Categorical Analysis of Spatial Variability In Corn Yield Response to Nitrogen.

Nitrogen (N) fertilizer can be applied to corn (Zea mays L.) in variable-rate (VRN) based on soil properties and topography measurements. However, we lack of basic knowledge and practical methods for identifying the most useful soil properties to guide VRN applications. The objective of this study was to develop a methodology for identifying predictable relationships between economic yield response (YR), a yield increase that pays for N, and commonly measured soil and terrain attributes in the presence of spatial dependence with fields. Six 30-ha no-till fields were studied during 6 yr. in central Iowa. Urea-ammonium nitrate solution was sidedressed at 112 and 140 kg N ha^-1 in alternating strips replicated from 10 to 22 times within each field. Yield responses to the high N rate were calculated in a 20 x 25 m grid pattern and classified into profitable and non-profitable categories within each field. Autologistic models, which address spatial dependence of categorical response variables, were used to identify which (if any) of the following factors economically affected YR: elevation, apparent soil electrical conductivity (ECa), slope, topographic wetness index (TWI), or digital soil map units.  Significant effects of some of the factors were found within eight of 15 site-years. Within five of these eight site-years, well-drained areas with lower ECa and TWI values and higher elevation and slope had the higher probability of profitable YR, but these effects were not constant over time. The proposed methodology makes use of high- resolution spatial data that increase the ability for identifying areas within fields profitable to N. Also, farmers can explore the feasibility of VRN by applying several fertilizer strips with only two rates that are slightly below or above their uniform optimal N rates.