Public Funding for Agri-Epi Centre Limited

This proposal builds on the work of the Regulatory Horizon Council, summarised in their 2023 report _Unlocking the potential of robotics in Agriculture and Horticulture,_ and follows the Government's Food Strategy (2022), Defra's Automation in Horticulture Review (2022), and Defra's _Independent review into labour shortages in the food supply chain_ (2023). All these papers endorse the role of agri-robotics in the sustainability and resilience of the agricultural and horticultural sectors, and identify regulatory barriers to adoption, and potential future policy enablers. This proposed network for agri-robotics regulatory science and innovation will raise the sector's profile with regulators, delivering evidence to build progressive regulation and policy which will support the widespread adoption of agri-robotics technologies. A wide range of regulation, policy and standards impact agri-robotics development and deployment, leading to a complex landscape and uncertain path to adoption. The network will reflect a diverse and inclusive representation of farmers, technology developers, researchers, regulators and policy makers, and key enablers such as the finance sector, insurers and investors. This will ensure needs, requirements, and perspectives are well-represented to build a shared way forward. We will also seek to learn from other sectors such as manufacturing, automotive and construction, where similar challenges exist or have been overcome. This initial Discovery phase of work will lay the foundation for this network, engaging and securing support from across the agri-robotics sector and its stakeholders, scoping its remit and working collaboratively to develop the Implementation proposal. The consortium for the initial phase comprises two agri-tech centres and a leading academic centre for agri-robotics science, R&D and training. This gives us a strong basis for establishing this network with our extensive collective links in the sector, technical and market knowledge, and independence.

Since the first known examples of grain storage dating back to ~11,000 years ago in the Jordan valley, the process of storing grain (e.g. whole wheat/barley/oilseeds in sheds and silos) has been a critical part of the agriculture industry, essential to preserving the grain's quality and value, as well as to bridge the gap between harvest and its subsequent use. There is an unmet need in the grain storage industry to reduce mass and quality losses (\\\>20%) and improve the health and safety of grain storage operations, as farmers and grain storage operators are still forced to walk on dangerous grain bulks to collect grain samples. The objective of this project is to create the first commercial robotic device able to safely and autonomously collect physical samples from grain bulks at various points and depths, while the grain is still idle in storage and/or large transportation units (e.g. cargoes), where existing methods cannot. While current grain sampling solutions that can only reach near the surface pose a safety hazard to operators collecting the samples, Crover's remote probing device will be able to collect samples throughout the whole shed/silo/truck/cargo. This will provide farmers, grain storage operators, traders and transportation companies with a tool to obtain highly representative and verified samples at different points within grain bulks, hence enabling them to reduce grain claims/rejection, improve the health and safety of their operations, detect potential spoilage, and allowing proactive management to reduce losses and maintain grain quality. The project is made possible by Crover's proprietary technology for locomotion in bulk solids (e.g. sand, grains, powders) and it is based around the CROVER robot: the world's first 'granular drone', in the sense of a device able to move through bulk solids and powders.

**Background** OxiTech's **Pulse Oxidation** technology is a unique, patented, system that creates charged Oxygen within water by using just tap water and small amounts of electricity to create Ozone in-situ, thus chemical free disinfection with a multitude of benefits to dairy farmers: * **Green-tech:** Removing toxic chemicals from the cleaning process with the Ozone dissipating within minutes leaving pathogen free water * **Energy and Carbon Dioxide savings** as much as 5 Tonnes per year on a typical UK dairy farm, achieved mostly through the elimination of waste around the production / transport / disposal of plastic containers with chemical cleaners. Unlike chemical cleaners, OxiTech works with cold water eliminating significant costs and associated CO2 from heating the water * **Animal and farmer friendly:** OxiTech poses none of these risks of traditional cleaning chemicals to either farmer or animals * **Simple to install on existing farms** and proven to work with milking robots and conventional milking equipment * **Controllable:** finely controlled doses and concentration * **Connected:** Intelligent control with IOT remote access * **Easy to use and maintain:** Cells replaced during regular maintenance of existing milking equipment **Project Objective:** To demonstrate that chemical free water disinfection can be used to replace chemicals in the robotic Milking system, thus improving the carbon footprint and sustainability of Dairy Farming.

Bradford Farming is the in-hand farming business of Bradford Estates, located in the Shropshire/Staffordshire borders, farming 5,000 acres producing combineable crops, potatoes, lettuce, wildflower seed, and sheep as part of a sustainable mixed farming system. We propose to explore the feasibility of developing a new weed suppressant product for the horticulture sector, based on wool. Wool is a low value product which barely breaks even at best after shearing costs. Enhancing its value through developing a new product will support improved profitability of sheep farming. The commercial horticulture sector is grappling a number of challenges including reduced chemical weed control options, an upcoming ban on peat in commercial operations, increasingly challenging growing conditions with seasonal extremes. Few non-chemical weed control options exist, and growers rely heavily on manual weeding. Alternative materials have a range of sustainability challenges, and we believe wool offers a sustainable and viable alternative. The novel wool weed suppressant will be trialled in commercial ornamental (roses) and edible (blueberries) horticultural crops. We believe wool could provide a sustainable, UK-produced, viable weed control, benefiting growers and sheep farmers UK-wide. The idea has arisen from discussion with edible and ornamental horticulture growers, seeking sustainable solutions; and sheep producers seeking to add value to wool.

