Traditional nitrogen (N) management schemes for corn production in the USA have resulted in low N use efficiency (NUE), environmental contamination, and considerable public debate regarding use of N fertilizers in crop production. Hence, development of alternative schemes that improve NUE and minimize environmental impact will be crucial to sustaining corn-based farming in the USA. The major causes for low NUE of traditional N management practices are: 1) pre-plant application of large doses of N, and 2) uniform application rates to spatially variable landscapes. Pre-plant applications of high N rates results in poor synchronization between N supply and crop uptake. Uniform applications within fields discount the fact that N supplies from the soil and crop N uptake is spatially variable. When N is managed in this way it is at considerable risk for environmental loss. The use of a soil-based management zones (MZ) approach has been proposed as a means do direct variable N application rates to better match N supply with landscape spatial variation in crop N requirements. However, evidence has accumulated suggesting that the MZ approach alone will not be completely effective in making accurate variable N applications, given the large effect temporal variation in corn belt climate has on expression of spatial variation in crop N needs. We have assembled a prototype high-clearance tractor configured with active crop canopy sensors, drop nozzles with electronic valves, and variable rate controller that is intended to deliver in-season variable rates of liquid N fertilizer period from canopy closure up to flowering based on crop needs. Various small plot and on farm strip trials were conducted in central Nebraska to evaluate the various components of the high-clearance applicator and the response of corn grain yields to varying rates of N applied at different growth stages and across landscape spatial variability. Spatial variation in soil properties like soil color and apparent electrical conductivity were also assessed. Results indicated that the active sensors are capable of detecting variation in corn canopy N status during the window we propose to apply N. Yield responses to N application were observed to vary across the landscape, and N responsiveness was associated with sensor-determined variation in canopy N status as well as spatial variation in soil properties such as soil color. This poster presentation will highlight our vision for combining the soil-based MZ and the crop-based remote sensing approaches into an integrated system for making in-season variable N applications under site-specific soil and ever-changing climatic conditions, to more efficiently apply N.