Public Funding for Sruc

SRUC provides commercial services to growers of agricultural and horticultural crops through two Crop Clinics via its associate company, SAC Commercial Ltd. This project aims to identify a protocol for the efficient and accurate extraction of the DNA of important crop pathogens and pests from soil samples. By knowing what species of pathogen and/or pest are present in soil, growers can assess the risk of crop damage, and plan more effectively for the deployment of pesticides, choice of resistant varieties for the current crop and in crops to be grown in subsequent years. Currently, protocols for the extraction of DNA from soil is often pathogen/pest specific, so for a grower to know what pathogens or pests may be present relies on multiple soil samples for each pathogen/pest, and different protocols to be used for each one. This is time consuming in terms of the collection of multiple soil samples, the laboratory processing, and ultimately an expensive process for the grower. By streamlining the process through identifying a single reliable protocol that is effective across a range of soil types, and assessing areas of the protocol that may be suitable for automation, the cost of these diagnostic tools to the grower will become more attractive, particularly when multiple pathogens/pests are being identified across a range of different crops. With over 50 soil-borne pathogens and pests of agricultural and horticultural crops in the UK, a means to cost-effectively identify them from soil samples would be a significant benefit to sustainable crop production.

This project aims to improve the fatty acid composition of selected pork products through a novel process of inclusion of an emerging ingredient within the diets of finishing pigs. This project brings together stakeholders and expertise at each stage of the supply chain process to address this challenge. The consortium consists of industrial and academic partners, and including feed ingredient suppliers, for the production and marketing of the specific ingredient, a feed company, for formulation of commercially viable finisher pig feeds, a renowned academic for undertaking the academic dose-response trial, and a major pig supplier, for hosting a large scale pork supply chain trial. The project is led by a major retailer who provide the nutrition, customer insights and technical expertise who will be responsible for assessment of composition, shelf life and sensory properties of resulting pork products. The project management is being sub-contracted to a company with previous experience of projects of this type.

Currently, farmers have few ways to measure their farm's soil health other than labour-intensive manual sampling and inspection or hiring an expensive agronomy consultant. These solutions are not scalable and do not provide the continuous monitoring required to evidence improved farming techniques or baseline future biodiversity/natural capital markets. Acoustic monitoring is emerging as a promising non-invasive technique to provide distributed and continuous measurements of the biological and physical properties of soil and its ecosystem. Biofonic, a new UK startup formed by 2x alumni of the renowned Innovation Design Engineering Masters programme at Imperial and the Royal College of Art, is pioneering a new technique for continuous, distributed monitoring. This 18 month industrial research project is led by Biofonic in collaboration with Harper Adams University and Scotland's Rural College (SRUC). Trials of the newly developed TRL6 demonstrator will take place at farms associated with SRUC, Harper Adams, and others. By 2034, Biofonic's sensors will be monitoring 2.6m+ hectares of UK farmland and the company will have hired 62 technical staff and reached a cumulative turnover of £52.5m.

CHROMACITY Ltd., a world leader in development of infra-red lasers, Scotland's Rural College (SRUC) and the UK Centre for Ecology and Hydrology (UKCEH) will work together to develop and test new instrument technology for real-time in-the-field measurement of common greenhouse gases and atmospheric pollutants for the quantification of concentrations and area source emissions including in, but not limited to, agriculture, agroforestry, forestry, landfill sites, anaerobic digestion plants, and wastewater treatment. The aim is to provide a step change in capability, addressing limitations of current measurement solutions by taking the technology developed by CHROMACITY from TRL4 to TRL7 with the help of project partners. The proposed new Fourier-transform infra-red instrument works by analysing absorption of infra-red light over the light source to reflector path. Absorption is dependent on the concentration of gas under analysis, allowing gas concentrations in the path to be measured. This technique is proven but limited by the type of infra-red radiation source used for the analysis. Current commercial offerings either use non-coherent light sources with poor beam quality, which forces the use of large high-cost retroreflectors to define the measurement path, or narrow-linewidth lasers with limited tuning range, which mean many instruments are required to measure multiple pollutants. CHROMACITY's key advancement derives from the use of its patented state-of-the-art broad bandwidth, tuneable infra-red pulsed laser source. This advanced laser technology has a high quality, high brightness beam, which enables the system to cover an extremely wide measurement area, with only small low-cost reflectors. It is also able to scan a wide range of wavelengths, covering the main areas of interest where the target gases absorb light. The output of the project will be a system capable of the following: * Simultaneous detection of multiple pollutant gases. * Analysis of multiple pollutant gases in near real-time (seconds), thus enhancing the ability to understand the immediate relationship between pollutants. * Detection of pollutants in a 'stand-off' configuration, remote from the pollution source, reducing the possibility of instrument contamination, and reducing setup time. * Creation of a quasi-3D map of pollutants over a wide area (\>100 m-by-\>100 m field or interior space) The solution will be capable of being deployed at scale both in the UK and internationally and will find a use in agricultural and industrial settings, helping scientists, engineers, permitters and end-users develop mitigation solutions and deliver on Net Zero and pollutant emission targets.

