PhD Studentship: Leveraging AI, Deep Learning and LLMs for Plant Health Monitoring to Support Biosecurity and Biodiversity

Plants and trees are essential to the UK, contributing £15.7 billion annually in economic and environmental benefits, and are critical to achieving NetZero by 2050. In partnership with Plant Health at Defra (Department for Environment, Food & Rural Affairs), this project aims to leverage computer vision, deep learning, and LLM technology to detect plant and tree health issues—such as pests and diseases—in alignment with the UK Plant Biosecurity Strategy. This solution will help protect Great Britain’s plant life, supporting effective risk and threat management and enabling cost-effective health monitoring and disease detection.

The project will combine advanced deep-learning analytics with digital imaging technology, utilizing images captured from cameras, drones, satellites, and multispectral and hyperspectral sensors to monitor plant health across various scales—from large-scale aerial views to subtle, microscopic changes.

Through the development of deep learning models, the project will analyse extensive multimodal datasets of images and text. The AI algorithms will interpret visual and textual data (vision LLMs), identifying patterns and symptoms (e.g. discoloration, wilting, or spotting) for accurate and automated health analysis. This approach will enable early warnings of potential issues, disease hotspots, or outbreaks, supporting timely, informed decision-making and efficient plant health management across the UK.

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