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Multi-user Equipment (MUE) approved in the grant 20/07611-9: Real Time Quantitative PCR (qPCR) Instrument

Abstract

Some plant diseases are becoming very difficult to control due to lack of host resistance cultivars and limited availability of fungicides for crop protection. Fungicide resistance, tighter regulations and a slowing pipeline of new products are reducing the range of available chemical classes. This leads to greater dependence on fewer active ingredients with fungicide modes of action, and subsequently increases the selective pressure 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 increase the shelf life of new and currently available fungicide actives, "evolution-smart" (i.e., guided) 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. This project will focus on the plant pathogen Pyricularia oryzae Triticum lineage (PoTl), the causal agent of wheat blast, an important fungal disease in Brazil that is very difficult to control, with several groups of fungicides (e.g., sterol demethylase, quinone outside and succinate dehydrogenase inhibitors) became (or having become) ineffective. In addition, onset of disease epidemics is poorly understood and, therefore, appropriate anti-resistance strategies and optimal disease control cannot be achieved. To improve wheat blast control, a better understanding of the disease epidemiology, the fungicide sensitivity/resistance status and new disease management strategies are needed. In this project we will focus on all three aspects using the latest spore trapping technology, fungicide pheno- and genotyping sensitivity/resistance assays 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. We will then develop molecular diagnostics for rapid, high-throughput monitoring of fungicide resistance. These tools are generic and can be applied to study evolution and selection of fungicide resistance mechanisms in other pathogens that are important to Brazil. (AU)

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