Estimating Nitrogen Sufficiency Index using a Natural Local Reference approach

Information-based crop management, such as variable rate technology, allows for changing rates of fertilization according to local needs. Fertilizer prescription maps can be derived from crop growth status assessed through proximal canopy sensing technologies. Typically, a vegetation index, such as the NDVI, is used to estimate a Nitrogen Sufficiency Index (NSI=NDVI/NDVI_N-rich). NSI is related to N intake in comparison to the measurements in N-rich reference areas created artificially with high N rates applied at planting. This approach requires N-rich areas representative of different field conditions, which is not always practical. To circumvent this limitation `naturally N-rich´ reference areas linked to natural field characteristics can be identified. The goal of this present work was to show that the NSI_NLR estimated using less laborious Natural Local References (NLR) has a benefit comparable to the more traditional NSI_N-rich from N-rich plots. Experiments were performed on corn fields located in the Montérégie area of Quebec. The NDVI values were measured using 5 tractor-mounted GreenSeeker sensors. The spatial variability of the soil was analyzed using maps of apparent electrical conductivity (EC_a) obtained using a Veris 3100 system. The NSI_NLR, set at the 90^th percentile of the NDVI values obtained around each sensed area, was compared to NSI_N-rich. The NSI values estimated using both techniques were strongly correlated and demonstrated a high capacity to estimate the optimal N rate for corn.