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Background and Aims: Scaling from single-leaf to whole-canopy photosynthesis faces several complexities related to variations in light interception and leaf properties. To evaluate the impact of canopy strucuture on gas exchange, we developed a functional–structural plant model to upscale leaf processes to the whole canopy based on leaf N content. The model integrates different models that calculate intercepted radiation, leaf traits and gas exchange for [ver mas...]
dc.contributor.authorPrieto, Jorge Alejandro
dc.contributor.authorLouarn, Gaëtan
dc.contributor.authorPerez Peña, Jorge Esteban
dc.contributor.authorOjeda, Hernan
dc.contributor.authorSimonneau, Thierry
dc.contributor.authorLebon, Eric
dc.date.accessioned2020-11-09T14:48:18Z
dc.date.available2020-11-09T14:48:18Z
dc.date.issued2020-09
dc.identifier.issn0305-7364
dc.identifier.issn1095-8290
dc.identifier.otherhttps://doi.org/10.1093/aob/mcz203
dc.identifier.urihttp://hdl.handle.net/20.500.12123/8216
dc.identifier.urihttps://academic.oup.com/aob/article/126/4/647/5677523
dc.description.abstractBackground and Aims: Scaling from single-leaf to whole-canopy photosynthesis faces several complexities related to variations in light interception and leaf properties. To evaluate the impact of canopy strucuture on gas exchange, we developed a functional–structural plant model to upscale leaf processes to the whole canopy based on leaf N content. The model integrates different models that calculate intercepted radiation, leaf traits and gas exchange for each leaf in the canopy. Our main objectives were (1) to introduce the gas exchange model developed at the plant level by integrating the leaf-level responses related to canopy structure, (2) to test the model against an independent canopy gas exchange dataset recorded on different plant architectures, and (3) to quantify the impact of intra-canopy N distribution on crop photosynthesis. Methods: The model combined a 3D reconstruction of grapevine (Vitis vinifera) canopy architecture, a light interception model, and a coupled photosynthesis and stomatal conductance model that considers light-driven variations in N distribution. A portable chamber device was constructed to measure whole-plant gas exchange to validate the model outputs with data collected on different training systems. Finally, a sensitivity analysis was performed to evaluate the impact on C assimilation of different N content distributions within the canopy. Key Results: By considering a non-uniform leaf N distribution within the canopy, our model accurately reproduced the daily pattern of gas exchange of different canopy architectures. The gain in photosynthesis permitted by the non-uniform compared with a theoretical uniform N distribution was about 18 %, thereby contributing to the maximization of C assimilation. By contrast, considering a maximal N content for all leaves in the canopy overestimated net CO2 exchange by 28 % when compared with the non-uniform distribution. Conclusions: The model reproduced the gas exchange of plants under different training systems with a low error (10 %). It appears to be a reliable tool to evaluate the impact of a grapevine training system on water use efficiency at the plant level.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherOxford University Presses_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.sourceAnnals of Botany 126 (4) : 647–660. (September 2020)es_AR
dc.subjectVitis viniferaes_AR
dc.subjectVides_AR
dc.subjectGrapevineseng
dc.subjectNitrógenoes_AR
dc.subjectNitrogeneng
dc.subjectIntercambio de Gaseses_AR
dc.subjectGas Exchangeeng
dc.subjectFotosíntesises_AR
dc.subjectPhotosynthesiseng
dc.subject.otherCanopeoes_AR
dc.subject.otherCanopyeng
dc.titleA functional–structural plant model that simulates whole- canopy gas exchange of grapevine plants (Vitis vinifera L.) under different training systemses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenEEA Mendozaes_AR
dc.description.filFil: Prieto, Jorge Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina.es_AR
dc.description.filFil: Louarn, Gaëtan. Institut National de la Recherche Agronomique; Franciaes_AR
dc.description.filFil: Perez Peña, Jorge Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentinaes_AR
dc.description.filFil: Ojeda, Hernan. Institut National de la Recherche Agronomique. Unité expérimentale de Pech Rouge; Franciaes_AR
dc.description.filFil: Simonneau, Thierry. Institut National de la Recherche Agronomique. LEPSE Montpellier; Franciaes_AR
dc.description.filFil: Lebon, Eric. Institut National de la Recherche Agronomique. Unité Mixte de Recherche; Franciaes_AR
dc.subtypecientifico


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