The fruit industry relies on a small number of varieties and a decreasing number of chemicals, presenting serious challenges for future sustainable growth. No suitable high-quality varieties with resistant to pests and diseases are available. This is coupled with climate change where unpredictability in phenotypic expression is resulting at both small and large spatial scales. The ultimate aim of much of the research, therefore, is to understand the development of phenotype and to facilitate knowledge-based breeding of sustainable high quality resistant soft fruit varieties through the development of tools and training of modern breeders. The identification of links between genotype and phenotype, and the subsequent identification of molecular markers for deployment in a breeding context is essential so that efficiency of selection and ultimately time to cultivar release can be improved and accelerated beyond current timescales. The research has been possibly through the development of genetic linkage maps in raspberry and blueberry and other fruit crops and mapping QTL to assist in the understanding of complex traits of commercial and environmental importance. In raspberry genome sequences and GbS maps have allowed us to link traits to underlying genes. A range of other genomics tools are being utilised to study changes in gene expression in response to various conditions. The traits of most interest include pest and disease resistance, season and fruit quality traits including flavour, colour and softening.

InnovateUK-funded research

Imaging sensor solutions in the soft fruit industry for high-throughput phenotyping and monitoring of abiotic and biotic stresses for premium variety production and maximised yields

New crop varieties that can tolerate abiotic/biotic stresses are essential for maintaining crop productivity in current and future growing environments. Breeding stress-tolerant crop varieties, however, is limited by the precision and throughput of plant phenotyping. This project will develop and apply a novel method for precise and high-throughput field phenotyping of soft fruit crops using infrared thermography and hyperspectral imaging combined with precision agriculture to optimise crop inputs. Changes in shoot and leaf physiology can provide an indirect indicator of abiotic and biotic root stresses, which can be monitored with imaging techniques. Soft fruit crops such as raspberry can experience multiple stresses in field conditions, including poor soil conditions, variable water availability, and attack by root rot pathogens and root-feeding vine weevil larvae. Phenotyping data will be linked to genetic markers to facilitate breeding of productive, stress-resistant soft fruit varieties. This novel high-throughput phenotyping platform will accelerate the development and release of productive high-quality soft fruit varieties that perform well in sustainable reduced input cropping.

Using genomics technologies to determine the mechanism of resistance to phytophthora root rot in raspberry for future breeding applications to raspberry and other crops

In the Northern Hemisphere with damper conditions, Phytophthora root rot is causing a rapid decline in raspberry plantations grown in soil and also greatly decreasing the life span of production of raspberries grown in substrate with negative environmental consequences. Plant-based resistance is the only way forward and limited material exists that consistently withstands infection with little/no symptom production. The development of gene-based techniques offers an opportunity to identify genes that have a significant role in this plant-pathogen interaction to determine the mechanisms of resistance and develop novel strategies of protection including breeding. How both resistant and susceptible varieties respond at the level of gene expression and how the pathogen responds to the differing phenotypes will identify gene markers and allow strategies for control to be developed.

Application of genomics in raspberry variety development

Significant advances have been made in the development of genomics and metabolomics technologies in raspberry. Industry has recently identified a gap in the process of transferring these technologies into breeding platforms which can be utilised to improve speed and precision in variety development possibly reducing 5 years or more in development. Currently there is an unmet demand for UK-grown soft fruit and great scope for increasing the number of consumers who purchase soft fruit in season with currently only 36% uptake. The fruit industry relies on a small number of varieties and a decreasing number of chemicals, presenting serious challenges for the future. No suitable high-quality varieties with resistant to pests and diseases are available. A technology platform for breeding multiple traits utilised in high throughput format would lead to significant advances in time to variety development, precision in selection, cost and the pipeline could be transferred to other berry crops.

Breeding for physical resistance traits - protecting soft fruit crops from pests and pathogens

This project aims to understand and utilise plant physical mechanisms for resistance to pest and diseases in soft fruit bush crops, to overcome changes in EU Directive 91/414/EEC and WFD and satisfy future consumer demand for residue-free, high-quality fruit grown in the UK. Fresh fruit accounts for a market of £4 billion in the UK, and berries account for 17% of this. UK raspberries have a value of £121 million, strawberries £196 million, blackcurrants £12 million and blueberry, currently a minor player in cropping area has a value of £95 million. Demand for UK-grown fruit is increasing dramatically; however, few high-quality soft fruit varieties are available with adequate pest and disease resistance due to the emphasis placed on fruit quality by major commercial fruit breeding companies. For production to be sustainable, a greater understanding of plant-derived resistances to pests and diseases is required that can be deployed in IPDM programmes to reduce reliance on chemicals but still produce high-quality fruit. Physical resistance traits are particularly promising for crop protection because they tend to be more durable against pest and disease adaptation, and unlike chemically-based resistance traits, are less likely to adversely affect fruit quality. This work aims to look at root architecture and morphology, leaf trichomes, cane/stem architecture and plant habit to determine how variation in these physical traits contributes to resistance against major soft fruit pest and diseases. Using raspberry as a model, key genes in chromosomal regions controlling variation in these traits can be selected across different fruits and used to greatly reduce the timescale for variety development.

Developing genetic resources in blueberries

Lack of blueberry cultivars with high fruit and nutritional quality combined with early and late ripening is a key issue negatively impacting UK blueberry growers. UK growers are currently planting mixtures of existing varieties, mainly from the USA, but the long-term performance, fruit quality, yield and consumer acceptance of these varieties in the UK varies considerably. This proposed project aims to develop genetic resources in blueberries to identify appropriate breeding and new mapping populations, with pre-selection for traits of economic importance for the UK in order to produce new cultivars that are specifically suited for UK production. A parallel examination to explore genotyping by sequencing as a rapid method to identify SNP dosages in a mapping population of autotetraploid blueberry, will be conduced in order to construct a high-density SNP linkage map and to relate the map information to phenotypic data to improve the speed and precision of a targeted breeding programme.

Improving yield stability in UK blueberry production

Lack of yield stability is a key issue negatively impacting UK soft fruit growers, preventing accurate profit prediction and maximisation, causing volatility of UK supply.  The problem is now well recognised within industry, though the causes of significant season to season yield variation are unknown. This proposal aims to identify the physiological, biochemical & genetic processes underlying yield limitations, thereby identifying causes of the yield volatility phenotype. An examination of the impact of growing environment and management on yield will be undertaken to allow development of predictive yield maps & models that provide frameworks for yield optimisation in the short to medium term. This underpinning knowledge will be transferred to growers and also used to develop molecular markers for yield stability allowing long-term solutions to the problem, thereby future proofing the UK soft fruit industry, particularly blueberry crops with application to other fruit crops.