TransformDairyNet will harness the expertise of 26 European partners to create 11 National Innovation Practice Hubs and a European Knowledge and Innovation Network of dairy farmers, veterinarians, advisors, supply chain actors, farmer organisations, researchers and policy makers, to work together to upscale cow calf contact (CCC) dairy production and beyond. Keeping cows and calves together for months rather than the usual hours/days promotes health, growth and normal, pleasurable behaviour, and is the most consumer accepted ethical practice for increasing the sustainability of dairy systems in line with the Green Deal. TransformDairyNet aims to accelerate the adoption of CCC orientated-practice through: (1) compiling existing knowledge and identifying end-user needs; (2) co-creating new CCC knowledge–generating ideas and solutions; (3) sharing knowledge ready for practice, and (4) CCC legacy and tools for transforming systems. Through a multi-actor approach, TransformDairyNet will bring science and practice together to create a comprehensive CCC knowledge map, champion farmer-led innovation and share practice to upskill European dairy farmers and advisors at differences stages of adoption. TransformDairyNet will build resilience and normalise and spread CCC practice by co-creating harmonised, farmer–facing tools, materials and peer-to-peer activities, leveraging trusted channels and networks and engaging with existing and new dairy and CCC focused EIP-AGRI Operational Groups. TransformDairyNet will work with EU FarmBook to maintain the Knowledge and Innovation Networks beyond the project as a community of practice, able to pivot to other issues for the continued transition to sustainable dairy production into the future. Looking forward, TransformDairyNet will provide insights and recommendations for the acceleration of other novel agricultural practices with high citizen and practitioner demand, through reflecting on the thematic network processes.

**Pioneering Sustainable Livestock Enhancement in Eastern Innovation Zone** East-Anglian-based Oxcel is pioneering an innovative water enhancement technology-as-service to transform productivity, efficiency, and animal welfare in the UK's Eastern Innovation Zone's intensive livestock industry. Collaborative large-scale trials with Scotland's Rural College (SRUC) and major Eastern-England-based farms will position the UK as a global leader in a new sustainable agriculture market. Through advanced water enhancement technology, Oxcel seeks to enhance broiler chickens' growth rates, feed efficiency, and meat quality through drinking water. This innovation promises substantial feed cost reductions, a significant expense in intensive farming while elevating high-quality protein output. Beyond cost savings, improved gut health and enhanced immune function offer substantial animal welfare benefits. Increased disease resilience without additional antibiotic usage and reduced mortality rates contribute to ethical standards. Integration into existing infrastructure ensures ease of adoption without extensive overhauls. Oxcel plans comprehensive replicated trials at SRUC to validate these benefits scientifically. Concurrently, on-farm pilots in the UK's Eastern Innovation Zone with major poultry integrators will showcase real-world performance and integration. Success within the concentrated UK broiler industry could swiftly lead to widespread adoption across the country's 1.1 billion meat chickens, fortifying sustainability and self-reliance in domestic protein supply. Potential regional job creation aligns with commercialisation goals. Following its establishment within the UK, the initiative aims to expand into pig and dairy farming, addressing similar productivity challenges to enhance competitiveness. Long-term aspirations encompass the global application of this technology. Oxcel aims to revolutionise livestock water innovation, transitioning previous research from theoretical small-scale trials to practical, impactful infrastructure. This transformative project aligns with net-zero and food security goals, positioning Britain as a global leader in sustainable agriculture.

Calves from dairy herds are the foundation animals for dairy farms and the dairy-beef industry, but several diseases are endemic. Bovine respiratory disease (BRD) affects 11% of all calves and is the leading cause of poor performance (and mortality) in cattle <10 months of age, costing UK farmers ~£80Mp.a.(veterinary treatments, reduced lifetime productivity, mortality;Zoetis,2022). Thermal stress impacts the immune status and leaves calves more susceptible to illness(Vet Sci,2020). Integrating health and production data across a calf's life represents a significant challenge to the industry, thus management decisions are currently made without any prior knowledge of a farm or animal's disease or production status. CATL's automated monitoring solutions for health surveillance improves results but further potential for optimisation exists. The initial aims of the WELL-CALF project were to (i) develop and implement a data platform integrating health and production parameters across animal lifetime, (ii) to develop an innovative agri-engineering system for calf-rearer units integrating a novel multi-sensor platform with performance data to monitor calf health status, and (iii) to utilise advanced data analytics to classify health conditions in individuals, to facilitate rapid, individually-tailored treatment. For this project, we aim to extend and improve on the WELL-CALF project by refining prediction models for bovine respiratory disease, using advanced machine learning techniques.

