Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

Porcar‐Castell, Albert; Malenovský, Zbyněk; Magney, Troy S.; Wittenberghe, Shari Van; Fernández‐Marín, Beatriz; Maignan, Fabienne; Zhang, Yongguang; Maseyk, Kadmiel; Atherton, Jon; Albert, Loren P.; Robson, T. Matthew; Zhao, Feng; García-Plazaola, J. I.; Ensminger, Ingo; Rajewicz, Paulina A.; Grebe, Steffen; Tikkanen, Mikko; Kellner, James R.; Ihalainen, Janne A.; Rascher, Uwe; Logan, Barry A.

doi:10.1038/s41477-021-00980-4

Cited by 122 publications

(88 citation statements)

References 127 publications

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“…Accurate quantification of terrestrial photosynthesis at different spatiotemporal scales is a long‐sought goal in carbon cycle science (Schimel, 1995; Beer et al ., 2010; Ciais et al ., 2014). The rapidly growing, cross‐scale observational capability of solar‐induced Chl fluorescence (SIF), the only optically detectable signal that probes the whole photosynthetic process (Porcar‐Castell et al ., 2014), offers a promising opportunity to achieve the goal of quantifying photosynthesis at different spatiotemporal scales (Mohammed et al ., 2019; Porcar‐Castell et al ., 2021). This is evident in the dramatic growth of SIF research and efforts to transform SIF observations to terrestrial photosynthesis estimates over the last few decades (Mohammed et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

The physiological basis for estimating photosynthesis from Chla fluorescence

Han

Chang

et al. 2022

New Phytologist

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Solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis.In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIF PSII ) as an input (MLR-SIF). Utilizing 29 C 3 and C 4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level.The MLR-SIF model is capable of accurately reproducing photosynthesis for all C 3 and C 4 species under diverse light, temperature, and CO 2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIF PSII .Once inferred from direct observables of SIF, SIF PSII provides 'parameter savings' to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.

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Section: Introductionmentioning

confidence: 99%

The physiological basis for estimating photosynthesis from Chla fluorescence

Han

Chang

et al. 2022

New Phytologist

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“…Multiple models have been developed to simulate fluorescence yield at the photosystem‐level (Bennett et al., 2018; Johnson & Berry, 2021; Lee et al., 2013; Porcar‐Castell, 2011; van der Tol et al., 2014; Zaks et al., 2012). Most models focus on photosystem II or do not distinguish fluorescence emission from the two photosystems due to the lack of available data (Porcar‐Castell et al., 2021; van der Tol et al., 2014). However, the distribution of fluorescence emission from the two photosystems is one of the challenges for interpreting and accurate simulating fluorescence emission (Porcar‐Castell et al., 2021).…”

Section: Discussionmentioning

confidence: 99%

Representation of Leaf‐to‐Canopy Radiative Transfer Processes Improves Simulation of Far‐Red Solar‐Induced Chlorophyll Fluorescence in the Community Land Model Version 5

Lombardozzi

Shi

et al. 2022

J Adv Model Earth Syst

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“…Chlorophyll is positively related with the plant photosynthetic rate and productivity and provides important information about the physiological level of plants [198]. Chloro-phyll is analyzed using extract-based and digestion or combustion methods, or a fusion of two [199].…”

Section: Chlorophyllmentioning

confidence: 99%

Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring

et al. 2022

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Digital farming approach merges new technologies and sensor data to optimize the quality of crop monitoring in agriculture. The successful fusion of technology and data is highly dependent on the parameter collection, the modeling adoption, and the technology integration being accurately implemented according to the specified needs of the farm. This fusion technique has not yet been widely adopted due to several challenges; however, our study here reviews current methods and applications for fusing technologies and data. First, the study highlights different sensors that can be merged with other systems to develop fusion methods, such as optical, thermal infrared, multispectral, hyperspectral, light detection and ranging and radar. Second, the data fusion using the internet of things is reviewed. Third, the study shows different platforms that can be used as a source for the fusion of technologies, such as ground-based (tractors and robots), space-borne (satellites) and aerial (unmanned aerial vehicles) monitoring platforms. Finally, the study presents data fusion methods for site-specific crop parameter monitoring, such as nitrogen, chlorophyll, leaf area index, and aboveground biomass, and shows how the fusion of technologies and data can improve the monitoring of these parameters. The study further reveals limitations of the previous technologies and provides recommendations on how to improve their fusion with the best available sensors. The study reveals that among different data fusion methods, sensors and technologies, the airborne and terrestrial LiDAR fusion method for crop, canopy, and ground may be considered as a futuristic easy-to-use and low-cost solution to enhance the site-specific monitoring of crop parameters.

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Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

Cited by 122 publications

References 127 publications

The physiological basis for estimating photosynthesis from Chla fluorescence

The physiological basis for estimating photosynthesis from Chla fluorescence

Representation of Leaf‐to‐Canopy Radiative Transfer Processes Improves Simulation of Far‐Red Solar‐Induced Chlorophyll Fluorescence in the Community Land Model Version 5

Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring

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