Which corn nitrogen recommendation tools best help farmers achieve corn economically-optimal nitrogen rate?

Authors: RANSOM, CURTIS - University Of Missouri; Kitchen, Newell

Submitted to: Crops and Soils
Publication Type: Trade Journal
Publication Acceptance Date: 4/20/2020
Publication Date: 9/8/2020
Citation: Ransom, C., Kitchen, N.R. 2020. Which corn nitrogen recommendation tools best help farmers achieve corn economically-optimal nitrogen rate?. Crops and Soils. 53(5):56-60. https://doi.org/10.1002/crso.20069.
DOI: https://doi.org/10.1002/crso.20069

Interpretive Summary: Nitrogen (N) fertilizer inputs are generally necessary for optimizing corn yields, but for this crop, N is the most challenging plant nutrient to manage optimally. 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. 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. The better tools tended to underestimate EONR for sites where a large amount of N fertilizer was needed. Overall, these findings demonstrate the difficulty of recommending rates close to the EONR. While current publicly available N recommendation tools may be successful on individual fields or sub-regions, they were not universally reliable over the diversity of soils and weather in this study. This research shows that better tools are needed that are adaptive to varying soil and weather conditions for Midwest corn acres. This research will help producers and their consultants recognize the need for using site-specific soil and in-season weather information for corn N fertilizer recommendations.

Technical Abstract: Nitrogen (N) fertilizer inputs are generally necessary for optimizing corn yields, but for this crop, N is the most challenging plant nutrient to manage optimally. It is challenging because crop N need is impacted by a combination of weather conditions, management practices, and the crop’s genetics. These factors, expressed through the soil and distinctive growing conditions, can change crop N need both between and within fields. Being able to manage this complexity correctly and apply the correct rate of N is paramount for optimizing profits and minimizing N lost to the environment. To assist farmers with corn N rate decisions, multiple publicly- available recommendation tools have been developed over the years. This research was conducted to evaluate these tools in a side-by-side manner to see how their recommendations performed relative to the economically optimal N rate (EONR). Tools that included some type of soil test (like the pre-plant or pre-sidedress soil nitrate tests) generally preformed best. Additionally, crop canopy sensing performed well. These tools that worked better tended to underestimate EONR for sites where a large amount of N fertilizer was needed. With some tools average N recommendations were approximately the same as EONR, but this resulted because the values of sites with over-application were approximately the same as the values of sites with under-application. Therefore, another performance metric was needed for ranking the tools based on the percentage of sites that came close to EONR. Sites within ± 27 lbs N/ac of EONR were considered reasonably close to EONR (or “Good”). The MRTN (Maximum Return To Nitrogen) tool as well as the tools using some soil testing performed best, but the best tools still only had about 40% of sites within that “good” category. These tools performed best on sites that tended to require between 120 and 200 lbs N/ac. Yield-goal based tools generally performed poorly in this study. Overall, these findings demonstrate the difficulty of recommending rates close to the EONR, and that while current publicly available N recommendation tools may be successful on individual fields or sub-regions, they were not universally reliable over the diversity of soils and weather in this study. Refinement of current tools or development of new tools that are adaptive and more responsive to soil and weather conditions have the potential for improved performance.