First and fourth authors: Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom; second author: Curtin University, Centre for Crop and Disease Management, Department of Environment and Agriculture, Bentley, WA 6845, Australia; and third author: Rothamsted Research, Harpenden, AL5 2JQ, United Kingdom.
Phytopathology. 2018 Jul;108(7):803-817. doi: 10.1094/PHYTO-08-17-0277-R. Epub 2018 May 22.
Whether fungicide resistance management is optimized by spraying chemicals with different modes of action as a mixture (i.e., simultaneously) or in alternation (i.e., sequentially) has been studied by experimenters and modelers for decades. However, results have been inconclusive. We use previously parameterized and validated mathematical models of wheat Septoria leaf blotch and grapevine powdery mildew to test which tactic provides better resistance management, using the total yield before resistance causes disease control to become economically ineffective ("lifetime yield") to measure effectiveness. We focus on tactics involving the combination of a low-risk and a high-risk fungicide, and the case in which resistance to the high-risk chemical is complete (i.e., in which there is no partial resistance). Lifetime yield is then optimized by spraying as much low-risk fungicide as is permitted, combined with slightly more high-risk fungicide than needed for acceptable initial disease control, applying these fungicides as a mixture. That mixture rather than alternation gives better performance is invariant to model parameterization and structure, as well as the pathosystem in question. However, if comparison focuses on other metrics, e.g., lifetime yield at full label dose, either mixture or alternation can be optimal. Our work shows how epidemiological principles can explain the evolution of fungicide resistance, and also highlights a theoretical framework to address the question of whether mixture or alternation provides better resistance management. It also demonstrates that precisely how spray tactics are compared must be given careful consideration. [Formula: see text] Copyright © 2018 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .
几十年来，实验人员和建模人员一直在研究通过混合（即同时）或交替（即顺序）喷洒具有不同作用模式的化学物质来优化杀菌剂抗性管理的问题。然而，结果尚无定论。我们使用已参数化和验证的小麦叶斑枯病菌和葡萄白粉病菌的数学模型来测试哪种策略提供更好的抗性管理，使用抗性导致疾病控制在经济上无效之前的总产量（即“寿命产量”）来衡量效果。我们专注于涉及低风险和高风险杀菌剂组合的策略，以及高风险化学物质的抗性完全（即没有部分抗性）的情况。通过尽可能多地喷洒低风险杀菌剂，并结合略高于初始疾病控制所需的高风险杀菌剂来优化寿命产量，这些杀菌剂以混合物的形式施用。混合物而不是交替的表现更好，这对于模型参数化和结构以及所涉及的病理系统都是不变的。然而，如果比较侧重于其他指标，例如，在全标签剂量下的寿命产量，混合物或交替都可能是最优的。我们的工作表明，流行病学原理如何解释杀菌剂抗性的演变，同时也强调了一个理论框架来解决混合物或交替是否能提供更好的抗性管理的问题。它还表明，必须仔细考虑如何比较喷雾策略。[公式：见正文]版权所有 © 2018 作者。这是一个开放获取的文章，根据 CC BY 4.0 国际许可发布。
