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Title:   Author  item
                                            Daughtry, Craigitem
                                            Russ, Andrew

                                                         - *Andy*item
                                            Hunt Jr, Earleitem
                                            Gish, Timothy
  Submitted to: American Society of Agronomy Meetings
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 9/15/2007
                                    Publication  Date: 11/5/2007
                                    Citation: Daughtry, C.S., Russ, A.L., Hunt, E.R., Gish, T.J. 2007. Spectral estimates of leaf chlorophyll concentrations in corn fields [abstract]. American Society of Agronomy Meetings. 2007 CDROM.Interpretive Summary:
                                Technical Abstract: Efficiently managing nitrogen (N) fertilizer applications is a major factor in site-specific corn production. Variations in soil reflectance and leaf area index (LAI) often confound assessments of leaf chlorophyll concentrations by remote sensing techniques. Our objective was to evaluate strategies for assessing leaf chlorophyll status of corn (Zea mays L.) plants grown at a range of N fertilization rates.  Corn canopy reflectance was measured with a ground-based spectro-radiometer over the 400-2400 nm wavelength region on several dates during the growing season.  Reflectance and transmittance of corn leaves were also acquired and canopy reflectance was simulated with a radiation transfer model (SAIL).  As predicted by the simulated canopy reflectance data and observed in the measured field data, the subtle differences due to changes in leaf chlorophyll concentration early in the season were overwhelmed by the large changes associated with soil reflectance and LAI. Spectral indices that combined near infrared reflectance and red reflectance (e.g., NDVI, NIR/Red) responded primarily to LAI, while indices that combined the reflectance of near infrared and other visible bands (MCARI and NIR/Green) responded to both leaf chlorophyll concentrations and soil reflectance. Adjustments for local conditions (soil reflectance) improved estimates of leaf chlorophyll concentrations.  A test of the strategy using aerial hyperspectral imagery and ground sampling showed consistent patterns of leaf chlorophyll concentrations even when LAI varied significantly. This approach holds promise as a management decision aid because leaf chlorophyll concentrations were determined with minimal confounding due to variations in soil reflectance and LAI.


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