Nitrogen application in agriculture is a vital process for optimal plant growth and yield outcomes. Different factors such as topography, soil properties, historical yield, and crop stress affect nitrogen (N) needs within a field. Applying variable N within a field could improve precision agriculture. Optimal N management is a system that involves applying a conservative variable base rate at or shortly after planting followed by in-season assessment and, if needed, variable rate application—with the plant being the predictive integrator of this process. The object of this study was to evaluate variable rate pre- and in-season N (VRPIN) system compared to traditional N management used by the grower in a potato-wheat-wheat cropping system in terms of yield and crop quality. Nitrogen zones were created within four potato fields near Grace, Idaho, USA. Zones delineations were based on farmer field knowledge, historical yield maps, topography, bare soil imagery, and normalized difference vegetation index (NDVI) and visible imagery history. Nitrogen rates for each zone were determined dependent upon yield goal and residual topsoil N, legume credits, manure credits, crop residue, and irrigation water N concentration. Number of zones varied between 2 and 4 depending on the field. Uniform strips were placed through all zones as a positive control based on N management used by the grower. All N for the growing season was applied shortly after planting with a polymer coated urea (PCU). Crop canopy was monitored in-season at least twice weekly for visible and NDVI remote sensing to check for pattern changes and specifically row closure differences. Tissue samples were taken in mid-rate N zones three times and in every zone once and analyzed for nitrate-N. If nitrate-N levels were low, fertilization plots were created to apply variable rate N (VRN) to small portions of each zone. This was performed to check if in-season VRN would benefit yields and crop quality. Yield samples were collected at 4-6 locations within each zone and the uniform strips to assess crop quality and specific gravity by grade. Data will be analyzed with an analysis of variance (ANOVA) to determine significant differences between zones and uniform strips.