Soil hydrologic grouping guide which soil and weather properties best estimate corn nitrogen need. (27th October 2021)

• Record Type: Journal Article
• Authors: Bean, Gregory Mac; Ransom, Curtis J.; Kitchen, Newell R.; Scharf, Peter C.; Veum, Kristen S.; Camberato, James J.; Ferguson, Richard B.; Fernández, Fabián G.; Franzen, David W.; Laboski, Carrie A. M.; Nafziger, Emerson D.; Sawyer, John E.; Nielsen, Robert L.
• Is Part Of: Agronomy Journal. Volume 113:Number 6(2021)
• Page Start: 5541
• Page End: 5555
• Publication Date: 2021-10-27
• Subjects: Agronomy -- Periodicals; 630
• DOI: 10.1002/agj2.20888
• Languages: English
• ISSNs: 0002-1962

Abstract

Abstract: Nitrogen fertilizer recommendations in corn (Zea mays L.) that match the economically optimal nitrogen fertilizer rate (EONR) are imperative for profitability and minimizing environmental degradation. However, the amount of soil N available for the crop depends on soil and weather factors, making it difficult to know the EONR from year‐to‐year and from field‐to‐field. Our objective was to explore, within the framework of hydrologic soil groups and drainage classifications (HGDC), which site‐specific soil and weather properties best estimated corn N needs (i.e., EONR) for two application timings (at‐planting and side‐dress). Included in this investigation was a validation step using an independent dataset. Forty‐nine N response trials conducted across the U.S. Midwest Corn Belt over three growing seasons (2014–2016) were used for recommendation model development, and 181 independent site‐years were used for validation. For HGDC models, soil organic matter (SOM), clay content, and evenness of rainfall distribution before side‐dress N application were the properties generally most helpful in predicting EONR. Using the validation data, model recommendations were within 34 kg N ha –1 of EONR for 37 and 42% of the sites with a root mean square error (RMSE) of 70 and 68 kg N ha –1 for at‐planting and side‐dress applications, respectively. Compared to state‐specific recommendations, sites needing <100 kg N ha –1 or no N were better estimated with HGDC models. In contrast, for sites where EONR was >150 kg N ha –1, HGDC models underestimated N needs compared to state specific. These results show HGDC groupings could aid in developing tools for N fertilizer recommendations. Core Ideas: Soil hydrologic classifications aid in determining corn N fertilizer rates. Economically optimal N rate was best predicted by different soil and weather properties for each hydrologic group. Soil organic matter, clay, and rainfall evenness generally helped in estimating economically optimal N rate. Compared to state N recommendations, developed models were better when economically optimal N rate <100 kg ha −1 .