NemaRecognition will be a machine learning based automatic image recognition technique capable of real-time detection of PPNs using digital images/videos. Plant clinics carry out a suite of services for growers and their advisers. A key service is the assessment of soil samples for PPN. PPN screening is carried out through time-intensive taxonomic identification, this is reliant on taxonomic expertise and several years of training. Trained nematologists are in short supply, causing concern in the industry as accurate and reliable identification of PPN is a critical factor influencing agronomic decisions. PPN affect various crops and can devastate yields, with losses up to 35% (AHDB, 2017). Growers screen fields prior to planting to identify and quantify PPN to help decide on the crop to be planted/avoided, guide variety choice, and advise control strategies. PPN screening can cost £70 per field per season and represents a substantial cost. More rapid, cost-effective assessment methods would represent a cost saving to growers. Alternatives, such as molecular-based tests, have been developed but have substantial shortcomings in accuracy, breadth of use, and grower-confidence. AI algorithms have been developed for nematode identification; however, the majority only identify one PPN genera (Bogale et al., 2020; Akintayo et al., 2018). NemaRecognition would represent an innovative state-of-the-art solution for PPN assessment by providing recognition for multiple PPN genera, and through further development would become one of the first machine learning-based techniques providing plant health services to UK growers. Image-recognition techniques have been developed for other agricultural pests (e.g., insects). However, significant challenges to producing a transformative PPN recognition system using machine learning techniques remain, including recognition of a range of PPN genera, detection in field samples, recognition through video-capture, validation, benchmarking, and selection of appropriate models. NemaRecognition would have myriad benefits, including reduced grower costs (passed down through plant clinic cost savings), increased accessibility to PPN screening in regions where services are inhibited by a taxonomic skills shortage, and as a training tool to help address the taxonomic skills shortage within the industry. Global challenges have been influential in creating this opportunity: UK net-zero farming, EU Sustainable Use Directive, UK path to sustainable farming. The NemaRecognition project will showcase the feasibility and applicability of this technology toward PPN detection and would also represent proof-of-concept for developing similar innovations for other soil-dwelling organisms, with significant potential in the growing area of soil health services.

Most major changes in UK wheats, such as the introduction of dwarfing genes (which reduced plant height, but increased the yield) have been introduced from wide crosses. Wide crosses can still be used to introduce new genes which allow further major changes to be made in UK wheats. The proposal presented here will introduce new genes conferring longer ear rachis (= axis of the ear) associated with improved ear fertility from Mexican wheats (from CIMMYT) which could facilitate a quantum leap in overall yield in UK wheats. The material to test this has already been produced. Specifically, we have created a population of lines from a cross between the Mexican 'big-ear' line and a productive (highly efficient at turning sunlight into sugar) UK adapted wheat, Rialto. In a preliminary study, we have shown rachis length to be positively correlated with ear fertility (and grain number per unit land area). This proposal asks for funds to look at why the Mexican wheat produces more grain for each ear than UK wheat and whether we can use the same genes to improve UK wheat yields. The programme works with UK plant breeders from CPB-Twyford Ltd to produce wheat pre-breeding lines containing these new genes from the Mexican material. For breeders to introduce novel traits into elite UK varieties, they must first know which genes are responsible for controlling the traits and how they work to cause differences between varieties. So, we will map the genes controlling ear fertility and in doing so develop genetic markers to facilitate their selection in breeding programmes. The weather and environmental conditions can vary considerably between different countries and genes that may be useful in some countries may not be in others. We plan to carry out physiological experiments which would identify why the Mexican wheat has more grains in each ear and how this might help improve wheat yield in the UK varieties. We will also carry out experiments to examine whether these genes influence other important determinants of yield at the crop level, such as ear number and grain weight. Crucially, there should be added benefits due to the high photosynthetic ability of Rialto combined with more fertile ears in the 'big-ear' line. We already have seed from the crosses which are needed to do this work, but need funding to understand how wheat controls the number of grains produced per ear. Our industrial partner will use their breeding expertise to make new lines suited to UK breeding, and we will help develop these lines and also use these lines to help us understand the genetics of how many grains are produced per ear. Using this combined approach we will then identify a pool of candidate genes which may directly influence this trait.

