What we do
We take a cross-disciplinary approach to understand how climate change impacts plant productivity and health. By quantifying dynamic growth, molecular and metabolic responses, we are learning how plant growth strategy changes in different field and climatic conditions. This research has provided valuable insights into how plants are able to withstand temperature change. It has also found practical low-tech and molecular methods to improve production in crowded field and indoor crop conditions.
At a field and landscape scale we have expertise in water, carbon and nitrogen use efficiency in natural and farmed systems. We use aerial and satellite imaging methods to monitor plant growth across landscapes in near real time. This approach is being applied to optimise crop management by precision agriculture and as a tool to forecast the impact of different weather scenarios on crop yield.
Scalable Predictive Modelling:
Integrates data across different scales, from growth rooms to glasshouse and field levels. The single plant level we have constructed models that help us understand how the external environment controls plant growth and resource partitioning. At field scale, we combine aerial (e.g. UAV) and satellite imaging data with high performance computing to model plant growth across space and time. Our dual approach provide powerful tools to decipher the effects of a changing environment at the plant, field and landscape scales.
We are developing affordable 3D and 2D imaging platforms to capture dynamic plant growth. The 3D platform enables detailed time-resolved precision analysis of aerial plant architecture. The 2D platform (http://phenotiki.com) scales up to multi-plant imaging using standalone or iPlant-based software for trait extraction from Arabidopsis (e.g. growth, morphology, leaf count and semi-automated leaf segmentation). Software is driven by machine learning algorithms and relies on a simple user interface to ease interaction. Both platforms can be deployed in controlled environments or field conditions and are being adapted for use in a range of plant species.
Alongside these platforms we are also assembling a low-cost analytical platform that captures dynamic root growth and architectural traits throughout the plant life cycle in soil. It is currently used for Arabidopsis but will be extended to root systems of most non-tuberous plants (http://doerner.bio.ed.ac.uk).
Field Scale Surveillance:
We employ aerial (e.g. UAV) and satellite imaging to monitor plant growth at field sites and across landscapes. We are using advanced sensing, ecological principles and information technology to guide management for increased yield resilience and nutrient use efficiency at farm scale.
Our goal is to improve sustainable agriculture in the UK by precision farming. We plan to use new technologies to assist farmers in managing their crops for the most efficient production. These technologies include satellite monitoring of crop states, use of drones to fly over crops for intensive measurements, modelling of crop development, and large computing power. We then generate maps identifying for farmers those areas on their farms where yields are below what they could be, and by how much, and what they should do to improve yields. Our approach is designed to help farmers use fertilisers more sparingly, to target their efforts on soil improvement in the areas that need them most, and to optimise their irrigation. Our focus crops are wheat and potatoes.