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Evaluating Multiple Indices from a Canopy Reflectance Sensor to Estimate Corn N Requirements
Author(s) -
Sripada Ravi P.,
Schmidt John P.,
Dellinger Adam E.,
Beegle Douglas B.
Publication year - 2008
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2008.0017
Subject(s) - mathematics , radiance , canopy , yield (engineering) , randomized block design , sowing , reflectivity , zea mays , calibration , agronomy , vegetation (pathology) , grain yield , statistics , geography , remote sensing , physics , optics , pathology , biology , thermodynamics , archaeology , medicine
With the increasing cost of fertilizer N, there is a renewed emphasis on developing new technologies for quantifying in‐season N requirements for corn ( Zea mays L.). The objectives of this research are (i) to evaluate different vegetative indices derived from an active reflectance sensor in estimating in‐season N requirements for corn, and (ii) to consider the influence of the N:Corn price ratio on the economic optimum nitrogen rate (EONR) developed using these indices. Field experiments were conducted at eight site‐years in central Pennsylvania. A two‐way factorial experiment was implemented as a split‐plot randomized complete block (four blocks) design, with different rates of N applied (i) at planting (N PL ) to create a range of N supply, corn color, and radiance; and (ii) at V6 (N V6 ) to measure yield response to N V6 . Canopy reflectance measurements were obtained using a Crop Circle (Holland Scientific, Lincoln, NE) sensor just before N V6 applications, and grain yield was determined at harvest. The EONR was determined using a quadratic‐plateau yield response function for price ratios from zero to 14:1, then regressed on 21 combinations of absolute and relative spectral bands and indices. The EONR at V6 at 6:1 price ratio ranged from 0 to 221 kg ha −1 among the eight site‐years, with a mean of 69 kg ha −1 Better prediction of EONR was obtained by indices calculated relative to a high N plot rather than absolute indices. Relative Green Difference Normalized Vegetation Index by ratio (RGNDVI R ) was the best predictor of EONR at V6 when expressed as a linear‐floor model ( R 2 of 0.79). A relationship was developed so that EONR estimates derived using the Crop Circle sensor could be easily adjusted based on the current N:Corn price ratio. When N requirements are high (RGNDVI R = 0.8) and if the price ratio changes from 4:1 to 10:1, the EONR would change from 267 to 214 kg ha −1 N.

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