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Automated monitoring in horticulture through spectral analysis with quantum dot detectors and high-resolution optical filters

Project description

Growing orchard health to power precision farming innovation

In European orchards, detecting diseases and monitoring plant health have been persistent challenges, often resulting in excessive pesticide use. This not only poses environmental risks but also impacts food quality and safety. Traditional methods lack precision, leading to inefficiencies and increased costs for farmers. In this context, the EU-funded HORTIQD project will develop an innovative machine vision system for precision farming. Using lead- and mercury-free quantum dot technology, it aims to develop a hyperspectral short-wave infra-red camera that is suitable for orchard monitoring. By using deep learning algorithms, it will detect diseases early and assess plant health in real time. Integrated with autonomous tractors, it promises to enhance farming sustainability and reduce pesticide dependency.

Objective

The HortiQD project aims to develop an affordable and easy-to-use machine vision system for precision farming. The objective is to build a hyperspectral Short-Wave Infra Red camera working in the wavelength range of 1 - 2 µm with integrated point detection at smaller wavelengths, specifically suitable for orchard monitoring. To reach this goal we propose a novel detector type based on QD technology, based on lead- and mercury-free QDs in compliance with EU regulations and reducing the component cost by approximately 99%. The optical filter will allow for high spectral and spatial resolution, tunable to specific application requirements by design. The hyperspectral images, recorded in-vivo, will be analyzed by deep-learning algorithms in order to identify diseases in an early state and assess the plant health, starting with apples. A data management and correlation system will be set up and present the derived diagnoses and measures directly to the farmer in real-time. The system will be mounted on an already existing autonomous tractor, customized for horticulture, in order to verify the feasibility and targeted TRLs under realistic conditions in several orchard types.
HortiQD will help to reduce or avoid the usage of pesticides in European orchards, paving the way towards sustainable farming and increasing food quality. It will scale up the intensity of monitoring by automation, hence, ensure the reliability of European food production. It will help analyze and address the impacts of climate change.
The project aims for a fully integrated solution, consisting of several innovative sub components. Each of the developments brings benefit to the industry it addresses and opens up new markets, beyond agriculture and food.

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Topic(s)

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HORIZON-IA - HORIZON Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-CL4-2023-DIGITAL-EMERGING-01

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Coordinator

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 893 402,49
Address
HANSASTRASSE 27C
80686 MUNCHEN
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
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Total cost

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Participants (11)

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