Simulation of canopy fluorescence as a function of canopy structure and leaf fluorescence

Olioso, Albert; Méthy, M.; Lacaze, Bernard

doi:10.1016/0034-4257(92)90081-t

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…The relationship between leaf and canopy fluorescence parameters could be further investigated through the use of a simple model taking into account leaf fluorescence profile inside the canopy, structural variations of the canopy, and background reflection [81]. Such information can be useful to evaluate the possibility to use the proposed method in conjunction with remote sensing fluorescence measurements obtained from an unmanned aerial vehicle (UAV) [82], aerial or satellite remote sensing [83,84].…”

Section: Implications For Practical Application and Future Research Nmentioning

confidence: 99%

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

et al. 2020

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Nitrogen (N) is one of the most essential nutrients that can significantly affect crop grain yield and quality. The implementation of proximal and remote sensing technologies in precision agriculture has provided new opportunities for non-destructive and real-time diagnosis of crop N status and precision N management. Notably, leaf fluorescence sensors have shown high potential in the accurate estimation of plant N status. However, most studies using leaf fluorescence sensors have mainly focused on the estimation of leaf N concentration (LNC) rather than plant N concentration (PNC). The objectives of this study were to (1) determine the relationship of maize (Zea mays L.) LNC and PNC, (2) evaluate the main factors influencing the variations of leaf fluorescence sensor parameters, and (3) establish a general model to estimate PNC directly across growth stages. A leaf fluorescence sensor, Dualex 4, was used to test maize leaves with three different positions across four growth stages in two fields with different soil types, planting densities, and N application rates in Northeast China in 2016 and 2017. The results indicated that the total leaf N concentration (TLNC) and PNC had a strong correlation (R2 = 0.91 to 0.98) with the single leaf N concentration (SLNC). The TLNC and PNC were affected by maize growth stage and N application rate but not the soil type. When used in combination with the days after sowing (DAS) parameter, modified Dualex 4 indices showed strong relationships with TLNC and PNC across growth stages. Both modified chlorophyll concentration (mChl) and modified N balance index (mNBI) were reliable predictors of PNC. Good results could be achieved by using information obtained only from the newly fully expanded leaves before the tasseling stage (VT) and the leaves above panicle at the VT stage to estimate PNC. It is concluded that when used together with DAS, the leaf fluorescence sensor (Dualex 4) can be used to reliably estimate maize PNC across growth stages.

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Section: Implications For Practical Application and Future Research Nmentioning

confidence: 99%

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

et al. 2020

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“…The intensity of the fluorescence signal at canopy level depends on the photosynthetic rates, biophysical, biochemical and structural characteristics of the canopy, incoming radiation and background contributions (Cerovic et al, 1996;Damm, Guanter, Paul-Limoges et al, 2015;Damm, Guanter, Verhoef et al, 2015;Daumard et al, 2010;Fournier et al, 2012;Hoge, Swift, & Yungel, 1983;Moya, Daumard, Moise, Ounis, & Goulas, 2006;Olioso, M ethy, & Lacaze, 1992;Rossini et al, 2016;Van Wittenberghe et al, 2013;Verrelst et al, 2015). These parameters are highly variable in space and time and they should all be considered to correctly interpret the fluorescence signal.…”