MI:RNA Ltd is a veterinary diagnostics company with a unique, patent-pending, biomarker testing technology and we aim to use our expertise to explore the early and accurate diagnosis of Bovine Tuberculosis (bTB).This project builds upon our previous successful Innovate UK funded trial which demonstrated the potential of our technology to detect early-stage Johne's disease, part of the same mycobacterial family as bTB. Bovine Tuberculosis is a chronic wasting disease with enormous implications economically, environmentally and in terms of productivity and sustainability for the UK farming sector. Despite decades of an extensive, policy driven eradication schemes, this notifiable disease remains prevalent in many parts of England. Current testing methods have limitations with poor sensitivity and frequent inconclusive reactors (IRs), hampering disease control efforts. The potential introduction of bTB vaccination (e.g. BCG vaccination) to the UK is a further complication, as animals can test falsely positive after vaccination. Consequently, improved diagnostics will result in enhanced disease control leading to increased productivity, mitigation of economic losses and assistance in achieving a sustainable and safe, carbon neutral business model. This project will combine MI:RNA's innovation with the research expertise of colleagues within Scotland's Rural College (SRUC). The assembled team will work with the APHA, the UK government animal health laboratory, from whom samples and data will be sourced, along with their specialist and experience guidance. Project phases: Phase 1: A bespoke panel of microRNA (miRNA) biomarkers will be created specific to bTB pathology. This will be trialled with negative control and bTB positive serum samples to generate expression profiles of these markers, which will be analysed by advanced supervised AI algorithms, generating an initial modelling system for detection of bTB. Phase 2: This phase will see the model being optimised and challenged with longitudinal time course samples from previous APHA studies of bTB challenged animals. This will allow further refinement of the model for improving early-stage diagnostic accuracy. Phase 3: This phase will see the mature model being challenged with the task of differentiating between bTB vaccinated animals and true bTB cases, success here would be hugely beneficial to planned bTB vaccination programmes. The outcomes of these trials will be released publicly in peer-reviewed academic journals and protected with patents, and we will finalise our next stage research and development objectives. This will feed directly into our commercialisation plan to make the product available to the market, positively impacting the UK livestock sector.

The OPTI-BEEF project, initiated in May 2019, was awarded substantial funding of £1.2m from UK Research and Innovation, through the Industrial Strategy Challenge Fund. This support was part of a broader initiative to bolster 'Productive and Sustainable Crop and Ruminant Agricultural Systems'. Over its four-year duration, OPTI-BEEF aimed to create an enhanced decision support system that integrates on-farm whole-life performance monitoring with detailed carcass measurements from precision agriculture technology. This integration was designed for deployment both on-farm and in-abattoirs. The project successfully developed new on-farm technologies for individual animal monitoring, innovative parameter extraction algorithms for both live animal and carcass images, precise grading prediction models, and user-friendly on-farm and abattoir data platforms. However, to transition to a commercially viable product, further refinements are essential. The project now focuses on real-time image processing to cater to abattoirs' needs and ensuring reliable linkage of cattle IDs to images captured within the fast/complex abattoir environment. Additionally, to achieve commercial licensing, there is a need to enhance the accuracy of grading models on a 15-point scale and devise a reliable method for assessing fat coverage/depth. Key objectives include: * Crafting a fully automated software integration solution for reliable image and UKID linkage. * Developing an algorithm for accurate carcass fat coverage/depth prediction. * Refining the image processing algorithm to account for real-time abattoir conditions. * Creating a commercial-grade algorithm for predicting carcass conformation and fat classifications and carcass weight. * Develop predictions of new carcass traits and explore their use within grading/pricing models. By the project's conclusion, the goal is to have a robust abattoir imaging product ready for licensing by Defra. This product will be among the few licensed VIA options for UK abattoirs. It will synergise with the recently developed on-farm technology, offering the beef industry an invaluable integrated management tool. This tool aims to facilitate informed decision-making, leading to more animals meeting abattoir requirements, better input management by producers, reduced environmental impact, and increased returns on reared animals. The beef industry's ongoing need for an integrated decision-making platform is addressed by this advanced and innovative solution.

Our proposed System is a completely non-intrusive face-based (artificial) intelligent monitoring system that can automatically capture welfare and health data for monitoring and management of pigs. Why? Being able to continuously monitor and assess farm animal health and welfare depends on the deployment of practical, valid, and reliable measurement tools. Current on-farm welfare assessment protocols involve daily spot-checks by staff, and periodic spot-checks by veterinarians or quality assurance inspectors. Assessed welfare parameters are often resource-based concerning provision for basic needs, or animal-based, looking mainly at easily-measurable factors such as physical condition. Most are performed at a group level as individual identification can be difficult. Rarely is animal behaviour recorded and even rarer still are measures that can tell us something about the emotional state of the individual animal. How will the system work? Our innovative approach is to measure an animal's emotional state as well as its body condition using a completely non-intrusive face-based, (artificial) intelligent monitoring system. We have already successfully developed machine learning algorithms that identify individuals using facial biometrics and are able to detect changes in facial expression that indicate whether a pig is stressed or not. We have also developed body condition scores and weight estimation using these techniques. Here we propose to combine all of these capabilities into one face based, non-intrusive animal health and welfare monitoring station for use on commercial farms. By employing these state-of-the-art machine learning techniques, our system will offer the capacity for on-going learning about individual animals, and consequently allow for early detection of altered health/welfare, personalised thresholds for intervention, and tailored treatment approaches. Such individualised data recording can be integrated with other measurable parameters, such as individual food and water intake, treatment history, growth and weight gain, which will allow better optimisation of farm production efficiency.

