A real-time remote surveillance system for fruit flies of economic importance: sensitivity and image analysis

Yoshua Diller, Aviv Shamsian, Ben Shaked, Yam Altman, Bat Chen Danziger, Aruna Manrakhan, Leani Serfontein, Elma Bali, Matthias Wernicke, Alois Egartner, Marco Colacci, Andrea Sciarretta, Gal Chechik, Victor Alchanatis, Nikos T. Papadopoulos, David Nestel

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Timely detection of an invasion event, or a pest outbreak, is an extremely challenging operation of major importance for implementing management action toward eradication and/or containment. Fruit flies—FF—(Diptera: Tephritidae) comprise important invasive and quarantine species that threaten the world fruit and vegetables production. The current manuscript introduces a recently developed McPhail-type electronic trap (e-trap) and provides data on its field performance to surveil three major invasive FF (Ceratitis capitata, Bactrocera dorsalis and B. zonata). Using FF male lures, the e-trap attracts the flies and retains them on a sticky surface placed in the internal part of the trap. The e-trap captures frames of the trapped adults and automatically uploads the images to the remote server for identification conducted on a novel algorithm involving deep learning. Both the e-trap and the developed code were tested in the field in Greece, Austria, Italy, South Africa and Israel. The FF classification code was initially trained using a machine-learning algorithm and FF images derived from laboratory colonies of two of the species (C. capitata and B. zonata). Field tests were then conducted to investigate the electronic, communication and attractive performance of the e-trap, and the model accuracy to classify FFs. Our results demonstrated a relatively good communication, electronic performance and trapping efficacy of the e-trap. The classification model provided average precision results (93–95%) for the three target FFs from images uploaded remotely from e-traps deployed in field conditions. The developed and field tested e-trap system complies with the suggested attributes required for an advanced camera-based smart-trap.

Original languageEnglish
Pages (from-to)611-622
Number of pages12
JournalJournal of Pest Science
Volume96
Issue number2
DOIs
StatePublished - Mar 2023

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).

Funding

This project was partially financed by the European Union Horizon 2020 Research and Innovation Program (FF-IPM) (Grant agreement No 818184) and by the International Atomic Energy Agency Research Contract (No. 22412). We appreciate assistance provided by Maria Rosaria Tabilio (Research Centre for Olive, Citrus and Tree Fruit, CREA, Italy) and Umberto Berardo (Institute for the Sustainable Protection of Plants, CNR, Italy) for their assistance in identifying locations and deploying e-traps in Italy. We enormously appreciate NC Manoukis, USDA-ARS, Hilo, Hawaii USA, and two anonymous reviewers for their valuable suggestions to a previous version of this manuscript. This project was partially financed by the European Union Horizon 2020 Research and Innovation Program (FF-IPM) (Grant agreement No 818184) and by the International Atomic Energy Agency Research Contract (No. 22412). We appreciate assistance provided by Maria Rosaria Tabilio (Research Centre for Olive, Citrus and Tree Fruit, CREA, Italy) and Umberto Berardo (Institute for the Sustainable Protection of Plants, CNR, Italy) for their assistance in identifying locations and deploying e-traps in Italy. We enormously appreciate NC Manoukis, USDA-ARS, Hilo, Hawaii USA, and two anonymous reviewers for their valuable suggestions to a previous version of this manuscript.

FundersFunder number
FF-IPM818184
Maria Rosaria Tabilio
NC Manoukis
Agricultural Research Service
Consiglio Nazionale delle Ricerche
International Atomic Energy Agency22412
Horizon 2020
Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria

    Keywords

    • Bactrocera dorsalis
    • Bactrocera zonata
    • Ceratitis capitata
    • Deep-learning
    • Detection
    • Smart-trap

    Fingerprint

    Dive into the research topics of 'A real-time remote surveillance system for fruit flies of economic importance: sensitivity and image analysis'. Together they form a unique fingerprint.

    Cite this