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Data-driven Reduction Of Pesticide Spread in high volume orchard treatments with smart sprayers.

Project description

Smarter spraying for healthier orchards

Pesticides are essential for protecting fruit tree crops – cornerstones of EU agriculture – but traditional spraying methods waste large amounts through drift and runoff, endangering ecosystems and human health. Even new smart sprayers using pulse-width modulation (PWM) valves cannot fully control droplet size during high-volume spraying, leading to uncontrolled dispersion. Supported by the Marie Skłodowska-Curie Actions programme, the DROPS project is tackling this head-on. By measuring droplet sizes directly in orchards and combining that data with advanced fluid dynamics and machine learning, the team will create a real-time Decision Support System (DSS) for farmers. Overall, the DSS will guide smarter, safer pesticide use to reduce waste and environmental harm while helping Europe’s orchards thrive.

Objective

In fruit tree crops, which are vital to EU agriculture, efficient pesticide use is crucial for maintaining high yields and assuring market quality. However, traditional spraying methods often result in significant pesticide losses through drift and runoff, posing environmental and health risks. Although new smart sprayers equipped with pulse width modulation (PWM) valves are designed to control flow rates and minimise off-target losses, the droplet size variations caused by pressure fluctuations when spraying high volumes to control pests and diseases are still poorly understood, and often lead to uncontrolled pesticide dispersion to the environment. The DROPS project will optimise pesticide application in orchards by developing a novel methodology for predicting pesticide dispersion and improving spraying practices. Specifically, DROPS will directly measure droplet size in orchards and integrate computational fluid dynamics (CFD) models with machine learning to create a Decision Support System (DSS) that guides farmers in optimising pesticide applications. The project will adapt and validate droplet size measurement techniques for dynamic outdoor orchard conditions, using PWM-based sprayers. This will provide accurate data on droplet behaviour under varying environmental conditions and sprayer settings. The data will inform predictive models of droplet size variation, enhanced by machine learning algorithms for greater accuracy. These models will then be integrated into CFD simulations to predict pesticide dispersion in different orchard environments. In the final phase, the DSS will be developed and field-validated to provide real-time recommendations for minimising off-target pesticide dispersion. The system will be implemented in smart sprayers and tested with an industry partner to ensure practical application under real-world conditions.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

UNIVERSITAT POLITECNICA DE VALENCIA
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.

€ 242 593,20
Address
CAMINO DE VERA SN EDIFICIO 3A
46022 VALENCIA
Spain

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Region
Este Comunitat Valenciana Valencia/València
Activity type
Higher or Secondary Education Establishments
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Total cost

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Partners (2)

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