Industry data has revealed that sheep feed prices have increased from £250/tonne (Feb 21) to £350/tonne (Jan 23).This represents a 40% increase in feed prices in less than 2 years. This price increase has had to be absorbed by the industry and passed on to the consumer. Distillery co-products (pot-ale syrup, yeast residues and draff) have historically been used as cattle feed. Unfortunately the high copper content has made these products unsuitable for sheep as they are copper intolerant. Yeast and fine grain residues represent around 1-2% of the volume of pot-ale, which is the main liquid co-product arising from the distillation process. It is estimated that up to 40,000 tonnes of these residues arising from Scottish distillers are dumped, either to land or sea, each year. If output from UK bioethanol plants was added to this then the total amount of new material created could be up to 200,000 tonnes per annum. This project seeks to produce a low copper content pellet using yeast residues from distillery effluent. The use of innovate hydrocyclonic filters can ensure that the fine yeast particles, which are currently treated as a waste, can now be captured, without any copper accumulation. The technology has the capacity to extract material down to a size of 3 microns. This project seeks to capture these residues and combine them with existing grains to produce a nutritional and sustainable sheep pellet. The project will benefit from the input of Professor Jos Houdijk at Scottish Rural College (SRUC). He is a UK recognised expert in animal nutrition. His recent work has had a particular focus on developing soya alternatives for animal feed. Yeast is an excellent source of protein and could potentially be used as a soya substitute. The UK imports around 3,000,000 tonnes of soya , 90% of which goes into animal feed. It estimated that around two-thirds of UK imported soya comes from Brazil . In some cases this soya production has lead to deforestation. The carbon cost of Brazilian soya has been estimated to be 0.77tCO2/tonne. Harnessing 200,000 tonnes of yeast residues would therefore save 154,000 tonnes of carbon dioxide per annum. Reduction in reliance on imported soya could therefore assist UK farming with its net zero ambitions.

Reducing the energy wastage and carbon footprint of the dairy supply chain is one of the greatest challenges of this sector given net-zero targets set by the Scottish and UK Governments. The core of this project is to: * automate the gathering of operational data on a range of cooperative members' dairies for key energy consuming equipment; * present the analysis of that data to the management and staff in such a way that it highlights waste & opportunities for improvement; * track and reinforce efficiency improvements to embed it in the dairy's operation, lock in greenhouse gas (GHG) reduction and increase business sustainability; * facilitate peer-to-peer comparison and identification of best practice between farms; * identify opportunities for optimisation of logistics collections based on bulk milk storage status on farm through real time data; and * sustain the cycle of continuous improvement whilst maintaining and improving quality of product. A significant part of achieving Net Zero is behavioural change of individuals. The project's digital solution, by scoping GHGE from the milk vat to the creamery, will enable farmers and dairy plant operators to edge closer to their net-zero targets and engage as wide a spectrum as possible of stakeholders in the process of continuous improvement. This project will leverage the data produced by stakeholders to identify opportunities for improvement and to quantify the impact of changes made along the supply chain management to benefit all involved (including quality premiums for the farms, energy efficient transport and better creamery products). The traceability of CO2e value of every litre of milk (Emission Index) processed through this digital supply chain will lead to betterment of operational decisions on a daily basis. This approach also provides a marketable answer to the ever-growing demand of the supermarkets /consumer for carbon aware sources of dairy products. This project will be setup using 10 farms from the MSA coop in collaboration with other partners in South and West of Scotland.

Calves from dairy herds are the foundation animals for both dairy farms and for the dairy-beef industry. However, there are several major health and welfare issues suffered by these calves. Pneumonia is a major problem for young calves, with an estimated 11% of all calves suffering from this problem. A case of pneumonia causes distress and ill health in the affected animal, but also has wider consequences including long-term adverse effects on growth, health, and fertility in that animal, and over-use of antimicrobial drugs. Poor ventilation and air quality in calf housing is known to be a major factor that increases rates of pneumonia. To address this challenge, **CEVEC** will design and deliver a **LOW-COST** purpose-built calf rearing building, with **REAL-TIME** monitoring, and **AUTOMATED ENVIRONMENTAL CONTROL** to ensure high health, welfare, and productivity of calves, whilst reducing labour costs associated with calf management. The **AMBITION** of CEVEC is to provide clear evidence that investing in a purpose-built calf rearing building brings profitable returns to the farmer. The **KEY OBJECTIVES** of CEVEC: 1. Design a low-cost building specifically for calves using novel housing design and ventilation technology with embedded monitoring systems and automated control to ensure optimum environmental conditions and air quality. 2. Design the data acquisition, monitoring, and automated control system to deliver a consistent optimal calf environment. 3. Install the CEVEC building on a commercial farm in South-West (SW) Scotland and assess the impacts on calf health, productivity, labour use and associated running costs. 4. Conduct a robust commercial trial to assess and compare calf health and productivity outcomes of CEVEC and current sub-optimal housing. 5. Conduct a full cost-benefit analysis of CEVEC and develop a robust commercialisation strategy -- detailing the business/operating model, marketing plan, and pricing/service model. 6. Develop and deliver a joint communications and dissemination plan using a range of Knowledge Exchange (KE) processes (open days in the South and West and Cumbria region, mixed media platforms and scientific outputs). The project will develop the first purpose-built, low-cost, automatic controlled environment, designed specifically for calves.

