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Phenology affects differentiation of crop and weed species using hyperspectral remote sensing

Published online by Cambridge University Press:  18 August 2020

Nicholas T. Basinger Open the ORCID record for Nicholas T. Basinger [Opens in a new window] ,
Katherine M. Jennings Open the ORCID record for Katherine M. Jennings [Opens in a new window] ,
Erin L. Hestir Open the ORCID record for Erin L. Hestir [Opens in a new window] ,
David W. Monks ,
David L. Jordan  and
Wesley J. Everman Open the ORCID record for Wesley J. Everman [Opens in a new window]
Nicholas T. Basinger*
Affiliation:
Graduate Research Assistant, North Carolina State University, Department of Horticultural Science, Raleigh, NC, USA
Katherine M. Jennings
Affiliation:
Associate Professor, North Carolina State University, Department of Horticulture Science, Raleigh, NC, USA
Erin L. Hestir
Affiliation:
Assistant Professor, University of California, Department of Civil and Environmental Engineering, Merced, CA, USA
David W. Monks
Affiliation:
Professor, North Carolina State University, Department of Horticultural Science, Raleigh, NC, USA
David L. Jordan
Affiliation:
Professor, North Carolina State University, Department of Crop and Soil Science, Raleigh, NC, USA
Wesley J. Everman
Affiliation:
Associate Professor, North Carolina State University, Department of Crop and Soil Science, Raleigh, NC, USA
*
Author for correspondence: Nicholas T. Basinger, Department of Crop and Soil Sciences, University of Georgia, 3111 Miller Plant Sciences, 120 Carlton St., Athens, GA30602. (Email: nicholas.basinger@uga.edu)
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Abstract

The effect of plant phenology and canopy structure of four crops and four weed species on reflectance spectra were evaluated in 2016 and 2017 using in situ spectroscopy. Leaf-level and canopy-level reflectance were collected at multiple phenologic time points in each growing season. Reflectance values at 2 wk after planting (WAP) in both years indicated strong spectral differences between species across the visible (VIS; 350–700 nm), near-infrared (NIR; 701–1,300 nm), shortwave-infrared I (SWIR1; 1,301–1,900 nm), and shortwave-infrared II (SWIR2; 1,901–2,500 nm) regions. Results from this study indicate that plant spectral reflectance changes with plant phenology and is influenced by plant biophysical characteristics. Canopy-level differences were detected in both years across all dates except for 1 WAP in 2017. Species with similar canopy types (e.g., broadleaf prostrate, broadleaf erect, or grass/sedge) were more readily discriminated from species with different canopy types. Asynchronous phenology between species also resulted in spectral differences between species. SWIR1 and SWIR2 wavelengths are often not included in multispectral sensors but should be considered for species differentiation. Results from this research indicate that wavelengths in SWIR1 and SWIR2 in conjunction with VIS and NIR reflectance can provide differentiation across plant phenologies and, therefore should be considered for use in future sensor technologies for species differentiation.

Keywords

Hyperspectral remote sensingplant morphologyspecies differentiationspectral discriminationspectral variabilityspectroscopy
Type
Research Article
Information
Weed Technology , Volume 34 , Issue 6 , December 2020 , pp. 897 - 908
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of Weed Science Society of America

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Footnotes

Associate Editor: Prashant Jha, Iowa State University

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