Lameness in dairy cows is an industry-wide issue, effecting farmers' bottom lines and cow welfare, leading to production inefficiencies and increased carbon emission per litre of milk produced. Considered to be the second only to mastitis in cost to the national dairy herd (£53.5 million per year (Royal Veterinary College, 2022)) and the third most common cause of cow cull, with an estimated 22% of all English and Britishdairy cows being lame at any given time, and 55% being lame at some point in the year (Universities Federation for Animal Welfare, 2020); with 1.07million dairy cows in England in 2021 and approximately 800,000 across Wales, Scotland and Northern Ireland (AHDB, 2022) the scale of the welfare issue this represents is immediately appreciable. To be treated, lameness must first be detected and diagnosed; however, depending on the particular cause of lameness, decreases in milk yields may begin up to four months before lameness visibly presents due to DMI intake suppression (DAERA, 2021), leading to financial losses beyond the cost of treatment. NADIS (2021) estimates the average cost of lameness as £178 per case, with 25% of this attributable to reduced milk yield, prolonged calving interval, premature culling and treatment. Given the welfare and cost implications of lameness, English and UK dairy farmers are proactive in reducing and monitoring lameness, with mobility scoring, foot-bathing and regular foot-trimming commonplace. Accelerometer-based precision livestock farming (PLF) tech such as collars, anklets and smart boli have enabled farmers to remotely monitor lameness via movement profiles with more objectivity than a manual mobility score. However, these products are rarely able to reliably detect which foot requires treatment. "Second-generation" technologies utilising camera technologies and AI (Cattle Eye, Herd Vision) are appearing on the market, operating by visually monitoring and analysing cow gait. This project will develop an initial proof of concept design for an affordable lameness and scaleable detection system, utilising thermal and visible light imagery and AI analysis. The system will be able to detect cases of lameness very early and in individual feet, allowing for extremely early, targeted treatment. Rather than detecting changes in gait, the system will detect localised increases in body (foot) temperature and indicative of inflammation and pain. This will allow extremely early inspection and/or intervention with anti-inflammatory drugs, reducing the cost of treatment and loss of production, making for a more productive, higher-welfare and lower-carbon herd.

Along with water and sunlight, nitrogen is essential to the growth of plants and life on the planet Earth. Until the early 20th century, farmers were relying on manure as a scarce commodity to enrich their crops. The Haber-Bosch process enabled the production of synthetic nitrogen fertiliser. Agricultural productivity skyrocketed and food became more available and affordable. However, production, distribution and application of synthetic nitrogen fertilisers now account for 4.4% in total global CO2 equivalent emissions (2.6Gt CO2eq for 2021). Production heavily relies on fossil fuels leading to greenhouse gas emissions and it is centralized, while the consumption is dispersed globally. In fact, there are only about 200 fertiliser manufacturing facilities in the world. The fertilisers made in these facilities are distributed to five billion acres of agricultural land, so the need for transportation further increases emissions. We must fundamentally change the way we have been fertilizing soil (for more than a hundred years). Debye proposes to replace this centralized carbon-intensive process with a decentralized electricity-based one. In this process, farmers would not rely on resource and capital-intensive fertiliser factories and the associated high-cost distribution networks, instead produce their own fertiliser on site by the use of air, water and electricity. It has the advantage of integration with renewable energy making the production completely sustainable. This project aims to show the feasibility of a plasma-based mobile fertiliser machine that produces synthetic nitrogen fertiliser in a completely sustainable and affordable way using only air, water and electricity.

UK fruit growers are facing a major challenge, exacerbated by the diminishing availability of plant protection products (PPP's): controlling crop disease. The phasing out of traditional PPP's, driven by environmental concerns, has added complexity to this issue. Despite utilisation of PPP's, UK apple growers experience an annual crop loss of approximately 10-12% due to apple scab, a fungal disease. Without PPP's, this figure would skyrocket to 70-80%. However, there is a promising solution on the horizon: biostimulants. These are natural substances or micro-organisms that can enhance the natural defences and overall health of the plants when applied to them. However, one significant challenge of biostimulants is assessing their effectiveness as they operate distinctively from conventional PPP's. Biostimulants serve as preventative measures rather than curative, necessitating timely application before visible disease symptoms emerge. Accurately timing their use is difficult, as the critical phase of scab infection remains invisible to the naked eye. Our project aims to address the challenge of evaluating the effectiveness of biostimulants by utilising advanced technologies such as hyperspectral cameras and drones. Hyperspectral sensors can capture and analyse a wide range of spectral bands, providing detailed and precise characterisation of objects or materials based on their unique spectral signatures. By identifying specific spectral signatures for crop diseases, like apple scab, and determining which spectral bands indicate the efficacy of biostimulants, we can develop an affordable camera tailored to the needs of growers. This camera will serve as an early warning system, helping prevent disease spread, enhancing crop yield and operational efficiency, and reducing reliance on traditional PPP's. Upon project success, our system has the potential for broader applications. It can be adapted to test various biostimulants, crops, and diseases, extending its usefulness beyond the initial scope. This adaptability will enable us to gather valuable insights and drive advancements in biostimulant research, crop management, and disease control practices in other UK crops. We can also extend our technology to growers globally, addressing shared challenges related to universal disease, crops, and biostimulants. Our system will contribute to the UK's goal of achieving net-zero emissions by 2050 by facilitating the widespread adoption of environmentally conscious crop management practices and biostimulant use. Moreover, international implementation will promote environmental awareness, reduce carbon emissions, and mitigating the effects of climate change globally.

One of the most essential tasks involved in the production of lamb is the weighing of growing lambs in order to monitor their liveweight gain and suitability for sale. However, this is a time-consuming process and can be stressful to the lambs being gathered and weighed (Dwyer and Gauci, 2004) leading to considerable weighing intervals, limiting the use of weighing to a means of drafting lambs for sale as opposed to gathering extensive datasets to build in-depth pictures of individual and flock growth rates. Such data would allow lamb producers to monitor growth rates, enabling advanced and accurate prediction of lamb sales as well as providing information with which to alter feeding, grazing and breeding management. In order to turn lamb weighing into a less stressful and time-intensive activity, this project will design, prototype and validate on-farm an automated, in-field lamb weighing solution. Three different designs will be evaluated, with a walk-over weigher, creep-feed attractant and platform (designed to utilise a lamb's play instinct) designs, with a data-handling app being developed alongside which will work with all designs. The project will also develop a creep feed meter to monitor whole-flock and individual animal feed intake, in order to provide DMI data to relate to lamb DLWG in creep-feeding settings. Using one of Ritchie's trial farms and three of AEC's satellite farms, Ritchie will construct initial prototypes for each design of weigher and commission them on-farm for validation. Farmers will continue to weigh their lambs as they currently do, with data gathered from this and the auto-weighers being compared to gain insights into the reliability and value of the data gathered from the auto-weigher versus conventional weighing practice by AEC's data and automation team. Lamb weight data will also be carried through to Ritchie's existing auto-drafting equipment to allow for lamb with sufficient weight data to be drafted automatically, reducing lamb stress and operator time at drafting. Lifecycle assessment will be used to examine the differences in carbon intensity between lamb systems with and without auto-weigher solutions to quantify the difference high-resolutions DLWG monitoring may bring. Given the time between weighing intervals and The project will be managed by AEC's PRINCE2-qualified project management team and dissemination will be carried out by AEC's marketing and communications department via their existing multimedia dissemination channels and in conjunction with the National Sheep Association utilising their dissemination channels to broaden the dissemination audience.

