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Collaborative project: Early detection of apple proliferation and pear decline with remote sensing and analyses based on machine learning methods - subproject 2 (Digitaler Obstbau)
Project
Project code: 28RF4052
Contract period: 14.05.2019
- 31.12.2022
Purpose of research: Applied research
Keywords: plant diseases (virusus, bacteria, fungi, phytoplasma), crop production, crop protection, plant health, fruit production, pome, precision farming, monitoring, digital world
Apple proliferation and pear decline are economically important phytoplasma diseases of apple and pear. However, there is no direct control measure for these quarantine diseases, which are widespread in European fruit growing. In order to prevent the further spread of these phytoplasma diseases, only prophylactic measures, such as control of the insect vectors by insecticide treatments and the uprooting of infested trees, help. Economically, uprooting only makes sense if less than 10% of the trees are affected. In addition, disease containment requires a coordinated regional approach. Consequently, it is very important for the grower to detect the disease at an early stage. The aim of the project is therefore to develop a diagnostic method that can detect the diseases in aerial and satellite images, both early and on a large scale. The biochemical change in the plant caused by the phytoplasmas, e.g. the induction of a specific reddening, will be used for this purpose. Multi- and hyperspectral data will be analyzed using machine learning methods and results used for developing a remote sensing method specifically suitable for the detection of apple proliferation and pear decline. Remote sensing data acquired by drones or satellites are planned to be offered in a decision support system as a service adapted to the needs of individual growers, cooperatives or, at regional level, for crop protection services. Ideally, the method can replace the laborintensive on-site visual monitoring and improve diagnostic reliability, especially for pear.
Section overview
Subjects
- Crop Protection
- Computer science
Framework programme
Funding programme
Excutive institution
Fraunhofer Institute for Factory Operation and Automation (IFF)
Funding institution
Project management agencies
Associated projects: Digitaler Obstbau
- Collaborative project: Early detection of apple proliferation and pear decline with remote sensing and analyses based on machine learning methods - subproject 1
- Collaborative project: Early detection of apple proliferation and pear decline with remote sensing and analyses based on machine learning methods - subproject 3