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

Funded by: 

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    Project 104624

Cherry Berry is a study of how environmental conditions can disrupt the development of both blueberry and cherry. 

Throughout their life cycle, plants are subjected to many adverse environmental conditions including low light levels and periods of drought or extreme temperatures.  These can dramatically affect plant survival and limit productivity. In order to cope with such stresses, plants adjust themselves both metabolically and physiologically which can cause variations in crop development resulting in yield instability which has significant negative impacts on the rural economy, environment and wellbeing.

Cherry and blueberry are prime examples of this.  Depending on the conditions of the season, a condition known as Cherry June Drop can occur where unripe cherry fruit falls from the tree to excessive levels, drastically reducing yield. Similarly, in blueberry, seasonal factors have an impact on bud initiation and varying yield is achieved.

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. 

The Cherry Berry project uses a field-based plant and environmental monitoring approach to develop environmental models of blueberry bud initiation and cherry June Drop, attempting 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 will also be applicable to a wide range of other crops where other phenotypic disorders can be detected and methods developed for mitigation developed; and also for plant breeding where varieties can be selected based on imaging signals of plant responses to environmental conditions.

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