The **FLEXBOT** project aims to improve labour productivity in English soft fruit farming operations by integrating collaborative logistics robots (cobots) into the farms. Lead partner **Fox Robotics** will develop and showcase three primary outcomes: demonstrating the feasibility of supply chain interoperability between suppliers, exploring a sustainable business model for small to medium-sized fruit and crop farmers, and establishing an autonomous fruit-farming cobot undertaking various logistics tasks. The project aims to illustrate English fruit farms' scalable productivity and profitability while encouraging a small ecosystem of add-on suppliers and demonstrating the potential for cobot integration into other farm types. The project is a multidisciplinary collaborative R&D activity that aims to align with Defra recommendations and remediate significant fragmentation between technology providers and end-users. Fox Robotics will work with **Agri-EPI Centre**, **three British fruit farms**, and the **University of Surrey** on this project and hire four small innovative businesses to improve their value proposition to farmers by providing complementary technology, products, and services that can be integrated into the cobot platform and scaled as farmers invest in their fleet. The FLEXBOT project aims to move the fragmented and siloed Agri-tech industry towards standardisation using mobile cobot platforms.

This project is a collaboration between VANDENBERGHUK (VDB), Agri-EPI Centre, PEEQUAL Ltd, Royal Agricultural University, Green Square Agro Consulting and Pilio. The focus of our innovation is to convert urine into a viable fertiliser.

The UK wine industry is growing rapidly in size and in sophistication. But even as British wines are winning more and more awards, the industry faces rising labour costs, changing climate conditions, and pressure to reduce reliance on fertilisers and chemical agents. We believe the solution to these challenges is to adopt a data-driven approach to farming. The vineyard of the future will be built on software systems that understand where the crop is and what its condition is. The autonomous farming systems of the future will run on high resolution maps of the vineyard, showing them the location of each vine, row, post, irrigation pump and more. The VISTA project is developing the digital maps that will drive the shift to data-driven farming. We are building the VISTA-Map, an open source mapping protocol that can be used on any commercial vineyard in the UK or in the rest of the world. The map will be high resolution, easy to integrate with other farming systems, and will support data from a variety of sources. Using drones and ground robot systems, we will create high resolution maps of several UK vineyards and use them in two practical applications. First, the VISTA-Map will then be used to generate high accuracy harvest yield estimates for the vineyards. Having better yield forecasts before harvest will allow growers to secure a better price for their crop, and reduce the amount of crop that is wasted because it cannot be sold. Second, the VISTA-Map will be used to create precision application maps, where chemical agents or fertilisers are applied in varying rates using GPS-guided machinery. Using precision techniques like this is common in other areas of farming, and results in reductions of chemical usage and increases in crop yield. The project consortium will also explore how the VISTA-Map could be expanded into a full vineyard digital twin, capturing and modelling aspects of the crop such as weather and climate, soil health, disease mapping and irrigation. To achieve this project, we have assembled a fantastic consortium for this work. Partners bring expertise in viticulture, crop monitoring, drones, robot systems, and 3D and semantic mapping. The VISTA project is a clear route for the UK vineyard industry to move to data-driven farming, providing a solid foundation of data to tackle the problems facing growers in the present and the future.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Grassland accounts for 40% of agriculture land in the England. Yet, the sector is underserved by the precision farming revolution. Working closely with farmers in England, the Agricultural Engineering Precision Innovation Centre (Agri-EPI) & CKX bring a novel approach to gather and analyse data from satellites and digital platforms to support grassland farmers. With access to our cloud-based service via mobile app, farmers can make informed decisions to raise productivity. For instance, an increased utilisation of 1% of grassland, could increase the UK dairy and livestock sector annual profitability by £22m.

Ash Dieback Disease (ADD) is a highly destructive disease of Ash trees, especially England's native Ash species, common Ash (_Fraxinus excelsior_). It is caused by a fungus named _Hymenoscyphus fraxineus_ (_H. fraxineus_), which is of eastern Asian origin. ADD is also known as 'Chalara', which can distinguish it from dieback on Ash trees caused by other agents (Forest Research). ADD was first detected in the UK in 2012 and is forecast to eventually kill 80% of UK ash trees, at a predicted cost of £15bn, with £7.6 billion being the estimate for the next 10 years (Hill et al., 2019). The Woodland Trust (2021) reports that only 7% of UK native woodlands are in good ecological condition. In England, poor condition is characterised by "inappropriate management." Poor woodland and tree health threatens forestry productivity and economic value, biodiversity and ecosystem services, and the ability of woodland to securely store and sequester carbon, undermining progress towards net zero and eroding the confidence in and security of carbon offsetting schemes. Ash also provides an important commercial revenue stream to the growers who produce Ash across the UK. Ash timber is strong, durable, flexible, and attractive, with a wide range of practical and decorative uses such as tool handles, flooring, furniture and joinery It is also important for the making of sports goods, such as rowing oars, sporting bats and hurley sticks, due to its almost entirely shock resistant nature. As one of England's most useful and versatile native tree species, Ash provides valuable habitat for a wide range of dependent species. It grows in a variety of soils and climatic conditions. The 'airy' nature of its foliage allows light to penetrate to the woodland floor, encouraging ground plants and fauna. Several insects, other invertebrates, lichens, and mosses depend wholly on Ash for habitat. Emerging technology from the agri-tech sector will be deployed in the project. The physiology and structure of tree canopies can be estimated by measuring the reflected light with these specialist sensors. By combining this information with expert knowledge of ADD, we can produce predictive models of ADD and other tree diseases. This project will investigate how these models are integrated with decision support systems for informing management of England's Ash trees, developing an affordable solution to benefit smaller woodland owners in identify disease infestation, to allow them to take proactive intervention measures.

