1. General Model Information

Name: CAcao Simulation Engine level 1

Acronym: CASE1

Main medium: terrestrial
Main subject: biogeochemistry
Organization level: ecosystem
Type of model: ordinary differential equations
Main application:
Keywords: crop growth, production, cacao, field scale, spatially lumped parameters


Ir. W. Gerritsma
Dept. of Agronomy, Wageningen Agricultural University,
Haarweg 333
6709 AH Wageningen, The Netherlands.

Phone: + 31-(0)317-483074
Fax: +31 8370 84575
email: Wouter.Gerritsma@USERS.AGRO.WAU.NL
Homepage: http://www.agro.wau.nl/agro/organiz/gerritsm.htm


Ir. W. Gerritsma.


A general crop growth model SUCROS87 [Notice: see SUCROS 1 and SUCROS 2] has been adapted to simulate the growth and production of cacao crops. The model can be used to simulate the growth and productivity of cacao stands under potential productivity circumstances. Long term assimilate pools are included. Productivity difference between years rather than productivity variation within years, are modelled.

Author of the abstract:
CAMASE Register of Agro-ecosystems Models

II. Technical Information

II.1 Executables:

Operating System(s): Mainframe, mini, or PC Executables are available from the Author

II.2 Source-code:

Programming Language(s): FORTRAN and FSE,Source-code is available from the Author

II.3 Manuals:

Gerritsma, W., 1995. Physiological aspects of cocoa agronomy and its modelling. Wageningen,Vakgroep Agronomie, Landbouw Universiteit Wageningen, 129 pp.

II.4 Data:

III. Mathematical Information

III.1 Mathematics

Rate variables: Daily canopy photosynthesis, maintenance and growth respiration,evapotranspiration, yield, organ death rates, development of pods.
Number of rate variables: 23.
State variables: Weight of leaves, wood, roots and fruits, and reserve pool, weight of death andharvested organs.
Number of state variables: 13.

III.2 Quantities

III.2.1 Input

Input data: All state and rate variables, site information and daily weather.
Number of input data: 61.

III.2.2 Output

Output data: All state and rate variables plus intermediate values.
Number of output data: > 50.
Time interval of simulation: 1 Day.
Basic spatial unit: 1 ha.

IV. References

Anten, N.P.R., W. Gerritsma & M. Wessel, 1993. Modelling as a tool for cocoa research, preliminary results. Proceedings of the 11th International Cocoa Research Conference, 18-24 July, 1993, Yamoussoukro, Ivory Coast.
Gerritsma, W. & M. Wessel, 1994. Calculated yield trends in various countries. Paper presented at the Malaysian International Cocoa Conference '94. 21-22 October 1994, Kuala Lumpur, Malaysia.
Gerritsma, W., 1995. Physiological aspects of cocoa agronomy and its modelling. Wageningen, Vakgroep Agronomie, Landbouw Universiteit Wageningen, 129 pp.
Gerritsma, W. & Wessel, M.1996. Calculated yield trends of cocoa in different countries. Proceedings MICC'94. Kuala Lumpur, Malaysia, 20-21 October 1994, p. 210-226.
Gerritsma, W. 1995. Physiological aspects of cocoa agronomy and its modelling. Final report. Wageningen Agricultural University. 129 p.
Gerritsma, W. & Wessel, M. 1996. CASE2, a model for cocoa growth and production. Paper prepared for presentation at the 12th Int. Cocoa Res. Conf., 17-23 Nov. 1996, Salvador, Bahia, Brazil.
Gerritsma, W. & Koning, G.H.J. de 1997. Modelling long-term cocoa production. Presentation at the ICCO workshop 'Long-term forecasting of cocoa production', London, 10 March 1998.

V. Further information in the World-Wide-Web

VI. Additional remarks

Last review of this document by: T. Gabele: 20. 6. 1997 -
Status of the document:
last modified by Joachim Benz Mon Jul 2 18:31:37 CEST 2007

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