Better breeding leveraging more biology.

Hierarchical genome-phenome frameworks are proposed to improve predictive modeling of crop performance under climate-driven environmental variability, enabling more accurate breeding decisions.

• Why it matters: Climate variability is undermining reliable prediction of crop performance across environments, which in turn limits genetic gain in breeding programs. There is a need for predictive frameworks that reflect plant-environment interactions across diverse genetics and management conditions.
• What they did: The work outlines how integrating mechanistic plant-science insights into predictive models can be used within breeding programs, leveraging emerging hierarchical genome-phenome frameworks. It focuses on evaluating how biological knowledge informs predictions across target environments.
• The result: The approach is intended to improve prediction accuracy, precision, and interpretability, supporting long-term genetic gain under changing environments. It also provides a framework for assessing plant-environment interactions using biological knowledge.

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