University of Reading

Country: United Kingdom
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1,475 Projects, page 1 of 295
  • Funder: UKRI Project Code: G0601762
    Funder Contribution: 67,409 GBP
    Partners: University of Reading

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: BB/L02697X/1
    Funder Contribution: 10,081 GBP
    Partners: University of Reading

    United Kingdom

  • Funder: UKRI Project Code: 1943033
    Partners: University of Reading

    The integrity and traceability of food products are of interest to consumers, farmers, manufacturers and policy makers throughout the world. Recent focus on traceability, the supply chain , fraud including the so called 'horsegate' crisis of 2013 demonstrate a need for improved systems for monitoring and authenticating the source(s) and supply chain of food products(1). A recent government commissioned report (1) contained eight recommendations to regain and enhance public trust in the food supply chain. Of these recommendations, four are of direct relevance to this proposal including the development of resilient and sustainable laboratory services that use standardized, validated approaches to authenticate the provenance, integrity and traceability of food products. Recent analytical developments in high throughput DNA sequencing (HTS) now make it possible to analyse ecology samples containing a mixture of species at relatively low cost (2). Furthermore, DNA barcodes exist for UK flowering plants which will act as a database against which unknown mixtures of DNA can be compared. In addition, advancements in stable isotope ratio mass spectrometry (SIRMS) technology mean that high throughput; high precision analyses of food materials are now routinely possible. However, for both these techniques there is a lack of fundamental understanding of the nature and precision of the molecular and isotopic signals derived in many food products. This proposal therefore seeks to develop a multi-proxy, cost-effective authentication protocol for the UK honey industry by understanding the molecular and isotopic signals. The project will integrate, for the first time, evidence from stable isotopes, pollen identification and DNA sequencing to provide robust and repeatable evidence of the provenance, authenticity & traceability of UK honey and an understanding of the nature of these signals in honey. This novel, multi-disciplinary research integrates expertise from geochemistry, molecular biology, phyloinformatics, melissopalynology, and communications technology to provide practical solutions to detect fraud and authenticate the botanical source(s) of honey in the UK. The research will be carried out in collaboration with the Bee Farmers Association and our industrial partner the British Honey Company. Honey samples will be analyzed for a range of stable isotopes, DNA and pollen.These data will be modelled using an 'isoscape' (isotope mapping) approach in ArcGIS ModelBuilder as well as a fully mechanistic ecological model in R that would aim to build a model parameterised by the data from the field. This would be a process-based model for honey to predict the impact of environmental changes based on a raster dynamic distribution approach. The model will also have data incorporated from BHC to produce a predictive element for honey distribution using a probabilistic assignment from the isotope data, together with water datasets available from the literature. The project will finally develop with our industrial partner a system of ScanLife barcodes and QR codes that will be placed on each analyzed hive, to provide an authenticated and scientifically provenanced source to offer consumers scientifically accredited, product to source traceability assurance.

  • Funder: UKRI Project Code: 507297
    Funder Contribution: 91,266 GBP
    Partners: University of Reading

    To develop the core technical platform, dynamic niche website creator and innovative distribution channels necessary to broaden and extend the existing business model.

  • Funder: UKRI Project Code: NE/N018591/1
    Funder Contribution: 626,133 GBP
    Partners: University of Reading

    Climate change is one of the leading global challenges facing society and the planet. Predicting how the climate will change as human activities lead to emission of more greenhouse gases is a global scientific challenge for climate scientists. We use models of the climate to make predictions. Because of limitations in computing power, and because of gaps in our understanding of the climate, these models are not perfect. Predictions from the models are, therefore, also not perfect. We are faced by the huge challenge of extracting robust information from climate models about how real-world climate will change in the future under specified scenarios of different greenhouse gas emissions. Such projections are central to leading climate change assessments, such as those produced by the Intergovernmental Panel on Climate Change (IPCC). This project will provide a step-change in the ability of climate scientists to produce robust projections of climate change and to quantify the uncertainties in projections. A new framework will be developed that combines information from models, observations and our basic understanding of climate with modern statistical techniques to produce projections. This new framework will be applied to three important climate regimes of Earth: tropical and subtropical temperature and precipitation change; middle latitude cyclones and anti-cyclones; and polar temperature and sea-ice changes. We will bring together leading UK scientists (many are IPCC authors) from the Universities of Exeter, Reading, Oxford and East Anglia, and the Met Office, to address this grand challenge in climate science. We aim to precipitate a cultural shift that unifies diverse approaches from techniques to understand climate process and statistical methods and consolidate the UKs position as a world-leading centre for climate projection science.