This chapter highlights the significance of plant architecture across various plant-related disciplines, with a focus on the AMAP and GreenLab models. It introduces the use of three-dimensional (3D) plant mock-ups for computer graphics in landscaping and urban planning, as well as their utility in remote sensing for assessing plant stand health and productivity. This chapter emphasizes the potential of plant breeding using source–sink dynamics, offering a more stable and functional approach in comparison to traditional measurements techniques. It also discusses the application of functional–structural models in optimizing farming systems to reduce resource waste and pollution, and in improving pruning and thinning techniques through simulation. Additionally, the text points to the relevance of such models in forestry for analysing tree mechanics and wood quality. Heuristic methods using neural networks are also mentioned as a promising tool for estimating environmental impacts on model parameters. Agronomy should make increasing use of these structural–functional models which require the consideration of the plant structure.

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Applications of Plant Architecture Modelling

  • Philippe De Reffye,
  • Marc Jaeger,
  • Mengzhen Kang

摘要

This chapter highlights the significance of plant architecture across various plant-related disciplines, with a focus on the AMAP and GreenLab models. It introduces the use of three-dimensional (3D) plant mock-ups for computer graphics in landscaping and urban planning, as well as their utility in remote sensing for assessing plant stand health and productivity. This chapter emphasizes the potential of plant breeding using source–sink dynamics, offering a more stable and functional approach in comparison to traditional measurements techniques. It also discusses the application of functional–structural models in optimizing farming systems to reduce resource waste and pollution, and in improving pruning and thinning techniques through simulation. Additionally, the text points to the relevance of such models in forestry for analysing tree mechanics and wood quality. Heuristic methods using neural networks are also mentioned as a promising tool for estimating environmental impacts on model parameters. Agronomy should make increasing use of these structural–functional models which require the consideration of the plant structure.