This is a contract result notice, not an open opportunity. Details from the official award data.

Drosophila (D) suzukii has become a serious pest in Europe since its spread in 2008 to Spain and Italy, and the UK in 2012, 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 crops and surrounding areas, 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 a low spatial resolution and prone to errors.

It is proposed 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 the number of D. suzukii per trap location.

Automated monitoring has an advantage over current methods in terms of (1) labour intensity, (2) sampling interval, (3) automatic integration into Decision Support Systems (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 for the selection of 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 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.