The proposed project focusses on developing an **AUTOMATED** data-driven **INNOVATION** for **NON-INVASIVE** and **REAL-TIME** monitoring of respiratory disease in dairy-bred calves. Bovine respiratory disease (BRD) is the most serious issue facing beef and dairy farmers, costing the UK sector alone around £80M per annum (Zoetis 2022) through mortality, veterinary costs, increased labour and reduced animal productivity at the point of infection, but also in later life. The **AMBITION** of **DETECT** is to utilise state-of-the-art technology, alongside commercially relevant lower-cost sensors, to characterise the volatile metabolites found on the breath of healthy cattle, and of those diagnosed with respiratory infection. The system will be designed with flexibility in mind -- in that it will be able to integrate into any calf shed/equipment to provide **ADAPTABLE**, **AUTOMATED** and **REAL-TIME** monitoring of disease at the individual animal level. The **KEY OBJECTIVES** of **DETECT**: 1.Develop an automated disease-detection system, based on passive measurement of breath from individual calves. 2.Identify differences in the breath of healthy and BRD-diagnosed calves, using these findings to optimise a low-cost automated real-time sensor system. 3.Apply advanced data analytics to distinguish between breath and cattle shed background, and to develop models for disease detection. 4.Demonstrate the ability of the tool to diagnose (sub-) clinical instances of BRD across a range of farm management and feeding systems. 5.Develop a user-friendly decision-support platform to aid early health and management decisions by co-designing the platform with end-users and understanding opportunities and challenges. The project will develop the first passive breath monitoring system designed specifically for calves for the early detection of BRD. This will facilitate early intervention and optimise treatment of individual animals. Reducing the impact of disease in younger calves will improve production efficiency and reduce greenhouse gas (GHG) emissions/kg product (through reduced losses associated with mortality and poor performance). Optimised disease management offers aligned societal benefits (improved welfare, optimised antimicrobial use) and will support increased resilience of the UK's beef and dairy sectors.

The main objective of BIOservicES is to understand the interconnection between soil organisms (virus, bacteria, archaea, fungi, protists, nematodes, microarthropods, earthworms, isopods, millipedes, insects and spiders) and the delivery of multiple soil ecosystem functions and services at different scales (field vs landscape), identifying the pressures and drivers resulting from different land uses and climate change, and performing an economic valuation of the contribution of soil organisms to ecosystem services. BIOservicES will also deepen in the relationship between soil organisms and soil structure, and how this interaction is affected by land use and management intensity, to contribute to the Soil Mission objective 6 “Improve soil structure to enhance habitat quality for soil biota and crops”. BIOservisES will thus deliver new knowledge, new indicators based on soil organisms and the ecosystem functions and services in which they are involved and digital decision-support tools and models to help design climate resilient management practices and monitoring/conservation/ restoration programmes adapted to a range of environments (land uses and biogeographic regions) across Europe, to maintain and foster the multiple soil ecosystem functions and services in which soil organisms are involved. It will also give relevance to soil health and soil ecosystem functions and services delivered by soil organisms in the update of EU and National legislations. For this, BIOservicES is using experimental sites across 8 land uses and 5 biogeographic regions from Europe, as central hubs for co-creation and co-design (multi-actor approach, responsible research and innovation (RRI) and open science)

Climate change presents a global crisis that impacts people, environments and economies worldwide, with more severe impacts for those who have the least resources to combat them. It is unarguably an existential threat to humanity. To halt warming, we will need to reduce emissions by 75% and massively increase biodiversity across the planet. For our food chain, this means eliminating emissions wherever possible and finding sustainable sources of protein for human and animal feed without water and land needs. We will need to rehabilitate our soils, bio-diversify much of our agricultural land, and continue to offer appropriate nutrition to the world's population. Seaweed offers us an opportunity to grow nutrient-dense biomass in the UK without the need to commit more land to crop production. Seaweed farms also have the potential to be co-located alongside offshore wind farms, with benefits to both industries. The proposed project is focused on creating technology and infrastructure that can unlock the potential of seaweed in the global battle against climate change. This project aims to establish the UK's first commercial cultivation system for dulse, a highly desirable red seaweed that could become a viable low-emission home-grown protein alternative to replace soyabean meal in chicken feed in UK. Dulse is a particularly desirable protein rich red seaweed with many growth-promoting effects that has so far proved challenging to grow. This feasibility study will allow a full assessment of the cultivation inputs required (and corresponding emissions) for pure tank based vs. at-sea cultivation. The project will enable us to establish the most biologically and commercially viable route to successful cultivation of dulse. The biochemical analysis of the pure tank based vs. at-sea cultivated seaweed will allow us to select the most nutritious and protein-rich species of dulse. The efficacy and potential of dulse produced and selected will be tested in poultry feed trials (in vivo) to explore the seaweed soyabean meal replacement potential. As dulse has great potential to improve gut health, arising from its immune-modulating functions, as a consequence, its impact on the gut microbiome could contribute to the use of seaweed to reduce reliance on antibiotics. The impact of dulse on the gut microbiome will be further explored by studying its impact on gut microbial diversity, antimicrobial resistance (AMR) and the occurrence of zoonotic pathogens.

