Departmental Research Themes
As with many research providers, the questions that we are being asked to investigate by our funders are becoming more complex, requiring multiple disciplines to come together. Interdisciplinarity and collaborative work are becoming the norm and NIAB EMR is committed to expanding this way of working by creating teams to address specific problems.
- Crop breeding and genetics – this theme contains commercial breeding programmes and applied genetics. Advances such as speed breeding and marker-assisted breeding are also led from this research theme
- Durable disease resistance- combining multiple disease resistance targets to lead to varieties that have robust and long-lasting resistance is crucial as part of integrated pest and disease management
- Fruit development and quality– underpinning this theme is the identification of specific characteristics implicated in yield (i.e photosynthesis), and the aroma and flavour profile of fruits. The knowledge gained here will be used to develop new varieties with higher yields, improved flavour and quality suitable for commercial utilisation.
- Imaging and measurement technologies– advances in computer vision, machine learning, the internet of of things and automated image acquisition are crucial technologies for quantifying variation in plants and microbes. This theme utilises these technologies to inform both crop breeding and functional trait characterisation
- Microbial and population genomics– this theme aims to both improve our understanding of microbial diversity and to harness microbial diversity of both pathogenic and beneficial microbes associated with horticulture. It involves going from population level data to candidate DNA regions associated with phenotypes of interest that can be functionally validated. It also explores what evolutionary processes drive the expansion of pathogen populations and how growing systems affect this.
- Technology development– work in this theme revolves around developing and deploying new technologies that can be applied in the field of crop genetics, for example- the development of rapid and cost-effective genotyping
- Statistical genetics and informatics– modern breeding requires the latest developments in quantitative genetics to be married to bioinformatics, in order to optimise breeding through prediction of crop performance using high volumes of phenotypic and genotypic data