World demand for food is growing because of population growth and economic development – as people get richer they tend to eat more meat which indirectly raises the demand for grain. Supply growth – higher yields, better performing crops, agronomy, farming skills, and the supply of land – has not kept up.

Meanwhile, the threat of climate change is becoming clearer with preliminary studies showing that rising global temperatures alone could reduce the productivity of the world’s main crops by over 25%. Climate change will also increase the number of droughts and floods that can wipe out an entire season of crops.

One of the simplest insurance strategies to pursue to help combat this risk is to breed better varieties that yield more food and to fight off the myriad threats that farmers and their crops face.

But we are in a hurry. Never before has the world’s environment – under man-made climate change – been shifting so fast. And never before has the planet seen so many hungry human mouths to feed – nine billion at 2050 and counting. 

Previous simulations on crop improvement show that the benefits of using improved crop varieties can be substantial provided that the traits of interest are identified early. Useful traits include tolerance to heat, drought, salinity and resistance to major pests and crop diseases.

If the world is to efficiently unlock the potential of plant genetics to feed a hungry world in the future, then new systems of ‘mining’ these genetic resources held in agricultural gene banks need to be developed. Plant breeders are in a hurry to solve problems of rampant pest and disease loss, cold, heat and drought tolerance, and salinity tolerance.

The task, as it stands, has been described as looking for a needle in a haystack. Using current methods and funding levels it is impossible to screen all available plant genetic materials to identify seed samples carrying the genetic variation required for new crop breeding improvements and breakthroughs.

This technical barrier to accessing novel genes is a major constraint to increasing crop productivity, to reducing poverty, and to ensuring food security, all of which are now even more acutely needed due to climate change and environmental pressures.

FIGS uses cutting-edge applied Bayesian mathematics and geographical information data to help plant breeders more effectively sort through the millions of plant samples conserved in the world’s seed gene banks. Put simply, it facilitates the rapid identification of traits that make crop varieties tolerant to drought, excessive heat or cold, and resistant to insect pests and a variety of crop diseases that reduce field yields in low-income and more developed countries.