Plant sensing to determine environmental impacts on developmental processes leading to crop yield

在其整个生命周期中，植物受到许多不利的环境条件的影响，包括低光照水平和干旱或极端温度的时期，这会显著影响植物的存活并限制生产力。为了科普这种压力，植物在代谢和生理上进行调整。在一系列作物品种中，作物发育的意外变化已经很明显，导致产量不稳定，对农村经济、环境和福祉产生重大负面影响。樱桃和蓝莓是最好的例子，根据季节的不同，可能会发生一种被称为樱桃六月下降的情况，未成熟的水果从树上掉到过多的水平，大大降低产量。类似地，在蓝莓中，根据季节实现了广泛变化的产量，其中诸如芽萌发的因素是重要的。目前还没有方法来了解植物的发育何时以及如何被破坏，或者确定负责的关键环境信号。在这两个领域缺乏知识严重限制了积极作物管理的能力，以优化产量或培育未来的环境适应力。这项工作将使用基于现场的植物和环境监测的方法来开发蓝莓芽的启动和樱桃六月下降的环境模型。我们将尝试识别由植物对环境条件的短期响应（“感知”）产生的信号，以识别植物发育导致不想要的表型（过度的六月落或过度的营养芽发育）的点。蓝莓和樱桃是英国生产潜力巨大的主要作物，但目前仅分别占英国水果市场的7%和5%。目前的扩张，特别是在樱桃目前阻碍了这种不可预测的发展表型，“六月下降”，这可能导致80%的果实损失。蓝莓的产量在不同季节的变化高达50%。项目产出将首次允许进行现场环境监测和作物表型分析，以了解控制作物生产的环境因素，并开发定制的作物管理系统，以减轻环境变化的影响，确保未来作物产量稳定，并鼓励新种植园减少樱桃进口。这些输出还将应用于广泛的其他作物，其中可以检测其他表型病症，并开发用于缓解的方法，以及用于植物育种，其中可以基于植物对环境条件的响应的成像信号来选择品种。

Throughout their life cycle, plants are subjected to many adverse environmental conditions including low light levels and periods of drought or extreme temperatures which can dramatically affect plant survival and limit productivity. In order to cope with such stresses, plants adjust metabolically and physiologically. Unanticipated variation in crop development is already in evidence in a range of crop varieties resulting in yield instability with significant negative impacts on the rural economy, environment and wellbeing. Cherry and blueberry are prime examples where, depending on season, a condition known as Cherry June Drop can occur where unripe fruit fall from the tree to excessive levels, drastically reducing yield. Similarly in blueberry widely varying yield is achieved depending on season with factors such as bud initiation being important. Currently no methods exist to understand when and how a plant's development has been disrupted or to characterise the key environmental signals responsible. The lack of knowledge in these two areas severely limits the capacity for active crop management to optimise yield or to breed for future environmental resilience. This work will use a field based plant and environmental monitoring approach to develop environmental models of blueberry bud initiation and cherry June Drop. We will attempt to identify signals that arise from the plants short-term responses to environmental conditions ('sensing'), to identify the point(s) at which the plant's development leads to the unwanted phenotype (excessive June Drop or excessive vegetative bud development). Blueberry and Cherry are key crops with great potential for UK production but which currently supply only 7% and 5% respectively of the market with UK fruit. Current expansion particularly in cherry is presently impeded by this unpredictable developmental phenotype, 'June Drop', which can lead to fruit losses of 80%. In blueberry, yield varies as much as 50% across seasons. Project outputs will allow, for the first time, the ability to carry out in-field environmental monitoring and crop phenotyping to understand environmental factors controlling crop production and develop bespoke crop management systems that will mitigate the effect of environmental variation and ensure future crop yield stabilisation and for cherry to encourage new plantations to reduce imports. The outputs would also have application to a wide range of other crops where other phenotypic disorders can be detected and methods developed for mitigation and also for plant breeding where varieties can be selected based on imaging signals of plant responses to environmental conditions.