Corn nitrogen rate recommendation tools’ performance across eight US midwest corn belt states

Authors: RANSOM, C - University Of Missouri; Kitchen, Newell; CAMBERATO, J - Purdue University; CARTER, P - Dupont Pioneer Hi-Bred; FERGUSON, R - University Of Nebraska; FERNANDEZ, F - University Of Minnesota; FRANZEN, D - North Dakota State University; LABOSKI, C.A.M. - University Of Wisconsin; NAFZIGER, E - University Of Illinois; SAWYER, J - Iowa State University; SCHARF, P - University Of Missouri; SHANAHAN, J - Fortigen

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/15/2019
Publication Date: 1/9/2020
Citation: Ransom, C.J., Kitchen, N.R., Camberato, J.J., Carter, P.R., Ferguson, R.B., Fernandez, F.G., Franzen, D.W., Laboski, C., Nafziger, E.D., Sawyer, J.E., Scharf, P.C., Shanahan, J.F. 2020. Corn nitrogen rate recommendation tools’ performance across eight US midwest corn belt states. Agronomy Journal. 112(1):470-492. https://doi.org/10.1002/agj2.20035.
DOI: https://doi.org/10.1002/agj2.20035

Interpretive Summary: Applying nitrogen (N) fertilizer at the rate sufficient for crop N needs, but not more, can improve farmer’s profits and help reduce loss of N off agricultural fields. An evaluation of current publically-available tools used for determining fertilizer rates for corn was assessed across a wide range of growing conditions. In all, a total of 31 tool recommendations were evaluated using research conducted on 49 fields across eight U.S. Midwest states. These tools were evaluated for how well they related to the economic optimal N rate (EONR) from each field. Additionally, each tool was assessed for how profitable and their environmental costs were relative to EONR. No one tool performed well for predicting EONR across all 49 fields, but the better performing tools included tools that utilized a soil nitrate test or measurements of the canopy color. Tools that on average came close to EONR included the maximum return to N and soil nitrate tests. Most tools had similar profitable returns. Yield-goal tools had the greatest negative environmental impact. This research shows that better tools are needed for Midwest corn acres that are adaptive to varying soil and weather conditions. This research will help producers and their consultants recognize the need for using site-specific soil and in-season weather information when making corn N fertilizer recommendations.

Technical Abstract: Determining which corn (Zea mays L.) N fertilizer rate recommendation tools best predict crop N need would be valuable for maximizing profits and minimizing environmental consequences. Simultaneous comparisons of multiple tools across varied environmental conditions have been limited. The objectives of this research were to evaluate the performance of publicly-available N fertilizer recommendation tools across diverse soil and weather conditions for: 1) prescribing N rates for planting and split fertilizer applications, and 2) economic and environmental impact. Corn N response trials using standardized methods were conducted at 49 sites, spanning eight U.S. Midwest states and three growing seasons. Nitrogen applications included eight rates in 45 kg N/ha increments all at-planting and matching rates with 45 kg N/ha at-planting plus at the V9 development stage (split). Recommendation tool performance was compared to the economically optimal N rate (EONR). Over this large geographic region only 11 of 31 recommendation tools (soil NO3–N tests and canopy reflectance sensing) produced N rate recommendations related to EONR (P = 0.10); even for those 11, coefficients of determination were always = 0.20. With other metrics of performance the maximum return to N and soil NO3–N tests came close to matching EONR. Only the Maize-N crop growth model showed decrease in profitability. Yield goal based tools resulted in the highest environmental costs. These findings demonstrate the difficulty of predicting EONR correctly and they were not universally reliable over the diversity of soils and weather in this study. Better tools are needed.