An active crop canopy reflectance sensor could increase N-use efficiency in corn (Zea mays L.), if temporal and spatial variability in soil N availability and plant demand are adequately accounted for with an in-season application. Our objective was to evaluate the success of using an active sensor for making N recommendations to corn. Seven increments of in-season N fertiliser (0 to 280 kg/ha) were applied to corn at each of 15 sites during two years. These sites were selected to represent the corn production regions of east central and southeastern Pennsylvania, conditions typical in the USA mid-Atlantic region. Canopy reflectance in the 590 nm and 880 nm wavelengths, soil samples, and above-ground biomass were collected at the 6th-7th-leaf growth stage (V6-V7). Relative Green Normalised Difference Vegetation Index (GNDVIrelative) was determined, as GNDVI(0N) / GNDVI(280 kg N/ha applied at planting). Grain yield was determined at harvest. Economic Optimum N Rate (EONR) was determined using a quadratic-plateau yield response function. Observations from the current study were compared to relationships between EONR and GNDVIrelative or the presidedress NO3 test (PSNT) that were developed in an earlier study, based on an absolute mean difference (AMD) between observed EONR and the previously determined predicted relationships. The AMD for the EONR and GNDVIrelative relationship from the current study was 62.9 kg N/ha. The same measure of AMD was 75.0 kg N/ha for the relationship between EONR and PSNT. GNDVIrelative captured similar information as the PSNT, as reflected in a strong relationship (R2=0.57) between these two measurements. Above-ground biomass at V6-V7 was correlated with PSNT (R2=0.38), and GNDVIrelative was dependent on above-ground biomass (R2=0.51). While the PSNT has been considered one of the best methods for making N recommendations to corn in Pennsylvania, GNDVI relative provided as good or better an indicator of EONR as PSNT, and provides an opportunity to easily adjust in-season N applications spatially.