Mastitis in dairy cattle is a massive issue facing English and British Agriculture, costing the industry £170 million per year (Volac, 2022). Mastitis-causing pathogens can be spread through the contamination of milking equipment but two of the major mastitis pathogens, E.coli and S. uberis are spread through the environment, which includes transmission via bedding (NADIS, 2022). Therefore, providing the cleanest possible bedding to dairy cows is paramount. The dominant bedding type for dairy cows in the UK is the cubicle due to the high stocking density they can provide in housing and the relative cleanliness compared to lose straw bedding (AHDB, 2022). However, cubicles must be well-designed and kept clean to ensure the cleanest possible bedding environment. Cubicle cleanliness is dependent on the frequency and method of cleaning and the bedding type and conditioners used. Cubicle cleaning is carried out either using a manual brush or a self-propelled or tractor-mounted rotary brush. These methods of cleaning offer no disinfection and can in fact spread pathogens between cubicles. Many bedding materials, used to coat the cubicle mat or mattress are often organic materials (with inorganic materials such in use also) which can culture mastitis pathogens, particularly where cubicles are heavily soiled with manure and leaked milk. This project seeks to start the development of an innovative new self-cleaning cubicle design, which will automatically provide a sterilised cubicle for cows. A move towards automated cubicle cleaning furthers the automation of dairy operations but will also aid in the reduction of on-farm mastitis. Mastitis is costly to the industry due to the use of antibiotics to control infection which leads to a rejection of milk from cows under antibiotic withdrawal, as well as the rejection of milk with a high somatic cell count. Therefore, an auto-cleaning cubicle system could be well-received by the industry. Removing the labour and material cost of conventional cubicles would also represent considerable cost savings to the industry.

40% of insect species risk extinction, a further 30% endangered (New Scientist 2019), yet few farmers actively monitor or quantify on farm biodiversity, despite it being a critically important measure of ecosystem, landscape, overall biological health of the farm, and key public good. This project will monitor biodiversity 24/7 where three separate remote sensing digital technologies will detect, identify, and quantify varieties of invertebrates, and birds, and the correlation to flowering plants that they rely on. Escalating ecological challenges combined with Government policies devised to address the crisis - such as Biodiversity Net Gain, Local Nature Recovery, and emerging Natural Capital markets - mean that efficient methods - which can be widely deployed - to monitor wildlife are in demand. There are not enough expert ecologists to cover the areas and hours required to accurately quantify the state of nature in any one location which makes the capability and accuracy of technological solutions valuable. A key priority of this research project is to act as a 'pilot' which will test and aim to demonstrate the effectiveness of digital technology as a means of remotely monitoring wildlife diversity and abundance in a farming context.

Marine ingredients, in the form of fishmeal, are one of the best sources of nutrients for young farm animals, both terrestrial (especially young broilers and peri-weaning piglets) and aquatic.However, harvesting (fishing) of marine ingredients has a significant impact on the environment, sustainability is stretched to its limits, GHG emissions are significant due to long distance transport and the long-term resilience of the sector is dependent on a fragile environmental balance under climate change threat. Additionally, the animal feed sector is growing rapidly between 2 and 6% a year, for example broiler meat production has increased 500% in the last 40 years, while marine ingredients harvests have been stagnating for the last 40 years. This has led to the current marine protein ingredient crisis.To address the core marine protein availability problem with a long-term solution, as opposed to producing alternative ingredients, Aquanzo is developing technologies to produce, sustainably, at scale and on land, artemia, a marine zooplankton and process it into marine protein ingredients for the animal feed industry. By farming artemia, this novel animal feed production system will offer a long-term solution to the marine protein ingredient crisis. It will benefit the consumers by offering a product with no ocean-harvested ingredients but without losing the proven benefits of marine ingredients inclusion for the animal's health and farming productivity. Additionally, the ability to exploit agricultural byproducts as a feedstock to grow artemia will enhance the UK circular economy. It will benefit the compound feed manufacturers by access to tailored marine proteins, sustainably produced and of constant quality with reduced emission (precision farming system), all of which are not possible from harvesting marine protein. A comprehensive life cycle assessment (LCA) of Artemeal as an alternative protein source is included and will provide a robust quantification of the proposed solution sustainability.To ensure the project aligns to the industry technical, environmental and commercial needs, dissemination and knowledge exchange is a strong component of this project, including through engagement with our expert advisory panel and wider stakeholders. Demonstrating the feasibility of using artemia meal in starter broiler feed (replacing fishmeal) will pioneer a new sector in the animal feed industry. Farmed marine proteins, alongside other novel ingredients such as insects and single cell proteins will develop a portfolio approach to support the development of a strong and resilient animals industry in England, the UK and further afield.

