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Pulse-Downy Mildew Pathosystem: deploying disease resistance pathogenomics and microbial biocontrol

Objective

Accessing adequate amounts of nutritious, safe, and culturally appropriate foods in an environmentally sustainable manner is important for a growing population. Producing enough food in the future is possible but care must be taken not to damage the ecosystem and biodiversity. The current recommended approach promotes sustainable intensification: using less water, fertilizer and pesticides to obtain greater yield. Many pesticides may leave residues in or on treated fruits, vegetables, and grains as well as in soil even if they are used according to the manufacturer's instructions. We hypothesise that identifying new sources of disease resistance, coupled with the identification and proper monitoring of the prevailing pathogen isolate, and selection and use of a beneficial microorganism could in combination control downy mildew on pulses, enabling more effective control of disease while reducing pesticide use. In current predictive breeding programmes, identifying the prevailing isolates is imperative for the efficient use of gene pools. This project focuses on the identification of new disease resistance sources and development of tools for accurate detection and diagnostics of pea and broad bean downy mildew isolates, Peronospora viciae f. sp. pisi (Pvp) and P. viciae f. sp. fabae (Pvf), respectively. Specifically, we aim to: 1) Characterise the genetic basis of resistance in pea and broad bean to Pvp and Pvf, respectively; 2) Construct annotated genomes of Pvp/Pvf to enable pathogenomics to generate molecular markers for monitoring DM races; 3) Develop isolate-specific diagnostic tools to increase speed/accuracy of detection of Pvp/Pvf and decrease reliance on lengthy differential testing; 4) Identify effectors that differentiate Pvp and Pvf races; and 5) Explore microbial biological control agents to suppress Pvp/Pvf.

Investigators
Dr Thomas Wood
Institution
National Institute of Agricultural Botany
Start date
2020
End date
2023
Project number
BB/T016019/1
Categories