FSPM-P: towards a general functional-structural plant model for robust and comprehensive model development

Abstract

In the last decade, functional-structural plant modelling (FSPM) has become a more widely accepted paradigm in crop and tree production, as 3D models for the most important crops have been proposed. Given the wider portfolio of available models, it is now appropriate to enter the next level in FSPM development, by introducing more efficient methods for model development. This includes the consideration of model reuse (by modularisation), combination and comparison, and the enhancement of existing models. To facilitate this process, standards for design and communication need to be defined and established. We present a first step towards an efficient and general, i.e., not speciesspecific FSPM, presently restricted to annual or bi-annual plants, but with the potential for extension and further generalization.

Model structure is hierarchical and object-oriented, with plant organs being the base-level objects and plant individual and canopy the higher-level objects. Modules for the majority of physiological processes are incorporated, more than in other platforms that have a similar aim (e.g., photosynthesis, organ formation and growth). Simulation runs with several general parameter sets adopted from the literature show that the present prototypewas able to reproduce a plausible output range for different crops (rapeseed, barley, etc.) in terms of both the dynamics and final values (at harvest time) of model state variables such as assimilate production, organ biomass, leaf area and architecture.

Keywords

functional-structural plant model / prototyping / modelling standards / teaching / learning FSPM / GroIMP

References

[1] Goudriaan J, Van Laar H H. Modelling Potential Crop Growth Processes: Textbook with Exercises. Dordrecht: Kluwer Academic Publishers, 1994

[2] Lopez G, Favreau R P, Smith C, Costes E, Prusinkiewicz P, DeJong T M. Integrating simulation of architectural development and source-sink behaviour of peach trees by incorporating Markov chains and physiological organ function submodels into L-PEACH. Functional Plant Biology, 2008, 35(10): 761–771

[3] Allen M T, Prusinkiewicz P, DeJong T M. Using L-systems for modeling source-sink interactions, architecture and physiology of growing trees: the L-PEACH model. New Phytologist, 2005, 166(3): 869–880

[4] Xu L F, Henke M, Zhu J, Kurth W, Buck-Sorlin G H. A rule-based functional-structural model of rice considering source and sink functions. In: Proceedings of the 3rd International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications. 2009, 245–252

[5] Buck-Sorlin G H, de Visser P H B, Sarlikioti V, Burema B S, Heuvelink E, Marcelis L F M, van der Heijden G W A M, Vos J. SIMPLER: an FSPM coupling shoot production, human interaction with the structure, morphogenesis, photosynthesis and light environment in cut-Rose. In: Proceedings of the 6th International Workshop on Functional-Structural Plant Models. 2010, 222–224

[6] Groer C, Kniemeyer O, Hemmerling R, Kurth W, Becker H, Buck-Sorlin G H. A dynamic 3D model of rape (Brassica napus L.) computing yield components under variable nitrogen fertilization regimes. In: Proceedings of the 5th International Workshop on Functional- Structural Plant Models. 2007

[7] Buck-Sorlin G H, Kniemeyer O, Kurth W. Barley morphology, genetics and hormonal regulation of internode elongation modelled by a relational growth grammar. New Phytologist, 2005, 166(3): 859–867

[8] Buck-Sorlin G H, Kniemeyer O, Kurth W. A grammar-based model of barley including genetic control and metabolic networks. In: Vos J et al., eds. Functional-Structural Plant Modelling in Crop Production. Dordrecht: Springer, 2007, 243–252

[9] Buck-Sorlin G H, Hemmerling R, Kniemeyer O, Burema B, Kurth W. A rule-based model of barley morphogenesis, with special respect to shading and gibberellic acid signal transduction. Annals of Botany, 2008, 101(8): 1109–1123

[10] Barczi J F, Rey H, Caraglio Y, Reffye d P, Barthélémy D, Dong Q X, Fourcaud T. AmapSim: a structural whole-plant simulator based on botanical knowledge and designed to host external functional models. Annals of Botany, 2008, 101(8): 1125–1138

[11] Hu B G, Reffye P D, Zhao X, Yan H P, Kang M Z. GreenLab: a new methodology towards plant functional-structural model — structural aspect. In: Hu B, Jaeger M, eds. Plant Growth Modeling and Applications. Beijing: TsingHuo University Press and Springer, 2003, 21–35

