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.
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 […]
Original by IFDC Staff | August 9, 2021 From July 26 to July 30, 2021, IFDC hosted the 15th Decision Support System for Agrotechnology Transfer (DSSAT) Development Sprint. The development sprint had three goals: improve DSSAT and its associated tools and databases; provide a forum for communications and information exchange among developers, users, and others interested in modeling and […]
During the last week of July the first “Hybrid” DSSAT Development Sprint was held, hosted by Dr. Upendra Singh and Dr. Willingthon Pavan at the International Fertilizer Development Center in Muscle Shoals, Alabama. In-person participants included five representatives from the University of Florida and three representatives from IFDC, while there were around 18 on-line participants […]
Original by Ashley N Biles for CAES News Anyone familiar with agriculture knows that a successful harvest largely relies on environmental factors. An especially hot summer with no rain in sight or poor soil quality can cause as many problems as a late cold snap right in the middle of planting season. Often farmers must rely on trial […]
DSSAT Foundation – The University of Georgia – Griffin Campus, Griffin, Georgia USA Scientists from across the world met from May 17-22, 2021 on the University of Georgia Griffin Campus to learn about the latest version of the Decision Support System for Agrotechnology Transfer (DSSAT) computer software program. The DSSAT crop modeling ecosystem helps researchers […]
Dynamic crop simulation models can be transformed into gene-based models by replacing an existing process module with a gene-based module for simulating the same process. Dynamic crop simulation models are tools that predict the phenotype (i.e. observable characteristics) of plants grown in specific environments. In these models, genotypic differences among cultivars are represented by empirical […]
Budding agricultural researchers are being trained in crop modeling to take on pressing and ever-present challenges of land, climate and food security. In a recent training program at ICRISAT-Mali, eight students learned to model agrosystems with DSSAT software, taking into account smallholder farming constraints. Crop modeling is a process that describes different stages of crop […]
