U.S. Department of Agriculture: Agricultural Research Service, Lincoln, Nebraska


Improving publicly available corn nitrogen rate recommendation tools with soil and weather measurements

Curtis J. Ransom, USDA Agricultural Research Service
Newell R. Kitchen, USDA Agricultural Research Service
John E. Sawyer, Iowa State University
James J. Camberato, Purdue University
Paul R. Carter, Independent Agronomist
Richard B. Ferguson, University of Nebraska–Lincoln
Fabián G. Fernández, University of Minnesota Twin Cities
David W. Franzen, North Dakota State University
Carrie A.M. Laboski, University of Wisconsin-Madison
D. Brenton Myers, Corteva Agriscience
Emerson D. Nafziger, University of Illinois Urbana-Champaign
John F. Shanahan, Soil Health Institute

Document Type Article


Improving corn (Zea mays L.) N fertilizer rate recommendation tools is necessary for improving farmers’ profits and minimizing N pollution. Research has repeatedly shown that weather and soil factors influence available N and crop N need. Adjusting available corn N recommendation tools with soil and weather measurements could improve farmers’ ability to manage N. The aim of this research was to improve publicly available N recommendation tools with site-specific soil and weather measurements. Information from 49 site-years of N response trials in the U.S. Midwest was used to evaluate 21 rate recommendation tools for a single (at-planting) and split (at-planting + sidedress) N application. Using elastic net and decision tree algorithms, the difference between each tool's N recommendation and the economically optimum nitrogen rate (EONR) was modeled against soil and weather measurements. The model's predicted values were used to adjust the tools. Unadjusted the best performing tool had r2 =.24; after adjustment, the best performing tool had r2 =.57. Overall tool improvement was modest and sometimes required many additional inputs. Using weather measurements (e.g., evenness of rainfall or abundant and well-distributed rainfall) helped increase N recommendations by accounting for N loss while soil measurements (e.g., pH and total C) helped decrease N recommendations when there was sufficient available soil N. This investigation showed that incorporating soil and weather measurements is a viable approach for improving corn N recommendation tools regionally; but even with adjustments, tools still have room for additional improvement.