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a Texas A&M Univ. Texas Agric. Exp. Stn., RR 3, Box 219, Lubbock, TX 79403
b Texas Coop. Ext., RR 3, Box 213AA, Lubbock, TX 79403
c Cotton Inc. World Headquarters, 6399 Weston Parkway, Cary, NC 27513
* Corresponding author (k-bronson{at}tamu.edu)
Received for publication April 1, 2004. 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 R2 of 0.64 in 2002 and 2004 when an N fertilizer response was observed. In 2003, there was no added N effect, and the R2 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.
Abbreviations: DGPS, differential global positioning system NDVI, normalized difference vegetative index NDVI-G-P, normalized difference vegetative indexgreen-passive NDVI-R-A, normalized difference vegetative indexred-active NDVI-R-P, normalized difference vegetative indexred-passive NIR, near infrared PLS, partial least squares
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