ABSTRACT

A field experiment was conducted to examine the usefulness of remote sensing technology for evaluating cotton (Gossypium hirsutum L.) regrowth control strategies for post-harvest destruction of cotton stalks. Ten treatments (one control and nine combinations of three herbicide mixtures and three application timings) were assigned to 30 shredded cotton plots according to a randomized complete block design in a south Texas cotton field in 2002. Ground reflectance spectra were collected on randomly selected sites from each plot 32 days after the first three of the nine herbicide treatments were applied. Meanwhile, airborne multispectral digital imagery was obtained from the field and plant regrowth was visually rated at five levels ranging from no live plants to mostly healthy plants based on ground observations. The reflectance spectra were able to separate regrowth differences among some of the treatments, though a large number of spectra were needed to achieve reliable results. The airborne imagery did not provide sufficient visual differentiation among the treatments, but the reflectance information extracted from the imagery allowed quantitative separations among the treatments. Seven spectral variables, including the green, red, and near-infrared (NIR) bands of the multispectral imagery and four vegetation indices derived from the three bands, were used to compare the differences among the treatments. Multiple comparisons showed that the green band and the four vegetation indices detected significant differences among some of the treatments as detected by the visual efficacy rating. These results indicate that remote sensing can be a useful tool for evaluating cotton regrowth control strategies.