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The HortiQD project aims to develop an affordable and user-friendly machine vision system for precision farming, specifically tailored for orchard monitoring

The objective is to create a hyperspectral Short-Wave Infra Red camera operating in the wavelength range of 1 - 2 µm, with integrated point detection at smaller wavelengths. To achieve this, we propose a novel detector type based on Quantum Dot (QD) technology, utilising lead- and mercury-free QDs in compliance with EU regulations, thereby reducing component costs by approximately 99%. The optical filter will offer high spectral and spatial resolution, tunable to specific application requirements through design.

Hyperspectral images, captured in vivo, will be analysed by deep-learning algorithms to detect diseases in early stages and assess plant health, initially focusing on apples. A data management and correlation system will be implemented to present derived diagnoses and measures directly to farmers in real-time. The system will be mounted on an existing autonomous tractor, customised for horticulture, to verify feasibility and target Technology Readiness Levels (TRLs) under realistic conditions in various orchard types.

HortiQD aims to reduce or eliminate pesticide usage in European orchards, promoting sustainable farming practices and enhancing food quality. By automating monitoring processes, it will increase the reliability of European food production and help analyse and address the impacts of climate change.

The project targets a fully integrated solution comprising several innovative subcomponents. Each development brings benefits to its respective industry and opens up new markets beyond agriculture and food.