Next generation agricultural system data, models and knowledge products: Introduction.

Area of Science:

• Agricultural systems modeling
• Data science in agriculture
• Climate change adaptation

Background:

• Agricultural system models are crucial for decision-making but are often based on outdated research.
• Significant advancements in information and communication technology (ICT) have not been fully integrated into current models.
• Existing models are descendants of research from 30-40 years ago, limiting their predictive capabilities.

Purpose of the Study:

• To lay the foundation for the next generation of agricultural systems data, models, and knowledge products.
• To address the gap between current agricultural modeling capabilities and the potential offered by modern ICT.
• To support decision-makers in the private and public sectors with improved agricultural insights.

Main Methods:

• A "NextGen" study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP).
• Leveraging advancements in data and information and communication technology (ICT).
• Collaborative efforts supported by the Bill and Melinda Gates Foundation.

Main Results:

• The study identifies critical areas for improving agricultural models.
• It highlights the need for integrating new data sources and ICT.
• It sets the stage for developing advanced agricultural knowledge products.

Conclusions:

• Next-generation agricultural models are essential for future food security and sustainable agriculture.
• Integrating modern ICT and data science will enhance the predictive and assessment capabilities of agricultural models.
• This work provides a roadmap for developing more robust and relevant agricultural systems knowledge products.