Spectral discrimination using infinite leaf reflectance and simulated canopy reflectance

2021 ◽  
Vol 42 (8) ◽  
pp. 3039-3055
Author(s):  
E. Raymond Hunt
Keyword(s):  
Canopy Reflectance ◽  
Leaf Reflectance ◽  
Spectral Discrimination

scholarly journals Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch

2019 ◽  
Vol 11 (24) ◽  
pp. 2884 ◽  
Author(s):  
Maya Deepak ◽  
Sarita Keski-Saari ◽  
Laure Fauch ◽  
Lars Granlund ◽  
Elina Oksanen ◽  
...  
Keyword(s):  
Principal Component ◽  
Common Garden ◽  
Dry Weight ◽  
Leaf Traits ◽  
Tree Canopy ◽  
Canopy Reflectance ◽  
Canopy Layer ◽  
Leaf Reflectance ◽  
Individual Trees ◽  
Reflectance Indices

The availability of light within the tree canopy affects various leaf traits and leaf reflectance. We determined the leaf reflectance variation from 400 nm to 2500 nm among three canopy layers and cardinal directions of three genetically identical cloned silver birches growing at the same common garden site. The variation in the canopy layer was evident in the principal component analysis (PCA), and the influential wavelengths responsible for variation were identified using the variable importance in projection (VIP) based on partial least squares discriminant analysis (PLS-DA). Leaf traits, such as chlorophyll, nitrogen, dry weight, and specific leaf area (SLA), also showed significant variation among the canopy layers. We found a shift in the red edge inflection point (REIP) for the canopy layers. The canopy layers contribute to the variability in the reflectance indices. We conclude that the largest variation was among the canopy layers, whereas the differences among individual trees to the leaf reflectance were relatively small. This implies that within-tree variation due to the canopy layer should be taken into account in the estimation of intraspecific variation in the canopy reflectance.

scholarly journals High-resolution spectral information enables phenotyping of leaf epicuticular wax in wheat

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Fátima Camarillo-Castillo ◽  
Trevis D. Huggins ◽  
Suchismita Mondal ◽  
Matthew P. Reynolds ◽  
Michael Tilley ◽  
...  
Keyword(s):  
Abiotic Factors ◽  
Indirect Selection ◽  
Wheat Breeding ◽  
Epicuticular Wax ◽  
Canopy Reflectance ◽  
Cuticular Waxes ◽  
Leaf Reflectance ◽  
Single Leaf ◽  
Selection For ◽  
Experimental Trials

Abstract Background Epicuticular wax (EW) is the first line of defense in plants for protection against biotic and abiotic factors in the environment. In wheat, EW is associated with resilience to heat and drought stress, however, the current limitations on phenotyping EW restrict the integration of this secondary trait into wheat breeding pipelines. In this study we evaluated the use of light reflectance as a proxy for EW load and developed an efficient indirect method for the selection of genotypes with high EW density. Results Cuticular waxes affect the light that is reflected, absorbed and transmitted by plants. The narrow spectral regions statistically associated with EW overlap with bands linked to photosynthetic radiation (500 nm), carotenoid absorbance (400 nm) and water content (~ 900 nm) in plants. The narrow spectral indices developed predicted 65% (EWI-13) and 44% (EWI-1) of the variation in this trait utilizing single-leaf reflectance. However, the normalized difference indices EWI-4 and EWI-9 improved the phenotyping efficiency with canopy reflectance across all field experimental trials. Indirect selection for EW with EWI-4 and EWI-9 led to a selection efficiency of 70% compared to phenotyping with the chemical method. The regression model EWM-7 integrated eight narrow wavelengths and accurately predicted 71% of the variation in the EW load (mg·dm−2) with leaf reflectance, but under field conditions, a single-wavelength model consistently estimated EW with an average RMSE of 1.24 mg·dm−2 utilizing ground and aerial canopy reflectance. Conclusions Overall, the indices EWI-1, EWI-13 and the model EWM-7 are reliable tools for indirect selection for EW based on leaf reflectance, and the indices EWI-4, EWI-9 and the model EWM-1 are reliable for selection based on canopy reflectance. However, further research is needed to define how the background effects and geometry of the canopy impact the accuracy of these phenotyping methods.

