Landscape‐scale patterns and predictors of potato viruses in Scotland

IF 2.3 3区 农林科学 Q1 AGRONOMY Plant Pathology Pub Date : 2024-03-16 DOI:10.1111/ppa.13891
Peter Skelsey
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Abstract

Virus diseases represent important economic threats to seed potato production worldwide, yet relatively little is known of their epidemiology at the landscape‐scale. In this study, data was compiled from the Scottish national seed potato classification scheme on the incidence of 10 different potato viruses for the years 2009–2022. A co‐occurrence analysis identified that 12 virus species pairs occurred together more often than expected by chance, and potato blackleg was positively associated with eight potato viruses. ArcGIS was used to investigate spatial and spatiotemporal variation in incidence rates of the three most prevalent viruses (potato virus Y, potato leaf roll virus and potato virus A), and this revealed prominent geographic differences in long‐term disease outcomes. Focusing on potato virus Y as the most commonly occurring single infection, interpretable machine‐learning techniques were used to investigate the influence of key crop, management and environmental factors on patterns of incidence in space and time. The results showed that health characteristics of seed stocks were among the most important predictors of incidence, along with blackleg infection, several management features, cultivar resistance, distance to the nearest seed and ware crop, temperature variables and several soil features. This approach provides a comprehensive overview of potato viruses in Scotland, a deeper understanding of epidemiological risk factors at the landscape‐scale and a forecast model that could serve as the basis of a decision support tool for improved management of potato virus Y.

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苏格兰马铃薯病毒的景观尺度模式和预测因素
病毒病是全球马铃薯种薯生产的重要经济威胁,但人们对其在景观尺度上的流行病学却知之甚少。在这项研究中,我们从苏格兰国家马铃薯种薯分类计划中汇编了 2009-2022 年 10 种不同马铃薯病毒的发病率数据。通过共现分析发现,有 12 种病毒同时出现的频率高于偶然出现的频率,马铃薯黑腿病与 8 种马铃薯病毒呈正相关。利用 ArcGIS 调查了三种最流行病毒(马铃薯病毒 Y、马铃薯卷叶病毒和马铃薯病毒 A)发病率的空间和时空变化,发现了长期病害结果的显著地理差异。马铃薯病毒 Y 是最常发生的单一感染病害,研究人员利用可解释的机器学习技术研究了作物、管理和环境等关键因素对发病率时空模式的影响。结果表明,除黑胫病感染、几种管理特征、栽培品种抗性、与最近的种子和器皿作物的距离、温度变量和几种土壤特性外,种群的健康特征也是预测发病率的最重要因素之一。这种方法提供了苏格兰马铃薯病毒的全面概况,加深了对景观尺度上流行病风险因素的理解,并提供了一个预测模型,可作为改进马铃薯病毒 Y 管理的决策支持工具的基础。
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来源期刊
Plant Pathology
Plant Pathology 生物-农艺学
CiteScore
5.60
自引率
7.40%
发文量
147
审稿时长
3 months
期刊介绍: This international journal, owned and edited by the British Society for Plant Pathology, covers all aspects of plant pathology and reaches subscribers in 80 countries. Top quality original research papers and critical reviews from around the world cover: diseases of temperate and tropical plants caused by fungi, bacteria, viruses, phytoplasmas and nematodes; physiological, biochemical, molecular, ecological, genetic and economic aspects of plant pathology; disease epidemiology and modelling; disease appraisal and crop loss assessment; and plant disease control and disease-related crop management.
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