Digital twins for plant and crop improvement

Plant digital twins (DTs) are dynamic, data-aware virtual representations that integrate plant structure, physiology, and environmental inputs to simulate plant function, growth, and performance. By combining process-based models, phenomics data, and environmental states in a continuous feedback loop linking physical and virtual plants, DTs offer a novel approach for investigating complex biological systems. In this opinion article, we outline the conceptual foundations of DTs and how they offer new opportunities to bridge the genotype-to-phenotype gap and aid in crop improvement. Despite their promise, major challenges remain in DT development, scalability, and accessibility. Addressing these challenges will be critical for enabling the broad adoption of DTs as transformative tools for accelerating plant science research and crop improvement.