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C-IPM ERAnet: AAPM - CH0210

Drosophila suzukii has become a serious pest in Europe since its spread in 2008 to Spain and Italy, attacking many soft-skinned crops such
as several berry species, cherry and grapevines. Pest monitoring is the basis of its control. Therefore, an efficient and accurate monitoring
system is essential in order to identify the presence of D. suzukii in the crops and the surrounding area, and to prevent damage to
economically valuable fruit crops. Existing methods for monitoring D. suzukii are costly, time and labor intensive and consequently
conducted at low spatial resolution and prone to errors. We therefore propose to develop a novel system to overcome current monitoring
limitations consisting of traps which are monitored by means of an Unmanned Aerial Vehicle (UAV) and an automatic image processing
pipeline for the identification and count of number of D. suzukii per trap location. The automated monitoring has an advantage over current
methods in terms of (1) labor intensity, (2) sampling interval, (3) automatic integration into DSS, (4) monitoring of diverse and even hardly
accessible habitats, and (5) population monitoring in vast areas in relation to climatic and other geo-processed parameters. A multi-variable
sticky trap evaluation will allow selecting the most suitable one to attract the target insect. A small multi-rotor UAV platform will be flown at
multiple intervals to capture high resolution color aerial photographs of the insect traps. The photographs will be subjected to image
processing algorithms to identify the presence or absence of D. suzukii and their counts. The data collected will be transferred to a decision
support system (DSS) to provide valuable information for growers in a format that is both meaningful and accessible, thereby demonstrating
the added value and social importance of applied science and technology to the wider community and food security.
Project Documents
• EVID4 - Final project report : AAPM Final Defra Report (002)   (2109k)
Time-Scale and Cost
From: 2017

To: 2020

Cost: £41,666
Contractor / Funded Organisations
University of Aberdeen
Pest Control