1. General Model Information
Name: Decision Support System for Agrotechnology Transfer Version 3.5
Main medium: terrestrial
Main subject: biogeochemistry, agriculture
Organization level: ecosystem
Type of model: not specified
Main application: decision support/expert system, research, education
Keywords: environment, agriculture, agroecosystem, agricultural management effects, rotation, yield, crop growth, corn, bean, soybean, peanut, decision support system, modellling system, multiple growth models, Ceres, Cropgro, database
International Consortium for Agricultural Systems Applications
2440 Campus Rd., Box 527
Honolulu, HI 96822, USA
DSSAT Crop Models:
Dr. Gerrit Hoogenboom
Coordinator of Research, Extension and Instruction
Department of Biological and Agricultural Engineering
The University of Georgia
165 Gordon Futral Court
Griffin, Georgia 30223-1797, USA
Phone: ICASA: +1-808-956-7531 G. Hoogenboom: +1-770-229-3438
Fax: ICASA: +1-808-956-2711 G. Hoogenboom: +1-770-228-7218
email: ICASA Gerrit Hoogenboom
Homepage: International Consortium for Agricultural Systems Applications Gerrit. Hoogenboom
The goal of the International Benchmark Sites Network for Agrotechnology
Transfer (IBSNAT) Project is to accelerate the flow of agrotechnology and
increase the success rate of technology transfer from agricultural research
centers to farmers' fields. To do this, IBSNAT has developed computer software
which helps match crop requirements to land characteristics using crop
simulation models, data bases, and strategy evaluation programs. The
resulting system is called the Decision Support System for Agrotechnology
Transfer (DSSAT). DSSAT provides easy access to data bases and crop models so that
the user may "test" on screen the performance of new cultivars, sites, or manag
practices. This system allows user to screen new technology packages, such as
a new cultivar or fertilizer management strategy, whithout spending excess time
on expensive, time consuming field trials. By simulating outcomes of strategies
on the computer screen, user can ask "what if" questions and explore the options
on screen. Sustainable agriculture requires tools that enable decision makers to explore
the future. A decsion support system must help users make choices today that
result in desired outcomes, not only next year, but 10, 25, and 50 or more years into
DSSAT was designed primarily for user groups in agriculture, but owing to its
break with traditionaly ways of diagnosing and prescribing solutions, it has been
adopted by other types of users. The emergence of issues which require assessment
of conditions not in the past or present, but in the future calls for the systems
approach to problem solving encompassed by DSSAT, which includes:
- Global climate studies,
- Use with geographic information systems,
- Whole-farm system models,
- Pest-crop interaction models,
- Fertilizer strategies,
- Plant breeding.
DSSAT is comprised of the following components:
- a Data Base Management System (DBMS) to enter, store, and retrieve the
"minimum data set" needed to validate, list and use the crop models to provide
outcomes to alternative management input
- a set of validated crop models
- an application program for analyzing and displaying outcomes
of long-term simulated agronomic experiments.
The following crop models are currently accessible under the
DSSAT shell. They include:
All crops share a common input-output format, and are similar in level of detail.
They operate on a daily time step, and are based on an understanding of biophysical
- the CERES family of models:
CERES-wheat, CERES-rice, CERES-barley, CERES-sorghum, and CERES-millet;
CROPGRO series of models for legumes:
CROPGRO-soybean, CROPGRO-peanut, CROPGRO-dry bean (Phaseolus)
- the CROPSIM model series for root crops: CROPSIM-cassava and SUBSTOR-potato
- and for other crops: CROPGRO-Tomato, CROPGRO-Chickpea, Sugarcane, Sunflower
- (Taro, tanier and pineapple will be added in the near future.)
These models are process oriented, designed to have global
applications, and work independent of location, season, crop cultivar, and
management system. The models simulate the effects of weather, soil water, genotype,
and soil and crop nitrogene dynamics on crop growth and yield.
The Data Base Management System (DBMS) in DSSAT is used to organize and store
the Minimum Data Set (MDS). The MDS is the minimum data required to run DSSAT's
crop models, and has become an international standard data set for model calibration
and validation. The DBMS provides easy access to four data bases.
- The Weather Data Base
This data base contains daily weather data from the Minimum Data Set experiments,
and allows easy editing, and printing of data.
