Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: February 15, 2002
Publication Date: N/A
Interpretive Summary: Traditional methods for evaluating defoliation strategies are based on visual observations and ground measurements. This paper presents a remote sensing-based method for evaluating the effectiveness of different defoliation treatments. Results from two cotton fields indicated that airborne imagery permitted both visual and quantitative differentiation among treatments as early as 3 days after the chemical application; although, the images collected 6 days after the application revealed the most significant differences among the treatments. The remote sensing-based approach is more effective and efficient than traditional approaches if a large number of treatments are to be evaluated over large fields.
Visual observations and ground measurements are commonly used to evaluate cotton harvest aids for defoliation, boll opening, and regrowth control. This paper presents a remote sensing-based method for evaluating the effectiveness of different defoliation treatments. Field experiments were conducted on two cotton fields in south Texas in 2001. Eight treatments (one control and seven combinations of defoliants and insecticides) with three replications were assigned across 24 experimental plots in a randomized complete block design in each of the two fields. Airborne color-infrared (CIR) digital images were obtained from the first field 6 days after chemical application and from the second field on the day of application and 3 more times afterwards. Ground reflectance spectra and plant physical data, such as number of leaves, were collected on selected sites within each plot. The reflectance spectra effectively separated different levels of defoliation, but a large number of spectra were required to obtain reliable results. The airborne images permitted visual differentiation among the treatments as early as 3 days after the chemical application; although, the images collected 6 days after the application revealed the most significant differences among the treatments. For quantitative analysis, the green, red, and near-infrared (NIR) bands of the CIR images and the normalized difference vegetation index (NDVI) derived from the NIR and red bands were used as spectral variables to compare the differences among the treatments. Multiple comparisons showed that spectral variables differed significantly among some of the defoliation treatments. These results indicate that remote sensing can be a useful tool for evaluating the effectiveness of cotton defoliation strategies.