Data science to feed a changing world: superior drought tolerance in nutritious traditional beans

越来越多的极端天气事件威胁着人类确保全球粮食安全、消除贫困和实现公平、可持续社会的努力。因此，有必要确定和改进更能耐受极端气候（如干旱和热胁迫）的主粮作物品种。该项目将使用高光谱成像和基因组学方法来筛选来自安第斯山脉的普通豆地方品种对缺水胁迫的反应，安第斯山脉是它们的起源中心之一。普通豆类是世界三分之一人口的蛋白质和必需营养素的主要来源，也是有用的饲料和土壤肥料。该项目将有助于为豆类育种提供信息，以在气候变化的情况下保障未来的豆类产量。

The growing number of extreme weather events threatens humankind's efforts to ensure global food security, eradicate poverty and achieve fair, sustainable societies. There is consequently a need to identify and improve staple food crop varieties that are more tolerant of climate extremes, such as drought and heat stress.The project will use hyperspectral imaging and genomics methods to screen the response to water deficit stress of common bean landraces from the Andes, one of their centres of origin. Common beans are the primary source of proteins and essential nutrients for a third of the world population as well as useful forage and soil fertilisers. The project will help to informing bean breeding to safeguard future bean yields under climate change.