mentioning

confidence: 99%

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Colombo

Celesti

Bianchi

et al. 2018

Global Change Biology

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Leaf fluorescence can be used to track plant development and stress, and is considered the most direct measurement of photosynthetic activity available from remote sensing techniques. Red and far-red sun-induced chlorophyll fluorescence (SIF) maps were generated from high spatial resolution images collected with the HyPlant airborne spectrometer over even-aged loblolly pine plantations in North Carolina (United States). Canopy fluorescence yield (i.e., the fluorescence flux normalized by the light absorbed) in the red and far-red peaks was computed. This quantifies the fluorescence emission efficiencies that are more directly linked to canopy function compared to SIF radiances. Fluorescence fluxes and yields were investigated in relation to tree age to infer new insights on the potential of those measurements in better describing ecosystem processes. The results showed that red fluorescence yield varies with stand age. Young stands exhibited a nearly twofold higher red fluorescence yield than mature forest plantations, while the far-red fluorescence yield remained constant. We interpreted this finding in a context of photosynthetic stomatal limitation in aging loblolly pine stands. Current and future satellite missions provide global datasets of SIF at coarse spatial resolution, resulting in intrapixel mixture effects, which could be a confounding factor for fluorescence signal interpretation. To mitigate this effect, we propose a surrogate of the fluorescence yield, namely the Canopy Cover Fluorescence Index (CCFI) that accounts for the spatial variability in canopy structure by exploiting the vegetation fractional cover. It was found that spatial aggregation tended to mask the effective relationships, while the CCFI was still able to maintain this link. This study is a first attempt in interpreting the fluorescence variability in aging forest stands and it may open new perspectives in understanding long-term forest dynamics in response to future climatic conditions from remote sensing of SIF.

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“…Nevertheless, the relationships found are not universally applied, and it has been suggested that C 3 and C 4 plants dissipation mechanisms are different due to the contribution of other processes to electron use in C 3 plants (Lichtenthaler et al 1998 ;Flexas et al 2000 ) . Actually, not only the carbon fi xation mechanism but also leaf roughness and thickness and the vegetation structure are in fl uencing the fl uorescence signal (Rosema et al 1991 ;Olioso et al 1992 ;Moya et al 2006 ) .…”

Section: Chlorophyll Fluorescencementioning

confidence: 95%

“…In particular, as an attempt to minimize structural effects, indices related to fl uorescence emission bands located in the red and far red have been proposed to assess the relationship between apparent re fl ectance and chlorophyll fl uorescence at both leaf and canopy levels (Olioso et al 1992 ;Zarco-Tejada et al 2000a, b ) . It has been suggested that while changes in chlorophyll fl uorescence emission in the red are related to nutrient stress leading to lower chlorophyll content, blue/red and blue/near-infrared fl uorescence ratios are sensitive to abiotic stress (Lichtenthaler et al 1998 ) .…”

Section: Chlorophyll Fluorescencementioning

confidence: 99%

Spectral Response of Citrus and Their Application to Nutrient and Water Constraints Diagnosis

Suárez

Berni

2012

Advances in Citrus Nutrition

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The early diagnosis of nutrient and water stress is a key issue for the proper management of orchards. Unfortunately, the measurement of indicators in the fi eld to assess those de fi ciencies is expensive and time consuming. Remote sensing provides the possibility of assessing water and nutrient stress over every single stand on the whole area of interest. Leaf and canopy spectra are affected by every vegetation process or change in leaf pigments. However, the effect of each nutrient de fi ciency on the canopy spectrum is very subtle and the wavelength ranges affected by the different nutrients are generally overlapping. Then, an analysis in detail is needed in order to properly discriminate between the different stress causes. This chapter presents a review of previous studies dealing with remote sensing of nutrient and water stress, de fi ning the spectral regions affected and the methodologies that have been applied for vegetation stress assessment. Speci fi c multispectral indices related to leaf pigment content and physiological vegetation processes, thermal imagery, and fl uorescence studies are presented. Finally, some results obtained from radiative transfer modeling simulations highlight the importance of the spatial resolution for precise agriculture purposes.There is extensive future research needed focusing on dissembling the overlapping effects of different nutrient de fi ciencies on the electromagnetic spectrum. Generally, vegetation indices used for nutrient assessment are affected by more than one nutrient content; a speci fi c diagnosis is dif fi cult to solve. As an example, pertinent indices can be developed in order to perform a proper stress diagnosis. Additionally, leaf-level radiative transfer models can be improved to account for differences in speci fi c pigments. If leaf re fl ectance can be modeled for different nutrient levels, tree nutrient status can be assess through modeling inversion. Modeling inversion techniques are especially interesting because they do not rely on site-speci fi c empirical relationships, being applicable to extensive areas.

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Simulation of canopy fluorescence as a function of canopy structure and leaf fluorescence

Cited by 10 publications

References 12 publications

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Spectral Response of Citrus and Their Application to Nutrient and Water Constraints Diagnosis

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