A field study on solar-induced chlorophyll fluorescence and pigment parameters along a vertical canopy gradient of four tree species in an urban environment

Wittenberghe, Shari Van; Alonso, Luis; Verrelst, Jochem; Hermans, Inge; Valcke, Roland; Veroustraete, Frank; Moreno, José; Samson, Roeland

doi:10.1016/j.scitotenv.2013.07.024

Cited by 29 publications

(18 citation statements)

References 27 publications

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“…For the forward fluorescence spectra (Figure 5b,d), the left peak is weak, and almost unnoticeable for wheat leaves (Figure 5b). Highest contrasts between the left and right peaks for both backward and forward fluorescence are observed for soybean leaves (Figure 5c Generally, shapes of the fluorescence spectra and positions of left peak (occurs in the range of 686-691 nm) and right peak (in the range of 739-743 nm) measured in this study are consistent with the spectra measured by a specifically designed equipment (FluoWat) to measure leaf fluorescence reported in other studies [24][25][26]. However, intensity of the lamp with the filter used in this study is much weaker than that of FluoWat.…”

Section: Distributions Of the Fluorescence Spectrasupporting

confidence: 90%

“…The ChlF signal can provide critical information about the growth status of plants, and therefore it has been used as an effective tool to monitor plant stress induced by air pollution [25,26], water deficit [28,29], herbicide treatment [2], and salt and drought [30]. Quantitative estimation of the fluorescence parameters for crop leaves would be of high importance in assessing the photosynthetic rates of green plants and monitoring the stress conditions of crops.…”

Section: Potential and Limitations Of Applying Model Inversion For Thmentioning

confidence: 99%

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Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion

et al. 2015

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Abstract:In this study, backward and forward fluorescence radiance within the emission spectrum of 640-850 nm were measured for leaves of soybean, cotton, peanut and wheat using a hyperspectral spectroradiometer coupled with an integration sphere. Fluorescence parameters of crop leaves were retrieved from the leaf hyperspectral measurements by inverting the FluorMODleaf model, a leaf-level fluorescence model able to simulate chlorophyll fluorescence spectra for both sides of leaves. This model is based on the widely used and validated PROSPECT (leaf optical properties) model. Firstly, a sensitivity analysis of the FluorMODleaf model was performed to identify and quantify influential parameters to assist the strategy for the inversion. Implementation of the Extended Fourier Amplitude Sensitivity Test (EFAST) method showed that the leaf chlorophyll content and the OPEN ACCESSRemote Sens. 2015, 7 14180 fluorescence lifetimes of photosystem I (PSI) and photosystem II (PSII) were the most sensitive parameters among all eight inputs of the FluorMODleaf model. Based on results of sensitivity analysis, the FluorMODleaf model was inverted using the leaf fluorescence spectra measured from both sides of crop leaves. In order to achieve stable inversion results, the Bayesian inference theory was applied. The relative absorption cross section of PSI and PSII and the fluorescence lifetimes of PSI and PSII of the FluorMODleaf model were retrieved with the Bayesian inversion approach. Results showed that the coefficient of determination (R 2 ) and root mean square error (RMSE) between the fluorescence signal reconstructed from the inverted fluorescence parameters and measured in the experiment were 0.96 and 3.14 × 10 −6 W· m −2 · sr −1 · nm −1 , respectively, for backward fluorescence, and 0.92 and 3.84 × 10 −6 W· m −2 · sr −1 · nm −1 for forward fluorescence. Based on results, the inverted values of the fluorescence parameters were analyzed, and the potential of this method was investigated.

