European Union
December 8, 2023
Published: 8 December 2023
Approved: 3 May 2023
Wiley Online Library
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EFSA Journal 2023;20(12):EN-8143
DOI : https://doi.org/10.2903/sp.efsa.2023.EN-8143
Question Number : EFSA‐Q‐2023‐00389
Disclaimer: The present document has been produced and adopted by the bodies identified above as author(s). In accordance with Article 36 of Regulation (EC) No 178/2002, this task has been carried out exclusively by the author(s) in the context of a grant agreement between the European Food Safety Authority and the author(s). The present document is published complying with the transparency principle to which the Authority is subject. It cannot be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.
Abstract
Plant‐parasitic nematodes cause significant economic losses in crop production, with root‐knot nematodes (RKN) and potato cyst nematodes (PCN) being the top two in terms of agronomic impact. Early detection is crucial as nematode damage can take years to become visible and lead to full field infestations if unmanaged. Accurate detection and monitoring methods are needed for effective management. Remote sensing is a promising approach, but it needs to reliably distinguish between biotic stress from nematodes and abiotic stress such as drought. This project focuses on four nematode species and includes drought stress in experiments to ensure accuracy. The project is divided into four parts: literature review, identifying implementation opportunities, pilot case studies, and knowledge transfer. The literature review analyses the current state‐of‐the‐art in remote sensing for plant health assessment and provides guidelines for future research. Identifying implementation opportunities assesses the potential of remote sensing for nematode detection and monitoring. Pilot case studies test the effectiveness of remote sensing in detecting nematode infestation and distinguishing between biotic and abiotic stress. Knowledge transfer disseminates the findings to stakeholders. The pilot case study used hyperspectral imaging to identify infested tubers, showing promise for early detection and management. The project's guidelines for future research and implementation are also published in various manuscripts and a monography. Remote sensing is a promising approach to improve crop yields, reduce pesticide use, and promote sustainable agriculture by detecting and monitoring nematode infestations in plants.
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