|Kaspar, Thomas - Tom|
|Karlen, Douglas - Doug|
Submitted to: Agricultural Systems
Publication Type: Peer reviewed journal
Publication Acceptance Date: 5/24/1999
Publication Date: N/A
Citation: Paz, J.O., Batchelor, W.D., Babcock, B.A., Colvin, T.S., Logsdon, S.D., Kaspar, T.C., Karlen, D.L. 1999. Model-based technique to determine variable rate nitrogen for corn. Agricultural Systems. 61:69-75. Interpretive Summary: One of the primary goals of precision farming is to maximize profit for corn production. We have measured a great deal of corn yield variability across fields. It appears that it would be a good idea to vary the application rate of nitrogen fertilizer across the field to optimize yield and net return. Models have been developed that can predict the growth of corn in response to weather and the application of nitrogen. One of the models named CERES-Maize was used to try to identify the proper amount of nitrogen to apply on 224 locations within a 40-acre field. We have measured yields at these 224 locations for 10 years and used this information along with the historical weather record to calibrate and test the model. The model was able to explain about 57% of the yield variability over 3 test years. The best rate of nitrogen fertilization varied from less than 60 to more than 180 pounds per acre on individual locations if the goal was to have maximum net return for the whole field. Farmers can use this information to alter their management practices to maximize their yield and profit.
Technical Abstract: Past efforts to correlate yield from small field plots to soil type, elevation, fertility, and other factors have been only partially successful for characterizing spatial variability in corn (Zea mays L.) yield. Furthermore, methods to determine optimum nitrogen rate in grids across fields depend upon the ability to accurately predict yield variability and corn response to nitrogen. In this paper, we developed a technique to use the CERES-Maize crop growth model to characterize corn yield variability. The model was calibrated using 3 years of data from 224 grids in a 16 ha field near Boone, IA. The model gave excellent predictions of yield trends along transects in the field, explaining approximately 57% of the yield variability. Once the model was calibrated for each grid cell, optimum nitrogen rate to maximize net return was computed for each location using 22 years of historical weather data. Results show high spatial distribution of optimum nitrogen fertilizer prescriptions for grids across the field. Grid-level nitrogen fertilizer management used lower amounts of fertilizer, produced higher yields, and was more profitable than either transect- or field-level (single rate) fertilizer application.