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

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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.