scholarly journals High-resolution Spectral Information Enables Phenotyping of Leaf Epicuticular Wax in Wheat

2020 ◽  
Author(s):  
Fatima Camarillo-Castillo ◽  
Trevis D. Huggins ◽  
Suchismita Mondal ◽  
Matthew P. Reynolds ◽  
Michael Tilley ◽  
...  
Keyword(s):  
Abiotic Factors ◽  
Indirect Selection ◽  
Wheat Breeding ◽  
Epicuticular Wax ◽  
Canopy Reflectance ◽  
Cuticular Waxes ◽  
Leaf Reflectance ◽  
Single Leaf ◽  
Selection For ◽  
Experimental Trials

Abstract Background: Epicuticular wax (EW) is the first line of defense in plants for protection against biotic and abiotic factors in the environment. In wheat, EW is associated with resilience to heat and drought stress, however, the current limitations on phenotyping EW restrict the integration of this secondary trait into wheat breeding pipelines. In this study we evaluated the use of light reflectance as a proxy for EW load and developed an efficient indirect method for the selection of genotypes with high EW density. Results: Cuticular waxes affect the light that is reflected, absorbed and transmitted by plants. The narrow spectral regions statistically associated with EW overlap with bands linked to photosynthetic radiation (500 nm), carotenoid absorbance (400 nm) and water content (~900 nm) in plants. The narrow spectral indices developed predicted 65% (EWI-13) and 44% (EWI-1) of the variation in this trait utilizing single-leaf reflectance. However, the normalized difference indices EWI-4 and EWI-9 improved the phenotyping efficiency with canopy reflectance across all field experimental trials. Indirect selection for EW with EWI-4 and EWI-9 led to a selection efficiency of 70% compared to phenotyping with the chemical method. The regression model EWM-7 integrated eight narrow wavelengths and accurately predicted 71% of the variation in the EW load (mg·dm-2) with leaf reflectance, but under field conditions, a single-wavelength model consistently estimated EW with an average RMSE of 1.24 mg·dm-2 utilizing ground and aerial canopy reflectance.Conclusions: Overall, the indices EWI-1, EWI-13 and the model EWM-7 are reliable tools for indirect selection for EW based on leaf reflectance, and the indices EWI-4, EWI-9 and the model EWM-1 are reliable for selection based on canopy reflectance. However, further research is needed to define how the background effects and geometry of the canopy impact the accuracy of these phenotyping methods.

scholarly journals Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

2021 ◽  
Author(s):  
Hibiki M. Noda ◽  
Hiroyuki Muraoka ◽  
Kenlo Nishida Nasahara
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Spectral Reflectance ◽  
Canopy Structure ◽  
Terrestrial Ecosystems ◽  
Optical Remote Sensing ◽  
Canopy Reflectance ◽  
Broadleaf Forest ◽  
Leaf Optical Properties ◽  
Deciduous Broadleaf Forest

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

scholarly journals The Deviation between Dairy Cow Metabolizable Energy Requirements and Pasture Supply on a Dairy Farm Using Proximal Hyperspectral Sensing

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 240
Author(s):  
Federico Duranovich ◽  
Nicolás López-Villalobos ◽  
Nicola Shadbolt ◽  
Ina Draganova ◽  
Ian Yule ◽  
...  
Keyword(s):  
Milk Fat ◽  
Supply And Demand ◽  
Dairy Farm ◽  
Energy System ◽  
Metabolizable Energy ◽  
Feeding Strategies ◽  
Canopy Reflectance ◽  
Estimate Variance ◽  
Hyperspectral Sensing ◽  
Daily Total

