Variable-rate in-season N applications have the potential to increase nitrogen use efficiency and optimize profitability. The challenge is to calibrate the vegetation indices derived from canopy sensors or imagery to account for crop growth stage, local cultural practices, and spatial variability in plant vigor. The concept of using a high N reference area to calculate a sufficiency index for plants being considered for supplemental N application was developed for plot research with SPAD chlorophyll meters. Extending this calibration approach to field scale operations involves establishment of high N reference strips. In both cases, sufficiency index values of plants are used to calculate an in-season N application rate based on active sensor reflectance values. Many producers and commercial applicators feel the establishment and use of high N reference strips in fields will be problematic and lead to confusion and errors. A statistical approach was coupled with real-time data collection to progressively update and analyze the data base to generate a reference vegetation index value from which to calculate a sufficiency index. This automated approach to calibration of the in-season N application algorithm was tested on field strips containing randomized N rate plots. Nitrogen application rates determined by this real-time calibration approach were compared with rates based on an approach that involved scanning the strip prior to making the N applications (i.e., establish a high N crop reference value). The real-time calibrated N rates quickly locked-in on nearly the same rates as those based on pre-scanned crop data. Risk of under-application with the real-time calibration approach would be minimized by starting in a part of the field with relatively high crop vigor. The real-time approach to calibration of in-season N application algorithms provides good accuracy considerable convenience by eliminating the hassles associated with high N reference strips.