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Updated: Nov 4, 2025

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Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
Published on: June 24, 2019
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Linking remote sensing parameters to CO2 assimilation rates at a leaf scale.
Kouki Hikosaka1, Katsuto Tsujimoto2
1Graduate School of Life Sciences, Tohoku University, Aoba, Sendai, 980-8578, Japan. hikosaka@tohoku.ac.jp.
Journal of Plant Research
|May 21, 2021
Summary
Remote sensing of photosynthesis using solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) shows promise. Combining SIF and PRI can improve estimates of CO2 assimilation, aiding global carbon cycle understanding.
Area of Science:
- Plant Physiology
- Remote Sensing
- Ecology
Background:
- Solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) are key indicators of photosynthetic activity.
- These indices are valuable for assessing ecosystem functions at various spatial scales.
Purpose of the Study:
- To review the relationship between SIF, PRI, and CO2 assimilation rates at the leaf scale.
- To explore the potential of combining SIF and PRI for accurate photosynthesis estimation.
Main Methods:
- Analysis of energy allocation within photosystem II, including photochemistry, fluorescence, and non-photochemical quenching (NPQ).
- Correlation of PRI with xanthophyll cycle pigments involved in heat dissipation.
- Examination of environmental factors influencing the relationship between SIF, PRI, and photochemical efficiency.
Main Results:
- SIF and PRI are linked to photochemical efficiency, but this relationship can be affected by environmental conditions like low temperatures and photoinhibition.
- Simultaneous measurement of SIF and PRI can enhance the accuracy of photosynthesis estimation.
- Stomatal conductance is a critical factor in converting photochemical efficiency to CO2 assimilation rates.
Conclusions:
- SIF and PRI offer valuable insights into photosynthetic activity and can be used for remote sensing applications.
- Accurate estimation of CO2 assimilation requires considering both SIF and PRI, alongside environmental factors like stomatal conductance.
- Developing models that integrate SIF and PRI will advance our understanding and prediction of the global carbon cycle.
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