[12] Letort V. Analyse multi-échelle des relations source-puits dans les modèles de développement et croissance des plantes pour l’identification paramétrique. Cas du modèle GreenLab. Dissertation for the Doctoral Degree. Châtenay-Malabry: École Centrale Paris, 2008

[13] Breckling B. An individual based model for the study of pattern and process in plant ecology: an application of object oriented programming. EcoSys, 1996, 4: 241–254

[14] Perttunen J, Sievänen R, Nikinmaa E, Salminen H, Saarenmaa H, Väkevä J. LIGNUM: A tree model based on simple structural units. Annals of Botany, 1996, 77(1): 87–98

[15] Kniemeyer O. Design and implementation of a graph grammar based language for functional-structural plant modelling. Dissertation for the Doctoral Degree. Cottbus: Brandenburg University of Technology, 2008

[16] Kurth W. Morphological models of plant growth. Possibilities and ecological relevance. Ecological Modelling, 1994, 75: 299–308

[17] Prusinkiewicz P, Lindenmayer A. The Algorithmic Beauty of Plants. New York: Springer Science & Business Media, 2012

[18] Hemmerling R. Extending the programming language XL to combine graph structures with ordinary differential equations. Dissertation for the Doctoral Degree. Göttingen: University of Göttingen, 2012

[19] Hemmerling R, Kniemeyer O, Lanwert D, Kurth W, Buck-Sorlin G H. The rule-based language XL and the modelling environment GroIMP illustrated with simulated tree competition. Functional Plant Biology, 2008, 35(9/10): 739–750

[20] Van Antwerpen D G. Unbiased physically based rendering on the GPU. Dissertation for the Master Degree. Delft: Delft University of Technology, 2011

[21] Veach E. Robust Monte Carlo Methods for Light Transport Simulation. Dissertation for the Doctoral Degree. Palo Alto: Stanford University, 1998

[22] Buck-Sorlin G H, Hemmerling R, Vos J, de Visser P H. Modelling of spatial light distribution in the greenhouse: Description of the model. In: Proceedings of the 3rd International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications. 2009, 79–86

[23] Evers J B, Vos J, Yin X, Romero P, Van Der Putten P E L, Struik P C. Simulation of wheat growth and development based on organlevel photosynthesis and assimilate allocation. Journal of Experimental Botany, 2010, 61(8): 2203–2216

[24] Preetham A J, Shirley P, Smits B. A practical analytic model for daylight. In: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. 1999, 91–100

[25] Gijzen H. Development of a simulation model for transpiration and water uptake and an integral growth model. AB-DLO Report 18. 1994

[26] Nikolov N T, Massman W J, Schoettle A W. Coupling biochemical and biophysical processes at the leaf level: an equilibrium photosynthesis model for leaves of C3 plants. Ecological Modelling, 1995, 80: 205–235

[27] Müller J, Wernecke P, Diepenbrock W. LEAFC3-N: a nitrogensensitive extension of the CO2 and H2O gas exchange model LEAFC3 parameterised and tested for winter wheat (Triticum aestivum L.). Ecological Modelling, 2005, 183: 183–210

[28] Müller J, Braune H, Diepenbrock W. Photosynthesis-stomatal conductance model LEAFC3-N: specification for barley, generalised nitrogen relations, and aspects of model application. Functional Plant Biology, 2008, 35: 797–810

[29] Baldocchi D. An analytical solution for coupled leaf photosynthesis and stomatal conductance models. Tree Physiology, 1994, 14: 1069–1079

[30] Kim S H, Lieth J H. A coupled model of photosynthesis, stomatal conductance and transpiration for a rose leaf (Rosa hybrida L.). Annals of Botany, 2003, 91(7): 771–781

[31] Lieth J H, Pasian C C. A simulation model for the growth and development of flowering rose shoots. Scientia Horticulturae, 1991, 46: 109–128

[32] Thornley J H M. A model to describe the partitioning of photosynthate during vegetative plant growth. Annals of Botany, 1969, 33: 419–430

[33] Thornley J H M. Dynamic model of leaf photosynthesis with acclimation to light and nitrogen. Annals of Botany, 1998, 81(3): 421–430