SusProt is unique in creating an on-farm platform to exploit currently unharvested food-grade broccoli biomass and extract food-grade protein from it along with other valuable co-products. The on-farm application and exploitation of currently unutilised broccoli biomass offers significant economic and emission reduction opportunities. Success here will see the platform application extended to other unused primary crop food-safe biomass

Methane emissions are a major cause of climate change and farmers are coming under pressure to act. Every sector of UK farming is responsible for finding ways to minimise their carbon footprint, including the sheep sector. There's a huge opportunity to use genotyping and selective breeding to drive down methane emissions from sheep. The main goal of this feasibility study is to explore how cutting edge technology can be leveraged to produce sheep with 10-25% lower emissions. Research on this concept has been done in New Zealand previously, leading researchers to believe that methane emissions are a heritable trait in sheep. This means sheep emissions can be managed quickly and easily throughout flocks by changing their rams. This project will work towards breeding 'Ultra-Low Emission Sheep' by comparing UK sheep DNA markers with NZ DNA markers for low methane emitting sheep. By using a USA based laboratory for DNA markers and a genetics company in NZ, the first world class breeding program in the UK to drive this technology forward will be developed. Working with international partners will help us produce a global solution to a global problem. The project will also incorporate in-field methane measurement from Scotland's Rural College (SRUC), who are an industry leader in livestock emissions research. This will provide ground truthing data to confirm the DNA comparison made between the UK and NZ sheep. In addition, we will look at increasing meat and wool yield further to reduce carbon per kg of meat for no increased inputs. Wool itself stores carbon so increasing wool yield will enable further carbon sequestration - 1.4kg of wool stories 1kg of carbon. The aim: to offer UK farmers the world's lowest carbon and most efficient sheep.

Viticulture is an expanding sector in the UK with up to 500 vineyards and an increasing interest to expand established areas, but the sector is currently at a crossroads. Advancements in digital technology deployed in other sectors make it easier to capture and manage data and gain insights for effective decision making. Growers, agronomists and AgriTech solution providers are looking at the application of these technologies but there are obstacles to overcome particularly around data sharing and integration. Existing AgriTech solutions have largely been developed in isolation with their own data model driven by the vendor and the application, and when a grower is using multiple different systems, they are frustrated that these systems do not talk to one another making effective decision making more difficult. Some systems appear to be designed to ensure customer retention however there are technical problems in the absence of an industry standard. Overcoming these barriers and creating an open access, industry standard geo-spatial data model will provide new opportunities and accelerate innovation for precision viticulture. Creating a digital infrastructure within a vineyard, mapping all the critical features such a posts, vines and pathways and other infrastructure like boundaries, irrigation points and converting this geospatial information into an open source dataset will allow multiple AgriTech solutions to be deployed without the need to survey on each occasion, therefore saving time and money, and allowing a grower to choose between multiple potential solution providers with the confidence that each would be able to navigate around the vineyard with a drone, robot or tractor based upon the information provided by the grower. The nature of deploying this technology will provide agronomic data on crop growth, stress incidences, and yield which will enable effective decisions to be made on targeted inputs, therefore increasing environmental, economic, and social sustainability of this expanding sector, and create a broader audience for innovative solutions. By creating and developing a digital solution tailored by and for the benefit of the viticulture industry will ensure the outcome will fit the needs of the end users

Hoofcount Ltd are researching the development of an early detection lameness monitoring system. Dairy cows are susceptible to a range of hoof issues including Digital dermatitis, sole ulcers, white line disease and overgrown hooves. These generally show a visual change in the underside and back of the hoof. Particularly in the development of lesions on the skin in the form of Digital Dermatitis (Mortellaro). These issues can develop initially without the animal showing visuals signs in its gait. Detecting and treating these issues at an early stage is beneficial to the animal in keeping the hooves healthy and preventing severe lameness which leads to a lower production, increased veterinary / treatment costs, reduced animal welfare, a higher Carbon footprint along with many other issues. Developing a system that can visualise these changes on a daily basis and detect any potential issues early will be of huge benefit to the national herd. Utilising computer vision and computer learning is Hoofcount's preferred method to monitoring and detecting these issues.

Broccoli one of the UK's favourite vegetables is even today harvested by seasonal workers who walk in the crop to select and cut only the ripe broccoli heads. Growers have been facing chronic labour shortages and increasing costs. In 2021 £' millions of broccoli crops were left unharvested due to a shortage of seasonal labour UK. For 2022 broccoli and brassica growers have cut back their plantings so more broccoli will be imported to meet needs -- driving up costs and increasing food mile CO2 emissions. Farmers across the world are searching for an automated harvesting solution. This project will take a world-leading proof of concept broccoli harvesting machine to infield testing in 2022 and a pre-production prototype in 2023\. The new automated approach will harvest the whole plant, opening up the potential to create valuable and nutritious plant-based foods from what was previously seen as crop waste.

Cereal grains are the basis of staple food, yet post-harvest losses during long-term storage are exceptionally high, above 20% in the UK and worldwide. Pests are to blame, with grain moisture content and temperature being the most significant factors. Cereal storage sites such as farms, grain merchants, millers and breweries, experience these challenges, which have high cost implications in terms of lost revenue and cost to rectify. The scope of this feasibility study is to develop a novel non-contact sensor for non-contact grain analysis able to detect specific molecular compounds within a radius of up to a few tens of centimetres, based on a novel miniaturised sensing technology, and to integrate it onto the ever-improving CROVER robot, the world's first 'underground drone', which fluently 'swims' grain bulks and which is at the core of the CROVER autonomous Grain Storage Management system. This will allow for the potential readings that go far beyond the typical grain storage safety parameter (humidity and temperature, which we will still provide). During the project, we will focus on some of the most prominent variables of grain storage and grain quality: proteins and mycotoxins. Down the line, the result of this project is expected to allow for the expansion of the parameters that we will be able to measure, including specific nutrients (amino-acid composition, fatty acid composition and FFAs presence and quantity and - particularly relevant for oilseeds), or insect presence and species identification (including at eggs and larval stages) aligned with different customer requirements. The rationale for this project is aligned with the arable sector (and of the whole grain value chain) need for novel and alternative crop protection solutions, in support of the current push toward holistic Integrated Pest Management (IPM) approaches.

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**Project:** Oxi-Tech Solutions seek to demonstrate that ozonated water provides a chemical-free alternative for cleaning robotic milking machinery while lowering both costs and environmental impact. The proposal is to also improve herd health, deliver a safer working environment, and lower carbon footprint. **Innovation:** Oxi-Tech core technology is new and disruptive, building on 2 years of concept and market testing. It produces in situ dissolved ozone (eco-friendly disinfectant) from water, using only electricity. This project will deliver a feasibility study to demonstrate ozone efficacy, and how this integrates with milking robots, providing consistently powerful disinfection where and when it is needed.

