Parameter optimization and field validation of the functional-structural model GREENLAB for maize

Annals of Botany

Volumn 97, Issue 2, 2006, Pages 217-230

  Guo, Yan ^a   Ma, Yuntao ^a   Zhan, Zhigang ^a   Li, Baoguo ^a   Dingkuhn, Michael ^b   Luquet, Delphine ^b   De Reffye, Philippe ^b,c  

^a CHINA AGRICULTURAL UNIVERSITY   (China)

^b CIRAD   (France)

^c INRIA ROCQUENCOURT   (France)

Author keywords

Competition among sinks; Functional structural models; Model parameterization; Plant architecture; Source sink relationships; Zea mays

Indexed keywords

MAIZE;

AGRICULTURE; ARTICLE; BIOLOGICAL MODEL; FORECASTING; GENETICS; GROWTH, DEVELOPMENT AND AGING; HISTOLOGY; MAIZE; METHODOLOGY; PHENOTYPE; SEASON; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

AGRICULTURE; FORECASTING; IMAGING, THREE-DIMENSIONAL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PHENOTYPE; SEASONS; ZEA MAYS;

ZEA MAYS;

EID: 31744441850     PISSN: 03057364     EISSN: 10958290     Source Type: Journal    
DOI: 10.1093/aob/mcj033     Document Type: Article

References (36)

