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
Contact:
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
Author(s):
Ir. W. Gerritsma.
Abstract:
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