Sun-induced Fluorescence Research Articles

Estimating variability in the quantum yield of Sun-induced chlorophyll fluorescence: A global analysis of oceanic waters

While empirical and semi-analytical algorithms that retrieve phytoplankton biomass from satellite ocean color have matured over the last few decades, the use of Sun-induced chlorophyll fluorescence data measured by spaceborne sensors remains in its infancy. Sun-induced fluorescence has the potential to provide a synoptic global view of aspects of phytoplankton biology that go beyond biomass by observing the quantum yield of fluorescence. While several algorithms have been developed to retrieve the quantum yield, they are prone to biases from different sources. In this study, we assessed the accuracy of several ocean color algorithms to estimate phytoplankton chlorophyll or absorption when they are used together with Sun-induced fluorescence algorithms. Our analysis led us to develop a new type of algorithm for retrieving variability in the quantum yield of fluorescence. Based on a three dimensional lookup table, this algorithm avoided many of the biases present in older algorithms and provided distributions of the quantum yield that showed significant differences compared to previous methods. This algorithmic approach also has the advantage of being robust with respect to sensor characteristics and to the set of underlying proxies that are used, namely phytoplankton biomass, the absorption by chromophoric dissolved organic matter, and the incident irradiance. As such, it would be suitable for merging data from multiple satellite ocean color sensors.

Non-invasive approaches for phenotyping of enhanced performance traits in bean.

Plant phenotyping is an emerging discipline in plant biology. Quantitative measurements of functional and structural traits help to better understand gene-environment interactions and support breeding for improved resource use efficiency of important crops such as bean (Phaseolus vulgaris L.). Here we provide an overview of state-of-the-art phenotyping approaches addressing three aspects of resource use efficiency in plants: belowground roots, aboveground shoots and transport/allocation processes. We demonstrate the capacity of high-precision methods to measure plant function or structural traits non-invasively, stating examples wherever possible. Ideally, high-precision methods are complemented by fast and high-throughput technologies. High-throughput phenotyping can be applied in the laboratory using automated data acquisition, as well as in the field, where imaging spectroscopy opens a new path to understand plant function non-invasively. For example, we demonstrate how magnetic resonance imaging (MRI) can resolve root structure and separate root systems under resource competition, how automated fluorescence imaging (PAM fluorometry) in combination with automated shape detection allows for high-throughput screening of photosynthetic traits and how imaging spectrometers can be used to quantify pigment concentration, sun-induced fluorescence and potentially photosynthetic quantum yield. We propose that these phenotyping techniques, combined with mechanistic knowledge on plant structure-function relationships, will open new research directions in whole-plant ecophysiology and may assist breeding for varieties with enhanced resource use efficiency varieties.

Optical properties of Peter the Great Bay waters compared with satellite ocean colour data

The shipboard measurements of optical and hydrological properties of seawater were used for development of regional bio-optical algorithms of waters of Peter the Great Bay. The shipboard measurements of chlorophyll-a and dissolved organic matter (DOM) concentrations were obtained by flow-through laser fluorometer (LF-3) (Institute for Automation and Control Processes, Vladivostok, Russia) and Sea-Bird Profiling CTD SBE-19plus (Conductivity, Temperature and Depth Sea-Bird Electronics, Sea-Bird Electronics, Inc., Washington, USA) equipped with WetStar fluorometers (WET Labs, Oregon, USA). The measurements were optically weighted according to light attenuation by depth. Ocean colour Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua data were used for our comparative analysis. Chlorophyll-a concentrations from ocean colour data were retrieved by OC3M, Garver-Siegel-Maritorena (GSM) and Carder algorithms. Relationships of the shipboard and satellite sensor data were analysed comparatively in our work. The Carder model gives the most general results of estimation of chlorophyll-a concentrations for all observed water cases. OC3M and GSM algorithms show good performance in case I water but they have large errors in the Amur Bay waters because of a large impact of the Razdolnaya river and Vladivostok city anthropogenic activity. Two regional chlorophyll-a algorithms were offered and they improve significantly the accuracy of chlorophyll-a concentration estimation. The first one is based on empirical regression between chlorophyll-a concentration and remotely sensed reflectance ratio. The second one uses satellite-derived values of sun-induced chlorophyll-a fluorescence when chlorophyll-a concentrations are higher than 3 mg m−3. The last one gives the best results for all water cases and provides an approach for separation between DOM produced by phytoplankton and DOM not connected with phytoplankton activity. This allows a regional DOM algorithm to be made.

