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Cotton Canopy Reflectance at Landscape Scale as Affected by Nitrogen Fertilization
Author(s) -
Bronson Kevin F.,
Booker J. D.,
Keeling J. Wayne,
Boman Randy K.,
Wheeler Terry A.,
Lascano Robert J.,
Nichols Robert L.
Publication year - 2005
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/agronj2004.0093
Subject(s) - lint , canopy , reflectivity , fiber crop , malvaceae , human fertilization , growing season , nitrogen , partial least squares regression , linear regression , agronomy , fertilizer , zoology , horticulture , mathematics , biology , botany , chemistry , physics , optics , organic chemistry , statistics
Multispectral reflectance of crop canopies has potential as an in‐season indicator of N status in cotton ( Gossypium hirsutum L.). The objectives of this study were to correlate leaf N with reflectance at 16 wavebands from 450 to 1700 nm and to assess the effect of N fertilization on vegetative ratio indices using two bands of reflectance. We also compared regressions of leaf N on ratio indices with partial least squares (PLS) regression using reflectance at 16 wavebands. Reflectance was measured at 50 cm above the canopy at 135 points in a 14‐ha field of irrigated cotton at early squaring in the Texas High Plains in 2002 and at an 80‐cm height in 2003 and 2004. Leaf N had weak, negative correlation with green reflectance in all 3 yr. Normalized difference vegetative indices (NDVIs) using red (670 nm) or green (550 nm) reflectance were significantly greater in N‐fertilized plots than zero‐N plots in 2 of 3 yr. However, the NDVIs related poorly or not at all with leaf N, biomass, and lint yield. Leaf N was estimated by PLS regression with three factors having R 2 of 0.64 in 2002 and 2004 when an N fertilizer response was observed. In 2003, there was no added N effect, and the R 2 for PLS regression of leaf N was 0.41. The poor correlation between NDVIs and leaf N was not expected, and these results suggest that use of NDVIs to determine need of in‐season N may be most successful using well‐fertilized areas and the sufficiency index approach.