Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.
PLoS Comput Biol. 2023 Mar 28;19(3):e1010969. doi: 10.1371/journal.pcbi.1010969. eCollection 2023 Mar.
Plant pathogens respond to selection pressures exerted by disease management strategies. This can lead to fungicide resistance and/or the breakdown of disease-resistant cultivars, each of which significantly threaten food security. Both fungicide resistance and cultivar breakdown can be characterised as qualitative or quantitative. Qualitative (monogenic) resistance/breakdown involves a step change in the characteristics of the pathogen population with respect to disease control, often caused by a single genetic change. Quantitative (polygenic) resistance/breakdown instead involves multiple genetic changes, each causing a smaller shift in pathogen characteristics, leading to a gradual alteration in the effectiveness of disease control over time. Although resistance/breakdown to many fungicides/cultivars currently in use is quantitative, the overwhelming majority of modelling studies focus on the much simpler case of qualitative resistance. Further, those very few models of quantitative resistance/breakdown which do exist are not fitted to field data. Here we present a model of quantitative resistance/breakdown applied to Zymoseptoria tritici, which causes Septoria leaf blotch, the most prevalent disease of wheat worldwide. Our model is fitted to data from field trials in the UK and Denmark. For fungicide resistance, we show that the optimal disease management strategy depends on the timescale of interest. Greater numbers of fungicide applications per year lead to greater selection for resistant strains, although over short timescales this can be oset by the increased control oered by more sprays. However, over longer timescales higher yields are attained using fewer fungicide applications per year. Deployment of disease-resistant cultivars is not only a valuable disease management strategy, but also oers the secondary benefit of protecting fungicide effectiveness by delaying the development of fungicide resistance. However, disease-resistant cultivars themselves erode over time. We show how an integrated disease management strategy with frequent replacement of disease-resistant cultivars can give a large improvement in fungicide durability and yields.
植物病原体对疾病管理策略施加的选择压力做出反应。这可能导致杀菌剂抗性和/或抗病品种的失效，这两者都严重威胁着粮食安全。杀菌剂抗性和品种失效都可以定性或定量地描述。定性（单基因）抗性/失效涉及病原体种群在控制疾病方面的特征发生突变，通常是由单一遗传变化引起的。定量（多基因）抗性/失效则涉及多个遗传变化，每个变化都会导致病原体特征的较小变化，从而随着时间的推移逐渐改变疾病控制的效果。尽管目前使用的许多杀菌剂/品种都具有定量抗性/失效，但绝大多数建模研究都集中在定性抗性的简单情况上。此外，目前存在的极少数定量抗性/失效模型都不适用于田间数据。在这里，我们提出了一个适用于引起叶斑病的禾谷丝核菌的定量抗性/失效模型，叶斑病是全世界小麦最普遍的病害。我们的模型适用于英国和丹麦田间试验的数据。对于杀菌剂抗性，我们表明，最佳的疾病管理策略取决于关注的时间尺度。每年使用更多的杀菌剂应用程序会导致对抗性菌株的更大选择，尽管在短时间内，这可以通过更多喷雾提供的更大控制来抵消。然而，在较长的时间内，每年使用较少的杀菌剂应用程序可以获得更高的产量。部署抗病品种不仅是一种有价值的疾病管理策略，还通过延迟杀菌剂抗性的发展来保护杀菌剂的有效性提供了次要好处。然而，抗病品种本身会随着时间的推移而失效。我们展示了如何通过频繁更换抗病品种的综合疾病管理策略，可以大大提高杀菌剂的耐用性和产量。
