Comparing Canopy Hyperspectral Reflectance Properties of Palmer amaranth to Okra and Super-Okra Leaf Cotton

Cotton (Gossypium spp.) is an important crop grown throughout the world. It is an important source of fiber and is one of the few crops with unique leaf shapes: 1) normal, 2) sub-okra, 3) okra, and 4) super-okra. Leaf shape plays a major role in cotton survival.

Palmer amaranth (Amaranthus palmeri S. Wats.) is a major weed affecting cotton production systems in the southern U.S. In ideal environmental conditions, it grows faster and outcompetes cotton plants for available resources, and it has been linked to a reduction in cotton yield.

Hyperspectral remote sensing has shown promise as a tool for crop weed discrimination, and there is a growing interest in using this technology for identifying weeds in cotton production systems. Currently, there is no research available comparing the canopy hyperspectral profiles of okra and super-okra leaf cotton to the canopy hyperspectral profile of Palmer amaranth. Also, no information is available on which regions of the spectrum are optimal for okra and super-okra leaf canopies separation from Palmer amaranth.

In this paper, two greenhouse studies were conducted to compare canopy hyperspectral reflectance profiles of Palmer amaranth to canopy hyperspectral reflectance profiles of okra and super-okra leaf cotton and to identify optimal regions of the electromagnetic spectrum for their discrimination. Ground-based hyperspectral measurements of the plant canopies were obtained with a spectroradiometer (400 - 2350 nm range). Analysis of variance (ANOVA, p ≤ 0.05), Dunnett’s test (p≤ 0.05), and difference and sensitivity measurements were tabulated to determine the optimal wavebands for Palmer amaranth and cotton discrimination. 

Results were inconsistent for Palmer amaranth and okra leaf cotton separation. Optimal wavebands for distinguishing Palmer amaranth from super-okra leaf cotton were observed in the shortwave infrared region (2000 nm and 2180 nm) of the optical spectrum. Ground-based and airborne sensors can be tuned into the shortwave infrared bands identified in this study, facilitating application of remote sensing technology for Palmer amaranth discrimination from super-okra leaf cotton and implementation of the technology as a decision support tool in cotton weed management programs. The future research initiatives will focus on testing vegetation indices and derivative spectra as tools for discriminating Palmer amaranth and okra leaf cotton.

Article by Reginald S. Fletcher and Rickie B. Turley, from Agricultural Research Service, United States Department of Agriculture, Stoneville, USA.

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