Analysis, modeling and multi-spectral sensing for the predictive management of Verticillium wilt in olive groves

Verticillium wilt of olive is a vascular pathogen and the intensive cultivation of olives  in almost all olive growing countries has caused significant spread of this disease. Within MyOlivGroveCoach, we will focus on empowering olive growers and agronomists with diagnosis and management tools for the timely detection of infected trees with non-visible symptoms (initial stage of the infection or asymptomatic stress). This system will provide a management mobile and web application integrated with a pipeline of advanced analysis and multispectral processing algorithms, ensuring end users awareness and providing also treatments and cultural practices. The required data will be collected by remote and multispectral sensing via unmanned aerial vehicles, allowing end users to identify trees with non-visible symptoms, so that the timely management of the disease can take place, guiding the farmers towards the effective treatment of the disease, minimizing the economic losses.

Duration: 24 months
Timeline: 2019 – 2020
Project Types: National Research Projects
Funding Agency:Research and Innovation Strategies for Smart Specialisation (RIS3), Region of Western Greece, NSRF 2014-202

Project Manager: Dr. Aris Lalos
Other Group Members: Industrial System Institute (ISI), Irida Labs, Papadopoulos Elaia
Research Area:Real-time and Networked Embedded Systems, Manufacturing Systems, Processes and Enterprise Interoperability