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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #333528

Research Project: Application Technologies to Improve the Effectiveness of Chemical and Biological Crop Protection Materials

Location: Crop Production Systems Research

Title: Spectral discrimination of two pigweeds from cotton with different leaf colors

Author
item Fletcher, Reginald
item Reddy, Krishna
item Turley, Rickie - Rick

Submitted to: American Journal of Plant Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/25/2016
Publication Date: 10/28/2016
Citation: Fletcher, R.S., Reddy, K.N., Turley, R.B. 2016. Spectral discrimination of two pigweeds from cotton with different leaf colors. American Journal of Plant Sciences. 7:2138-2150.

Interpretive Summary: To implement strategies to control Palmer amaranth and redroot pigweed infestations in cotton production systems, managers need effective techniques to identify the weeds. Leaf light reflectance measurements have shown promise as a tool to distinguish crops from weeds. Studies have targeted plants with green leaves. Cotton lines exist that have bronze, green, or yellow leaves; these plants are currently being evaluated at experiment stations and eventually might be grown in fields. ARS scientists at Crop Production Systems Research Unit, Stoneville, MS, evaluated leaf light reflectance profiles of cotton lines with bronze, green, and yellow leaves, Palmer amaranth, and redroot pigweed. Three regions of the light spectrum were identified (600 to 700 nm, 710 nm, and 1460 nm) for differentiating the cotton lines from Palmer amaranth and redroot pigweed. Ground-based and airborne sensors can be tuned into the regions of spectrum identified, facilitating using remote sensing technology for Palmer amaranth and redroot pigweed identification in cotton production systems.

Technical Abstract: To implement strategies to control Palmer amaranth (Amaranthus palmeri S. Wats.) and redroot pigweed (Amaranthus retroflexus L.) infestations in cotton (Gossypium hirsutum L.) production systems, managers need effective techniques to identify the weeds. Leaf light reflectance measurements have shown promise as a tool to distinguish crops from weeds. Studies have targeted plants with green leaves. This study focused on using leaf hyperspectral reflectance data to develop spectral profiles of Palmer amaranth, redroot pigweed, and cotton and to determine regions of the light spectrum most sensitive for pigweed and cotton discrimination. The study focused on cotton near-isogenic lines created to have bronze, green, or yellow colored leaves. Reflectance measurements within the 400 to 2500 nm spectral range were obtained from cotton and weed plants grown in a greenhouse in 2015 and 2016. Two scenarios were evaluated for the comparison: (1) Palmer amaranth versus cotton lines and (2) redroot pigweed versus cotton lines. Statistical significance (p = 0.05) was determined with analysis of variance (ANOVA) and Dunnett’s test. Sensitivity measurements were tabulated to determine the optimal region of the light spectrum for weed and cotton line discrimination. Differences among group spectral curves were determined to be statistically significant (ANOVA p = 0.05) in the visible, red edge, near infrared, and shortwave infrared regions of the light spectrum in both years. Dunnett’s analysis also indicated statistically significant differences occurred between a specific weed and a specific cotton line in the visible, red edge, near infrared, and shortwave infrared regions of the light spectrum. Optimal bands for weed and cotton separation were 600 to 700 nm (both weeds versus cotton bronze and cotton yellow), 710 nm (Palmer amaranth versus cotton green), and 1460 nm (redroot pigweed versus cotton green). Spectral bands were identified for separating Palmer amaranth and redroot pigweed from cotton lines with bronze, green, and yellow leaves. Ground-based and airborne sensors can be tuned into the regions of spectrum identified, facilitating using remote sensing technology for Palmer amaranth and redroot pigweed identification in cotton production systems.