The UK is the eleventh largest milk-producer in the world, with 2.65 million dairy cows producing 12.6 billion litres of milk each year, worth £4.5billion. Across the UK, dairy cows produce dry mass of over 2 million tonnes/year of excreta, traditionally spread onto arable land and grassland as fertiliser. However, land-spreading causes land, water, and air pollution, damaging agricultural soils, leading to eutrophication of water courses, and increasing greenhouse gas emissions. Working with Agri-EPI Centre, SEM Energy will develop a pilot-scale, zero-waste, on-farm slurry management system to transform slurry into valuable byproducts including fertiliser, growth substrate, and water for reuse.

BioFactory are a design and engineering business focused on waste-to-energy technology. In the UK, high capital costs of commercial Anaerobic Digestion (AD) systems require unsustainable models to be effective. A lack of technological advances and innovation in this sector has led to a market gap between large scale AD solutions and expensive small-scale options. During this project, Agri-EPI will support BioFactory in assessing the feasibility of adapting its existing micro-AD technology to suit the needs of the small-scale agricultural sector, to reduce operating costs and positively impacting GHG emissions to move towards a Net Zero landscape.

This project will develop LightWeeder -- a world-first eye-safe, herbicide-free, carbon neutral, commercially viable light-based weeding system; delivered by lightweight autonomous field robots via UK agri-robotics company Earth Rover (ER).

The horticulture sector is heavily reliant on access to seasonal labour for many field operations, including harvest. Movement restrictions because of Covid-19, post-Brexit uncertainty, competition from other sectors, and the lack of suitable UK-based labour have driven growers to seek investments in labour-replacing technologies. 99,000 tonnes of lettuce were harvested by seasonal workers in the UK in 2019 with a farm gate value of £178 million (Defra BHS, 2020), UK's highest value field vegetable crop. This project has identified an opportunity to automate the process, and reduce the reliance on seasonal labour, by developing an innovative robotic solution. * We intend to adapt existing mechanical capability and lift the lettuce clear of the ground by discs and then gripping the stem with pinch belts. * The lettuce will then be presented to camera sensors that will direct an air blast which will blow the outer wrapper leaves of the lettuce head clear to expose the stem. * Machine vision via deep segmentation will then be deployed using a second camera sensor to train a deep learning model to identify the precise location to be cut. The three separate developments will be combined to form a prototype for field trials towards the end of the 2021 UK season. Engagement with end-users has confirmed their need and willingness to be part of the development of such a machine. Early indications are that harvesting costs could be reduced by around £5,000 per hectare per annum. 123,000ha of lettuce and chicory was grown in the EU in 2018 (FaoStat, 2020) with similar areas in the USA. These areas have similar issues to the UK with access to seasonal labour, therefore the potential market for such an innovative machine is extensive.

From time-to-time a technology comes along that offers potential for significant change and disruptive economic benefit, CDs and smart-phones being cases in point. More modest, but never-the-less significant is the emergent technology based on ultra-fine bubbles (UFBs), also known as nanobubbles. These UFBs are less than a millionth or so of a centimetre in diameter (1000 times smaller than the width of a human hair), which in their stabilised form exhibit a range of remarkable properties, notably their longevity (the period of time they remain as bubbles), and importantly their capability for carrying, in aqueous media, gases of various kinds and bubble surface adherents. As a consequence, they are already realising ground-breaking applications in many aligned industries, including, cleansing-sterilisation, oil, gas, and mineral extraction processes, pharmaceutical, food-flavouring and cosmetic industry, with in-roads into medicine and cancer treatment; each with, or the potential for, £multi-million market values. That versatility in UFB properties, together with advances in UFB research are pointing to significant potential for purposely incorporating appropriately characterised bubbles into agricultural aqueous media, for spraying and irrigation purposes, and with a view to achieving more effective reductions in inputs (water, chemicals, etc.) more effective coverage, water usage, delivery of crop nutrients, pest-control agents and agents for control of plant diseases. The aim of this project is to establish the feasibility of integrating UFB and proven magnetic-assist technology in a generic platform that can be used to specify a wide-ranging modalities and applications, and the basis for new, economically viable and environmentally-friendly products and services. A successful outcome can also mean a significant step towards new UK enterprise and new employment opportunities. Appropriately managed the outcome can turn the £0.25million investment into a rolling agenda for enterprise, conceivably capable of achieving a 100-fold return-on-the investment within five years. The need for greater productivity in agriculture to meet food security challenge is without question, as is the need to do so with regard to environmental protection and climate change. UFB technology has the potential as a technological platform to contribute significantly to meeting these demands. But the benefits do not end there, effective land use and land reclamation are significant considerations in meeting the challenge, as are other planetary boundaries, including, emissions and climate change impact, land and water usage, bio-geo chemical flows and biodiversity.The risk in the investment is modest, the potential for substantive returns for the UK is enormous.

The proposed project will create a precision technology solution for dairy farmers, focused on optimising the rearing of heifer replacements. The project will focus on the following areas: 1. Integration of information from various sources including advanced sensing technology and farm records to obtain the full picture of individual animal condition. 2. A data analysis platform which will continuously analyse the data sources and provide appropriate real-time and automated health and performance flags to optimise intervention strategies. 3. A decision support system to optimise health and management protocols and quantify impact. This will be developed using expert advice from across the supply chain, including veterinary and animal science expertise.

