Powered by OpenAIRE graph
Found an issue? Give us feedback

ENDORSE: ENhancing Diversity to Overcome ReSistance Evolution

Funder: UK Research and InnovationProject code: BB/S018956/1
Funded under: BBSRC Funder Contribution: 522,270 GBP

ENDORSE: ENhancing Diversity to Overcome ReSistance Evolution

Description

Despite its place as a global leader in agriculture, each year the Brazilian agricultural economy loses approximately $15 billion to insect crop pest outbreaks. Indeed, insects consume 10-20% of all global crops while growing or in storage. Current agricultural practices in Brazil rely heavily on widespread pesticide application, which has led to the evolution of pesticide resistance in several significant insect pests. Such practices undermine the sustainability of important crop pest control technologies, reduce associated economic returns, and exacerbate the risks to economic production and food security in Brazil. We propose a revolutionary approach to pest management that will enhance the sustainability and long-term resilience of crop production, providing the benefit of managing insect pests more predictably. Our solution comes from evolutionary science and the particular features of host-pathogen interactions. Insecticide resistance evolution occurs when a single control agent is applied over a broad area, then consistent evolutionary pressures drive rare resistance genes to spread rapidly through the pest population. To prevent these sweeps of resistant alleles, we are investigating how multiple fungal pathogen strains can be used in a spatial matrix across agricultural landscapes, so that selection for resistance varies in different locations, preventing a uniform evolutionary response. On their own, multiple pathogen strains may not be sufficient because of cross resistance: genes making pests resistant to one fungal strain could also confer resistance to others. However, in host-pathogen systems, the optimum genotype to defend against one pathogen is often highly sensitive to the organism's environment. Simultaneous manipulation of an environmental landscape variable (the type of crop grown by farmers) will substantially decrease the consistency of selection: we predict this will prevent resistance evolution. In order to achieve real-world effectiveness of this pest control system, an integrated team of Brazilian and UK researchers will work together to establish the long-term prospects of our new solution. The aims are to: 1. Examine whether genetic variation for insect susceptibility to multiple fungal biopesticides under heterogeneous agricultural landscapes is stable, and assess how it responds to selection in the long-term. This will allow us to anticipate and avoid selection for resistance to multiple strains, and ensure the long-term sustainability of our pesticide resistance management system. 2. Investigate the suitability of fungal biopesticides for industrial scale production and field application in Brazil, which will facilitate product development for future industrial investment. We will also provide farmers and the crop protection industry with solutions for crop protection technology deployment, including improved delivery systems, higher pest control consistency and enhanced performance under field conditions. 3. Identify the barriers to uptake of our new pest control technologies and research methods to encourage farmer behavioural change. This research will provide economic and social science data to underpin advice for policy recommendations regarding incentive schemes, publicity campaigns and marketing strategies, thereby promoting uptake of these sustainable pest management practices.

Data Management Plans
Powered by OpenAIRE graph
Found an issue? Give us feedback

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

All Research products
arrow_drop_down
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=ukri________::b9b6c2ed99cf922da7cd8d1d1fcfcb8f&type=result"></script>');
-->
</script>
For further information contact us at helpdesk@openaire.eu

No option selected
arrow_drop_down