14TSB_ATC_IR Exploiting novel canopy sensors for improved disease management, variety selection and resilience in wheat

Commercial production of wheat crops in the UK is currently highly dependent on timely applications of fungicides to optimise yield and the development of improved varieties by plant breeders with resilience to diseases and abiotic stresses. There is currently insufficient understanding and knowledge of how fungicide inputs can be optimised to grain yield and how plant health can be rapidly and precisely measured in the field to improve crop management decision-making and efficiency of selection in plant breeding. There is a continuous need to breed crops with improved performance, such as disease resistance and drought tolerance, to ensure food supplies are resilient in the face of a changing environment. The bottleneck is now in the ability to conduct field-based discovery and evaluation of traits (phenotyping), which are currently laborious, time-consuming and inefficient. The project will therefore develop canopy sensor phenomics platforms, based on chlorophyll fluorescence and hyperspectral imaging systems, which will allow a high throughput and detailed evaluation of crop performance. Chlorophyll fluorescence signatures (FP100 Fluorpen amd multiple detection probes Waltz) for estimating photosynthetic efficiency in the field will be developed to provide early signatures for biotic (Septoria) and abiotic (drought) stress on wheat. Firstly, this system will be developed in glasshouse conditions on 'stands' of wheat and secondly in-field (6 cultivars x 2 fungicide programmes) to relate these to crop management decisions and breeding selection. Ground-truthing measurements will include:(i) a molecular PCR assay developed for Septoria tritici DNA quantification, (ii) visual disease and (iii) crop growth by destructive harvesting.
We will also develop hyperspectral canopy-sensor signatures to enable imaging across wider wavelength ranges (300 -2300 nm) and larger plot areas and with a higher throughput than is currently used for in-field crop monitoring: A high throughput, automated imaging system using a hyperspectral camera mounted on a tractor will be used to produce a spatial map of a complete field experiment (6 cultiars x 2 fungicide treatments). Data sets will be mined to identify a new metric from a subset of wavelengths predicting key traits, e.g. canopy green area, crop biomass and N content. Groundtruthing measurements will include: (i) crop growth by destructive harvesting, (ii) handheld hyperspectral measurements (FieldSpecHandHeld 2 Pro (350-1075 nm), Analytik Ltd) and (iii) visual disease. A key objective here will be to investigate the feasibility of replicating hand-collected and tractor mounted hyperspectral datasets using UAV (Oktocopter2) mounted sensors for aerial imaging.
The phenotyping platforms will be validated by agronomists for optimised crop decision-making at three sites (high Septoria, high drought and control) in validation trials (6 cultivars x 2 fungicide programmes; 2 fungicide programmes x 6 fungicide treatments) and by breeders for varietal selections at one site in the project. The high-throughput canopy sensors (ground-based and aerial) will be tested as decision tools and provide a step change in the efficiency of wheat predictive agronomy and breeding and a basis for improving wheat for UK farmers, processors and consumers.

Commercial production of wheat crops in the UK is currently highly dependent on timely applications of fungicides to optimise yield and the development of improved varieties by plant breeders with resilience to diseases and abiotic stresses. The bottleneck is now in the ability to conduct field-based discovery and evaluation of traits (phenotyping) which are currently laborious, time consuming and inefficient. This project will therefore develop canopy sensor phenomics platforms, based on chlorophyll fluorescence and hyperspectral imaging systems, which will allow a high throughput and detailed evaluation of crop performance. Chlorophyll fluorescence signatures for estimating photosynthetic efficiency in the field will be developed to provide early signatures for biotic (Septoria) and abiotic (drought) stress on wheat. Firstly, this system will be developed in glasshouse conditions on 'stands' of wheat and secondly in-field to relate these to crop management decisions and breeding selection. We will also develop hyperspectral canopy-sensor signatures to enable imaging across wider wavelength ranges (300 -2300 nm) and larger plot areas and with a higher throughput than is currently used for in-field crop monitoring: A high throughput, automated imaging system using a hyperspectral camera mounted on a tractor will be used to produce a spatial map of a complete field experiment. Data sets will be mined to identify a new metric from a subset of wavelengths predicting key traits, e.g. canopy green area, crop biomass and N content. A key objective here will be to investigate the feasibility of replicating hand-collected and tractor mounted hyperspectral datasets using UAV mounted sensors for aerial imaging. The high-throughput canopy sensors (ground-based and aerial) will be tested as decision tools and provide a step change in the efficiency of wheat predictive agronomy and breeding and a basis for improving wheat for UK farmers, processors and consumers.

Who will benefit from the research?

In the short term, the project will benefit researchers, agronomists and plant breeders in the commercial and public sectors by providing access to techniques, tools, resources, software and datasets that include:
- Novel chlorophyll fluorescence and hyperspectral imaging to phenotype pre-symptomatic disease (Septoria leaf blotch) detection and early drought stress, canopy green area and biomass under field conditions.
- Image analysis software to aid aerial phenotyping activities using hyperspectral imaging combined with Unmanned Aerial Vehicles.
- Development of wheat guidelines with novel canopy-sensor traits for use in commercial agronomy and plant breeding programmes.
- The novel phenotyping tools will be relevant to other cereals species (e.g. barley, rice and maize) and other biotic stresses (foliar diseases).

In the medium to longer term, the project will have impact in the UK and internationally:

- Create a world-leading UK phenotyping capacity that will radically impact efforts to improve crop performance by collaborating agronomists and commercial breeders.
- Deliver a public database for international collaborators, commercial breeders and general users in which phenotyping and genotyping data will be linked in databases.
- The proposal will provide training for young researchers in a wide range of plant physiological, plant pathological, computer science and genetic approaches and techniques, including crop trait dissection and image analysis in hexaploid wheat. These skills are currently in very short supply in the commercial sector.
- The involvement of a major UK breeding company (RAGT Seeds Ltd) in the project will ensure that opportunities are not wasted in exploiting the deliverables of the project (pre-breeding germplasm, traits and genetic markers) for germplasm development.

The project will benefit policy makers in several ways:

- Novel chlorophyll fluorescence and hyperspectral imaging and the development of ideotypes combining favourable traits to buffer effects of climate change and exploit reduced agrochemical inputs in new sustainable cropping systems, thereby aiding delivery of Global Food Security.
- The new programme will enhance disease resistance/tolerance and yield stability of UK wheat germplasm and provide understanding of the biological basis of key canopy photosynthesis traits underlying enhanced disease resistance/tolerance and drought and yield in UK wheat.
- A major advantage of our project is that the UK plant breeders RAGT Ltd will deploy the phenotyping tools to for genetic improvement in their wheat-breeding programme. The benefits of genetic improvement are permanent and cumulative.
Accrued public good benefits from crop breeding to improve traits with improved nutrient- and water-use efficiency and the use of new, improved cultivars by farmers would include a reduction in greenhouse gases and overall energy use (climate change mitigation).