Novel real-time disease surveillance and fungicide resistance monitoring tools to foster a smart and sustainable crop protection platform in Brazil

对用于控制害虫、杂草和病原体的化学剂的抗药性是对有效作物保护的威胁，因此也是对粮食安全的威胁。更严格的法规和新产品开发的放缓也减少了可用化学品类别的范围。这导致了对更少的杀真菌剂和作用模式的更大依赖，增加了对更多抗性病例的选择。有效的作物保护产品供应有限，加上主要作物品种缺乏遗传抗性，使主要病原体越来越难以控制。为了延长现有和新的作物保护产品的有效寿命，需要进化智能的综合害虫管理策略。基于不同剂量率、交替和混合杀菌剂的策略已被提倡以减少抗性选择。然而，辩论仍在继续，哪些策略是最有效的，有必要对更多的经验数据的基本进化过程的基础上选择resistance.Three关键杀真菌剂类：唑类，QOI和SDHIs：目前用于控制许多植物病原体。该项目将侧重于巴西的三种主要疾病：小麦稻瘟病（Pyricularia graminis-triumphis）、亚洲大豆锈病（Phakopsora pachyrhizi）和香蕉叶斑病复合体（Mycosphaerella fijiensis和M. musicola）。在所有四种病原体中都检测到对一种或多种杀真菌剂的耐药性，但在巴西境内是否出现耐药性或产生耐药性的分子机制尚不清楚。此外，人们对疾病流行的发生知之甚少，因此，无法实现适当的抗耐药性战略和最佳疾病控制。为了合理化杀菌剂投入，（例如产品选择、剂量率、喷洒频率和时间以及杀真菌剂的混合/交替），并测试旨在减少病害接种物的抗抗性策略（例如大豆的作物空闲期的影响）和延迟对当前和新的杀真菌剂的抗性的进化和传播，高通量监测工具，需要能够定量测量病原体水平和检测杀真菌剂抗性等位基因，并结合疾病预测。我们将开发实时疾病监测，使用自动化孢子捕获与病原体DNA检测。巴西病原体分离株的杀菌剂抗性的状态和分子机制将被评估，并通过实验进化和抗性等位基因的功能特性预测进一步的抗性进化。然后，我们将开发快速，高通量监测杀菌剂耐药性的分子诊断。将创建一个在线门户网站，与农民、农业化学工业和其他利益攸关方分享工具、成果和建议。改进的疾病预测和优化的疾病管理策略将有利于种植者（降低生产成本），消费者（食品安全，减少残留）和环境（减少农药应用），避免不必要的（无流行预测）或无效的（高水平的抗性）杀菌剂应用，并延长杀菌剂的有效性。

Resistance to chemical agents used to control pests, weeds and pathogens is a threat to effective crop protection and therefore to food security. Tighter regulations and a slowing pipeline of new products have also reduced the range of available chemical classes. This has led to a greater dependence on fewer fungicides and mode of actions, increasing the selection for further cases of resistance. The limited availability of effective crop protection products, coupled with lack of genetic resistance in major crop varieties, is making key pathogens increasingly difficult to control. In order to prolong the effective life of current and new crop protection products, evolution-smart integrated pest management strategies are needed. Strategies based on different dose rates, alternations and mixtures of fungicides have been advocated to reduce the selection of resistance. However, debate continues as to which strategies are most effective and there is a need for more empirical data on the fundamental evolutionary processes underlying the selection of resistance.Three key fungicide classes: azoles, QoIs and SDHIs: are currently used for the control of many plant pathogens. This project will focus on three major diseases in Brazil: wheat blast (Pyricularia graminis-tritici), Asian soybean rust (Phakopsora pachyrhizi) and the banana Sigatoka disease complex (Mycosphaerella fijiensis and M. musicola). Resistance to one or more fungicide groups has been detected in all four pathogens, but the occurrence of resistance within Brazil or the molecular mechanisms conferring resistance are not yet known in all cases. In addition, onset of disease epidemics is poorly understood and, therefore, appropriate anti-resistance strategies and optimal disease control cannot be achieved. In order to rationalise fungicide inputs (e.g. product choice, dose rate, spray frequency and timing, and mixing/alternation of fungicides), and to test anti-resistance strategies aiming to reduce disease inoculum (for example effect of crop free periods of soybean) and delay evolution and spread of resistance against current and new fungicides, high throughput monitoring tools, enabling quantitative measurement of pathogen levels and detection of fungicide resistant alleles, in combination with disease forecasting, are needed. We will develop real-time disease surveillance, using automated spore trapping with pathogen DNA detection.The status and molecular mechanisms of fungicide resistance in Brazilian pathogen isolates will be assessed, and further resistance evolution predicted through experimental evolution and functional characterisation of resistant alleles. We will then develop molecular diagnostics for rapid, high-throughput monitoring of fungicide resistance. An online portal to share tools, results and recommendations with farmers, agrochemical industry and other stake holders will be created. Improved disease forecasting and optimised disease management strategies would benefit growers (lower production costs), consumers (food safety, residue reduction) and the environment (reduced pesticide applications), by avoiding unnecessary (no epidemic forecast) or ineffective (high levels of resistance) fungicide applications, and prolonging the effectiveness of fungicides for when they are needed.