This study aimed at determining the extent to which the deviation of daily total metabolizable energy (MEt) requirements of individual cows from the metabolizable energy (ME) supplied per cow (DME) varied throughout the production season in a pasture-based dairy farm using proximal hyperspectral sensing (PHS). Herd tests, milk production, herbage and feed allocation data were collected during the 2016–2017 and 2017–2018 production seasons at Dairy 1, Massey University, New Zealand. Herbage ME was determined from canopy reflectance acquired using PHS. Orthogonal polynomials were used to model lactation curves for yields of milk, fat, protein and live weights of cows. Daily dietary ME supplied per cow to the herd and ME requirements of cows were calculated using the Agricultural Food and Research Council (AFRC) energy system of 1993. A linear model including the random effects of breed and cow was used to estimate variance components for DME. Daily herd MEt estimated requirements oscillated between a fifth above or below the ME supplied throughout the production seasons. DME was mostly explained by observations made within a cow rather than between cows or breeds. Having daily estimates of individual cow requirements for MEt in addition to ME dietary supply can potentially contribute to achieving a more precise fit between supply and demand for feed in a pasture-based dairy farm by devising feeding strategies aimed at reducing DME.

scholarly journals Canopy reflectance models illustrate varying NDVI responses to change in high latitude ecosystems

2021 ◽  
Author(s):  
Karl Fred Huemmrich ◽  
Sergio Vargas Zesati ◽  
Petya Campbell ◽  
Craig Tweedie
Keyword(s):  
High Latitude ◽  
Canopy Reflectance

scholarly journals Root-associated entomopathogenic fungi manipulate host plants to attract herbivorous insects

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Belén Cotes ◽  
Gunda Thöming ◽  
Carol V. Amaya-Gómez ◽  
Ondřej Novák ◽  
Christian Nansen
Keyword(s):  
Host Plant ◽  
Entomopathogenic Fungi ◽  
Host Plants ◽  
Near Infrared ◽  
Delia Radicum ◽  
Host Plant Selection ◽  
Herbivorous Insects ◽  
Herbivorous Insect ◽  
Insect Performance ◽  
Leaf Reflectance

AbstractRoot-associated entomopathogenic fungi (R-AEF) indirectly influence herbivorous insect performance. However, host plant-R-AEF interactions and R-AEF as biological control agents have been studied independently and without much attention to the potential synergy between these functional traits. In this study, we evaluated behavioral responses of cabbage root flies [Delia radicum L. (Diptera: Anthomyiidae)] to a host plant (white cabbage cabbage Brassica oleracea var. capitata f. alba cv. Castello L.) with and without the R-AEF Metarhizium brunneum (Petch). We performed experiments on leaf reflectance, phytohormonal composition and host plant location behavior (behavioral processes that contribute to locating and selecting an adequate host plant in the environment). Compared to control host plants, R-AEF inoculation caused, on one hand, a decrease in reflectance of host plant leaves in the near-infrared portion of the radiometric spectrum and, on the other, an increase in the production of jasmonic, (+)-7-iso-jasmonoyl-l-isoleucine and salicylic acid in certain parts of the host plant. Under both greenhouse and field settings, landing and oviposition by cabbage root fly females were positively affected by R-AEF inoculation of host plants. The fungal-induced change in leaf reflectance may have altered visual cues used by the cabbage root flies in their host plant selection. This is the first study providing evidence for the hypothesis that R-AEF manipulate the suitability of their host plant to attract herbivorous insects.

scholarly journals Analysis of Common Canopy Reflectance Spectra for Indicating Leaf Nitrogen Concentrations in Wheat and Rice

2007 ◽  
Vol 10 (4) ◽  
pp. 400-411 ◽  
Author(s):  
Yan Zhu ◽  
Yongchao Tian ◽  
Xia Yao ◽  
Xiaojun Liu ◽  
Weixing Cao
Keyword(s):  
Leaf Nitrogen ◽  
Reflectance Spectra ◽  
Canopy Reflectance ◽  
Nitrogen Concentrations

LAI Retrieval Based on PROSPECT-SAILH Model from Multi-Angular Data of WiDAS Imaging System

2012 ◽  
Vol 518-523 ◽  
pp. 5697-5703
Author(s):  
Zhao Yan Liu ◽  
Ling Ling Ma ◽  
Ling Li Tang ◽  
Yong Gang Qian
Keyword(s):  
Remote Sensing ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Canopy Reflectance ◽  
Area Index ◽  
Sensing Data ◽  
Spectral Bands ◽  
Sensing Technology ◽  
Leaf Optical Properties ◽  
Angular Data

The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.

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