An early warning system to predict and mitigate wheat rust diseases in Ethiopia

Abstract

Wheat rust diseases pose one of the greatest threats to global food security, including subsistence farmers in Ethiopia. The fungal spores transmitting wheat rust are dispersed by wind and can remain infectious after dispersal over long distances. The emergence of new strains of wheat rust has exacerbated the risks of severe crop loss. We describe the construction and deployment of a near realtime early warning system (EWS) for two major wind-dispersed diseases of wheat crops in Ethiopia that combines existing environmental research infrastructures, newly developed tools and scientific expertise across multiple organisations in Ethiopia and the UK. The EWS encompasses a sophisticated framework that integrates field and mobile phone surveillance data, spore dispersal and disease environmental suitability forecasting, as well as communication to policy-makers, advisors and smallholder farmers. The system involves daily automated data flow between two continents during the wheat season in Ethiopia. The framework utilises expertise and environmental research infrastructures from within the cross-disciplinary spectrum of biology, agronomy, meteorology, computer science and telecommunications. The EWS successfully provided timely information to assist policy makers formulate decisions about allocation of limited stock of fungicide during the 2017 and 2018 wheat seasons. Wheat rust alerts and advisories were sent by short message service and reports to 10 000 development agents and approximately 275 000 smallholder farmers in Ethiopia who rely on wheat for subsistence and livelihood security. The framework represents one of the first advanced crop disease EWSs implemented in a developing country. It provides policy-makers, extension agents and farmers with timely, actionable information on priority diseases affecting a staple food crop. The framework together with the underpinning technologies are transferable to forecast wheat rusts in other regions and can be readily adapted for other wind-dispersed pests and disease of major agricultural crops.

Keywords: agricultural science; atmospheric transport; crops; epidemic modelling; food security; weather; wheat.

Figure 1

Environmental research infrastructures from the different project partners and how together with other components, these make up the Ethiopian Wheat Rust Early Warning System. Solid lines indicate the initial structure of information flows, dashed boxand arrows Indicate phase 2 flows in the next version of the Early Warning System. Green outline boxes indicate existing environmental research infrastructures. Yellow outline boxes show the new tools and models developed (or future planned development) especially for this wheat rust Early Warning System. Red boxes indicate the Early Warning System output. ^aNumerical Weather Prediction. ^bUnified Model ^cNumerical Atmospheric-dispersion Modelling Environment ^dOpen Data Kit. ^eMinistry of Agriculture and Livestock Resources. ^fOther stakeholders include Federal and Regional government agencies, Research institutes, Non-governmental organisations (NGO’s), Food and Agriculture Organization of the United Nations (FAO).

Figure 2

Cumulative weekly stripe rust spore deposition from the NAME dispersion forecasts issued on different days during the 2018 wheat season in Ethiopia. Specifically:(a) issued on 2018–08–10, (b) issued on 2018–09–06, (c) issued on 2018–10–15, (d) issued on 2018–11–17 (e) issued on 2018–12–18.

Figure 3

Cumulative weekly stem rust spore deposition from the NAME dispersion forecasts issued on different days during the 2018 wheat season in Ethiopia. Specifically: (a) issued on 2018–08–10, (b) issued on 2018–09–06, (c) issued on 2018–10–16, (d) issued on 2018–11–24 (e) issued on 2018–12–18.