Solar Induced Fluorescence Retrieved from Avocado (Persea americana Mill.) Canopies Along the Season Correlates with Sugar Levels in the Developing Fruit
Solar Induced Fluorescence (SIF) emitted from the photosynthetic apparatus is related indirectly to biomass production. In this study, a non-imager point spectroradiometer was mounted on a UAV (Unmanned Aerial Vehicle) system (SIF-UAV), and retrieved SIF at high spatial resolution, which is fitted f...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2025.2449940 |
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| Summary: | Solar Induced Fluorescence (SIF) emitted from the photosynthetic apparatus is related indirectly to biomass production. In this study, a non-imager point spectroradiometer was mounted on a UAV (Unmanned Aerial Vehicle) system (SIF-UAV), and retrieved SIF at high spatial resolution, which is fitted for precision agriculture applications. Spatial variation of SIF was tracked along the season over a commercial avocado (P. americana Mill.) orchard. The retrieved SIF signals were Krieg-interpolated to create a continuous SIF layer that allowed for its estimation for each tree within the studied area. In parallel, sugar content and derivatives were analysed by a metabolomics approach in order to track the accumulation of these sugars in the developing fruit. It was found that SIF687 correlates with perseitol at R2 = 0.87 and SIF760 correlates with fructose at R2 = 0.97, two sugars accumulating in the pericarp of the ripening fruits. This study thus advances one step further in reporting not only on photosynthetic activity sensed remotely but also on the actual relationship between photosynthesis products accumulated in the fruit. This study elaborates on the use of the SIF index as an indicator of natural variation of photosynthetic activity, which may lead to in-season adjustments of agronomic inputs using precision agriculture technologies. |
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| ISSN: | 2279-7254 |