The Quant Foundry Artificial Intelligence (AI) Livestock Surveillance Solution in collaboration with Bristol Veterinary School at the University of Bristol aims to provide a world-class solution for the identification of anomalous cattle behaviour to aid in the rapid identification of different ailments. The solution combines AI-driven video analytics of animals within an automated farm framework to increase health and welfare and lower production costs and emissions. While there are a number of existing solutions for remote monitoring of animals, many require an active involvement of people with little potential cost savings. Other solutions require the use of physical hardware that must be worn by the animal, requiring significant per-animal setup and maintenance costs. Internationally there are a number of ongoing research trials for image recognition, however there is little mention of their use identifying specific illnesses. Many video systems applied to livestock do not scale well with the number of animals, whereas the Quant Foundry system can identify and track multiple animals with little computational overhead. The unique innovation is our general computing model with standard off-the-shelf hardware that will be able to identify many different conditions for each animal. This considerably reduces the time and cost of development, deployment and upkeep. This research and feasibility study will be performed across two areas: (i) classification and identification of key animal behaviour features to be applied to our deep learning algorithm, and (ii) a commercial feasibility study to assess the commercial effectiveness of the hardware and identification algorithm for identifying anomalous behaviours such as lameness and other abnormal motions. The validation study will involve an installation of the system at Agri-EPI Centre's South West Dairy Development Centre to record continuous video of every cow after milking over a 9-month period. Through an existing AI system developed by the University of Bristol, individual cows will be identified and linked to production/veterinary data and behavioural annotations from Bristol Vet School experts, verified by external assessors. This data will be used to validate and refine the Quant Foundry AI solution, and will also be curated for public dissemination as a resource for the field. The final stage will be to assess the overall effectiveness of the primary lameness, mastitis and Johne's disease solution and determine its benefits for commercialisation and research. This would lead to further studies to advance fundamental animal welfare, behaviour and sustainability research.

Imagine being able to walk through a herd of cows, instantly recognising each one -- distilling key individual productivity and health data in real-time, so that you can make the best decisions in order to provide her with the optimal care to enhance her production and welfare. Whether a stockperson, vet, nutritionist, breeding technician, farm assurance auditor or supply chain rep -- you can instantly view a dashboard to understand how each cow is performing and her health status, at the cowside. The emergence of precision agri-tech in the dairy sector has given rise to a multitude of data collection platforms in, around and on dairy cows, such as animal mounted sensors (smart collars, pedometers, tags and boluses), smart milking machines and camera technologies, as well as individual cow records and observations. Farm staff, vets and other advisors are required to access and interpret these multiple data-streams in order to make data-driven decisions on cow health and production management. Yet, accessing multiple data-streams, let alone analysing and interpreting them, is extremely challenging. In practice, the value of much of this data is lost because it cannot be used in a timely and insightful fashion. We have combined technology from the gaming and agri-tech sectors to solve this deficiency. SmARtview integrates multiple data-streams from any technology platform that is deployed on the farm, using AI to identify an individual cow and access her data, together with AR to visualise the integrated analysis to support data-driven decision-making. This will enable livestock keepers and vets to readily access and interpret -- at the time and place of examining an animal - the data tools at their disposal, in an integrated form that magnifies the value of any single data source -- enabling it to be used to inform point-of-care decisions. This will advance herd health and productivity, elevating the overall performance of the farm through achieving efficiencies and resulting in improved financial, animal health and environmental performance. This project takes a radical cross-sector approach by combining expertise in dairy production with the up-to-the-minute technological knowledge, creativity and user experience expertise of the UK gaming industry.

Finger millet grain is a super-food, containing at least 9% protein and a good balance of amino acids. It is an excellent dietary source of calcium, iron, manganese, and methionine, an amino acid lacking in the diets of hundreds of millions of poor who live on starchy foods such as cassava, plantain, polished rice and maize meal. It is a versatile foodstuff used as whole, cracked, or ground flour; a dough; or a grain like rice. It is favoured by and recommended to breastfeeding mothers, given its high calcium and iron content and is often fortified with other grain as a supplementary food for infants. As such, there is high demand for millet flour outstripping production across the country. Over the last decade, consumption in Kenya has stagnated at 6kg/head, mostly owing to declining production. Additionally, yields have declined to a lowly 200kg/acre against a potential of 1,500-3000kg/acre, while unreliable supplies have led to the loss of interest by millers. This project seeks to introduce finger millet as a cash crop for farmers in marginal agricultural areas during the long rain season, and a rotation crop such as soybean, groundnut, or sesame in the short rain season, to maximise yield and allow farmers to operate beyond subsistence. We will provide farmers with critical support including access to inputs, agronomic support, data driven advice and mechanisation through a purpose-built precision farming platform. Additionally, USOMI, through use of forward contracting, will guarantee the purchase of the whole crop obtained. We already have market for the finger millet and must increase yield to sustain supplies. Poultry farming using chickens with higher egg and meat production (adapted to local conditions) will also be introduced not only as a risk mitigation strategy but also as a complementary income source. The poultry will utilise any lower quality grain and other feed sources available in the environment. The recycling of potential waste grain into highly nutritious protein will ensure long term sustainability of the farming system. Availability of these two complementary enterprises will ensure that socioeconomic, nutritional and food security needs are properly met. Considering most diets in rural Kenya rely on high starch foods lacking balanced nutritional content, this project will increase intake of highly nutritious animal source foods alongside millet, a super-food. The outcomes of this project will have a high impact on alleviating the paradox of hungry farmers so prevalent in rural Kenya.

Cereal grains are the basis of staple food, yet post-harvest losses during long-term storage are exceptionally high, above 20% in the UK and worldwide. Pests are to blame, with grain moisture content and temperature being the most significant factors. Cereal storage sites such as farms, grain merchants, millers and breweries, experience these challenges, which have high cost implications in terms of lost revenue and cost to rectify. The objective of this project, a partnership between Crover Ltd, Agri-EPI Centre and East of Scotland Farmers, is to create the first robotic device able to safely sample grain bulks at various depths and while still hidle in storage, where existing methods cannot. Unlike current grain solutions that can only reach near the surface pose a safety hazard to operators collecting the samples, Crover's remote probing device will be able to collect samples throughout the whole silo/shed. This gives early detection of potential spoilage allowing proactive management to reduce losses and maintain quality.

