil under field conditions, the large variability in weather, and the rising cost of N fertilizer. Amid this uncertainty, there is a need for developing a strategy that will help growers identify factors and management practices that show the highest economic and environmental risks. A large-scale multiple-year study is being conducted to develop infrastructure for educating growers on how to evaluate the performance of a variety of practices currently used in corn production in Iowa. The major part of this study included organizing 35 local groups of growers that utilized precision farming technologies, remote sensing, guided corn stalk nitrate survey, and strip trial methodology in over 1000 fields across Iowa in 2007. The data were collected and summarized for individual groups that had similar climate and soil conditions but often used different rates, forms, timing, and methods of N fertilizer and manure applications and for larger geographic areas with a wide range of climatic and site-specific conditions.  Group meetings were organized to discuss patterns in corn N stress observed on aerial images, collect and verify management information, and to adjust objectives of the evaluations.  The study showed high probability of N stress and yield loss when spring rainfall in 2007 exceeded above long-term average data in fields that received liquid swine manure, fall-applied anhydrous ammonia, and N fertilizer applied as urea ammonium nitrate solution. The evaluations revealed a large potential for adaptive N management for identifying the best performing practices, changing growers’ behavior, estimating relative risk of one practice under perform another, and therefore, reducing uncertainty associated with N management.