scholarly journals Estimation of chlorophyll fluorescence under natural illumination from hyperspectral data

2001 ◽  
Vol 3 (4) ◽  
pp. 321-327 ◽  
Author(s):  
Pablo J Zarco-Tejada ◽  
John R Miller ◽  
Gina H Mohammed ◽  
Thomas L Noland ◽  
Paul H Sampson
Keyword(s):  
Chlorophyll Fluorescence ◽  
Hyperspectral Data ◽  
Natural Illumination

scholarly journals Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 341
Author(s):  
Pauliina Salmi ◽  
Matti A. Eskelinen ◽  
Matti T. Leppänen ◽  
Ilkka Pölönen
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Strong Correlations ◽  
Algae Biomass ◽  
Chlorophyll A Concentration ◽  
Cost Efficient ◽  
Hyperspectral Camera

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.

scholarly journals Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4886
Author(s):  
Shilei Li ◽  
Maofang Gao ◽  
Zhao-Liang Li
Keyword(s):  
Chlorophyll Fluorescence ◽  
Fluorescence Spectrum ◽  
Singular Vector ◽  
Low Frequency ◽  
Information Criterion ◽  
Hyperspectral Data ◽  
High Spectral Resolution ◽  
Remotely Sensed Data ◽  
Spectral Window ◽  
Vector Decomposition

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.

scholarly journals Quantifying Chlorophyll Fluorescence Parameters from Hyperspectral Reflectance at the Leaf Scale under Various Nitrogen Treatment Regimes in Winter Wheat

2019 ◽  
Vol 11 (23) ◽  
pp. 2838 ◽  
Author(s):  
Min Jia ◽  
Dong Li ◽  
Roberto Colombo ◽  
Ying Wang ◽  
Xue Wang ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Field Experiments ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Spectral Features ◽  
Edge Region ◽  
Chlorophyll Fluorescence Parameters ◽  
Red Edge ◽  
Curvature Index ◽  
Plant Densities

Chlorophyll fluorescence (ChlF) parameters, especially the quantum efficiency of photosystem II (PSII) in dark- and light-adapted conditions (Fv/Fm and Fv’/Fm’), have been used extensively to indicate photosynthetic activity, physiological function, as well as healthy and early stress conditions. Previous studies have demonstrated the potential of applying hyperspectral data for the detection of ChlF parameters in vegetation. However, the performance of spectral features that have been documented to estimate ChlF is not ideal and is poorly understood. In this study, ChlF parameters and leaf reflectance were collected in two field experiments involving various wheat cultivars, nitrogen (N) applications, and plant densities, during the growing seasons of 2014 to 2015 and 2015 to 2016. Three types of spectral features, including vegetation indices (VIs), red edge position (REP), and wavelet features, were used to quantify ChlF parameters Fv/Fm and Fv’/Fm’. The results indicated that traditional chlorophyll fluorescence vegetation indices (ChlF VIs), such as the curvature index (CUR) and D705/D722 were capable of detecting Fv/Fm and Fv’/Fm’ under various scenarios. However, the wavelet-based REP (WREP-S4) and the wavelet feature (WF) (704 nm, scale 4) yielded higher accuracy than other spectral features in calibration and validation datasets. Moreover, the bands used to calculate WREP-S4 and WF (704 nm, scale 4) were all centered in the red edge region (680 to 760 nm), which highlighted the role of the red edge region in tracking the change of active ChlF signal. Our results are supported by previous studies, which have shown that the red edge region is vital for estimating the chlorophyll content, and also the ChlF parameters. These findings could help to improve our understanding of the relationships among active ChlF signal and reflectance spectra.

scholarly journals Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2

2013 ◽  
Vol 6 (10) ◽  
pp. 2803-2823 ◽  
Author(s):  
J. Joiner ◽  
L. Guanter ◽  
R. Lindstrot ◽  
M. Voigt ◽  
A. P. Vasilkov ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Spectral Resolution ◽  
Hyperspectral Data ◽  
Radiative Transfer Model ◽  
High Signal ◽  
Transfer Model ◽  
Good Precision ◽  
Atmospheric Absorption ◽  
Red Fluorescence ◽  
Global Coverage

Abstract. Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5° × 0.5°. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Automatic tumor tissue classification of oncological esophageal resectates based on hyperspectral data

2019 ◽  
Author(s):  
M Maktabi ◽  
H Köhler ◽  
R Thieme ◽  
JP Takoh ◽  
SM Rabe ◽  
...  
Keyword(s):  
Tumor Tissue ◽  
Hyperspectral Data ◽  
Tissue Classification

Quantification of small-scale heterogeneity in aquatic aminopeptidase activity

2020 ◽  
Vol 84 ◽  
pp. 127-140
Author(s):  
BM Gaas ◽  
JW Ammerman
Keyword(s):  
Chlorophyll Fluorescence ◽  
Leucine Aminopeptidase ◽  
Hudson River ◽  
Aminopeptidase Activity ◽  
Small Scale ◽  
Analysis Instrument ◽  
Sequential Samples ◽  
Degree Of Confidence ◽  
The Mean ◽  
Hydrolysis Of

Leucine aminopeptidase (LAP) is one of the enzymes involved in the hydrolysis of peptides, and is sometimes used to indicate potential nitrogen limitation in microbes. Small-scale variability has the potential to confound interpretation of underlying patterns in LAP activity in time or space. An automated flow-injection analysis instrument was used to address the small-scale variability of LAP activity within contiguous regions of the Hudson River plume (New Jersey, USA). LAP activity had a coefficient of variation (CV) of ca. 0.5 with occasional values above 1.0. The mean CVs for other biological parameters—chlorophyll fluorescence and nitrate concentration—were similar, and were much lower for salinity. LAP activity changed by an average of 35 nmol l-1 h-1 at different salinities, and variations in LAP activity were higher crossing region boundaries than within a region. Differences in LAP activity were ±100 nmol l-1 h-1 between sequential samples spaced <10 m apart. Variogram analysis indicated an inherent spatial variability of 52 nmol l-1 h-1 throughout the study area. Large changes in LAP activity were often associated with small changes in salinity and chlorophyll fluorescence, and were sensitive to the sampling frequency. This study concludes that LAP measurements in a sample could realistically be expected to range from zero to twice the average, and changes between areas or times should be at least 2-fold to have some degree of confidence that apparent patterns (or lack thereof) in activity are real.

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