Journal of Agricultural Big Data ›› 2021, Vol. 3 ›› Issue (3): 3-12.doi: 10.19788/j.issn.2096-6369.210301

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Over Two Decades of Research with Greenlab Model

Mengzhen Kang(), Xiujuan Wang(), Jing Hua   

  1. 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
    3.Beijing Engineering Research Center of Intelligent Systems and Technologies, Beijing 100190, China
    4.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    5.UMR AMAP, International Cooperative Research and Development of Agriculture (CIRAD), Montpellier F-34398, France
  • Received:2021-07-20 Online:2021-09-26 Published:2021-12-22
  • Contact: Xiujuan Wang E-mail:mengzhen.kang@ia.ac.cn;xiujuan.wang@ia.ac.cn

Abstract:

The GreenLab model is an organ-level Functional-Structural Plant Model (FSPM), which simulates plant growth and development processes with the discrete dynamic system, including biomass production, partitioning, and structure formation. It is a generic FSPM that integrates multi-disciplinary knowledge from botany, mathematics, agronomy, computer science, and automation science. Sino-French cooperation around GreenLab since 1998 has led to the development of new methods, algorithms, and software. These include a dual-scale automaton, parameter inversion for plants with branching structure, stochastic FSPM with theoretical computation, plant fast modelling and visualization, a plant growth modelling and fitting tool in Scilab and Matlab, and a simulator for complex structure in c++. The GreenLab model has been applied on dozens of plants with their own features, including maize, wheat, cucumber, tomato, rapeseed, pine tree, and maple tree, covering plants ranging from herbaceous crops to complex trees. The model is characterized by the fact that its source-sink parameters affecting the biomass production and partitioning can be inversely estimated through the measured organ biomass and quantity. It is applicable for single stem or branching structures, deterministic or stochastic cases, with common organ-level target data for parameter identification and model calibration. This paper reviews the development history and recent advances of the GreenLab model and presents the basic concepts and key methods. These include dual-scale automaton, organ series, the generic plant fitting. It gives some details on the structural model (the computation on organ quantities and the stochastic simulation on organ production) and the functional model (demand of organ and plant, biomass production and allocation, and organ growth). With the availability of plant phenotype technologies, GreenLab can be used for building parallel agricultural system, supporting the deep understanding of the plant-environment interaction, and the intelligent decision support for management and control of production management.

Key words: GreenLab, Functional-Structural Model, discrete dynamic model, parameter calibration, agriculture parallel system

CLC Number: 

  • TU205