Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn.

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four different sites in Waseca and Wabasha counties in Minnesota. At each of the four sites, experimental plots received different rates of nitrogen varying between 0 and 200 kg/ha and imagery was collected during corn growth stages V6, V10 and R6 at six cm spatial resolution. Ancillary data collected included SPAD readings, leaf N, biomass, and yield. Preliminary results show that, among the spectral bands and indices compared, combining the green and NIR bands into a green difference vegetation index (GDVI) had the highest correlation with nitrogen application rates, SPAD reading and yield. The GDVI index was used to compute a nitrogen sufficiency index (NSI). The correlation between nitrogen application rates and GDVI was higher (r=0.80) at early growth stages (V6) than later in the season. On the other hand, the correlation between yield and GDVI was highest at the end of the growing season (r = 0.75). Down scaling of six cm resolution imagery to 30 cm, 50 cm and 1m, allowed comparisons between index performance at different resolutions. There was no significant degradation in index value accuracy up to 30 cm resolution. High resolution remote sensing can accurately detect nitrogen deficiency early in the season, leading to timely correction. Our research also shows that accuracy is not degraded with 30 cm pixel resolution, thus allowing a greater areal footprint for images.