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.

Use of meteorological data in biosecurity

“…Wind speed and direction are vital for understanding dispersion plumes and potential incursions across borders, e.g. incursions of Culicoides , the Bluetongue midge into UK [ 82 ] or Sicily [ 83 ], or Wheat rust diseases in Ethiopia [ 84 ]. Although wind data are available from most sources of met observations or models and can be used for simple dispersion estimates, ADMs or trajectory models (see above) are typically needed to capture the complex dynamics and interdependencies involved in atmospheric dispersion and deposition [ 25 ].…”

Applications of Biotechnology for Characterization of Plants and Pests as the Key Components of Plant Protection and Production Strategies: A Review

“…(Wang et al, 2013). Early warning systems to predict and mitigate transboundary pant pests have been developed for desert locust (Schistocerca gregaria Forskål) (Cressman and Hodson (2009), Fall Army Worm (Spodoptera frugiperda JE Smith) (Prasanna et al, 2018), wheat rust diseases (Allen-Sader et al, 2019). The technology involves daily automated data flow and utilises expertise and environmental research infrastructures from within the cross-disciplinary spectrum of biology, agronomy, meteorology, computer science and telecommunications.…”

Wheat rust epidemics damage Ethiopian wheat production: A decade of field disease surveillance reveals national-scale trends in past outbreaks

“…Today, the on-going field disease surveillance efforts are the essential backbone of a near real-time wheat rust early warning system in Ethiopia. The early warning system integrates field surveys, phone surveys, meteorological and epidemiological models to assess risks and to predict wheat rust outbreaks [ 10 ]. Recently, disease monitoring was further improved by carrying out in-field gene-based disease diagnostics using MARPLE—a Mobile And Real-time PLant disEase system [ 11 ].…”