By Edd Gent

Supercomputers and genetic engineering could help boost crops' ability to convert sunlight into energy and tackle looming food shortages, according to a team of researchers.

Photosynthesis is far from its theoretical maximum efficiency, say the authors of a paper in Cell, published on 26 March. They say that supercomputing advances could allow scientists to model every stage in the process and identify bottlenecks in improving plant growth.

But the authors add that far more science spending is needed to increase yields through these sophisticated genetic manipulations, which include refining the photosynthesis process.

"Anything we discover in the lab now won't be in a farmer's field for 20 to 30 years," says lead author Stephen Long, a plant biologist at the University of Illinois at Urbana-Champaign (UIUC) in the United States. "If we discover we have a crisis then, it's already too late."

The paper says that, by 2050, the world is predicted to require 85 per cent more staple food crops than were produced in 2013. It warns that yield gains from last century's Green Revolution are stagnating as traditional approaches to genetic improvement reach biological limits.

Instead, the group says crops such as rice and wheat, which evolved the more common C3 method of photosynthesis, could be upgraded to the more efficient C4 process found in crops such as maize, sorghum and sugar cane.

This could be done by transplanting genes from C4 plants to widen the spectrum of light the receiving plants can process and improve their growth, the scientists say.

Long's lab has demonstrated in a soon-to-be-published paper that inserting genes from cyanobacteria, a type of photosynthetic bacteria, into crop plants can make photosynthesis 30 per cent more efficient. A project backed by the philanthropic Bill & Melinda Gates Foundation is now attempting to convert rice from C3 to C4

The paper identifies two steps necessary to achieve these gains. First, techniques that allow researchers to insert genes into targeted parts of the genome must be translated from microbe biotechnology into plant biotechnology. Second, existing partial computer models of crop plants must be combined into a complete simulation.

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