Summary
This domain analysis paper addresses a significant knowledge gap in agricultural digital twins by investigating how Functional Structural Plant Modelling can enhance virtual plant representations. The authors propose a framework for integrating 3D plant models with functional attributes into digital twin systems, identifying key requirements and challenges from existing literature. The framework is positioned as foundational for improving predictive accuracy in yield estimation, disease monitoring, and enabling precision agriculture applications such as robotic pruning and optimised spraying.
Regional applicability
The framework's applicability to UK horticultural and arable systems would depend on validation with UK crop varieties and growing conditions. The proposed approach to digital twins could inform UK precision agriculture policy and agri-tech development, though the paper itself does not address UK-specific implementation.
Key measures
Critical gaps in digital twin technology application; framework requirements and challenges for 3D FSPM integration; conceptual gaps between plant phenotyping and digital twin needs
Outcomes reported
The study conducted a domain analysis of 3D plant phenotyping and functional structural plant modelling (FSPM) to identify requirements and challenges for digital twin integration in agriculture. It proposed a framework for incorporating 3D plant representations with functional attributes into agricultural digital twins to improve predictive capabilities.
Topic tags
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