[34] Johnson I R, Thornley J H M. Dynamic model of the response of a vegetative grass crop to light, temperature and nitrogen. Plant, Cell and Environment, 1985, 8(7): 485–499

[35] Marshall B, Biscoe P V. A model for C3 leaves describing the dependence of net photosynthesis on irradiance I. Derivation. Journal of Experimental Botany, 1980, 31(1): 29–39

[36] Marshall B, Biscoe P V. A model for C3 leaves describing the dependence of net photosynthesis on irradiance II. Application to the analysis of flag leaf photosynthesis. Journal of Experimental Botany, 1980, 31(1): 41–48

[37] Rauscher H M, Isebrands J G, Host G E, Dickson R E, Dickmann D I, Crow T R, Michael D A. ECOPHYS: an ecophysiological growth process model for juvenile poplar. Tree Physiology, 1990, 7: 255–281

[38] Yin X Y, Goudriaan J, Lantinga E A, Vos J, Spiertz H J. A flexible sigmoid function of determinate growth. Annals of Botany, 2003, 91(3): 361–371

[39] Richards F J. A flexible growth function for empirical use. Journal of Experimental Botany, 1959, 29(10): 290–300

[40] Thornley J H M. Growth, maintenance and respiration: a reinterpretation. Annals of Botany, 1977, 41(6): 1191–1203

[41] Bertin N, Gary C. Évaluation d’un modèle dynamique de croissance et de développement de la tomate (Lycopersicon esculentum Mill), TOMGRO, pour différents niveaux d’offre et de demande en assimilats. Agronomie, 1993, 13: 395–405

[42] Marcelis L F M. A simulation model for dry matter partitioning in cucumber. Annals of Botany, 1994, 74(1): 43–52

[43] Marcelis L F M. Sink strength as a determinant of dry matter partitioning in the whole plant. Journal of Experimental Botany, 1996, 47: 1281–1291

[44] Qi R, Ma Y T, Hu B G, de Reffye P, Cournède P H. Optimization of source-sink dynamics in plant growth for ideotype breeding: a case study on maize. Computers and Electronics in Agriculture, 2010, 71(1): 96–105

[45] Pradal C, Dufour-Kowalski S, Boudon F, Fournier C, Godin C. Open-Alea: a visual programming and component-based software platform for plant modelling. Functional Plant Biology, 2008, 35(10): 751–760

[46] Vos J, Evers J B, Buck-Sorlin G H, Andrieu B, Chelle M, de Visser P H B. Functional-structural plant modelling: a new versatile tool in crop science. Journal of Experimental Botany, 2010, 61(8): 2101–2115

[47] Wilson G V. Where’s the real bottleneck in scientific computing? American Scientist, 2006, 94(1): 5–6

[48] McMaster G S, Hargreaves J N G. CANON in D(esign): composing scales of plant canopies from phytomers to whole-plants using the composite design pattern. NJAS- Wageningen Journal of Life Sciences, 2009, 57(1): 39–51

[49] Bouman B A M, Keulen v H, Laar v H H, Rabbinge R. The ‘school of de Wit’ crop growth simulation models: A pedigree and historical overview. Agricultural Systems, 1996, 52(2): 171–198

[50] Spitters C J T. Crop growth models: their usefulness and limitations. ISHS Acta Horticulturae 267: VI Symposium on the Timing of Field Production of Vegetables. 1990, 349–368

[51] Van Keulen H, Penning de Vries F W T, Drees E M. A summary model for crop growth. In: Penning de Vries F W T, van Laar H H, eds. Simulation of plant growth and crop production, Wageningen: Centre for Aqricultural Publishing and Documentation, 1982

[52] Lithourgidis A S, Dordas C A, Damalas C A, Vlachostergios D N. Annual intercrops: an alternative pathway for sustainable agriculture. Australian Journal of Crop Science, 2011, 5(4): 396–410

[53] Ouma G P J. Sustainable horticultural crop production through intercropping: the case of fruits and vegetable crops: a review. Agriculture and Biology Journal of North America, 2010, 1(5): 1098–1105

[54] Henke M, Sarlikioti V, Kurth W, Buck-Sorlin G H, Pagès L. Exploring root developmental plasticity to nitrogen with a three-dimensional architectural model. Plant and Soil, 2014, 385(1): 49–62

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg