54-4 Variables Impacting Vegetation Indices Utilized For The Management Of Nitrogen Applications In Maize.
Poster Number 709
fertilizer applications for improving Nitrogen Use Efficiency (NUE).
A multi-year assessment of the efficacy of spectral remote sensing derived vegetation indices (VIs) to discern N stress in corn has been conducted in Maryland from 2004 to 2013. Satellite multispectral imagery, aerial hyperspectral imagery, and ground based passive and active sensor
reflectance data were collected in addition to biophysical parameters including plant height, leaf area index (LAI), leaf chlorophyll content, and development stage. Data excluding imagery were collected weekly from growth stages V6 to R1. Canopy reflectance simulation models were run and their output data analyzed to explore the impacts of individual canopy components on VIs, including leaf pigment levels, LAI, and soil type.
The effectiveness of VIs for discerning N stress in corn plants was found to vary widely at growth stages prior to canopy closure due to background components and variations in plant biomass confounding the detection of leaf chlorophyll levels. VIs utilizing bands in the green and red-edge regions of the spectrum outperformed those that omitted them for detecting N stress. As LAI increased and the plant canopy closed the capability of VIs responsive to plant pigments to discern N stress converged. Normalizing a VI appropriate for detecting leaf chlorophyll levels with a VI well correlated to plant biomass may improve the ability to extract information about leaf chlorophyll variation from canopy level remote sensing spectra collected at growth stages prior to canopy closure.