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

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DOI: 10.4236/ajps.2018.913197    641 Downloads   1,275 Views  Citations

ABSTRACT

Palmer amaranth (Amaranthus palmeri S. Wats.) is a major weed problem of cotton (Gossypium hirsutum L.) production systems in the southern United States. 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. Information is lacking on differentiating Palmer amaranth from cotton with an okra leaf structure based on canopy hyperspectral reflectance properties. 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.

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Fletcher, R. and Turley, R. (2018) Comparing Canopy Hyperspectral Reflectance Properties of Palmer amaranth to Okra and Super-Okra Leaf Cotton. American Journal of Plant Sciences, 9, 2708-2718. doi: 10.4236/ajps.2018.913197.
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