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Section: Distributions Of the Fluorescence Spectrasupporting

confidence: 90%

Section: Potential and Limitations Of Applying Model Inversion For Thmentioning

confidence: 99%

Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion

et al. 2015

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“…Third, estimating wavelength‐specific reabsorption and emission is complicated by the spectrum of the incoming light source, which often differs between the light‐emitting diode (LED) source for PAM measurements and direct sunlight for SIF. The emission spectrum of the light source allows photons to penetrate into different leaf and canopy layers, resulting in wavelength‐dependent scattering, absorption, and reabsorption throughout the canopy (Buschmann & Lichtenthaler, ; Vogelmann & Evans, ; Van Wittenberghe et al ., , ). Moreover, the contribution of fluorescence differs between photosystems I (PSI) and PSII in that the contribution of PSI fluorescence is not affected by photochemical quenching as it lacks the back‐transfer mechanisms of excitation into the antenna system (Franck et al ., ; Hasegawa et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Connecting active to passive fluorescence with photosynthesis: a method for evaluating remote sensing measurements of Chl fluorescence

et al. 2017

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Recent advances in the retrieval of Chl fluorescence from space using passive methods (solar-induced Chl fluorescence, SIF) promise improved mapping of plant photosynthesis globally. However, unresolved issues related to the spatial, spectral, and temporal dynamics of vegetation fluorescence complicate our ability to interpret SIF measurements. We developed an instrument to measure leaf-level gas exchange simultaneously with pulse-amplitude modulation (PAM) and spectrally resolved fluorescence over the same field of view - allowing us to investigate the relationships between active and passive fluorescence with photosynthesis. Strongly correlated, slope-dependent relationships were observed between measured spectra across all wavelengths (F , 670-850 nm) and PAM fluorescence parameters under a range of actinic light intensities (steady-state fluorescence yields, F ) and saturation pulses (maximal fluorescence yields, F ). Our results suggest that this method can accurately reproduce the full Chl emission spectra - capturing the spectral dynamics associated with changes in the yields of fluorescence, photochemical (ΦPSII), and nonphotochemical quenching (NPQ). We discuss how this method may establish a link between photosynthetic capacity and the mechanistic drivers of wavelength-specific fluorescence emission during changes in environmental conditions (light, temperature, humidity). Our emphasis is on future research directions linking spectral fluorescence to photosynthesis, ΦPSII, and NPQ.

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“…However, the retrieval accuracies of them are different. Generally, the more strongly absorbed line is more suitable for Fs retrieval, and consequently produces a lower condition number of M T × M when solving Equation (6). Therefore, for each Fs value we assign it a weight w(i) which could adjust the impact of its retrieval accuracy on the determination of the coefficients of the singular vectors.…”

Section: Determination Of the Coefficients Of Singular Vectorsmentioning

confidence: 99%

A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements

et al. 2014

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A method for canopy Fluorescence Spectrum Reconstruction (FSR) is proposed in this study, which can be used to retrieve the solar-induced canopy fluorescence spectrum over the whole chlorophyll fluorescence emission region from 640-850 nm. Firstly, the radiance of the solar-induced chlorophyll fluorescence (Fs) at five absorption lines of the solar spectrum was retrieved by a Spectral Fitting Method (SFM). The Singular Vector Decomposition (SVD) technique was then used to extract three basis spectra from a training dataset simulated by the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes). Finally, these basis spectra were linearly combined to reconstruct the Fs spectrum, and the coefficients of them were determined by Weighted Linear Least Squares (WLLS) fitting with the five retrieved Fs values. Results for simulated datasets indicate that the FSR method could accurately reconstruct the Fs spectra from hyperspectral measurements acquired by instruments of high Spectral Resolution (SR) and Signal to Noise Ratio (SNR). The FSR method was also applied to an experimental dataset acquired in a diurnal experiment. The diurnal change of the reconstructed Fs spectra shows that the Fs OPEN ACCESSRemote Sens. 2014, 6 10172 radiance around noon was higher than that in the morning and afternoon, which is consistent with former studies. Finally, the potential and limitations of this method are discussed.

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A field study on solar-induced chlorophyll fluorescence and pigment parameters along a vertical canopy gradient of four tree species in an urban environment

Cited by 29 publications

References 27 publications

Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion

Quantitative Estimation of Fluorescence Parameters for Crop Leaves with Bayesian Inversion

Connecting active to passive fluorescence with photosynthesis: a method for evaluating remote sensing measurements of Chl fluorescence

A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements

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