ReviewAnnals of botany2021
Two decades of research with the GreenLab model in agronomy.
Review in Annals of botany, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Source-sink manipulations through shading, crop load and water deficit affect plant morphogenesis and carbon sink priorities leading to contrasted plant carbon status in grapevine.Annals of botany · 2025Article
- Practical Identifiability of Plant Growth Models: A Unifying Framework and Its Specification for Three Local Indices.Plant phenomics (Washington, D.C.) · 2024Article
- Functional-Structural Plant Model "GreenLab": A State-of-the-Art Review.Plant phenomics (Washington, D.C.) · 2024Article
- Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.Plant phenomics (Washington, D.C.) · 2023Review
- Predicting tomato water consumption in a hydroponic greenhouse: contribution of light interception models.Frontiers in plant science · 2023Article
- Combinatorial Maps, a New Framework to Model Agroforestry Systems.Plant phenomics (Washington, D.C.) · 2023Article
- Stronger wind, smaller tree: Testing tree growth plasticity through a modeling approach.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
- Article
- Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects.Frontiers in plant science · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith up to 200 published contributions, the GreenLab mathematical model of plant growth, developed since 2000 under Sino-French co-operation for agronomic applications, is descended from the structural models developed in the AMAP unit that characterize the development of plants and encompass them in a conceptual mathematical framework. The model also incorporates widely recognized crop model concepts (thermal time, light use efficiency and light interception), adapting them to the level of the individual plant. SCOPE: Such long-term research work calls for an overview at some point. That is the objective of this review paper, which retraces the main history of the model's development and its current status, highlighting three aspects. (1) What are the key features of the GreenLab model? (2) How can the model be a guide for defining relevant measurement strategies and experimental protocols? (3) What kind of applications can such a model address? This last question is answered using case studies as illustrations, and through the Discussion.
conclusionsThe results obtained over several decades illustrate a key feature of the GreenLab model: owing to its concise mathematical formulation based on the factorization of plant structure, it comes along with dedicated methods and experimental protocols for its parameter estimation, in the deterministic or stochastic cases, at single-plant or population levels. Besides providing a reliable statistical framework, this intense and long-term research effort has provided new insights into the internal trophic regulations of many plant species and new guidelines for genetic improvement or optimization of crop systems.
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Registered trials
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.