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dc.contributor.authorFahrentrapp, Johannes-
dc.contributor.authorRoosjen, Peter-
dc.contributor.authorKooistra, Lammert-
dc.contributor.authorGregory, Billy-
dc.contributor.authorGreen, David R-
dc.date.accessioned2021-02-04T10:57:38Z-
dc.date.available2021-02-04T10:57:38Z-
dc.date.issued2020-10-
dc.identifier.urihttps://www.alphavisa.com/team/2020/documents/Abstract-book_TEAM-2020.pdfde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21543-
dc.description.abstractSpotted 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.de_CH
dc.language.isoende_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectIntegrated Pest Managementde_CH
dc.subjectIPMde_CH
dc.subject.ddc632: Pflanzenkrankheiten, Schädlingede_CH
dc.titleAutomation of pest monitoring : examples from Drosophila suzukiide_CH
dc.typeKonferenz: Sonstigesde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Umwelt und Natürliche Ressourcen (IUNR)de_CH
zhaw.conference.details4th TEAM meeting, La Grande-Motte (France), 5-9 October 2020de_CH
zhaw.funding.euNot specifiedde_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start29de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewKeine Begutachtungde_CH
zhaw.title.proceedingsTephritid Workers of Europe, Africa and the Middle East TEAM : Book of Abstractsde_CH
zhaw.webfeedHortikulturde_CH
zhaw.funding.zhawAutomated Airborne Pest Monitoring AAPM of Drosophila suzukii in Crops and Natural Habitatsde_CH
zhaw.funding.zhawAlternatives Monitoring der Kirschessigfliege KEFde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Life Sciences und Facility Management

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