Epidemiologically-based strategies for the detection of emerging plant pathogens.

Abstract

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.

Plant phenotyping relevance

植物の病徴を目視検査する手法の検出性能を疫学的に評価しており、病害状態のフェノタイピング法の検証が中心です。

Code and data availability

The paper states its analysis code is included in the Supplementary Information, but no public repository or downloadable URL for that supplement (or any phenotype dataset, images, or trained model) is provided in the supplied blocks or allowed URLs. The other URLs are cited references (FAO surveillance guide, PRA PDF,

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