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Hands Free Farm is a collaborative industrial research project aiming to create the technologies required to operate a farm autonomously building on experience, criticism and learning from the Hands Free Hectare. This project will develop swarm robotic skills, smart machines and implements, providing a platform to evaluate technology development and economic studies to build the business case for robotic systems in agriculture. Developing practical solutions that are suitable for use on farm by farmers not software technicians. The project will utilise compact farm equipment to demonstrate the benefit of smaller more precise machines to agriculture and the wider world.

"There is currently extensive inefficiency in the UK beef sector. Producers routinely assess the performance of their animals by eye and frequently retain them on farm too long, resulting in animals becoming too fat. This leads to increased variable farm costs, reduced annual capacity of beef finishing units and sub-optimal price paid for carcasses -- for a finishing unit producing 300 animals per year this equates to a cost of £11,400\. Over-fat animals also increase the primary processing costs for abattoirs and have a higher environmental impact per kg of product produced. The price paid to the producer for a beef carcass is also predominantly assessed subjectively by eye. Lack of confidence in the reliability of carcass evaluation makes it difficult to agree quality-based payments that reflect the true value of carcasses. This project aims to develop on-farm and in abattoir technologies to automate and optimise on-farm selection of animals for slaughter and carcass evaluation. The project will integrate automated data gathered across the whole life of individual beef animals (from calf to carcass) to create an enhanced decision support platform to modernise and drive efficiency improvements across the UK beef supply chain."

"This proposed project is focused on developing a precision agriculture technology solution for optimising the production efficiency of the dairy-beef sector, through improvements in health and management throughout life.The product will consist of the following components: 1\. A data collection system integrating different sources of information from across the value chain using novel and advanced sensing and farm records containing the required environment and animal information. 2\. A data analysis platform which will continuously analyse the data sources and provide the appropriate real-time and automated health and performance flags to optimise intervention strategies. 3\. A decision support system to optimise health and management protocols. This will be developed using expert advice from across the supply chain, including veterinary and animal science expertise. The project will develop the first cloud-based decision support platform to support different levels of decision making. This will include farm-level decisions (e.g. health management, nutrition) through to policy and practice decisions at systems level. The project will also develop the first precision agriculture integrated monitoring system specifically designed for calves for the early detection of important diseases such as scour and pneumonia during the rearing period. This will allow for early intervention and optimise treatment and management practices at an individual animal level. The overall aim is to reduce disease incidence and spread, reduce antibiotic usage, improve productivity and optimise efficiency."

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This is a feasibility study to research and evaluate current and future communications and safety systems that will be required for off-road vehicles to operate in compliance with safety regulations in on-road situations. Commercially available sensing packages will be evaluated and subsequently the most applicable will be integrated and tested on pre-existing autonomous agricultural vehicles.

Tail biting in growing pigs is affected by many risk factors, but an outbreak can start without warning or obvious cause. This unpredictable tail biting results in pain and sickness for bitten pigs and severe economic losses for farmers: infection through tail wounds results in abattoir condemnation of meat. Tail docking of piglets is partly effective at reducing tail biting in later life, but is seen as an undesirable mutilation and its routine use is banned in the EU. Our innovative new solution to this long-standing problem begins with the observation that pigs hold their tails down before a damaging tail biting outbreak starts. In an earlier project, we used 3D cameras and developed machine vision software that automatically detects these changes in tail posture. In this project we will build on our promising early feasibility results to develop a prototype decision support system to give farmers early warning of tail biting. Testing it on diverse pig farm types in the UK with both tail docked and undocked pigs, we will assess its welfare and economic benefits for pig producers and breeders. There is considerable domestic demand and export potential for TailTech for use in pig production systems globally. Tackling tail biting and reducing tail docking involves a multi-disciplinary farm to fork approach which is reflected in our project team of Agri-tech engineers, animal scientists, veterinarians and pork supply chain partners.

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This project directly addresses the challenge of improved food security and livelihoods for international development. For about half a billion people in Asia, most of them poor, rice provides over 50% of the caloric supply so the size and stability of the rice harvest is crucial. The simplest way to increase yields is by the breeding of new rice varieties with greater resistance to diseases and pests and improved tolerance to stresses. To help in this breeding all Asian national rice breeding programmes use DNA markers. This project will develop LGC genomics' proprietary molecular technologies (called KASP) by providing thousands of new KASP markers. By the end of the project, KASP will become the marker of choice for rice breeders through greater choice of markers (available for any cross), reduced costs (allowing a three-fold increase in the size of the breeding programme) and increased speed and reliability. This will provide a revolution in rice breeding by making it possible to do genome-wide, selection instead of selecting for markers at a few target traits. A single improved rice variety can increase harvest value by millions of pounds a year so improved rice breeding methods in all Asian countries will have great impact on improved food security and improved farmers' livelihoods.

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Tail biting in growing pigs starts without warning. Outbreaks of tail biting result in pain and sickness for bitten pigs and economic losses for farmers, particularly when infection through tail wounds results in abattoir condemnation of meat. Recent research shows that pigs’ behaviour changes before a damaging tail biting outbreak starts. This project aims to develop a ‘smart farming’ product based on the latest video technology and machine-vision software to automatically detect these changes and warn farmers so they can intervene to stop tail biting. The project brings together SRUC’s expertise in pig behaviour analysis, Innovent Technology Ltd’s machine vision software development skills with Sainsbury’s pig supply chain perspective to ensure that end user needs are met. Experience with on-farm 3D video, and access to a network of Agri-tech expertise will be facilitated by the Agri-EPI Centre.

The benefits of precision farming (PF) - dividing land into management zones according to soil characteristics - has been proven to yield better results when compared to conventional farming. The perceived high entry cost into PF has long been a barrier to entry for some smaller arable farmers. This project aims to make the financial entry into PF more affordable whilst not compromising on the high resolution data required to produce meaningful soil management zones. This large-scale collaborative project aims to integrate satellite data with the UK’s most comprehensive soil datasets to produce a ‘precision soil map’. The resultant map would present an economically viable alternative to the current labour intensive methodology of soil surveying and represents a very exciting opportunity for arable and vegetable farming to embrace precision farming. Growers will be able to increase yields with lower input costs and reduced environmental impact.

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