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Epidemiological role of novel and already known ‘Ca. P. solani’ cixiid vectors in rubbery taproot disease of sugar beet in Serbia

Rubbery taproot disease (RTD) of sugar beet was recently associated with the plant pathogenic bacterium ‘Candidatus Phytoplasma solani’ (CaPsol) and reported throughout the Pannonian Plain with variations in severity. Tracing CaPsol epidemiological pathways was performed in the experimental sugar be...

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Detalles Bibliográficos
Autores principales: Kosovac, Andrea, Ćurčić, Živko, Stepanović, Jelena, Rekanović, Emil, Duduk, Bojan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877035/
https://www.ncbi.nlm.nih.gov/pubmed/36697493
http://dx.doi.org/10.1038/s41598-023-28562-8
Descripción
Sumario:Rubbery taproot disease (RTD) of sugar beet was recently associated with the plant pathogenic bacterium ‘Candidatus Phytoplasma solani’ (CaPsol) and reported throughout the Pannonian Plain with variations in severity. Tracing CaPsol epidemiological pathways was performed in the experimental sugar beet field in Rimski Šančevi (Serbia) in 2020–2021, where an RTD outbreak was recently recorded. A molecular epidemiology approach was applied to the study of three RTD occurrence scenarios: epidemic, non-epidemic and ‘absence of RTD’. As a result, Hyalesthes obsoletus ex Convolvulus arvensis was detected as a CaPsol vector to sugar beet, while two other cixiids were identified for the first time as vectors of the CaPsol-induced plant disease in crops: Reptalus quinquecostatus and R. cuspidatus. R. quinquecostatus was proposed culpable for the 2020 RTD epidemic outbreak in Rimski Šančevi when dSTOLg CaPsol strain predominated in the RTD-affected sugar beet, whereas R. cuspidatus had a negligible role in RTD occurrence and displayed ambiguous involvement in CaPsol epidemiology on a wider scale. The temporal discrepancy of the offset of CaPsol dissemination and disease occurrence is the main obstacle in predicting CaPsol-induced diseases. Predicting disease occurrence and severity can only be achieved by gaining a better understanding of CaPsol epidemiological pathways and insect vectors involved in disease outbreaks.