Sensing the gap: Expressions of crop stress from molecular to landscape scales

粮食安全是本世纪人类面临的最紧迫的挑战之一。不断增长的人口、不断变化的饮食习惯和不断变化的气候正在给农作物生产带来前所未有的压力。因此，未来的作物必须对气候变化和(A)生物压力具有弹性。虽然现代作物品种是为了高产而培育的，但这导致对作物品种和品种数量减少的依赖，导致对病虫害和气候变化的脆弱性。利用不同作物品种和地方品种存在的遗传多样性，通过确保作物根据当前和未来的环境进行优化，提供了可持续增加粮食产量和缩小产量差距的机会。然而，确定支撑作物对环境胁迫的生理反应的分子机制是复杂的。作物根据它们的基因组、环境和它们的管理方式之间的相互作用来表达表型特征。确定特定作物品种将如何对不同的环境条件做出反应，是指导育种计划的关键。表型研究的基础是测试作物基因组对环境条件的反应，以及这些条件如何影响作物的总产量和对压力的适应能力。然而，这是资源密集型的，而且范围受到作物生长的时间和环境的限制。迫切需要利用新的遥感技术和最先进的建模方法，在不同的环境情景下模拟受基因调控的作物的生化、结构和生理特性如何影响产量。缩小这种基因型到田间规模的差距需要强大的扩展方法，这些方法可以在高吞吐量下部署。利用我们对生理性状和通量的遗传控制的了解，将增强我们预测作物基因组在不同环境条件下的反应的能力。

Food security is one of the most pressing challenges that humans will face this century. A growing population, shifting dietary habits and a changing climate are placing unprecedented pressure on crop production. Future crops must therefore be resilient to climate change and (a)biotic stresses. Whilst modern crop varieties have been bred for high yields, this has led to a reliance on a diminished number of crop species and varieties, resulting in a vulnerability to pests and disease and a changing climate. Leveraging the genetic diversity that exists across different crop cultivars and landraces offers an opportunity to sustainably increase food production and close yield gaps by ensuring that crops are optimised to current and future environments. However, identifying the molecular mechanisms that underpin crop physiological responses to environmental stress is complex. Crops express phenotypic traits according to interactions between their genomes, the environment and how they are managed. Identifying how a given crop cultivar will respond to different environmental conditions is key to guiding breeding programmes. Phenotyping studies are underpinned by testing how crop genomes respond to environmental conditions, and how these conditions affects overall yields and the resilience of the crops to stress. However, this is resource intensive and limited in scope by the time and environment that the crops are grown under. There is a critical need to harness novel remote sensing techniques and state-of-the-art modelling approaches to model how genetically-regulated crop biochemical, structural and physiological traits affect yields, under different environmental scenarios. Closing this genotype to field-scale gap requires robust scaling methodologies that can be deployed at high throughputs. Leveraging our understanding of genetic controls on physiological traits and fluxes will enhance our ability to predict how crop genomes will respond under different environmental conditions.