Improving in-Season Corn Nitrogen Fertilizer Rates with a GIS-Based Nitrogen Transformation and Loss Model.

The year to year variability in optimum fertilizer nitrogen (N) rate within the same field clearly indicates that weather drives soil and fertilizer N transformations and crop N availability in the field. Combine yield monitor data usually show at least a 2:1 ratio in grain yield within the same field, indicating that both soil and topography clearly affect yield as well. To better predict in-season optimum N rates in the field, we developed an N model that couples soil surface and subsurface N mineralization algorithms and soil and fertilizer N transformation and loss processes with terrain attributes that lead to differences in net precipitation. Processes considered in the model include soil and manure N mineralization, nitrification, denitrification, ammonia volatilization, and nitrate leaching, and the model is driven by temperature, soil moisture, pH and terrain attributes. Readily available data including soil texture, pH and organic matter, daily air temperature, precipitation/irrigation, fertilizer N source, placement and timing and crop planting/emergence date are used as model inputs. Modeled N uptake and yield vs actual yield data collected from combine yield monitors at a 10m x 10m grid will be presented in a spatial context to demonstrate the ability of this model to predict corn N uptake and grain yield and to improve the prediction of optimum in-season fertilizer N rates in a spatial context. Comparisons of model results with traditional fertilizer N recommendation strategies will also be made.