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Advances in crop modelling for a sustainable agriculture

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.

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DSSAT 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.

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…

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.

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.

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.

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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.