1. General Model Information
Name: BEANGRO, SOYGRO and PNUTGRO
Acronym: CROPGRO
Main medium: air+terrestrial
Main subject: biogeochemistry
Organization level: ecosystem, organism
Type of model: compartment model, ordinary differential equations
Main application:
Keywords: crop growth, bean, soybean, peanut, deterministic,mechanistic, temperature, rainfall, solar radiation, soil, management
Contact:
Decision Support System for Agrotechnology Transfer (DSSAT)
Phone:
Fax :
email:
Author(s):
CROPGRO-DRY BEAN G. HOOGENBOOM, T.W. WHITE, J.W. JONES, K.J. BOOTE, W.T. BOWEN, N.B. PICKERING, AND W.D. BATCHELOR
University of Gerogia, Centro International de Agricultura Tropical, University of Florida, and International Fertilizer Development Center CROPGRO-Peanut K.J. BOOTE, J.W. JONES, G. HOOGENBOOM, N.B. PICKERING, T.W. WHITE, W.D. BATCHELOR, AND W.T. BOWEN
University of Florida, University of Gerogia, and International Fertilizer Development Center CROPGRO-SOYBEAN J.W. JONES, K.J. BOOTE, G. HOOGENBOOM, W.T. BOWEN, N.B. PICKERING, AND W.D. BATCHELOR
University of Florida, University of Gerogia, and International Fertilizer Development Center CROPGRO-CASSAVA R.B. MATTHEWS, L.A. HUNT, W. WILKENS, G. HOOGENBOOM, W.T. BOWEN
University of Guelph, International Fertilizer and Development Center, and University of Georgia
Abstract:
BEANGRO,SOYGRO and PNUTGRO comprise a group of related legume
production models (Hoogenboom et al., 1992)
see also
DSSAT.
They are deterministic and
mechanistic models which simulate physical, chemical, and biological
processes in the plant and related environment. Their purpose is
to predict crop yields and related agronomic parameters.The
models are constructed to simulate primary plant processes as a
function of weather, soil, and crop management conditions.
The model input data requirements are:
- Daily weather data (air temperature, precipitation, solar radiation);
- Soil physical conditions of the profile by layer;
- Soil chemical conditions of the profile by layer (nitrogen only);
- Crop management conditions (planting date, spacing, irrigation
management).
The models predict the weight of leaves, stems, roots, pods, shells, seeds,
LAI (leaf area index), and root length density on a daily basis.
They also predict main phenological events such as flowering and
maturity.
Author of the abstract:
CIESIN (CONSORTIUM FOR INTERNATIONAL EARTH
SCIENCE INFORMATION NETWORK):
Abstract of ASAE paper 95-365
information on CROPGRO
II. Technical Information
II.1 Executables:
Operating System(s): Model will operate on a personal computer with an 8088 processor, but simulation of one season can take as long as 15 minutes. On a 80486 computer a typical season will take about 10 seconds.
II.2 Source-code:
Programming Language(s): FORTRAN (Microsoft FORTRAN compiler)
II.3 Manuals:
II.4 Data:
III. Mathematical Information
III.1 Mathematics
III.2 Quantities
III.2.1 Input
III.2.2 Output
IV. References
Hoogenboom, G., J.W. Jones and K.J. Boote. 1992.Modeling the growth, development and yield of grain legumes usingSOYGRO, PNUTGRO and BEANGRO: a review. Transactionsof the ASAE .
V. Further information in the World-Wide-Web
VI. Additional remarks
Global change implications:The SOYGRO model is used withCERES-Wheat to study the impacts of climate change on crop yields and thepotential impacts of changes in crop yields on global agricultural economy(Adams et al., 1990). Also, because it is part of the CropSys mode(Caldwell and Hansen, 1993), these legume-GRO models can be used tostudy the potential of interactions of crop management to mitigate theeffects of climate change on yields and economics.
Author:
CIESIN (CONSORTIUM FORINTERNATIONAL EARTH SCIENCE INFORMATION NETWORK) :
Last review of this document by: T. Gabele: 25. 6. 1997 -
Status of the document:
last modified by
Tobias Gabele Wed Aug 21 21:44:41 CEST 2002