- The Soil Data Base
This data base is comprised principally of the 600 pedons in the USDA Soil
Conservation Service (SCS) International Benchmark Soil Data base.
- User's Input Data Base
This database allows the user to enter soil data collected by their own national
soil survey organization. Data is entered into the User's Input program using
a standardized format, so that the user can retrieve their own soil profiles and
combine them with the Weather and Experiment data bases.
- The Management and Experimental Data Base
Management information includes planting date, planting density, row spacing,
planting depth, crop variety, and irrigation and fertilizer practices.
The experimental data base includes the minimum data set required for
validating the crop models.
- Utilities and Summary Reports
The utility programs allow users to input data in ASCII format (i.e., a spread-sheet)
and the program converts it into the correct input/output file format used by the
crop models. The Summary Reports allow:
- chronological listing of activities and events for an experiment;
- summary of preplant soil fertility and preplant soil water content for
- date and fertilizer inputs by plot; and
- tables and/or graphs of weather data on a 10-day or monthly basis.
The Strategie Evaluation Program in DSSAT allows users to evaluate
the merits of simulated strategies and identify the best one. The program uses
cumulative probabilty functions to develop and select the strategy with
the preferred mean and variability characteristics. With this program users can
determine the effectiveness of crop management stragegies, the economic return
of a new cultivar, or the suitability of a site for a specific crop. Using weather
generators programs which generate coefficients from historical weather data, DSSAT
can simulate the growth and development of a crop for up to
50 consecutive years. DSSAT allows up to 15 combinations of options to be simulated
in a single experiment, generating in a few hours, amounts of data that have
traditionally required an agronomist's lifetime of work.
Source of abstract information (partially): DSSAT Information page,
Further information now at ICASA - DSSAT:
Actual version of DSSAT: 4.0
II. Technical Information
Operating System(s): DSSAT v3.5:
Any 486 or better IBM Personal Computer or compatible microcomputer with:
- 640K of random access memory (RAM); minimum free RAM required is 590K
- a hard disk (required); complete installation requires 25 MB disk space
- DOS version 3.3 or later
- an VGA graphic adapter or better
- a math coprocessor (recommended)
DSSAT v3.5 is distributed by the International Consortium for Agricultural Systems Applications (ICASA), Honolulu.
How to order:
- Management System for new DSSAT v3.5 files,
- Crop models and User's Guides for:
- Cereals - Maize, Wheat, Rice, Sorghum, Barley, and Millet models,
- Grain Legumes - Soybean, Peanut, Dry Bean, and Chickpea models,
- Root Crops - Cassava and Potato models, and
- Sugarcane, Tomato, Sunflower and Pasture.
- Seasonal, Sequence and Spatial (AEGIS/WIN) Analysis programs, and
- 4 Volume set of DSSAT v3.5 User's Guides.
Programming Language(s): Components of software are written in FORTRAN (crop models), C (shell), Pascal (graphics), DBase (database), and Basic (strategy and risk management programs)
III. Mathematical Information
View Input data requirements of DSSAT in comparison to other Soil Organic Matter related models:
These seven tables can be downloaded in Postscript Format
View output data of DSSAT in comparison to other SOM - related models:
Jones, C.A. and J.R. Kiniry. 1986.
CERES-Maize: A simulation model of maize growth and development. Texas A&M University Press, College Station.
Jones, J.W., K.J. Mishoe, G.G.Wilkerson, and S.S. Jagtap. 1986.
SOYGRO v. 5.3: Soybean crop growth and yield model,IBSNAT version. Technical documentation, University of Florida, Gainesville.
Carlos Pampulim Caldeira, Pedro Aguiar Pinto 1998, Linking DSSAT V3 to a relational database: the AGROSYS--DSSAT interface, Computers And Electronics In Agriculture (21)1 (1998) pp. 69
V. Further information in the World-Wide-Web
VI. Additional remarks
This mode of communication will allow each user to shareconcerns, successes, messages, and thoughts related to DSSAT and itsapplication. Additionally, information on updates and modifications willbe announced here as well as through conventional means.
Dr. Hoogenboom will serve as "caretaker" of the listserver.
Last review of this document by: T. Gabele: 23. 08. 1998, Juergen Bierwirth Mon Sep 25 16:54:43 CEST 2000
Status of the document:
last modified by
Joachim Benz Fri Apr 20 15:37:02 CEST 2007