scholarly journals Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data

2021 ◽  
Vol 13 (13) ◽  
pp. 2545
Author(s):  
Subhajit Bandopadhyay ◽  
Anshu Rastogi ◽  
Sergio Cogliati ◽  
Uwe Rascher ◽  
Maciej Gąbka ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Plant Cover ◽  
Vegetation Indices ◽  
Imaging Spectroscopy ◽  
Controlling Factors ◽  
Photochemical Quenching ◽  
Spectral Vegetation Indices ◽  
Airborne Imaging ◽  
Non Photochemical Quenching ◽  
Modelling Approach

In this study, we are testing a proxy for red and far-red Sun-induced fluorescence (SIF) using an integrated fuzzy logic modelling approach, termed as SIFfuzzy and SIFfuzzy-APAR. The SIF emitted from the core of the photosynthesis and observed at the top-of-canopy is regulated by three major controlling factors: (1) light interception and absorption by canopy plant cover; (2) escape fraction of SIF photons (fesc); (3) light use efficiency and non-photochemical quenching (NPQ) processes. In our study, we proposed and validated a fuzzy logic modelling approach that uses different combinations of spectral vegetation indices (SVIs) reflecting such controlling factors to approximate the potential SIF signals at 760 nm and 687 nm. The HyPlant derived and field validated SVIs (i.e., SR, NDVI, EVI, NDVIre, PRI) have been processed through the membership transformation in the first stage, and in the next stage the membership transformed maps have been processed through the Fuzzy Gamma simulation to calculate the SIFfuzzy. To test whether the inclusion of absorbed photosynthetic active radiation (APAR) increases the accuracy of the model, the SIFfuzzy was multiplied by APAR (SIFfuzzy-APAR). The agreement between the modelled SIFfuzzy and actual SIF airborne retrievals expressed by R2 ranged from 0.38 to 0.69 for SIF760 and from 0.85 to 0.92 for SIF687. The inclusion of APAR improved the R2 value between SIFfuzzy-APAR and actual SIF. This study showed, for the first time, that a diverse set of SVIs considered as proxies of different vegetation traits, such as biochemical, structural, and functional, can be successfully combined to work as a first-order proxy of SIF. The previous studies mainly included the far-red SIF whereas, in this study, we have also focused on red SIF along with far-red SIF. The analysis carried out at 1 m spatial resolution permits to better infer SIF behaviour at an ecosystem-relevant scale.

Hyperspectral Aerial Imaging for Grassland Yield Estimation

2017 ◽  
Vol 8 (2) ◽  
pp. 770-775 ◽  
Author(s):  
J. Geipel ◽  
A. Korsaeth
Keyword(s):  
Vegetation Indices ◽  
Imaging Spectroscopy ◽  
Principal Component ◽  
Spectral Signature ◽  
Yield Estimation ◽  
Grassland Species ◽  
Aerial Imaging ◽  
Harvest Dates ◽  
Airborne Imaging ◽  
The Individual

In this study, we investigated the potential of airborne imaging spectroscopy for in-season grassland yield estimation. We utilized an unmanned aerial vehicle and a hyperspectral imager to measure radiation, ranging from 455 to 780 nm. Initially, we assessed the spectral signature of five typical grassland species by principal component analysis, and identified a distinct reflectance difference, especially between the erectophil grasses and the planophil clover leaves. Then, we analyzed the reflectance of a typical Norwegian sward composition at different harvest dates. In order to estimate yields (dry matter, DM), several powered partial least squares (PPLS) regression and linear regression (LR) models were fitted to the reflectance data and prediction performance of these models were compared with that of simple LR models, based on selected vegetation indices and plant height. We achieved the highest prediction accuracies by means of PPLS, with relative errors of prediction from 9.1 to 11.8% (329 to 487 kg DM ha−1) for the individual harvest dates and 14.3% (558 kg DM ha−1) for a generalized model.

