ArticleFrontiers in plant science2012
L-py: an L-system simulation framework for modeling plant architecture development based on a dynamic language.
Article in Frontiers in plant science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Grass inflorescence morphodynamics guides yield improvement in wheat.Nature plants · 2026Article
- Root growth and branching are enabled by brassinosteroid-regulated growth anisotropy and carbon allocation.Nature communications · 2025Article
- Riemannian L-systems: modelling growing forms in curved spaces.Quantitative plant biology · 2025Review
- Biophysical modelling as a tool for advancing plant science and engineering.Frontiers in plant science · 2025Review
- The pipelines of deep learning-based plant image processing.Quantitative plant biology · 2025Review
- Predicting resprouting of Platanus × hispanica following branch pruning by means of machine learning.Frontiers in plant science · 2024Article
- Modeling the effects of strigolactone levels on maize root system architecture.Frontiers in plant science · 2023Article
- Segmentation of structural parts of rosebush plants with 3D point-based deep learning methods.Plant methods · 2022Article
- A graph-based approach for simultaneous semantic and instance segmentation of plant 3D point clouds.Frontiers in plant science · 2022Article
- Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities.Annals of botany · 2021Article
- What shoots can teach about theories of plant form.Nature plants · 2021Review
- Two decades of research with the GreenLab model in agronomy.Annals of botany · 2021Review
- Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology.Annals of botany · 2020Review
- V-Mango: a functional-structural model of mango tree growth, development and fruit production.Annals of botany · 2020Article
- Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics.Journal of the Royal Society, Interface · 2019Article
- WALTer: a three-dimensional wheat model to study competition for light through the prediction of tillering dynamics.Annals of botany · 2019Article
- Helios: A Scalable 3D Plant and Environmental Biophysical Modeling Framework.Frontiers in plant science · 2019Article
- A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes.Annals of botany · 2018Article
- The use of plant models in deep learning: an application to leaf counting in rosette plants.Plant methods · 2018Article
- A Statistical Description of Plant Shoot Architecture.Current biology : CB · 2017Article
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5 authors.
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Abstract
The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.