Our aim is to breed sheep with a naturally low carbon footprint to help English sheep farmers make a positive contribution to the journey towards Net Zero for UK agriculture. We are an alliance of forward-thinking sheep farmers and breeders who apply genetic science to the breeding of our sheep so that they can make the best, most efficient use of grass and forage to produce sustainable and healthy lamb of high nutritive value. Making use of grasslands by way of sheep grazing also helps sequester carbon into the soil. We collectively believe we can improve the sustainability of our sheep further by using genetic science and breeding to naturally reduce the amount of methane, which is a natural by-product of their forage digestion process, and therefore reduce the carbon footprint of sheep farming. This project will allow us to collect and build the necessary data, and develop the tools required to genetically reduce the methane emissions, and in turn, carbon footprint of sheep; and demonstrate the impact of using low-carbon sheep may have on whole farm carbon footprints. To achieve this, we will develop on-farm protocols to measure or predict methane emissions of sheep, alongside health, production and efficiency traits at the individual animal level, through using new innovative tools and technologies. We will investigate biological relationships between the genetic potential of sheep to emit lower levels of methane with rumen size and microbiota and with ewe productivity, efficiency and health, as we want to avoid any unintended changes in sheep physiology, health or welfare. To widen the impact of the project beyond our own flocks, we intend to carry out a wide-reaching programme of communication with other sheep breeders and farmers throughout England, in collaboration with supply chain partners and wider industry bodies. The integrated knowledge exchange programme will identify the most effective ways of communicating the outputs and implications of the project's work to other farmers to help educate and support them to make genetic changes in their flocks that will improve their productivity, sustainability, resilience and profitability.

This is a 48-month feasibility research project which aims to develop tools which will contribute to the COP26 Global Methane Pledge of cutting global methane emissions by at least 30% by 2030\. The project will seek to develop a naturally sourced nutritional additive to reduce methane emissions from ruminants, which currently account for 80% of the total methane emissions from agriculture in the UK. The project will also address the requirement to improve the efficiency of feed utilisation by ruminants, which will reduce the demand for imported high-protein feed materials, supporting sustainable milk and meat production. The rural economy will also benefit through diversification and employment opportunities for farming, an industry currently challenged by post-Brexit pressures. The project is based on greater use of locally available plant-based compounds called alkaloids, which can be extracted from daffodils. As daffodils are grown widely throughout the UK, production and extraction these compounds can be local, sustainable and resilient. Preliminary data estimates that by using a specific alkaloid from daffodils, direct methane emissions from ruminants can be significantly reduced whilst simultaneously improving the efficiency of feed protein utilisation by 50%. Improving feed protein utilisation will lead to increased productivity of the ruminant sector whilst reducing the production of nitrous oxide, another potent greenhouse gas. This would subsequently reduce the requirement for high-protein imported feeds such as soyabean meal, improving the sustainability of British farming. This project presents several benefits to both UK agriculture and wider society. \*Reduce the carbon footprint of the ruminant livestock sector by developing and validating a novel technology geared to boost feed protein efficiency whilst reducing methane emissions (currently more than 90% of the corporate dairy industry emissions are methane produced by cows). \*Improve productivity and resilience in the dairy sector by reducing the need to feed high-cost imported feed materials. \*Establish a UK-based supply chain to support the diversification of UK agriculture and boost the rural economy by providing higher incomes for farmers. \*Improve food security in the UK and provide rural job opportunities.

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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.

Genus is providing targeted genetic solutions for farmers to create more value for the beef supply chain. Internal trials have demonstrated the superiority of targeted genetics for increasing supply chain profitability relative to traditional practices. Beef calves that are more efficient will reduce carbon footprint are increasingly demanded by supply chain stakeholders to achieve UK carbon reduction targets. Genus and SRUC have carried out ground-breaking research on beef cattle showing the potential of ruminal microbiome-driven breeding to mitigate methane emissions with an expected reduction of up to 17% per generation (Martínez-Álvaro et al., 2022) and improvement of feed conversion ratio by up to 15% per generation. A conservatively estimated 10% reduction in GHG emissions in Genus-influenced animals alone, for example, is a 337,000 metric tons reduction per year in the UK, which is permanent and increasing with ongoing genetic improvement.

The UK Processors and Growers Research Organisation will lead this ambitious national research programme with 200 UK farms and 18 partners to design an environmentally transformative, economically sustainable arable rotation system to optimise crop rotations for climate benefit. UK farming accounts for 10% of the UK's total GHG emissions p/a (46.3 MT), 68% of total UK nitrous oxide emissions, 47% of total methane emissions and 1.7% of total CO2\. Arable cropping significantly contributes to these figures, utilising 596,496T of Nitrogen fertiliser p/a. Existing emission estimates are for individual crops, and the impact of these in successive rotational cropping remains unquantified. This project will investigate three opportunity gaps: (i) replacement of 20% of national grain crops with pulses and legumes rotations to establish a net zero farming pathway, (ii) the nutritional and financial feasibility of replacing feed grains (currently representing 70% of the UK grain market) with legumes in 30% national livestock feed and (iii) create a market for this additional yield. The proposed system outputs would contribute to UK Net Zero goals with a total potential reduction of 1.5MT CO2e p/a of the maximum potential 2.8MT for UK agriculture (Defra Agri Climate Report, 2021) in the following ways. * Removal of 233,000T of nitrogen fertiliser and 0.55MT (CO2e) - a 1.2% national reduction - by increasing pulse and legume cropping areas to the rotational optimum of 20% (1M Ha) across UK farms. * Use of subsequent produce in animal feed substitution (replacing 50% of imported soya meal) delivering a further 0.7MT CO2e reduction. * Delivery of a residual N benefit to following crops, leading to an additional 0.25MT CO2e (0.5%). * Delivering a national cost saving to farming of £1032M p/a, by removing 20% of N fertiliser across UK growers and 1.8MT soya imports respectively from the UK farming supply chain. * A policy tool that leads to the adoption of more measures and cost-effective solutions for reducing agricultural GHGs that fit with the farm business' (source: Defra Agri-Climate Report, October 2021). * A set of farmer and grower case studies that can be used to educate and inform the national farming community of the environmental and financial benefits of the research solution. We propose a technologically and financially accessible system for farmers/growers to achieve 100% uptake of a nationally resilient and sustainable food system. Secondary benefits will be the reduction of carbon footprint associated with the domestic replacement of 1.8MT of soya imports p/a.