Exploring the scattering and reabsorption of chlorophyll fluorescence: implications for remote sensing of photosynthesis

2020 ◽  
Author(s):  
Karolina Sakowska ◽  
Maria Pilar Cendrero-Mateo* ◽  
Christiaan van der Tol ◽  
Marco Celesti ◽  
Giorgio Alberti ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Heat Dissipation ◽  
Structural Parameters ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Photosynthetic Performance ◽  
Photochemical Quenching ◽  
Spectral Vegetation Indices ◽  
Leaf Level ◽  
Scope Model

<p>In recent years, technological progress in high-resolution field spectrometers have enabled the use of alternative tracer for constraining ecosystem-scale photosynthesis, i.e. sun-induced fluorescence (SIF). The principle underlying the use of SIF as a proxy of gross primary productivity (GPP) is based on the fact that the light energy absorbed by chlorophyll molecules can proceed into three different pathways: photochemistry, heat dissipation, and chlorophyll fluorescence. Since these processes directly compete for the same excitation energy, measurements of SIF and non-photochemical quenching (NPQ) are expected to provide information on photosynthetic performance.</p><p>However, SIF signal measured at the leaf level or beyond is affected by several processes, including wavelength dependent scattering and reabsorption, which may need to be considered when linking SIF data and photosynthetic CO<sub>2</sub> assimilation.</p><p>To address this question, we conducted a multi-scale and multi-technique study that considered measurements of photosynthetic (GPP), optical (SIF, reflectance - R and transmittance - T), physiological (NPQ) and biophysical (the amount of absorbed photosynthetically active radiation - APAR) parameters of two soybean varieties: the MinnGold mutant, characterized by significantly reduced chlorophyll content (Chl), and the wild type, non-Chl deficient Eiko. We further used the “Soil-Canopy Observation Photosynthesis and Energy fluxes” (SCOPE) model to investigate the reabsorption and scattering of SIF. The measured leaf R, T and SIF and top-of-the-canopy R were used to retrieve biochemical and structural parameters of both varieties by inversion of the SCOPE model, while its forward mode was used to determine and correct for the scattering and reabsorption of SIF at both leaf and canopy level.</p><p>Our study revealed that despite the large difference in Chl content (the ratio of Chl between MinnGold and Eiko was nearly 1:5), similar leaf and canopy photosynthesis rates were maintained in the Chl‐deficient mutant. This phenomenon was captured neither by traditional spectral vegetation indices related to canopy greenness, nor by SIF measured in-situ. However, the modelling simulations revealed that when correcting for leaf and canopy scattering and reabsorption processes both varieties presented similar SIF yield (SIF/APAR). Furthermore, field measurements showed that APAR and NPQ in MinnGold were lower than in Eiko. This together explains the similar measured GPP and simulated SIF yield between the two varieties, and indicates that interpretation and application of SIF as a GPP tracer requires understanding and quantification of all these processes.</p>

Errors associated with atmospheric correction methods for airborne imaging spectroscopy: Implications for vegetation indices and plant traits

2021 ◽  
Vol 265 ◽  
pp. 112663
Author(s):  
Ran Wang ◽  
John A. Gamon ◽  
Ryan Moore ◽  
Arthur I. Zygielbaum ◽  
Timothy J. Arkebauer ◽  
...  
Keyword(s):  
Plant Traits ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Imaging Spectroscopy ◽  
Airborne Imaging

Light Absorption and Partitioning in Response to Nitrogen in Apple Leaves

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 541a-541
Author(s):  
Lailiang Cheng ◽  
Leslie H. Fuchigami ◽  
Patrick J. Breen
Keyword(s):  
High Light ◽  
Thermal Dissipation ◽  
Photochemical Quenching ◽  
Light Conditions ◽  
Psii Efficiency ◽  
Fluorescence Measurements ◽  
Free Radical Formation ◽  
Highly Correlated ◽  
Non Photochemical Quenching ◽  
Leaf N

Bench-grafted Fuji/M26 apple trees were fertigated with different concentrations of nitrogen by using a modified Hoagland solution for 6 weeks, resulting in a range of leaf N from 1.0 to 4.3 g·m–2. Over this range, leaf absorptance increased curvilinearly from 75% to 92.5%. Under high light conditions (1500 (mol·m–2·s–1), the amount of absorbed light in excess of that required to saturate CO2 assimilation decreased with increasing leaf N. Chlorophyll fluorescence measurements revealed that the maximum photosystem II (PSII) efficiency of dark-adapted leaves was relatively constant over the leaf N range except for a slight drop at the lower end. As leaf N increased, non-photochemical quenching under high light declined and there was a corresponding increase in the efficiency with which the absorbed photons were delivered to open PSII centers. Photochemical quenching coefficient decreased significantly at the lower end of the leaf N range. Actual PSII efficiency increased curvilinearly with increasing leaf N, and was highly correlated with light-saturated CO2 assimilation. The fraction of absorbed light potentially used for free radical formation was estimated to be about 10% regardless of the leaf N status. It was concluded that increased thermal dissipation protected leaves from photo-oxidation as leaf N declined.

