PADI-web for Plant Health Surveillance

Roche Mathieu, Rabatel Julien, Trevennec Carlène, Pieretti Isabelle. 2024. PADI-web for Plant Health Surveillance. In : Intelligent information systems: CAiSE Forum 2024, Limassol, Cyprus, June 3–7, 2024, Proceedings. Islam Shareeful (ed.), Sturn Arnon (ed.). Cham : Springer, 148-156. (Lecture Notes in Business Information Processing, 520) ISBN 978-3-031-60999-2 International Conference on Advanced Information Systems Engineering, Limassol, Chypre, 3 Juin 2024/7 Juin 2024.

Résumé : Due to the increasing number of new and reemerging pests resulting from intensification, globalisation and climate change, monitoring of plant health is crucial. In this context, outbreak detection in digital media could be useful for improving plant disease surveillance. But manually extracting relevant information from unofficial sources is time-consuming. The Platform for Automated extraction of Disease Information from the web (PADI-web) has been developed initially for animal health surveillance, and recently for plant disease surveillance. In order to identify relevant news and information with this new PADIweb instance dedicated to plant health, machine learning approaches and language models (RoBERTa) have been integrated for monitoring plant diseases. This paper presents the PADI-web algorithms and visualisations implemented for specific case studies (i.e. Xylella fastidiosa and Fusarium Oxysporum Tropical) using text-mining approaches tuned on the plant disease domain.

Mots-clés libres : Epidemic intelligence, Event-based surveillance, Text Mining, Plant health, PADI-web

Agences de financement européennes : European Commission

Agences de financement hors UE : Agence Nationale de Recherches sur le Sida et les Hépatites Virales, Direction générale de l'alimentation

Projets sur financement : (EU) MOnitoring Outbreak events for Disease surveillance in a data science context, (FRA) Building epidemiological surveillance and prophylaxis with observations both near and distant, (FRA) Institut Convergences en Agriculture Numérique

Auteurs et affiliations

• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
• Rabatel Julien
• Trevennec Carlène
• Pieretti Isabelle, CIRAD-BIOS-UMR PHIM (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/609595/)

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