DSSAT v4.7.5

Latest Version: 4.7.5 (April 2019) | Free of charge!

23rd Annual Open Forum on Crop Modeling and Decision Support Systems

If you are attending the ASA-CSSA 2019 International Annual Meeting San Antonio, Texas, come and join us at the DSSAT Foundation Open Forum, where we will exchange what’s new on the crop modeling research, collaboration opportunities, and related data and tools development activities.

  • Day, Date: November 11, 2019
  • Start Time: 7:30 PM
  • End Time: 9:00 PM
  • Location: Room 225A of the Henry B. Gonzalez Convention Center

17720420720_05c8543ce5_zDSSAT International Training Workshop 2020

May 18-23, 2020
The University of Georgia at Griffin, Georgia, USA

Jointly presented by the DSSAT Foundation, University of Florida, University of Georgia, and the International Fertilizer Development Center – the workshop will cover the operation of DSSAT Version 4.7.5, description of the DSSAT-Cropping System Model, CSM and its modules, and the science embedded in the models, minimum data requirements and experimental data collection for systems simulation, integration of crop simulation models with database management and GIS, and the application of the DSSAT-CSM model to improve management of cropping systems.

Learn more about the workshop Workshop Brochure

DSSAT 2019 @ Pakistan

PMAS Arid Agriculture University, Rawalpindi, Pakistan

Sep 4-5, 2019

DSSAT 2019 @ Thailand

Chiang Mai University in Chiang Mai, Thailand
August 19th – August 24th, 2019


Date: 29 August 2019
Time: 08:30-9:30 AM Eastern Time

11th DSSAT Development Sprint

IFDC | July 15-19, 2019

DSSAT 2019

May 20-25, 2019. University of Georgia, Griffin.

AMEI Workshop

University of Florida, April 9-11, 2019

DSSAT 2019 @ Vietnam

Hotel Fortuneland, Can Tho City, Vietnam
March 5-9, 2019

Cross-continental disease and crop modeling collaborations to beat back wheat blast

Cross-continental collaborations facilitated by the CGIAR Platform for Big Data in Agriculture thrive to beat back the threat of wheat blast in Brazil and Bangladesh.

Wheat blast disease is a major threat to smallholder farmers. The disease was first discovered in Brazil in 1985. Decades later it escaped from South America when it crept its way across the ocean and appeared in Bangladesh in 2016. Wheat blast outbreaks are linked to the right climate conditions. More accurate weather forecasts, coupled with disease models are key for farmers to adapt to the threat of the disease. Effective forecasting and warning systems can also help farmers avoid unnecessary fungicide use, thereby saving them money and reducing environmental risks.

Because the disease is new, knowledge of wheat blast epidemiology and modeling was limited in Bangladesh. That’s why scientists at the International Maize and Wheat Improvement Center (CIMMYT) reached out to Professor Jose Mauricio Fernandes, a Crop Pathologist, and Mr. Felipe de Vargas, a Computer Scientist, within the Universidade de Passo Fundo (UPF) in Brazil… Read more…

GARDIAN and facilitating data interoperability at CGIAR

The CGIAR online search engine, GARDIAN, is easy to navigate and to perform simple queries to locate data and publications; however, there is a challenge to making these data useable on a large scale.

There is a major gap between the potential value of data collected in agricultural experiments and the value currently obtained through the use of those data. Typically, data collected in experiments are used for the original research purpose only, but a much greater value might be obtained if the data could be combined across locations, time, and management conditions.

Combinations of large datasets could enable scientific advances in such areas as genetic modeling, management optimization, and variety selection, and may potentially reduce the need for collection of additional field experimental data. The CGIAR research centers generate large amounts of data, which could gain value through the application of the FAIR (Findable, Accessible, Interoperable, Reusable) principles, particularly for data which are suitable for quantitative analyses.
Read more…

10th DSSAT Development Sprint

University of Florida | January 07-11, 2019

DSSAT 2018 @ Jamaica

University of the West Indies | July 16-27, 2018

CRAFT: A New Spatial Yield Forecasting Tool

The CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) is a software platform designed for yield forecasting at spatial resolutions of either 5 or 30 arc-minutes using an ensemble modeling approach. Currently the DSSAT, APSIM, and SARRA-H crop simulation models have been implemented for nine important food and feed crops using the AgMIP IT tools. CRAFT was an initiative of CCAFS and was developed in partnership with the Asia Risk Center, Washington State University, and the University of Florida.

Read More about CRAFT Download CRAFT v3.4

Globally Recognized UF/IFAS Crop-Model Researcher Wins National Soil Science Award

November 7, 2017

A University of Florida professor has received a top award from the Soil Science Society of America for helping to develop and apply practices that increase crops, income and help the environment. The L.R. Ahuja Ag Systems Modeling Award goes to a soil scientist, agronomist or crop scientist in recognition of distinguished contributions and their demonstrated impact in the past five to seven years.

