Genetically modified food has only been on the market for about 15 years, and has in that time attracted considerable controversy.

But farmers have, of course, manipulated the genetic make-up of crops for centuries, by selectively cultivating specimens with favourable attributes.

Now, a computer system being developed by Imperial University promises to boost the speed and efficacy of selective cultivation by allowing researchers to predict the impact of various environmental factors upon particular strains of a crop.  

Today, assessing the resistance of a new strain of a crop to, for example, a given pesticide or weather condition is the work of months. But by applying machine learning, whereby correlations between the genetic factors are calculated algorithmically, the Imperial team believes it can reduce that process to mere minutes.

“We believe our computing tool will revolutionise agricultural research by making the process much faster than is currently possible using conventional techniques,” says Professor Stephen Muggleton of the Department of Computing at Imperial. “We hope that our new technology will ultimately help farmers to produce hardier, longer-lasting and more nutritious crops,” he says.