Referent: Juan Andrés Chiavassa ǀ Johann Heinrich von Thünen-Institut – Institut für Agrartechnologie
Ort: Online via Webex. Hier geht es zur Registrierung:
https://thuenen.webex.com/thuenen/j.php?RGID=r2d7718e7299e9fa192c00fc6aebb9ad9
An essential tool for decision-making in agricultural production and in ecosystem management planning is the field monitoring of insects. However, the implementation of traditional monitoring systems can present various difficulties that may globally lead to a limited temporal and spatial resolution of the obtained information. Despite recent innovative developments in automatic insect monitoring traps that seek to resolve these difficulties and limitations, most of them focus exclusively on the study of agricultural pests and, regardless of their effectiveness, they are not suitable for monitoring a generalist population of insects. In this context, an automatic, low-cost, and generalist monitoring system is being developed to obtain high temporal resolution data for a quantitative and qualitative evaluation of insect diversity. We present the Field Automatic Insect Recognizer (FAIR)-Device, a novel non-lethal generalist field device, based on the capture and analysis of both photographic images and the wingbeat frequency of insects (WBF) using infrared sensors. Image selection of the recorded insects is currently semi-automatic, and classification is done with the help of the iNaturalist citizen science platform. Simultaneously, the frequency of wingbeats in flight is also considered a distinguishing feature of insects and therefore able to be used for carrying out species identification. We believe that IoT systems such as the FAIR-Device, capable of monitoring insects in real-time and 24 hours a day would open countless new doors to the study of insect populations, both in ecological research and in agricultural production.
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