Perez Raphaël, Vezy Rémi, Brancheriau Loïc, Boudon Frédéric, Grand François, Ramel Merlin, Raharjo Doni Artanto, Caliman Jean-Pierre, Dauzat Jean. 2022. When architectural plasticity fails to counter the light competition imposed by planting design: An in silico approach using a functional–structural model of oil palm. In Silico Plants, 4 (1), n.spéc. : Functional–Structural Plant Models:diac009, 16 p.
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Résumé : Functional–structural plant modelling approaches (FSPM) explore the relationships between the 3D structure and the physiological functioning of plants in relation to environmental conditions. In this study, we present a methodological approach that integrated architectural responses to planting design in an oil palm FSPM, and test the impact of planting design and architectural plasticity on physiological responses such as light interception and carbon assimilation. LiDAR-derived and direct measurements were performed on five planting designs to assess the phenotypic plasticity of architectural traits, and allowed evaluating the variations of the main parameters of an existing 3D plant model. Accordingly, we proposed a neighbourhood index (NI) as a simple explanatory variable of architectural plasticity, and used NI-based allometries to simulate architectural variations in 3D virtual plants. Light interception and carbon assimilation were then simulated on virtual plots reproducing the five studied designs. We found that the main traits affected by plant proximity were leaf dimensions, leaf weight and leaf erectness, whereas other structural traits like the frequency of leaflets along the rachis or biomechanical properties of leaves remained unchanged. Our simulation study highlighted model compliance to reproduce architectural plasticity and illustrated how architectural plasticity improved light interception via leaf area expansion, but how the competition for light imposed by the design can counterbalance this benefit in terms of carbon assimilation at stand scale. We conclude on the importance of planting patterns for plants with low architectural plasticity such as oil palm, and how in silico experiments can help in designing innovative planting patterns.
Mots-clés Agrovoc : physiologie végétale, modélisation, morphologie végétale, anatomie végétale, plasticité phénotypique, Elaeis guineensis
Mots-clés libres : Elaeis guineensis, FSPM, LiDAR, Phenotypic plasticity, Plant architecture, Planting design
Classification Agris : F50 - Anatomie et morphologie des plantes
F40 - Écologie végétale
U10 - Informatique, mathématiques et statistiques
Champ stratégique Cirad : CTS 2 (2019-) - Transitions agroécologiques
Auteurs et affiliations
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Perez Raphaël, CIRAD-BIOS-UMR AGAP (FRA)
ORCID: 0000-0001-5270-9212 - auteur correspondant
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Vezy Rémi, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-0808-1461
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Brancheriau Loïc, CIRAD-PERSYST-UPR BioWooEB (FRA) ORCID: 0000-0002-9580-7696
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Boudon Frédéric, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0001-9636-3102
- Grand François, Université de Montpellier (FRA)
- Ramel Merlin, INRAE (FRA)
- Raharjo Doni Artanto, SMARTRI (IDN)
- Caliman Jean-Pierre, SMART Research Institute (IDN)
- Dauzat Jean, CIRAD-BIOS-UMR AMAP (FRA)
Source : Cirad-Agritrop (https://agritrop.cirad.fr/602238/)
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