From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques
User-friendly handheld plant phenotyping devices, such as the MultispeQ, provide quick and easy measurements that effectively capture the dynamic nature of photosynthesis. This study demonstrates the added value of integrating measurements of such devices with both process-based and empirical modeli...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525000413 |
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| _version_ | 1832087335158677504 |
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| author | Georgios Ntakos Egor Prikaziuk Nastassia Vilfan Tamme van der Wal Christiaan van der Tol |
| author_facet | Georgios Ntakos Egor Prikaziuk Nastassia Vilfan Tamme van der Wal Christiaan van der Tol |
| author_sort | Georgios Ntakos |
| collection | DOAJ |
| description | User-friendly handheld plant phenotyping devices, such as the MultispeQ, provide quick and easy measurements that effectively capture the dynamic nature of photosynthesis. This study demonstrates the added value of integrating measurements of such devices with both process-based and empirical modeling approaches for estimating the maximum leaf photosynthetic capacity (Amax) and biomass production (DMP) of potato crops. Utilizing leaf fluorescence measurements, such as the efficiency of photosystem II (ϕ2) and the electron transport rate, gathered from two fields in the Netherlands from May to September 2019, we determined the Amax to be 34 kg CO2 ha−1hr−1 with a standard deviation of 6.6 kg CO2 ha−1hr−1. By incorporating dynamic photosynthetic parameters, leaf area index (LAI) retrieval, and crop modeling techniques to scale assimilation from the leaf to the canopy level, we successfully reduced the discrepancy between simulated and measured dry matter production in 16 out of 18 cases, offering significant advantages over fixed, literature-based photosynthetic parameter values. |
| format | Article |
| id | doaj-art-3aab20a78bc241a7abea2897f5a0df10 |
| institution | Kabale University |
| issn | 2772-3755 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-3aab20a78bc241a7abea2897f5a0df102025-02-06T05:13:02ZengElsevierSmart Agricultural Technology2772-37552025-03-0110100807From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniquesGeorgios Ntakos0Egor Prikaziuk1Nastassia Vilfan2Tamme van der Wal3Christiaan van der Tol4Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE, Enschede, the Netherlands; Business Unit Greenhouse Horticulture, Wageningen University & Research, P.O. Box 644, 6700 AP, Wageningen, the Netherlands; Corresponding author at: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE, Enschede, the Netherlands.Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE, Enschede, the NetherlandsPlant Production Systems, Department of Plant Sciences, Wageningen University & Research, P.O. Box 430, 6700 AK, Wageningen, the NetherlandsAgrosystems Research, Wageningen University & Research, P.O. Box 430, 6700 AA, Wageningen, the Netherlands; AeroVision B.V., 3811 HN, Amersfoort, the NetherlandsFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE, Enschede, the NetherlandsUser-friendly handheld plant phenotyping devices, such as the MultispeQ, provide quick and easy measurements that effectively capture the dynamic nature of photosynthesis. This study demonstrates the added value of integrating measurements of such devices with both process-based and empirical modeling approaches for estimating the maximum leaf photosynthetic capacity (Amax) and biomass production (DMP) of potato crops. Utilizing leaf fluorescence measurements, such as the efficiency of photosystem II (ϕ2) and the electron transport rate, gathered from two fields in the Netherlands from May to September 2019, we determined the Amax to be 34 kg CO2 ha−1hr−1 with a standard deviation of 6.6 kg CO2 ha−1hr−1. By incorporating dynamic photosynthetic parameters, leaf area index (LAI) retrieval, and crop modeling techniques to scale assimilation from the leaf to the canopy level, we successfully reduced the discrepancy between simulated and measured dry matter production in 16 out of 18 cases, offering significant advantages over fixed, literature-based photosynthetic parameter values.http://www.sciencedirect.com/science/article/pii/S2772375525000413MultispeQFluorescencePhotosynthesisBiomassRemote sensingCrop growth modeling |
| spellingShingle | Georgios Ntakos Egor Prikaziuk Nastassia Vilfan Tamme van der Wal Christiaan van der Tol From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques Smart Agricultural Technology MultispeQ Fluorescence Photosynthesis Biomass Remote sensing Crop growth modeling |
| title | From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques |
| title_full | From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques |
| title_fullStr | From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques |
| title_full_unstemmed | From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques |
| title_short | From fluorescence to biomass: A comprehensive analysis via crop modeling and sensing techniques |
| title_sort | from fluorescence to biomass a comprehensive analysis via crop modeling and sensing techniques |
| topic | MultispeQ Fluorescence Photosynthesis Biomass Remote sensing Crop growth modeling |
| url | http://www.sciencedirect.com/science/article/pii/S2772375525000413 |
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