Evaluating the Interaction of Agronomic Practices for Maximum Yield In Corn.

Increasing crop productivity requires identifying the practices that are most promising in the midst of new technologies. Historically, simultaneously evaluating multiple agronomic inputs has been a challenge using traditional factorial statistical approaches. However, evaluating the interaction of multiple agronomic management decisions is essential to determine which new technologies, combined with proven cultural practices, most enhance corn performance. Evaluating multiple new technologies on one site can expedite further research into determining the optimums of these yield-increasing practices and not wasting time on those that are not critical to increasing yield. This approach assists producers in evaluating the cost of these new practices and technologies against their yield increasing potential. Our proposed project uses a non-factorial approach that allows us to evaluate several management decisions while reducing the overall number of treatments required, thereby eliminating the limitations of traditional factorial approaches. The objective of this research is to evaluate the impact of multiple agronomic management decisions including the rate of nitrogen and potassium fertilizers, seeding rate, and timing of fungicide application. In addition to yield, the experiment will measure leaf disease severity as an additional method to evaluate the interaction of the fungicide treatments with the plant nutrients. Data from 5-site years in Ohio will be presented.