Evidence map›Paper›PMID 29905760›Full record

ArticleAnnals of botany2018

Modelling leaf spectral properties in a soybean functional-structural plant model by integrating the prospect radiative transfer model.

Jonas Coussement, Michael Henke, Peter Lootens, Isabel Roldán-Ruiz, Kathy Steppe, Tom De Swaef

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Article in Annals of botany, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jonas CoussementPlant Sciences Unit, Institute of Agricultural, Fisheries and Food Research (ILVO), Melle, Belgium.
Michael HenkeLeibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Stadt Seeland, Germany.
Peter LootensPlant Sciences Unit, Institute of Agricultural, Fisheries and Food Research (ILVO), Melle, Belgium.
Isabel Roldán-RuizPlant Sciences Unit, Institute of Agricultural, Fisheries and Food Research (ILVO), Melle, Belgium.
Kathy SteppeLaboratory of Plant Ecology, Faculty of Bioscience Engineering, Ghent University, Gent, Belgium.
Tom De SwaefPlant Sciences Unit, Institute of Agricultural, Fisheries and Food Research (ILVO), Melle, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Currently, functional-structural plant models (FSPMs) mostly resort to static descriptions of leaf spectral characteristics, which disregard the influence of leaf physiological changes over time. In many crop species, including soybean, these time-dependent physiological changes are of particular importance as leaf chlorophyll content changes with leaf age and vegetative nitrogen is remobilized to the developing fruit during pod filling. Methods: PROSPECT, a model developed to estimate leaf biochemical composition from remote sensing data, is well suited to allow a dynamic approximation of leaf spectral characteristics in terms of leaf composition. In this study, measurements of the chlorophyll content index (CCI) were linked to leaf spectral characteristics within the 400-800 nm range by integrating the PROSPECT model into a soybean FSPM alongside a wavelength-specific light model. Key Results: Straightforward links between the CCI and the parameters of the PROSPECT model allowed us to estimate leaf spectral characteristics with high accuracy using only the CCI as an input. After integration with an FSPM, this allowed digital reconstruction of leaf spectral characteristics on the scale of both individual leaves and the whole canopy. As a result, accurate simulations of light conditions within the canopy were obtained. Conclusions: The proposed approach resulted in a very accurate representation of leaf spectral properties, based on fast and simple measurements of the CCI. Integration of accurate leaf spectral characteristics into a soybean FSPM leads to a better, dynamic understanding of the actual perceived light within the canopy in terms of both light quantity and quality.

Indexed as

Models, BiologicalChlorophyllComputer SimulationGlycine maxLightNitrogenPlant LeavesRemote Sensing TechnologyTime FactorsChlorophyllNitrogen

Identifiers

PMID29905760
PMCPMC6153468

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