Radiation modelling offers crop disease hope

Wheat infected with wheat stem rust.
Wheat infected with wheat stem rust.

Aggressive new strains of the stem rust plant disease – such as Ug99, so named because it was first detected in Uganda in 1999 – have the potential to cause devastating crop epidemics, famine, and massive financial loss. 

Now, however, biosurveillance authorities can potentially head off invasions of these crop killers, thanks to the repurposing of early warning systems originally used to forecast ash dispersal from erupting volcanoes and radiation from nuclear accidents. 

A team of scientists from the University of Cambridge, Britain’s national weather service, the Met Office, and the International Maize and Wheat Improvement Centre (CIMMYT) have adapted disaster modelling systems to predict when and how Ug99 and other strains are most likely to spread.

The research, published this week in the journal Nature Plants, quantifies for the first time the circumstances – the routes, timings and outbreak sizes – under which dangerous strains of stem rust could spread out of East Africa to the large wheat-producing areas in India and Pakistan.

“The combined expertise from plant sciences and atmospheric dispersion sciences has delivered ground-breaking tools that highlight the risks, and support the management of the devastating potential of these diseases,” says the Met Office’s Matthew Hort, a co-author of the research.

Stem rust, named for the blackening pustules that infect plant stems, destroyed crops for centuries before being tamed by fungicides and resistance genes. Although Ug99-resistant varieties of wheat do exist, little of the crop grown in Africa and the Middle East has adequate defences.

The emergent strains threaten to disperse trillions of pathogenic fungal spores on winds across countries and continents. The current global economic loss from wheat stem rust is approximately $1.26 billion a year.

The fear is that these airborne and highly virulent strains could spread from current locations to some of the world’s most important breadbasket regions, such as the Punjab in South Asia.

Maps of spore dispersal networks in africa.
(A) This is a long-distance dispersal network of spores between all major wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. Nodes represent countries; communities of the same colour indicate regions with high airborne connectivity; the size of nodes indicates node-strength; pie charts show the fraction of out-strength to total node strength (indicating donor and receptor countries). (B) Spore transmission frequencies along principal migration routes in the Rift Valley zone for the scenario of large outbreaks.
Matthew Hort

“New races of wheat rust are threatening wheat worldwide, and we need to know which areas are at risk,” says senior author Chris Gilligan, from Cambridge’s Department of Plant Sciences.

Surveys have highlighted the role of Yemen as a potential stepping stone for the transmission of the disease between continents, in particular directly to Pakistan or India. In case of a large outbreak in eastern Yemen, research indicates a 30% chance for transmission to occur.

“From our work, we now believe that if we start to see Ug99 or other new wheat rust strains take hold in Yemen in early spring, then action must be taken immediately to mitigate the risk of further spread,” Gilligan says.

The modelling work also offers some encouraging news, however: the airborne transmission of the disease from East African countries directly to South Asia is highly unlikely, with transmission events possible only on less than one day a year.

The scientific team used field disease surveys from the International Maize and Wheat Improvement Centre and weather data from the Met Office as key input for the modelling framework.

The team says its work, including 3D spore dispersal animations and a catalogue of dispersal trends (indicating likely directions, frequencies, pathogen loads), provides new ways to raise awareness, communicate risks, and inform agricultural stakeholders.

The modelling framework can be applied as a tool to analyse risks in case new disease strains should be uncovered in other geographic areas. This has already helped in estimating dispersal risks from sites of other diseases in Europe and Siberia. 

In ongoing work the team is developing an early warning system forecasting rust risk in Ethiopia, East Africa’s largest wheat-producing country.

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