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Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices
Daniel Wasonga
, Chunhwa Jang
, Jung Woo Lee
, Kayla Vittore
, Muhammad Umer Arshad
, Nictor Namoi
, Colleen Zumpf
,
DoKyoung Lee
Crop Sciences
National Center for Supercomputing Applications (NCSA)
Institute for Sustainability, Energy, and Environment
Research output
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peer-review
Overview
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Dive into the research topics of 'Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices'. Together they form a unique fingerprint.
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Agricultural and Biological Sciences
Lignocellulose
100%
Panicum virgatum
100%
Vegetation Index
100%
Unmanned Aerial Vehicle
100%
Normalized Difference Vegetation Index
75%
Red Edge
75%
Hemicellulose
50%
Feedstock
25%
Cultivar
25%
Growing Season
25%
Bioenergy
25%
Least Squares Method
25%
Sustainable Aviation Fuel
25%
Random Forest
25%
Earth and Planetary Sciences
Vegetation Index
100%
Unmanned Aerial Vehicle
100%
Normalized Difference Vegetation Index
75%
Multispectral Image
50%
Field Scale
25%
Growing Season
25%
Fuel Production
25%
Sustainable Aviation Fuel
25%
Bioenergy
25%
Cultivar
25%
Keyphrases
Biomass Cellulose
66%