Background image for CIMMYT
  1. Home >
  2. Multimedia >
  3. Videos >
  4. Crop Modeling community of practice

Crop Modeling community of practice

Improving global coordination of crop modeling efforts.


 
The Community of Practice on Crop Modeling is part of the CGIAR Platform for Big Data in Agriculture and encompasses a wide range of quantitative applications, based around the broad concept of parametrizing interactions within and among the main drivers of cropping systems. These are namely: Genotype, Environment, Management and Socioeconomic factors (GEMS) to provide information and tools for decision support. The Community of Practice was formed in 2017 and is led by Wheat Physiologist Matthew Reynolds at the International Maize and Wheat Improvement Center (CIMMYT) in Texcoco, Mexico.

Crop modeling has already contributed to a better understanding of crop performance and yield gaps; predictions of potential pest and disease epidemics; more efficient irrigation and fertilization systems, and optimized planting dates. These outputs help decision makers look ahead and prepare their research and extension systems to fight climate change where it is most needed. However, there is a significant opportunity — and need — to improve the global coordination of crop modeling efforts in agricultural research. This will, in turn, greatly improve the world’s ability to develop more adaptive, resilient crops and cropping systems.

Our Community of Practice aims to promote a better-coordinated and more standardized approach to crop modeling in agricultural research. With over 900 members involving CGIAR centers and a wide range of international partners, the Crop Modeling Community of Practice is already facilitating and sharing knowledge, resources, “model-ready” data, FAIR (Findable, Accessible, Interoperable, Reusable) data principles, and other useful information; while promoting capacity building and collaboration within the CGIAR and its community.

Get more information about the Crop Modeling Community of Practice on the Big Data website.

Join the Crop Modeling mailing list to get information about publications, webinars, new tools, updates and collaboration opportunities.

Connect to our LinkedIn group: Crop Modeling CoP.