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

感知差距：从分子到景观尺度的作物胁迫表达

• 批准号: MR/Y034252/1
• 负责人: Holly Croft
• 金额: $ 75.89万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FY034252%2F1
• 关键词: Sensing; gap; Expressions; crop; stress

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.

粮食安全是人类本世纪将面临的最紧迫的挑战之一。人口不断增长，饮食习惯不断变化和气候变化正在给作物产量施加前所未有的压力。因此，未来的作物必须对气候变化和（a）生物胁迫有弹性。尽管现代农作物品种的产量很高，但这导致依赖数量减少的农作物和品种，导致对害虫和疾病的脆弱性以及气候变化。利用不同农作物品种和陆地上存在的遗传多样性为可持续的粮食生产和近距离差距提供了一个机会，通过确保农作物对当前和未来的环境进行了优化。但是，确定基础作物生理反应的分子机制是复杂的。根据其基因组，环境和如何管理它们之间的相互作用，作物表达表型特征。确定给定的作物品种将如何应对不同的环境条件是指导育种计划的关键。通过测试农作物基因组对环境条件的反应以及这些疾病如何影响整体产量和农作物对压力的弹性，通过测试作物基因组如何反应来支持表型研究。但是，这是资源密集的，并且在农作物种植的时间和环境的范围内有限。迫切需要利用新颖的遥感技术和最先进的建模方法，以模拟在不同的环境场景下，遗传调节的作物生化，结构和生理特征如何影响产量。关闭此基因型到场尺度间隙需要可在高吞吐量下部署的稳健缩放方法。利用我们对生理特征和通量遗传控制的理解将增强我们预测作物基因组在不同环境条件下如何反应的能力。