1. Allen RG, Pereira LS, Raes D, Smith M. 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56. Rome: FAO, 299.
2. Andrade FH, Vega C, Uhart S, Cirilo A, Cantarero M, Valentinuz O. 1999. Kernel number determination in maize. Crop Science 39: 453-459.
3. Borrás L, Otegui ME. 2001. Maize kernel weight response to postflowering source-sink ratio. Crop Science 49: 1816-1822.
4. Brisson N, Ruget F, Gate P, Lorgeau J, Nicoullaud B, Tayot X, et al. 2002. STICS: a generic model for simulating crops and their water and nitrogen balances. 2. Model validation for wheat and maize. Agronomie 22: 69-92.
5. Cantarero MG, Cirilo AG, Andrade FH. 1999. Night temperature at silking affects kernel set in maize. Crop Science 39: 703-710.
6. Chelle M, Andrieu B. 1998. The nested radiosity model for the distribution of light within plant canopies. Ecological Modelling 111: 75-91.
7. Clerget B, Dingkuhn M, Chantereau J, Hemberger J, Louarn G, Vaksmann M. 2004. Does panicle initiation in tropical sorghum depend on day-to-day change in photoperiod? Field Crops Research 88: 11-27.
8. Dauzat J. 1994. Radiative transfer simulation on computer models of Elaeis guineensis. Oléagineux 49: 8-90.
9. Dauzat J, Eroy MN. 1997. Simulation light regime and intercrop yields in coconut based farming systems. European Journal of Agronomy 7: 63-74.
10. Dingkuhn M, Luquet D, Quilot B, de Reffye P. 2005a. Environmental and genetic control of morphogenesis in crops: Towards models simulating phenotypic plasticity. Australian Journal of Agricultual Research 56: 1-14.
11. Dingkuhn M, Penning de Vries FWTT, De Datta SK, van Laar HH. 1991. Concepts for a new plant type for direct seeded flooded tropical rice. In: Direct Seeded Flooded Rice in the Tropics. Manila, The Philippines: International Rice Research Institute, 17-38.
12. Dingkuhn M, Singh BB, Clerget B, Chantereau J, Sultan B. 2005b. Past, present and future criteria to breed crops for water-limited environments in West Africa. Agriculture and Water Management (in press).
13. Fournier C, Andrieu B. 1999. ADEL-Maize: an L-system based model for the integration of growth processes from the organ to the canopy. Application to regulation of morphogenesis by light availability. Agronomie 22: 313-327.
14. Gambín BL, Borrás L, Otegui ME. 2004. Maize potential kernel weight: relation with plant growth rate around silking. Electronic Proceedings of the 4th International Crop Science Conference, Brisbane, Australia (www.cropscience.org).
15. Hammer GL, Kropff MJ, Sinclair TR, Porter JR. 2002. Future contributions of crop modelling - from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement. European Journal of Agronomy 18: 15-31.
16. Jones CA, Kiniry JR. 1986. CERES-Maize: a simulation model of maize growth and development. Texas: Texas A&M University Press.
17. Jones JW, Tsuji GY, Hoogenboom G, Hunt LA, Thornton PK, Wilkens PW, et al. 1998. Decision support system for agrotechnology transfer; DSSAT v3. In: Tsuji GY, Hoogenboom G, Thornton PK. Understanding options for agricultural production. Dordrecht: Kluwer Academic, 57-177.
18. Kurth W, Sloboda B. 1997. Growth grammars simulating trees-an extension of L - systems incorporating local variables and sensitivity. Silva Fennica 31: 285-295.
19. Lindenmayer A. 1968. Mathematical models for cellular interaction in development, parts I and II. Journal of Theoretical Biology 18: 280-315.
20. Lizaso JI, Batchelor WD, Westgate ME. 2003. A leaf area model to simulate cultivar-specific expansion and senescence of maize leaves. Field Crops Research 80: 1-17.
21. Luquet D, Zhang BG, Dingkuhn M, Dexet A, Clement-Vidal A. 2005. Phenotypic plasticity of rice seedlings: case of phosphorus deficiency. Plant Product Science 8: 145-151.
22. McFerson J, Pierce F. 2003. Technology Roadmap. Research priorities to enhance tree fruit production through technological innovation. Wenatchee, WA: Washington Tree Fruit Commission (www.treefruitresearch.org).
23. Martin A, Belastegui-Macadam X, Quilleré I, Floriot M, Valadier M-H, et al. 2005. Nitrogen management and senescence in two maize hybrids differing in the persistence of leaf greenness: agronomic, physiological and molecular aspects. New Phytologist 167: 483-492.
24. Perttunen J, Sievänen R, Nikinmaa E, Salminen H, Saarenmaa H, Väkevä J. 1996. LIGNUM: a tree model based on simple structural units. Annals of Botany 77: 87-98.
25. Prakash CS. 2001. The genetically modified crop debate in the context of agricultural evolution. Plant Physiology 126: 8-15.
26. Press WH, Flannery BP, Teukolsky SA, Vetterling WT. 1992. 'Fitting data to a straight line', 'Straight-line data with errors in both coordinates', and 'General linear least squares'. In: Numerical recipes in FORTRAN: the art of scientific computing, 2nd edn. Cambridge: Cambridge University Press, 655-675.
27. Prusinkiewicz P, Lindenmayer A, Hanan J. 1988. Developmental models of herbaceous plants for computer imagery purposes. Computer Graphics 22: 141-150.
28. de Reffye P, Edelin C, Francon J, Jaeger M, Puech C. 1988. Plant models faithful to botanical structure and development. Computer Graphics 22: 151-158.
29. de Reffye P, Biaise F, Chemouny S, Jaffuel S, Fourcaud T, Houllier F. 1999. Calibration of hydraulic growth model on the architecture of cotton plants, Agronomie 19: 265-280.
30. Ritchie JT, NeSmith DS. 1991. Temperature and crop development. In: Hanks RJ, Ritchie JT, eds. Modeling plant and soil systems. American Society of Agronomy Monograph 31. Madison, WI, 5-29.
31. Sievanen R, Nikinmaa E, Nygren P, Ozier-Lafontaine H, Perttunen L, Hakula H. 2000. Components of functional - structural tree models. Annals of Forestry Science 57: 399-412.
32. Sinoquet H, Thanisawanyangkura S, Mabrouk H, Kasemspa P. 1998. Characterization of the light environment in canopies using 3D digitizing and image processing. Annals of Botany 82: 203-212.
33. Smith AR. 1984. Plants, fractals and formal languages. Computer Graphics 18: 1-10.
34. Vose JM, Sullivan NH, Clinton BD, Bolstad PV. 1995. Vertical leaf area distribution, light transmittance, and application of the Beer-Lambert law in four mature hardwood stands in the southern Appalachians. Canadian Journal of Forest Research 25: 1036-1043.
35. Yan HP, Kang MZ, de Reffye P, Dingkuhn M. 2004. A dynamic, architectural plant model simulating resource-dependent growth. Annals of Boany 93: 591-602.
36. Zhan ZG, de Reffye P, Houllier F, Hu BG. 2003. Fitting a structural-functional model with plant architectural data. In: Hu BG, Jaeger M, eds. Proceeding of Plant Growth Modeling and Applications (PMA'03). Beijing, China. Tsinghua University Press/Springer-Verlag, 236-249.