scholarly journals Gradual Response of Cyanobacterial Thylakoids to Acute High-Light Stress—Importance of Carotenoid Accumulation

Cells ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1916
Author(s):  
Myriam Canonico ◽  
Grzegorz Konert ◽  
Aurélie Crepin ◽  
Barbora Šedivá ◽  
Radek Kaňa
Keyword(s):  
Single Cell ◽  
Thylakoid Membrane ◽  
Intermediate Phase ◽  
Light Stress ◽  
Fast Response ◽  
High Light ◽  
Photochemical Quenching ◽  
Second Phase ◽  
Ros Scavenging ◽  
Non Photochemical Quenching

Light plays an essential role in photosynthesis; however, its excess can cause damage to cellular components. Photosynthetic organisms thus developed a set of photoprotective mechanisms (e.g., non-photochemical quenching, photoinhibition) that can be studied by a classic biochemical and biophysical methods in cell suspension. Here, we combined these bulk methods with single-cell identification of microdomains in thylakoid membrane during high-light (HL) stress. We used Synechocystis sp. PCC 6803 cells with YFP tagged photosystem I. The single-cell data pointed to a three-phase response of cells to acute HL stress. We defined: (1) fast response phase (0–30 min), (2) intermediate phase (30–120 min), and (3) slow acclimation phase (120–360 min). During the first phase, cyanobacterial cells activated photoprotective mechanisms such as photoinhibition and non-photochemical quenching. Later on (during the second phase), we temporarily observed functional decoupling of phycobilisomes and sustained monomerization of photosystem II dimer. Simultaneously, cells also initiated accumulation of carotenoids, especially ɣ–carotene, the main precursor of all carotenoids. In the last phase, in addition to ɣ-carotene, we also observed accumulation of myxoxanthophyll and more even spatial distribution of photosystems and phycobilisomes between microdomains. We suggest that the overall carotenoid increase during HL stress could be involved either in the direct photoprotection (e.g., in ROS scavenging) and/or could play an additional role in maintaining optimal distribution of photosystems in thylakoid membrane to attain efficient photoprotection.

scholarly journals The Role of Acidic Residues in the C Terminal Tail of the LHCSR3 Protein of Chlamydomonas reinhardtii in Non-Photochemical Quenching

2021 ◽  
pp. 6895-6900
Author(s):  
Franco V. A. Camargo ◽  
Federico Perozeni ◽  
Gabriel de la Cruz Valbuena ◽  
Luca Zuliani ◽  
Samim Sardar ◽  
...  
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Photochemical Quenching ◽  
Acidic Residues ◽  
Non Photochemical Quenching

scholarly journals Effects of iron limitation on carbon balance and photophysiology of the Antarctic diatom Chaetoceros cf. simplex

Polar Biology ◽  
2021 ◽  
Author(s):  
Deborah Bozzato ◽  
Torsten Jakob ◽  
Christian Wilhelm ◽  
Scarlett Trimborn
Keyword(s):  
Oxygen Evolution ◽  
Photochemical Quenching ◽  
Gross Photosynthesis ◽  
Manganese Zinc ◽  
C Cycle ◽  
Uptake Rates ◽  
Carbon Pump ◽  
Non Photochemical Quenching ◽  
The Antarctic ◽  
Biological Carbon Pump

AbstractIn the Southern Ocean (SO), iron (Fe) limitation strongly inhibits phytoplankton growth and generally decreases their primary productivity. Diatoms are a key component in the carbon (C) cycle, by taking up large amounts of anthropogenic CO2 through the biological carbon pump. In this study, we investigated the effects of Fe availability (no Fe and 4 nM FeCl3 addition) on the physiology of Chaetoceros cf. simplex, an ecologically relevant SO diatom. Our results are the first combining oxygen evolution and uptake rates with particulate organic carbon (POC) build up, pigments, photophysiological parameters and intracellular trace metal (TM) quotas in an Fe-deficient Antarctic diatom. Decreases in both oxygen evolution (through photosynthesis, P) and uptake (respiration, R) coincided with a lowered growth rate of Fe-deficient cells. In addition, cells displayed reduced electron transport rates (ETR) and chlorophyll a (Chla) content, resulting in reduced cellular POC formation. Interestingly, no differences were observed in non-photochemical quenching (NPQ) or in the ratio of gross photosynthesis to respiration (GP:R). Furthermore, TM quotas were measured, which represent an important and rarely quantified parameter in previous studies. Cellular quotas of manganese, zinc, cobalt and copper remained unchanged while Fe quotas of Fe-deficient cells were reduced by 60% compared with High Fe cells. Based on our data, Fe-deficient Chaetoceros cf. simplex cells were able to efficiently acclimate to low Fe conditions, reducing their intracellular Fe concentrations, the number of functional reaction centers of photosystem II (RCII) and photosynthetic rates, thus avoiding light absorption rather than dissipating the energy through NPQ. Our results demonstrate how Chaetoceros cf. simplex can adapt their physiology to lowered assimilatory metabolism by decreasing respiratory losses.

scholarly journals Estimating and Monitoring Land Surface Phenology in Rangelands: A Review of Progress and Challenges

2021 ◽  
Vol 13 (11) ◽  
pp. 2060
Author(s):  
Trylee Nyasha Matongera ◽  
Onisimo Mutanga ◽  
Mbulisi Sibanda ◽  
John Odindi
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Critical Role ◽  
Spectral Characteristics ◽  
Vegetation Indices ◽  
Machine Learning Algorithms ◽  
Special Focus ◽  
Land Surface Phenology ◽  
Spectral Vegetation Indices ◽  
Satellite Sensors

Land surface phenology (LSP) has been extensively explored from global archives of satellite observations to track and monitor the seasonality of rangeland ecosystems in response to climate change. Long term monitoring of LSP provides large potential for the evaluation of interactions and feedbacks between climate and vegetation. With a special focus on the rangeland ecosystems, the paper reviews the progress, challenges and emerging opportunities in LSP while identifying possible gaps that could be explored in future. Specifically, the paper traces the evolution of satellite sensors and interrogates their properties as well as the associated indices and algorithms in estimating and monitoring LSP in productive rangelands. Findings from the literature revealed that the spectral characteristics of the early satellite sensors such as Landsat, AVHRR and MODIS played a critical role in the development of spectral vegetation indices that have been widely used in LSP applications. The normalized difference vegetation index (NDVI) pioneered LSP investigations, and most other spectral vegetation indices were primarily developed to address the weaknesses and shortcomings of the NDVI. New indices continue to be developed based on recent sensors such as Sentinel-2 that are characterized by unique spectral signatures and fine spatial resolutions, and their successful usage is catalyzed with the development of cutting-edge algorithms for modeling the LSP profiles. In this regard, the paper has documented several LSP algorithms that are designed to provide data smoothing, gap filling and LSP metrics retrieval methods in a single environment. In the future, the development of machine learning algorithms that can effectively model and characterize the phenological cycles of vegetation would help to unlock the value of LSP information in the rangeland monitoring and management process. Precisely, deep learning presents an opportunity to further develop robust software packages such as the decomposition and analysis of time series (DATimeS) with the abundance of data processing tools and techniques that can be used to better characterize the phenological cycles of vegetation in rangeland ecosystems.

scholarly journals Mapping leaf metal content over industrial brownfields using airborne hyperspectral imaging and optimized vegetation indices

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guillaume Lassalle ◽  
Sophie Fabre ◽  
Anthony Credoz ◽  
Rémy Hédacq ◽  
Dominique Dubucq ◽  
...  
Keyword(s):  
Metal Uptake ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Good Alternative ◽  
Entire Study ◽  
Metal Contents ◽  
Very High Spatial Resolution ◽  
Airborne Imaging ◽  
Very High ◽  
Plant Metal Uptake

AbstractMonitoring plant metal uptake is essential for assessing the ecological risks of contaminated sites. While traditional techniques used to achieve this are destructive, Visible Near-Infrared (VNIR) reflectance spectroscopy represents a good alternative to monitor pollution remotely. Based on previous work, this study proposes a methodology for mapping the content of several metals in leaves (Cr, Cu, Ni and Zn) under realistic field conditions and from airborne imaging. For this purpose, the reflectance of Rubus fruticosus L., a pioneer species of industrial brownfields, was linked to leaf metal contents using optimized normalized vegetation indices. High correlations were found between the vegetation indices exploiting pigment-related wavelengths and leaf metal contents (r ≤ − 0.76 for Cr, Cu and Ni, and r ≥ 0.87 for Zn). This allowed predicting the metal contents with good accuracy in the field and on the image, especially Cu and Zn (r ≥ 0.84 and RPD ≥ 2.06). The same indices were applied over the entire study site to map the metal contents at very high spatial resolution. This study demonstrates the potential of remote sensing for assessing metal uptake by plants, opening perspectives of application in risk assessment and phytoextraction monitoring in the context of trace metal pollution.

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