Effects of development stage and nitrogen status on corn (Zea mays l.) spectral reflectance, and prediction of nitrogen requirement from multispectral imagery acquired by unmanned aerial vehicle
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Abstract
The yield response to nitrogen, also called delta yield, is a key feature of many precision agriculture strategies to reduce the environmental and economic costs of nitrogen (N) fertilization of corn crops. Unmanned aerial vehicles (UAVs) are an emerging crop monitoring tool able to rapidly measure spectral reflectance of crop canopies. Vegetation index (VI) maps derived from UAVs may improve N rate determination through estimation of spatial and temporal variation in corn leaf-N concentration. A fixed-wing UAV carrying multispectral sensors captured images from the V4 to V14 development stages for six pre-plant N treatments, and the resulting data were compared against ground-based spectral and leaf tissue data. After normalizing against a non-limiting N treatment, the Normalized Difference Rededge Index (NDRE) at the V10 timing was the strongest predictor of delta yield but it could not predict the most economic rate of nitrogen (MERN) within a $25 ha-1 margin.