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Epidemiologically-based strategies for the detection of emerging plant pathogens

Emerging pests and pathogens of plants are a major threat to natural and managed ecosystems worldwide. Whilst it is well accepted that surveillance activities are key to both the early detection of new incursions and the ability to identify pest-free areas, the performance of these activities must b...

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Autores principales: Mastin, Alexander J., van den Bosch, Frank, Bourhis, Yoann, Parnell, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243127/
https://www.ncbi.nlm.nih.gov/pubmed/35768558
http://dx.doi.org/10.1038/s41598-022-13553-y
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author Mastin, Alexander J.
van den Bosch, Frank
Bourhis, Yoann
Parnell, Stephen
author_facet Mastin, Alexander J.
van den Bosch, Frank
Bourhis, Yoann
Parnell, Stephen
author_sort Mastin, Alexander J.
collection PubMed
description Emerging pests and pathogens of plants are a major threat to natural and managed ecosystems worldwide. Whilst it is well accepted that surveillance activities are key to both the early detection of new incursions and the ability to identify pest-free areas, the performance of these activities must be evaluated to ensure they are fit for purpose. This requires consideration of the number of potential hosts inspected or tested as well as the epidemiology of the pathogen and the detection method used. In the case of plant pathogens, one particular concern is whether the visual inspection of plant hosts for signs of disease is able to detect the presence of these pathogens at low prevalences, given that it takes time for these symptoms to develop. One such pathogen is the ST53 strain of the vector-borne bacterial pathogen Xylella fastidiosa in olive hosts, which was first identified in southern Italy in 2013. Additionally, X. fastidiosa ST53 in olive has a rapid rate of spread, which could also have important implications for surveillance. In the current study, we evaluate how well visual surveillance would be expected to perform for this pathogen and investigate whether molecular testing of either tree hosts or insect vectors offer feasible alternatives. Our results identify the main constraints to each of these strategies and can be used to inform and improve both current and future surveillance activities.
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spelling pubmed-92431272022-07-01 Epidemiologically-based strategies for the detection of emerging plant pathogens Mastin, Alexander J. van den Bosch, Frank Bourhis, Yoann Parnell, Stephen Sci Rep Article Emerging pests and pathogens of plants are a major threat to natural and managed ecosystems worldwide. Whilst it is well accepted that surveillance activities are key to both the early detection of new incursions and the ability to identify pest-free areas, the performance of these activities must be evaluated to ensure they are fit for purpose. This requires consideration of the number of potential hosts inspected or tested as well as the epidemiology of the pathogen and the detection method used. In the case of plant pathogens, one particular concern is whether the visual inspection of plant hosts for signs of disease is able to detect the presence of these pathogens at low prevalences, given that it takes time for these symptoms to develop. One such pathogen is the ST53 strain of the vector-borne bacterial pathogen Xylella fastidiosa in olive hosts, which was first identified in southern Italy in 2013. Additionally, X. fastidiosa ST53 in olive has a rapid rate of spread, which could also have important implications for surveillance. In the current study, we evaluate how well visual surveillance would be expected to perform for this pathogen and investigate whether molecular testing of either tree hosts or insect vectors offer feasible alternatives. Our results identify the main constraints to each of these strategies and can be used to inform and improve both current and future surveillance activities. Nature Publishing Group UK 2022-06-29 /pmc/articles/PMC9243127/ /pubmed/35768558 http://dx.doi.org/10.1038/s41598-022-13553-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Mastin, Alexander J.
van den Bosch, Frank
Bourhis, Yoann
Parnell, Stephen
Epidemiologically-based strategies for the detection of emerging plant pathogens
title Epidemiologically-based strategies for the detection of emerging plant pathogens
title_full Epidemiologically-based strategies for the detection of emerging plant pathogens
title_fullStr Epidemiologically-based strategies for the detection of emerging plant pathogens
title_full_unstemmed Epidemiologically-based strategies for the detection of emerging plant pathogens
title_short Epidemiologically-based strategies for the detection of emerging plant pathogens
title_sort epidemiologically-based strategies for the detection of emerging plant pathogens
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243127/
https://www.ncbi.nlm.nih.gov/pubmed/35768558
http://dx.doi.org/10.1038/s41598-022-13553-y
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