Crop Modeling

Community of Practice

 

Welcome!

The Community of Practice on Crop Modeling (CoPCM) 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 system.

The CM-CoP formed in 2017 and is led by Wheat Physiologist Matthew Reynolds at the International Maize and Wheat Improvement Center (CIMMYT) in El Batán, Mexico.

This space can be used as a discussion area, share and request relevant information and contribute towards building the community as a whole.

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Crop modeling science encompasses a wide range of quantitative applications based on 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.

By promoting FAIR (Findable, Accessible, Interoperable, Reusable) data principles, the CM-CoP fosters a culture that values GEMS data and enables its members to solve global grand challenges faster, better and at greater scale.

The CM-CoP has a virtual meeting space where crop modeling enthusiasts and specialists from 15 CGIAR Centers and other industry organizations can share ideas and resources, find collaborators and co-authors and participate in relevant discussions.

Get in touch

CoP Lead

Matthew Reynolds | Email
International Maize and Wheat Improvement Center (CIMMYT) Texcoco, México

CoP Coordinator

Anabel Molero Milan | Email
Consultant at International Maize and Wheat Improvement Center (CIMMYT)

Engage with the Community

i

BE INFORMED

Tune in to the latest CoP updates by subscribing to our newsletter.

w

ENGAGE

Interact with community members through our LinkedIn Group.

CONTRIBUTE

Share your expertise in our working groups.

Working Groups

The Crop Modeling CoP hosts a series of different short-life working groups and projects where the real work of the community takes place.

Peer-review Group

The aim of this group is to increase visibility and accessibility of crop modeling research activities through the publication of peer-review papers of interest and highlighting the last crop modeling research outcomes of interest to the crop modeling community. This group is currently working in the elaboration of 4 reviews that will showcase on-going modeling activities and potential impacts from CGIAR and partners among the main drivers of cropping systems:

Breeding (G Group) | Environment (E Group) |Crop Management (M group) | Policy and Socio-Economic (S group)

CMGap

The Crop Model CoP is in a unique position to convene a global consortium to address technology gaps that may otherwise slow the adoption or reduce impacts of recent investments in crop improvement. To identify these gaps, the CMGap group is conducting a wide gap analysis of modeling approaches and capabilities within the CGIAR centers and main partners to determine strengths, weaknesses, opportunities and needs in terms of modeling capacity and expertize.

CM Outreach Group

Increasing visibility and accessibility of crop research data is a key point to improve the global coordination of crop modeling efforts in agricultural research. The CM Outreach working group aims to accelerate dissemination of new crop information and technologies, share crop modeling skills, outcomes, opportunities, impacts and to promote FAIR (Findable, Accessible, Interoperable and Re-usable) crop research data.

Interested in contributing to our working groups?

Please select the group of interest:

15 + 10 =

Community News

 

Webinar - Potential climate-related impacts on future maize and wheat yields

Webinar – Potential climate-related impacts on future maize and wheat yields

This webinar by the Crop Modeling Community of Practice presents a recently published study showing potential climate-related impacts on maize ...
Webinar - Modeling with 40 years of international wheat data

Webinar – Modeling with 40 years of international wheat data

This webinar by the Crop Modeling Community of Practice presents selected outputs from big data analysis of four decades of ...
2020 Convention session - Gridded crop modeling advances & challenges

2020 Convention session – Gridded crop modeling advances & challenges

This session on gridded crop modeling advances and challenges aired live at the virtual 2020 CGIAR Convention on Big Data ...
2020 Convention session - Machine Learning and Crop Modeling: A Modern Affair?

2020 Convention session – Machine Learning and Crop Modeling: A Modern Affair?

This session on machine learning and crop modeling aired live at the virtual 2020 CGIAR Convention on Big Data in ...
2020 Convention session - Disease Crop Modeling Advances & Challenges for Large-Scale Simulation Studies

2020 Convention session – Disease Crop Modeling Advances & Challenges for Large-Scale Simulation Studies

This session by the Crop Modeling Community of Practice aired live at the virtual 2020 CGIAR Convention on Big Data ...
2020 Convention session - Phenotyping & Remote Sensing to Facilitate Minimum Data Set Requirements for Crop Simulation Modeling

2020 Convention session – Phenotyping & Remote Sensing to Facilitate Minimum Data Set Requirements for Crop Simulation Modeling

This session by the Crop Modeling Community of Practice aired live at the virtual 2020 CGIAR Convention on Big Data ...
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Resources

Documents

  • Work Plan 2018 – Detailed description of expected outcomes and deliverables for 2018
  • Work Plan 2019 – Detailed description of expected outcomes and deliverables for 2019
  • Work Plan 2020 – Detailed description of expected outcomes and deliverables for 2020

Webinars and presentations

Newsletters

Crop Modeling publications

The Community of Practice on Crop Modeling has compiled a list of relevant Crop Modeling literature published in the last 5 years. Links to the original papers can be found in each reference.

Go to list (Google Doc) →

Interested in joining our community of practice?

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