THE SARIC CHALLENGE: This translation project was directly formulated in response to a major industry challenge presented by Duncan Rose (Cawood Scientific) at the recent SARIC Sandpit Event. The challenge is to "understand why there is a poor uptake of soil analysis across the UK livestock sector and to design novel recommendation and interpretation systems for livestock farming systems". To address this, Bangor University and Rothamsted Research have teamed up with five influential industrial partner organisations (Cawood Scientific, British Grassland Society, RSK ADAS, Charlie Morgan GrassMaster Ltd & AHDB) alongside a range of associate partners (e.g. NIAB, Welsh Government, Yara-Lancrop, Farming Connect, Eurofins, SoilCares etc.). Their commitment to the project is highlighted in the numerous letters of support. NATURE OF THE PROBLEM: Soils represents a vital resource within UK livestock production systems and it is important that they are well managed to ensure the long-term economic survival of the industry. Fundamental to this is the regular testing of the soil to make sure that there are no chemical, physical or biological imbalances that either constrain production or cause environmental damage. While uptake of standard soil testing by farmers within the arable sector is high, there is compelling evidence that the opposite is true for the livestock sector. Consequently, despite encouragement from policymakers, regulators and farming organisations, numerous studies have shown that soils under livestock production in the UK are frequently sub-optimal in terms of their P and K status and soil pH, as well as soil structure. Ultimately, this lack of testing causes reductions in yields due to excess acidity, under-fertilisation and compaction, while in some cases, over-fertilisation results in wasting money on fertiliser and increasing the risk of environmental losses. This is resulting in underperforming farms and economic losses across the livestock sector. In the current era of sustainable intensification, it is essential that nutrients are used efficiently, and yield gaps are closed through simply 'getting the basics right', resulting in improved resource utilisation and farm incomes. This suggests that current strategies to promote soil testing are not working well and that new approaches are required. Looking to the future, it is also clear that the livestock sector will probably have to embrace soil-based agri-tech to retain its competitive advantage. Based on current evidence, it is likely that the adoption of these new methods of soil testing may also be very slow. A critical assessment of the barriers to adopting (i) basic soil testing, (ii) more comprehensive soil testing, and (iii) emerging technologies is therefore required. TACKLING THE ISSUE AND OUTCOMES: In response to this challenge, and together with our industrial partners, we have designed six interlinked work-packages (WP) to tackle the problem from multiple angles. Firstly, we will map the spatial and temporal trends in soil testing within the UK (WP1). Secondly, we will identify the major barriers which prevent farmers from undertaking soil testing (WP2). Thirdly, we will set up on-farm demonstrations to illustrate the benefits of soil testing in areas where adoption is poor (WP3). Looking to the future, we will also evaluate what soil-based agri-tech solutions are on the horizon and evaluate the likelihood that farmers will adopt these technologies (WP4). This information will provide the foundation for a series of participatory workshops and dissemination events with the stakeholder community to demonstrate the benefits of soil testing to grassland farmers (WP5). Lastly, we will synthesise all the information in WP1-5 to produce an industry-focused road map for promoting life-long adoption of soil testing within the livestock industry (WP6). We expect to see tangible benefits to the industry within 5 years of this project commencing.

