Submitted to: Journal of Cotton Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 2, 2006
Publication Date: June 2, 2006
Citation: Yang, C., Greenberg, S.M., Everitt, J.H., Norman, J.W. 2006. Assessing cotton stalk destruction with herbicides using remote sensing technology. Journal of Cotton Science. 10(2):136-145.
Interpretive Summary: Cotton stalk destruction following harvest is an important cultural practice for managing overwintering boll weevils. Despite recently implemented boll weevil eradication programs, stalk destruction remains an important measure to suppress boll weevils and other insects. This study evaluated remote sensing techniques, including ground reflectance spectra and airborne multispectral imagery, for assessing the effectiveness of different herbicide treatments on shredded cotton for regrowth control. Ground reflectance data and airborne imagery detected the differences in efficacy among the herbicide treatments as identified by traditional ground visual ratings. The results from this study indicate that remote sensing can be a useful tool for assessing the effectiveness of different herbicide treatments for stalk destruction.
Regrowth control with herbicides on standing or shredded cotton provides an alternative method for post-harvest destruction of cotton stalks. Field experiments were conducted in 2002 and 2003 in the Rio Grande Valley of south Texas to assess the effectiveness of different herbicide treatments for cotton regrowth control using remote sensing technology. Eight treatments (combinations of herbicides and application timings) and six treatments were evaluated on shredded cotton plots in 2002 and 2003, respectively, with each experiment arranged in a randomized complete block design. Airborne color-infrared (CIR) imagery was acquired from the test plots in both years shortly before the state-mandated date for cotton destruction. Ground reflectance spectra and visual ratings ranging from no live plants to mostly healthy plants were also obtained from each experimental plot. The reflectance spectra showed differences in regrowth among the treatments. The airborne CIR imagery only permitted limited visual differentiation among the treatments due to small amounts of regrowth. For quantitative analysis, the green, red, and near-infrared bands of the CIR imagery and four vegetation indices derived from the three bands were used as spectral variables to compare the differences among the treatments for each experiment. Statistical analysis showed that the spectral variables were able to identify the differences among the treatments as detected by the ground observations.