If you are attending the ASA-CSSA 2021 International Annual Meeting Salt Lake City, Utah, 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.
DSSAT International Training Workshop 2022Jointly 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 4.8, 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
• Crop model users;
• Crop model trainers;
• Crop model developers;
• Models for the most important food, feed, fiber, and fuel crops;
• Tools and utilities for data preparation;
• Minimum data for model calibration and evaluation; and
• Application programs for assessing real-world problems.
This collection summarises key advances in crop modelling, with a focus on developing the next generation of crop and whole-farm models to improve decision making and support for farmers.
Chapters in Part 1 review advances in modelling individual components of agricultural systems, such as plant responses to environmental conditions, crop growth stage prediction, nutrient and water cycling as well as pest/disease dynamics. Building on topics previously discussed in Part 1, Part 2 addresses the challenges of combining modular sub-systems into whole farm system, landscape and regional models. Chapters cover topics such as integration of rotations and livestock, as well as landscape models such as agroecological zone (AEZ) models. Chapters also review the performance of specific models such as APSIM and DSSAT and the challenges of developing decision support systems (DSS) linked with such models. The final part of the book reviews wider issues in improving model reliability such as data sharing and the supply of real-time data, as well as crop model inter-comparison.
Read More… Watch the informative video Buy the bookDownload brochure
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. Dec
ades 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…
CRAFT: A New Spatial Yield Forecasting ToolThe 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
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.
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.
Decision Support System for Agrotechnology Transfer (DSSAT) is software application program that comprises dynamic crop growth simulation models for over 42 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 applied to address many real-world problems and issues 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 used for more than 30 years by researchers, educators, consultants, extension agents, growers, private industry, policy and decision makers, and many others in over 174 countries worldwide. Learn more…
Original by Samantha Murray, October 21, 2021. Sam is a senior public relations specialist at UF/IFAS Communications. She loves learning about and communicating science. Supply chains for French fries and pasta sauce are surprisingly resilient to climate change, according to the predictions of a new study.The study’s authors made their predictions using an innovative modeling […]
This Special Issue of The Journal of Agricultural Science is dedicated to the iCROPM 2020 Symposium. It includes six papers that are based on both oral and poster presentations from the symposium, including the final keynote presentation. Read the Editorial:iCROPM 2020: Crop Modeling for the Futureby, Gerrit Hoogenboom, Eric Justes, Christophe Pradal, Marie Launay, Senthold […]
Texas A&M AgriLife study projects the genetic profile that cultivars will need to adapt Original by Kay Ledbetter, October 13, 2021. Kay Ledbetter is an associate editor/senior writer/media relations specialist for Texas A&M AgriLife. She is responsible for writing news releases and feature articles from science-based information generated by the agency across the state, as […]
Original by Brad Buck, October 7, 2021. A senior public relations specialist for UF/IFAS Communications, Brad is a huge Gator fan. He grew up in Gainesville, loves movies, sports and finding great stories to tell. Data sets are often easy to find but complicated to use because scientists store and use information differently, and they […]
The DSSAT Foundation will be sponsoring the 24th Annual Open Forum on Crop Modeling and Decision Support Systems during this year’s ASA-CSSA-SSSA 2021 International Annual Meeting. The forum is scheduled for Monday night, November 8, 2021, from 7:30 – 9:00 pm in Room 151 DEF of the Salt Palace Convention Center in Salt Lake City, […]
DSSAT 2021 European Training Course at the Technical University of Munich The first DSSAT European Training Course was held from August 30 through September 4, 2021 at the Technical University of Munich. The workshop was hosted by Professor Senthold Asseng, Chair Digital Agriculture and Director of the Hans Eisenmann Forum of the Technical University of […]
Original by Susan McCarthy, National Agricultural Library, Ming Chan, National Agricultural Library, and Cheryl Porter, University of Florida in Research and Science Sep 08, 2021. Crop researchers are hungry for data to feed their crop models. There is a wealth of historical data that’s inaccessible because today’s crop model software applications cannot easily interpret it. USDA’s […]
