scholarly journals Hyperspectral Reflectance Characteristics of Cyanobacteria

2021 ◽  
Vol 10 (03) ◽  
pp. 66-77
Author(s):  
Terrence Slonecker ◽  
Brittany Bufford ◽  
Jennifer Graham ◽  
Kurt Carpenter ◽  
Dan Opstal ◽  
...  
Keyword(s):  
Hyperspectral Reflectance

A Tentative Study on Utilization of Canopy Hyperspectral Reflectance to Estimate Canopy Growth and Seed Yield in Soybean

2013 ◽  
Vol 39 (2) ◽  
pp. 309 ◽  
Author(s):  
Qiong WU ◽  
Bo QI ◽  
Tuan-Jie ZHAO ◽  
Xin-Feng YAO ◽  
Yan ZHU ◽  
...  
Keyword(s):  
Seed Yield ◽  
Hyperspectral Reflectance

Identification and classification of Asian soybean rust using leaf-based hyperspectral reflectance

2021 ◽  
Vol 42 (11) ◽  
pp. 4177-4198
Author(s):  
Renato Herrig Furlanetto ◽  
Marcos Rafael Nanni ◽  
Monica Sayuri Mizuno ◽  
Luís Guilherme Teixeira Crusiol ◽  
Camila Rocco da Silva
Keyword(s):  
Soybean Rust ◽  
Hyperspectral Reflectance ◽  
Asian Soybean Rust

scholarly journals Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: progress and challenges

2021 ◽  
pp. 100209
Author(s):  
Marcin Grzybowski ◽  
Nuwan K. Wijewardane ◽  
Abbas Atefi ◽  
Yufeng Ge ◽  
James C. Schnable
Keyword(s):  
Quantitative Genetics ◽  
Hyperspectral Reflectance

scholarly journals Effect of leaf temperature on the estimation of photosynthetic and other traits of wheat leaves from hyperspectral reflectance

2020 ◽  
Author(s):  
Hammad A Khan ◽  
Yukiko Nakamura ◽  
Robert T Furbank ◽  
John R Evans
Keyword(s):  
Leaf Traits ◽  
Leaf Temperature ◽  
Physiological Traits ◽  
Leaf Mass Per Area ◽  
Hyperspectral Reflectance ◽  
Wheat Varieties ◽  
Unit Leaf ◽  
Temperature Signal ◽  
Wheat Leaves ◽  
Nitrogen Contents

Abstract A growing number of leaf traits can be estimated from hyperspectral reflectance data. These include structural and compositional traits, such as leaf mass per area (LMA) and nitrogen and chlorophyll content, but also physiological traits such a Rubisco carboxylation activity, electron transport rate, and respiration rate. Since physiological traits vary with leaf temperature, how does this impact on predictions made from reflectance measurements? We investigated this with two wheat varieties, by repeatedly measuring each leaf through a sequence of temperatures imposed by varying the air temperature in a growth room. Leaf temperatures ranging from 20 °C to 35 °C did not alter the estimated Rubisco capacity normalized to 25 °C (Vcmax25), or chlorophyll or nitrogen contents per unit leaf area. Models estimating LMA and Vcmax25/N were both slightly influenced by leaf temperature: estimated LMA increased by 0.27% °C–1 and Vcmax25/N increased by 0.46% °C–1. A model estimating Rubisco activity closely followed variation associated with leaf temperature. Reflectance spectra change with leaf temperature and therefore contain a temperature signal.

Detection of pitted morningglory (Ipomoea lacunosa) by hyperspectral remote sensing. I. Effects of tillage and cover crop residue

Weed Science ◽  
2004 ◽  
Vol 52 (2) ◽  
pp. 222-229 ◽  
Author(s):  
Clifford H. Koger ◽  
David R. Shaw ◽  
Krishna N. Reddy ◽  
Lori M. Bruce
Keyword(s):  
Cover Crop ◽  
Crop Residue ◽  
Field Experiments ◽  
Leaf Growth ◽  
Plant Size ◽  
Hyperspectral Reflectance ◽  
Discrimination Accuracy ◽  
Reflectance Measurement ◽  
Pitted Morningglory ◽  
Residue Systems

Field experiments were conducted to evaluate the potential of hyperspectral reflectance data collected with a hand-held spectroradiometer to discriminate soybean intermixed with pitted morningglory and weed-free soybean in conventional till and no-till plots containing rye, hairy vetch, or no cover crop residue. Pitted morningglory was in the cotyledon to six-leaf growth stage. Seven 50-nm spectral bands (one ultraviolet, two visible, four near-infrared) derived from each hyperspectral reflectance measurement were used as discrimination variables. Pitted morningglory plant size had more influence on discriminant capabilities than tillage or cover crop residue systems. Across all tillage and residue systems, discrimination accuracy was 71 to 95%, depending on the size of pitted morningglory plants at the time of data acquisition. The versatility of the seven 50-nm bands was tested by using a discriminant model developed for one experiment location to test discriminant capabilities for the other experiment, with discrimination accuracy across all tillage and residue systems of 55 to 73%, depending on pitted morningglory plant size.

Analysis of hyperspectral reflectance data for monitoring growth and development of lesquerella

2011 ◽  
Vol 33 (2) ◽  
pp. 524-531 ◽  
Author(s):  
K.R. Thorp ◽  
D.A. Dierig ◽  
A.N. French ◽  
D.J. Hunsaker
Keyword(s):  
Growth And Development ◽  
Hyperspectral Reflectance ◽  
Reflectance Data
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