The proposal aims to advance our understanding and predictions of interactions between hydrology and nutrient transfers in headwater catchments in the UK, under climate and land use change scenarios to 2050, using the very latest data and modeling approaches available for the UK. The study catchments will be the UK Demonstration Test Catchments (DTCs) and the aims will be achieved through: (1) using existing climate model scenarios to set baseline outcomes for change; (2) localized DTC-focused stakeholder elicitation workshops to develop scenarios for land use changes in response to the climate scenarios; (3) simulating current hydrological events and future changes in catchment hydrology in response to changing climate/land use; (4) new understanding of phosphorus (P) behaviour in extreme hydrological conditions, using experiments and newly available high resolution observations from the DTCs to inform model development; (5) improved prediction (with uncertainty) of future P behaviour scenarios arising from the new understanding of hydrology-P interactions; (6) attempting to scale up the information from headwater-catchment to full basin scale, and; (7) compare model performance with existing P models and assess uncertainties involved in this process, with further iterations of stakeholder consultation. We shall focus on the 10 km2 scale because this matches the size of the nine study catchments of the Defra DTCs (from the Eden, Wensum and Avon DTCs), which are our chosen study areas; this scale also represents the ideal size for studying processes along the mobilisation-delivery-in-stream impact 'transfer continuum'. These integrated studies will produce a prototype quantitative assessment and prediction of nutrient fluxes. Our hypothesis is that increased seasonal variability in storm patterns (more extreme events, long drought periods), combined with interactions with land use change, will greatly alter future dissolved and particulate P fluxes across the land-water continuum and subsequent retention in-stream and downstream eutrophication risk. We shall extend our initial 'Systems Evidence Based Assessment Methodology (SEBAM)' study that focused on mobilization of P at the farm scale (recently published by the team), into a prototype modeling framework that includes source, mobilization, delivery and in-stream processing functions for predicting P fluxes from UK headwater catchments, and considers land use change, and use this framework (combined with knowledge from other projects involving the team) to scale up our information to define the potential for predicting other nutrient behaviours at the full basin scale. We will capitalize on the new and unique high quality, high temporal resolution P monitoring data that is starting to emerge from the nine Defra DTC sub-catchments. A unique and exciting aspect of the work will be the use of expert elicitation procedures that incorporate fuzzy uncertainty-based analyses to develop tailored land use scenarios (building on the UK Land Use Foresight Initiative) for each of the unique landscape typologies for the 9 DTC focus catchments. Combining this information with the latest climate scenarios for the UK, we will include new developments in high-resolution numerical weather prediction. We shall then use these scenarios to study the impacts of climate and land use change to 2050 on hydrology, P mobilization, delivery and in-stream processing, informed from new empirical learning and experimentation. Model outputs will then be validated for other catchments in the wider UK (Conwy, Ribble, Tarland) using data from linked projects and our partners. Throughout the project, the outcomes will be tested with stakeholders. This will deliver a locally owned knowledge-based framework for understanding and managing future nutrient transfers from rural catchment systems, and some exciting new science on P transfers.

Soils are a life support system for global society and our planet. Soils directly provide the vast majority of our food; they are the largest store of carbon in the earth system; and they regulate water quality and quantity reducing the risk of floods, droughts and pollution. In this way, soils provide a natural form of infrastructure that is critical to supporting both rural and urban communities and economies. Despite the criticality of this infrastructure, we do not understand: - the current delivery of services in terms of food production, water flow and quality regulation and carbon storage - from which soils do these services derive and what value do they have for rural/urban communities? - how the decisions we make regarding land drainage, tillage, crop choice, livestocking, tree planting, deforestation, and urban development influence the capability of the soil to provide its' multiple services, or how these decisions may interact. - how resilient our soil infrastructure will be to a changing climate and the increasing pressures to produce more food from less land that our global society faces in trying to feed a population of 9 billion by 2050, and ongoing urbanisation. This lack of understanding stems from a lack of integration across traditionally separate scientific fields that relate to soil infrastructure. Soil functioning is the product of hydrological, physical (soil erosion and weathering), biological and chemical processes, and as such it requires knowledge to be combined across these fields. This fellowship will draw together these disciplines to create a new computer model that will improve our understanding of soil infrastructures, their value to society and their resilience. This model will be used to explore how future scenarios will influence the provision of food-water-carbon services to our societies. Uncertainty and risk analyses will be performed to provide a coherent robust evidence base for decision-making. This will allow us to find ways to enhance our soils to provide more benefits for our societies, improving sustainability and well-being. This fellowship aims to: a. Assess the value of soils as a natural infrastructure that protects and enhances both rural and urban areas through food production, water regulation and carbon storage. b. Estimate the resilience of soil infrastructure to climate change and changing land-use pressures and explore the potential for managing soil infrastructures to mitigate risks and enhance their value and resilience. c. Transform the perceived value of soil infrastructure in communities and businesses, and enhance decision-making capabilities across sectors to help create sustainable resilient societies. The outputs of this fellowship will include: - Scientific insights into soil functioning, sustainability and resilience. - The first valuations of soil as an infrastructure, it's capacity for enhancement, and it's vulnerability to a changing climate and increasing land use pressures. - Estimates of the uncertainties surrounding these estimations, and how this influences to the risk to delivery of food, water and carbon services. - Quantitative predictive modelling frameworks that can support sustainable, resilient decision making across food, water and environment sectors. - Deepened engagement between scientists, businesses, policy makers, and NGOs.