Abstract
AbstractConstant‐rate blanket applications of fertilizer N can result in both an over and under supply relative to crop utilization on a field‐by‐field basis. Variable‐rate (VR) applications tailored to better meet crop demand can improve N use efficiency on spatially variable soils. The objectives of this study were to compare the response in corn (Zea mays L.) canopy reflectance derived vegetation indices (VI) to varying fertilizer N rates and to determine relationships between resulting VIs acquired using two different sensing platforms. Four fertilizer N rates in 50/50 split at V1–2 and V6–7 leaf stages were applied, from deficient to excessive, to create varying corn nutritional N status. Sensing and biophysical sampling were performed throughout the season for analysis and comparison to calculated VIs. Grain yield plateaued around 135±10 kg N ha–1 across the study. Furthermore, strong relationships between VIs and fertilizer N rates were found, with the strongest using combined indices that incorporate the red‐edge wavelength (720 nm). Relationships strengthened at later growth stages. The response models were found to be sensor specific, VI specific, and mostly non‐transferable between sensors. Results from this study demonstrate the utility of using remote sensing technologies to predict corn N status more accurately for eventual use in VR prescription development.
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