Publikationstyp: Konferenz: Sonstiges
Art der Begutachtung: Keine Begutachtung
Titel: Automation of pest monitoring : examples from Drosophila suzukii
Autor/-in: Fahrentrapp, Johannes
Roosjen, Peter
Kooistra, Lammert
Gregory, Billy
Green, David R
et. al: No
Tagungsband: Tephritid Workers of Europe, Africa and the Middle East TEAM : Book of Abstracts
Seite(n): 29
Angaben zur Konferenz: 4th TEAM meeting, La Grande-Motte (France), 5-9 October 2020
Erscheinungsdatum: Okt-2020
Sprache: Englisch
Schlagwörter: Integrated Pest Management; IPM
Fachgebiet (DDC): 632: Pflanzenkrankheiten, Schädlinge
Zusammenfassung: Spotted Wing Drosophila SWD (Drosophila suzukii) has become a serious pest in Europe attacking soft-skinned crops such as several berry species and grapevine. An efficient and accurate monitoring system to identify the presence of SWD in crops and their surroundings is essential for the prevention of damage to economically valuable fruit crops. Existing methods for monitoring SWD are costly, time and labor intensive, prone to errors, and typically conducted at a low spatial resolution. To overcome these limitations, we are developing a novel system using photographable traps, which are monitored by means of Unmanned Aerial Vehicles (UAVs) and an image processing pipeline that automatically identifies and counts the number of SWD per trap location. To this end, we collected high resolution RGB imagery of SWD caught alternative traps taken from both a static position (tripod) and from a UAV, which were then used as input to train deep learning models. Results show that a large part of the of SWD can be correctly identified by the models. Trap performance and the autonomouse flight of UAV platforms as well as their sensor quality needs further investment and are part of current works. Drones will be programmed to capture imagery of the traps under field conditions. The collected imagery will be transferred directly to cloud-based storage for subsequent processing and analysis to identify the presence and count of SWD in near real time. This data will be used as input to a decision support system (DSS) to provide valuable information for farmers.
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: Life Sciences und Facility Management
Organisationseinheit: Institut für Umwelt und Natürliche Ressourcen (IUNR)
Publiziert im Rahmen des ZHAW-Projekts: Automated Airborne Pest Monitoring AAPM of Drosophila suzukii in Crops and Natural Habitats
Alternatives Monitoring der Kirschessigfliege KEF
Enthalten in den Sammlungen:Publikationen Life Sciences und Facility Management

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