Mathematics helps find food crops' climate-proof genes
Impacts - such as drought, pest and disease - could hit harvests and undermine global food security. Scientists hope the models will speed up the process of identifying traits, such as drought resistance, allowing breeders to grow climate-proof crops. Dry areas account for 40% of land cover and are home to more than 2.5bn people, BBC News reports. At a recent workshop in Morocco, leading mathematicians and crop scientists met to discuss ways that applied mathematics could be used to speed up the search through agricultural genebanks for climate change resistant traits in the banks' samples. Dry area characteristics include persistent water scarcity, frequent droughts and land degradation - features that are expected to worsen as a result of future climate change. Critical need Experts say there is a critical need for a new generation of crops that have improved tolerance to heat and drought in order to meet the food security needs in the future. "We are seeing the spread of diseases more now than in the past, and heat-related issues are becoming more prevalent than in the past," explained Abdallah Bari, a senior scientist at Syria-based International Center for Agricultural Research in the Dry Area (Icarda). Globally, there are 1,700 major agricultural genebanks that house in excess of seven million samples - a vast resource that researchers say makes the task of locating the sought-after traits a bit like finding a needle in a haystack. Dr Bari said that developing mathematical models would help focus the search by "targeting the [samples] with a high probability of finding those traits and reducing the time it takes". He explained that the Icarda team were developing a technique that used a "learning algorithm" to harvest the necessary data that would allow plant breeders to "zone in on the desired traits, such as tolerance to pests, diseases, drought and heat".