MI:RNA Ltd is a veterinary diagnostics company with a unique, patent pending, biomarker testing technology. This project builds upon our successful, initial Innovate UK funded preliminary trial which demonstrated the potential of our technology to detect early-stage Johne's disease in dairy and beef enterprises. Johne's disease leads to a significant reduction in milk yields and weight loss in affected cattle, as well as increasing the greenhouse gas production from animals affected. Consequently, improved early disease detection will benefit the sector with increased productivity, mitigation of economic losses and assistance in achieving a sustainable, carbon neutral business model. This project will combine MI:RNA innovation with the research expertise of colleagues within SRUC. The assembled team will work with English farms recruited by our collaborators in the Digital Dairy Chain and CIEL network, from which samples and data will be sourced, directly benefitting these enterprises with tailored input and guidance. Additional longevity data will be sourced from stored sample banks. CIEL market research workshops will scope the commercial landscape and help tailor the product to the producers' needs. Project phases and goals: Phase 1: The current preliminary data will be enhanced with further healthy and infected cattle serum samples in collaboration with SRUC research and veterinary services. This allows us to mature the AI model. Additionally, the accuracy of pooled samples and alternative sample mediums of milk and urine will be assessed and optimised. Phase 2: The accuracy and sensitivity of early disease detection will be established. This will be achieved through trialling the enhanced AI model with longitudinal Johne's disease samples from our specialist research collaborators including the University of Wageningen in the Netherlands and SRUC premium cattle health schemes. This allows modelling with predictive data and establishment of test accuracy at each stage of disease. Phase 3: The finalised model will be tested in a real-life setting. This will involve work with English farms linked with Digital Dairy Chain (NW England) and CIEL network (UK). In this extensive trial, we will receive and process samples from participating farms, optimize sample handling and processing and directly compare our test to existing solutions. The outcomes of these trials will be released publicly in peer-reviewed academic journals, and we will finalise our next stage research and development objectives. This will feed directly into our commercialisation plan to make the product available to the market, directly and positively impacting the agricultural protein production sector.

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The overall objective of Re-Livestock is to evaluate and mobilize the adoption of innovative practices applied cross-scale (animal, herd, farm, sector and region) to reduce GHG emissions from livestock farming systems and increase their capacity to dealing with potential climate change impacts. To reach our aim, Re-Livestock have brought together the excellence scientific expertise in Europe and Australia and across disciplines, including co-innovation, animal feeding, breeding, welfare, farm management, environmental and socio-economic assessment and policy analysis, to develop novel and scientifically supported integrated approaches specific for different dairy, beef and pig systems and geographic regions in the context of climate change. Strong collaboration with industry stakeholders to identify the innovations and to co-design the validation will ensure relevance and maximise the adoption of best practices. National groups of farmers (case studies) and ‘stakeholder forums’ together with a ‘European multi-actor platform’ will allow for an engaged co-design of transition pathways whilst ‘learning from innovation networks’ will allow for the testing and sharing of latest innovative solutions. A ‘community of practice’ will extend the multi-actor approach to a broad range of stakeholders

**What is FarmSense?** FarmSense is an intelligent user-friendly platform that brings together state-of-the-art image/sensor technologies combined with artificial intelligence (AI) to support farmers and their advisors in optimising livestock production whilst assuring the highest animal welfare standards. Compared to traditional labour-intensive farming methods where animals are visited periodically during the working day, our smart monitoring system continuously analyses animal growth, behaviour and gas profiles along with the animal's day and night patterns. Our AI system learns how to automatically detect any changes in pattern indicating problems such as early disease onset, tail biting or abnormal eating/drinking behaviours. The system then delivers early on-screen alerts/prompts to farm workers. FarmSense's 24/7 monitoring thus provides farmers with an autonomous stockman tool: a 'hands-free' continuous early warning system for pig production that can be readily integrated into the UK pork supply chain. **How does it work?** Our approach is based on smart 3D cameras that monitor animal growth and behaviours; and gas sensors that detect gases and vapours that animals emit when diseases start to take hold. The resulting data are analysed by machine learning methods (a type of AI that learns from data) to identify common health and welfare problems affecting individual animals. Integrated into the _"VetSupport+"_ software (Zoetis), it notifies farmers of anything unusual or alarming occurring within a herd and provides suggestions for early corrective action so that quick and effective farming management decisions can be made. **What are the benefits?** Previous studies \[1-4\] have shown that the parameters measured by our technologies affect health and productivity in other species, including poultry. Using our technology, we predict that disease and waste reduction using FarmSense will lead to a 10-15% increase in productivity in the pork supply chain \[7\]. Indeed, we've seen 8% revenue gains observed in current deployments of our camera systems; we expect that our integrated system will achieve higher gains. Finally, our early warning system stands to reduce the carbon footprint within the livestock industry in line with the Agricultural Transition Plan, thus markedly contributing to the UK's Net Zero Strategy. **Who can use FarmSense?** FarmSense will initially focus on pig farming to exemplify the benefits of applying 'Precision Livestock Farming' to pork production. However, FarmSense will be readily adaptable across other livestock, such as cattle and poultry, to improve farming efficiency, minimise waste and positively contribute to the global issue of climate change.