“It was a great honor to be recognized for my work in crop modeling and decision-support systems,” said Gerrit Hoogenboom, a UF/IFAS professor of agricultural and biological engineering and a preeminent scholar at the UF/IFAS Institute for Sustainable Food Systems.

Read more about the Award

ICASA Data Standards Version 2.0


Researchers increasingly seek to integrate results from multiple experiments. The ICASA V2.0 standards allow flexible description of field experiments. Major categories of data are management, soil, weather and crop responses. The standards may be implemented in diverse digital formats. Planned improvements emphasize data quality and appropriate usage.

Access at ScienceDirect
Download in PDF

Improving Soil Fertility Recommendations in Africa

The new book gives a detailed description of the application of DSSAT in simulating crop and soil processes within various Agro-ecological zones in Africa. The book provides examples of the application of DSSAT models to simulate nitrogen applications, soil and water conservation practices including effects of zai technology, phosphorus and maize productivity, generation of genetic coefficients, long-term soil fertility management technologies in the drylands, microdosing, optimization of nitrogen x germplasms x water, spatial analysis of water and nutrient use efficiencies and, tradeoff analysis.

Read Online Buy at Amazon

What is DSSAT?

Decision Support System for Agrotechnology Transfer (DSSAT) is software application program that comprises dynamic crop growth simulation models for over 40 crops. DSSAT is supported by a range of utilities and apps for weather, soil, genetic, crop management, and observational experimental data, and includes example data sets for all crop models. The crop simulation models simulate growth, development and yield as a function of the soil-plant-atmosphere dynamics. DSSAT has been used for many applications ranging from genetic modeling to on-farm and precision management to regional assessments of the impact of climate variability and climate change. DSSAT has been in use for more than 30 years by researchers, educators, consultants, extension agents, growers, private industry, policy and decision makers, and many others in over 150 countries worldwide.  Learn more…


23rd Annual Open Forum on Crop Modeling and Decision Support Systems

The DSSAT Foundation will be sponsoring the 23rd Annual Open Forum on Crop Modeling and Decision Support Systems during this year’s ASA-CSSA-SSSA 2019 International Annual Meeting. The forum is scheduled for Monday night, November 11, 2019, from 7:30 – 9:00pm in Room 225A of the Henry B. Gonzalez Convention Center in San Antonio, Texas. The […]

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DSSAT 2019 @ Pakistan

Hands-on Training workshop with titled  “Climate Change Impact Assessment and Adaptation Strategies for Wheat and Groundnut Production Using Decision Support System” was organized by Department of Agronomy, PMAS Arid Agriculture University, Rawalpindi, Pakistan on 4th to 5th September 2019. The goal of the training workshop is to develop capacity building of scientists, researchers and post-graduate students […]

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DSSAT 2019 @ Thailand

The DSSAT and MWCropDSS 2019 International Training Program entitled “Efficient and precision agricultural resource utilization under changes with simulation models and GIS” was successfully held from August 19 through August 24, 2019 at Chiang Mai University in Chiang Mai, Thailand. This workshop was jointly presented by Chiang Mai University, The University of Florida, and the […]

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Ask Gerrit and Cheryl Anything about DSSAT

The crop models in Decision Support System for Agrotechnology Transfer (DSSAT) simulate growth, development, and yield as a function of the soil-plant-atmosphere dynamics. For more than 30 years, DSSAT has been used for many applications ranging from genetic modeling to on-farm and precision management to regional assessments of the impact of climate variability and climate […]

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International DSSAT Training Workshop in South Africa

The Agricultural Research Council of South Africa will be hosting an International Crop Modeling Training Workshop on DSSAT in collaboration with the University of Florida and the DSSAT Foundation. The workshop will be held from September 30th to October 4th,  2019 at the ARC Offices in Pretoria, preceding the 35th Annual Conference of the South African […]

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11th DSSAT Development Sprint at IFDC

The 11th DSSAT Development Sprint was held from July 15-19, 2019, at the International Fertilizer Development Center (IFDC) in Muscle Shoals, Alabama. One of the main goals of the DSSAT Development Sprints is to improve both the science and the tools of the DSSAT crop modeling ecosystem using a “hackathon” approach. Significant achievements and outcomes […]

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Minimum Data Requirements for Crop Modeling

CGIAR Webinar by the Platform for Big Data in Agriculture’s Community of Practice on Crop Modeling – Minimum Data Requirements for Crop Modeling – Recorded Live on June 18th, 2019. Modelers are often frustrated because much of the research information available in crop data sets worldwide is either not in model-friendly format or lacking key […]

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