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

Abstract. The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO2 fluxes. It was combined with extensive ground-based quantification of leaf- and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype airborne sensor AirFLEX quantified fluorescence in the oxygen A and B bands, (ii) a hyperspectral spectrometer (ASD) measured reflectance along transects during 12 day courses, (iii) spatially high resolution georeferenced hyperspectral data cubes containing the whole optical spectrum and the thermal region were gathered with an AHS sensor, and (iv) the first employment of the high performance imaging spectrometer HYPER delivered spatially explicit and multi-temporal transects across the whole region. During three measurement periods in April, June and September 2007 structural, functional and radiometric characteristics of more than 20 different vegetation types in the Les Landes region, Southwest France, were extensively characterized on the ground. The campaign concept focussed especially on quantifying plant mediated exchange processes (photosynthetic electron transport, CO2 uptake, evapotranspiration) and fluorescence emission. The comparison between passive sun-induced fluorescence and active laser-induced fluorescence was performed on a corn canopy in the daily cycle and under desiccation stress. Both techniques show good agreement in detecting stress induced fluorescence change at the 760 nm band. On the large scale, airborne and ground-level measurements of fluorescence were compared on several vegetation types supporting the scaling of this novel remote sensing signal. The multi-scale design of the four airborne radiometric measurements along with extensive ground activities fosters a nested approach to quantify photosynthetic efficiency and gross primary productivity (GPP) from passive fluorescence.

Retrieval of phytoplankton biomass from simultaneous inversion of reflectance, the diffuse attenuation coefficient, and Sun‐induced fluorescence in coastal waters

A model has been developed to retrieve phytoplankton absorption, a proxy for phytoplankton biomass, from observations of reflectance (R) and the diffuse attenuation coefficient (Kd) collected by moored radiometers in coastal waters, where high concentrations of chromophoric dissolved organic matter (CDOM) confound conventional ocean color algorithms. The inversion uses simultaneously two forward models: (1) a look‐up table (LUT) that accounts for instrument geometry and the effect of the solar angle on both R and Kd and (2) an analytical function describing the effects of Sun‐induced fluorescence (SIF) of chlorophyll on R. Estimates of phytoplankton biomass (mostly from SIF), the absorption by colored matter, and the particulate backscattering coefficients (mostly from the LUT) are obtained by optimizing the amplitude and shape of the absorption and backscattering coefficients in the forward model to best match the observations. An equation describing the quantum yield of fluorescence (photons fluoresced/photons absorbed) as a function of incident irradiance constrains the model and allows estimates of phytoplankton absorption. Innovations include: the utilization of both R and Kd, providing good separation of the effects of backscattering from absorption; avoidance of reflectance bands between 400 and 600 nm, thereby avoiding interference from bottom reflection and CDOM fluorescence; utilization of the full emission band of SIF; and accounting for the irradiance‐dependence of its quantum yield. The model effectively retrieved chlorophyll concentration from an independent data set — r = 0.76, n = 93, with a mean absolute percent error (MAPE) of 24%; this is better than a modern ocean color algorithm (OC4V4) on its validation data set, when restricted to the same range of chlorophyll (r = 0.67, n = 384, MAPE = 51%).

Interpretation of Sun-induced Fluorescence Peak of Chlorophyll a on Reflectance Spectrum of Algal Waters

Interpretation of Sun-induced Fluorescence Peak of Chlorophyll a on Reflectance Spectrum of Algal Waters