Geoinformation Technologies in Pest Management: Mapping Olive Fruit Fly Population in Olive Trees

Androniki Papafilippaki (), George Stavroulakis () and George P. Petropoulos ()
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Androniki Papafilippaki: Hellenic Mediterranean University, Laboratory of Water and Soil Quality Control
George Stavroulakis: Hellenic Mediterranean University, Laboratory of Water and Soil Quality Control
George P. Petropoulos: Harokopio University of Athens

A chapter in Information and Communication Technologies for Agriculture—Theme I: Sensors, 2022, pp 289-304 from Springer

Abstract: Abstract Monitoring olive-fruit fly (Bactrocera oleae) population in olive groves allows for an early pesticide control and ensures sustainable agricultural production, also protecting the farmers’ income. In this study, the synergistic use of geoinformation technologies and specifically of Geographical Information Systems (GIS) and Global Positioning Systems (GPS) with a field-installed trap network for monitoring olive-fruit fly population and its changes in the field, is demonstrated. As a case study the hydrological basin of Keritis located in Chania, Crete is used, which is an agricultural area cultivated primarily by olive trees. In our approach, the olive-fruit fly population in the traps network mapping is obtained with a GPS; the pest population data recorded is subsequently imported in GIS platform from which all the information recorded can then be disseminated to end-users. The platform is also able to provide synthesised information in relation to the olive-fruit fly location and population density. It allows the immediate identification of the hotspots with high olive-fruit fly density, the correlation of the insect population with various environmental parameters (rivers-streams, north aspect etc.). As such, it provides a very useful and practical decision-making tool in support of local pesticide spraying on a case-by-case basis that can be accessed straightaway by experts and non-experts alike.

Keywords: Olive-fruit fly; Trap network; Pesticides; GIS; GPS; Geoinformation; Hydrological basin; Google Earth (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-84144-7_12

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