Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance

Farmers must balance the competing goals of supplying contributions of background reflectance, while spectral veg-etation indices that combined reflectances of near-infraredadequate N for their crops while minimizing N losses to the environment. To characterize the spatial variability of N and other visible bands (MCARI and NIR/Green) were re-sponsive to both leaf chlorophyll concentrations and back-over large fields, traditional methods (soil testing, plant tissue analysis, and chlorophyll meters) require many point ground reflectance. Pairs of these spectral vegetation indi-ces plotted together produced isolines of leaf chlorophyllsamples. Because of the close link between leaf chlorophyll and leaf N concentration, remote sensing techniques have concentrations. The slopes of these isolines were linearly related to leaf chlorophyll concentration. A limited testthe potential to evaluate the N variability over large fields quickly. Our objectives were to (1) select wavelengths sensi- with measured canopy reflectance and leaf chlorophyll data confirmed these results. The characterization of leaf chloro-tive to leaf chlorophyll concentration, (2) simulate canopy reflectance using a radiative transfer model, and (3) propose phyll concentrations at the field scale without the confound-ing problem of background reflectance and LAI variabilitya strategy for detecting leaf chlorophyll status of plants using remotely sensed data. A wide range of leaf chlorophyll levels holds promise as a valuable aid for decision making in managing N applications. Published by Elsevier Sciencewas established in field-grown corn (Zea mays L.) with the application of 8 N levels: 0%, 12.5%, 25%, 50%, 75%, Inc