Extent of stem colonization of Spanish Xylella fastidiosa strains in olive: A proximal sensing approach for early detection of infection
Emergence of Xylella fastidiosa (Xf) in Europe threatens agriculture and natural ecosystems. Its adaptability to diverse environments raises concerns on potential host shifts and increased virulence. Effective disease management depends on accurate and timely detection. Additionally, understanding i...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/407730 |
| Acceso en línea: | http://hdl.handle.net/10261/407730 |
| Access Level: | acceso abierto |
| Palabra clave: | Xylem Olea europaea Olive Quick Decline Syndrome (OQDS) Colonization Prompt detection Quarantine |
| Sumario: | Emergence of Xylella fastidiosa (Xf) in Europe threatens agriculture and natural ecosystems. Its adaptability to diverse environments raises concerns on potential host shifts and increased virulence. Effective disease management depends on accurate and timely detection. Additionally, understanding its interaction with local host cultivars is essential for developing risk mitigation measures. This study evaluated the pathogenicity and the extension of stem colonization of five Xf strains from different subspecies, isolated from almond and olive trees in Spain and Italy, inoculated on three widely cultivated Spanish olive cultivars. All strains successfully infected and colonized olive plants, although detection frequencies decreased over time, and none of the strains induced disease symptoms. Overall, strains XYL1961/18 and De Donno, from subspecies pauca showed higher colonization frequencies and bacterial loads compared to strains from subspecies multiplex. Furthermore, physiological responses were assessed using leaf spectral data retrieved with handheld proximal sensors, enabling the calculation of 74 vegetation indices to detect physiological alterations linked to infection status in asymptomatic plants. Of the 74 indices, between 17 and 31, mainly related to pigment composition (carotenoids, flavonoids, and xanthophylls), were selected as reliable predictors (>90% accuracy) of infection status across strains and olive cultivars. This study highlights the importance of evaluating the extent of stem colonization and interactions among local olive cultivars and Xf strains from different subspecies. We showed that proximal sensing may offer a promising non-invasive tool for early detection and monitoring of Xf infection, supporting timely management, thereby reducing the risk of new outbreaks. These methodologies may also assist in breeding programs aimed at developing Xf resistant olive cultivars. |
|---|