Zone-Selective Plant Protection based on AI Pest Early Detection

Autor: Berger, L. T., Polder, G, Tsiroppoulos, Z, Gil, E, Blok, P. M., Ortega, P, Voskakis, M
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: International Advances in Pesticide Application. AAB
International Advances in Pesticide Application
Popis: Vine downy mildew and Apple scab are endemic diseases that cause severe losses when not detected and treated at an early stage. On the other hand, reducing the use of pesticides in fruit production is a major global societal challenge and is in line with the European Green Deal and EU Directive 2009/128/EC, demanding integrated pest management as well as with 2016/2031/EC, which requires that a proportionate and effective response to plant health threats is established through a combination of technological, ecological and institutional management. Thus, on the quest for more targeted treatments, the EU Horizon 2020 OPTIMA research project (http://optima-h2020.eu/) addresses this problem through a.) an image analysis based pest Early Detection System (EDS) b.) post processing in a custom Decision Support System (DSS), as well as c.) downloading of generated application maps to cloud connected spraying equipment for precise application in desired application zones. Although, knowing that the majority of treatments against Vine downy mildew and Apple scab are of preventive and not of curative nature, selecting these frequent pests allowed the OPTIMA partners to prove that the underlying technologies and algorithms are able to support “Zone-Selective Plant Protection based on AI Pest Early Detection”.
The work is supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 773718, project OPTIMA (Optimised Pest Integrated Management to precisely detect and control plant diseases in perennial crops and open-field vegetables). The opinions expressed reflect only the authors' views.
Databáze: OpenAIRE
Externí odkaz: