Dynamic Plant Phenotyping for future proofing crop productivity

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One of the most pressing current research strategic challenges is meeting the demands for food production as the population increases, and it is estimated that we need to produce around 70% more food by the year 2050 and we also must achieve this in the face of climate change. Although there has been significant advances in molecular biology and genetically modified approaches to altering plant performance the bottleneck preventing advancement is now determining the phenotype of the plant. A plant phenotype refers to observable traits (e.g. height, colour) and plant phenotyping is the assessment of such traits, and in this application include the use of specialised cameras that capture spatial and temporal images of plants under various conditions and use these to determine key traits such as growth (using RGB), photosynthetic rates (using chlorophyll fluorescence), water loss and leaf temperature (using thermography). The PlantscreenTM also employed a hyperspectral camera that is capable of taking reflectance images from plants at a range of different wavelength that covers the electromagnetic spectrum.Although several UK phenotyping platforms provide phenotyping capabilities (including some of the sensors mentioned above) these are limited to glasshouses, small contained platforms, or the field and as such provide limited if any capability for those working on GM crops. In addition we need to be able to understand the phenotype of the plant in a real-world fluctuating environment such as the dynamic environment of a field situation or the predicted changes in climatic conditions in the future. Therefore the proposed equipment bid here will provide a dynamic screening platform (DynSCREEN) with a state-of-the-art robotic Plant ScreenTM housed in a novel newly constructed dynamic indoor environment capable of mimicking any outdoor environment both now and in the future. This capability will not only enable users to translate genetic resources into targets for crop improvement, but it will also facilitate the development of new phenotyping approaches. Hyperspectral reflectance will be used to develop new phenotyping tools and protocols by selecting various reflectance wavelengths that can be used as a proxy measurement for a trait of interest that it is not possible to image. For example, models have been developed from hyperspectral reflectance spectra that correlate with the maximal capacity of the key photosynthetic enzyme Rubisco. We will also build on previous work at Essex to develop a high throughput screen for plant water use efficiency which is a measure of carbon gained relative to water loss. This will be achieved by combining measurements of chlorophyll fluorescence that provide an indication of photosynthetic electron transports, with thermal measurements which are a proxy for water loss, producing images of intrinsic water use efficiency. This to date has not been achieved in any existing phenotyping platform and therefore will provide a unique UK capability and ensure that UK phenotyping remains at the forefront of this dynamic field of research.