Thursday, January 11, 2007 - 2:15 PM

Remotely Estimating Cotton Defoliation with Reflectance Data

Glen Ritchie, University of Georgia, 2356 Rainwater Rd., Tifton, GA 31793 and Craig W. Bednarz, Texas Tech University, Department of Plant and Soil Sciences, Box 42122, Lubbock, TX 79409-2122.

Cotton harvest readiness based on percent defoliation is usually judged by visual estimates, but these estimates are subjective and may differ from one reviewer to the next. A spectrometric method for quantifying cotton defoliation is proposed. Leaf area index (LAI) was monitored in multiple environments on 0.91 m sections of row to quantify percentage defoliation and compared with narrow-band spectrometer measurements of reflectance of each plot. Normalized difference vegetation index (NDVI) models composed of reflectance at all wavelengths were regressed against LAI to determine which wavelengths most accurately estimated changes in LAI. Linear and quadratic models were tested for their usefulness in estimating LAI. The results suggest that reflectance indices based on red edge measurements can offer accurate, consistent defoliation estimates, and could potentially increase defoliation efficiency and decrease costs.

Poster (.ppt format, 9502.0 kb)
Recorded presentation