**VISION** Creating 624 jobs and £64M p.a. additional GVA, the Digital Dairy Value-Chain will deliver an uplift in the rural economies of Cumbria and South West Scotland. It will develop a world-class research, innovation, business and skills platform to establish the region as a leader in advanced, sustainable and high-value dairy manufacturing. Inclusive, innovation-led growth will also deliver wider societal and environmental gains including reductions in carbon footprints. The project will develop innovative technologies (e.g. sensors, IoT, 5G-communications, blockchain), infrastructure and advanced manufacturing processes to create a fully-integrated and traceable supply chain. It will generate new opportunities to optimise manufacturing, develop new products and markets, and valorise consumer concerns around dairy production. **GEOGRAPHY** Spanning national boundaries, Cumbria and SW Scotland produce 1.9bn litres of milk annually. As the UK's second largest milk producer, dairy manufacturing is an important source of economic activity and employment. Our geography is remote and rural. Regional GVA is well below the national average, high-value employment opportunities are limited and business innovation activity is patchy. The impacts of BREXIT and changes to agricultural support will be significant. This project focuses on AgriFood manufacturing, sustainable exploitation of natural capital, and digitalisation; all are priorities for regional growth. With 63% of our local authority areas having a negative prosperity gap there is significant untapped human capital. Social inclusivity goals cut across our activities particularly focusing on advancing opportunity for young people and women who are under-represented in dairying, STEM and business innovation. **NETWORK** We draw on an impressive network of world-class research capability (SRUC; University of Strathclyde; University of the West of Scotland); technology innovation centre (CENSIS); regional and multi-national dairy-processing companies (First Milk, Lactalis, Arla, Kendal Nutricare, Appleby Creamery); SmartSTEMs; and technology businesses (Lely, Seric, North). The project is backed by strong support from civic leadership. **OBJECTIVES** The project will: * **Develop digital connectivity.** Establish the region as a beacon for digitally-connected, value-added milk processing. * **Stimulate R&D.** Facilitate access to state-of-the-art infrastructure and expertise, catalyse collaborative R&D and commercialisation of innovative products and processes. * **Facilitate business growth.** Provide business support and facilities for early ventures, scale-up businesses and established companies to undertake New Product Development (NPD) and process improvement. * **Attract talent and skills.** Foster a talent pipeline that advances opportunity and enables industry to exploit new technologies and market opportunities. This project leverages investments in the Borderlands Inclusive Growth Deal, Ayrshire Growth Deal, and Cumbria's Food Enterprise Zone.

D-FLOWS is focused on developing an innovative solution for optimising the production efficiency of the dairy-beef sector. The solution will adopt a two-pronged approach: 1\. A novel data solution that will collect and integrate key productivity, health, and environmental metrics across the value chain. 2\. A rewards system with aligned incentives for all actors along the supply chain. This approach will ensure increased integration within the sector, thus optimising productivity, environmental performance, and animal health. The overall aim is to support government targets of achieving NET-ZERO by 2040 and ensuring high standards of animal welfare.

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MI:RNA Ltd are a veterinary diagnostics company with a unique, patent pending, biomarker testing technology. This novel technique, coupled with our bespoke AI modelling system, can provide accurate, early diagnoses in a wide range of disease types and species. SRUC are a world leading research organisation focusing on livestock disease. Currently, agriculture accounts for one third of greenhouse gas (GHG) emissions, with cattle the primary source. Endemic, production limiting disease, such as Johne's disease make agriculture currently unsustainable. We aim to determine whether we can detect Johne's disease in the early stages and transform the production animal market.

Dairy production and processing are key industries for many rural areas in western Britain, converting human inedible feeds into valuable components of healthy varied diets and contributing to the sustainability of rural communities. Dairy production has the lowest carbon footprint of all of the ruminant production systems that can utilise the UK's grasslands for food production and so we focus on improving technical efficiency in dairy production and processing. The project addresses some of the key concerns of consumers and retailers of milk and dairy products, who need to be reassured about the environmental footprint and animal welfare standards of dairy production systems. It will develop new tools to provide consumers, retailers and processors with verifiable information about the environmental footprint and animal welfare standards in dairy production systems. We will use monitoring technologies, including environmental sensors, animal-mounted sensors and camera technologies that are already being used by farmers to manage technical aspects of their systems, such as feeding and fertility. We will avoid prejudging the potential of different technologies and start out by working with any equipment that is already being used commercially, or is about to be commercialised. By relating this information to manually recorded information, using advanced machine learning techniques, we will be able to develop new algorithms to provide indexes of environmental emissions and cow welfare in ways that are both easier, cheaper and more reliable. Our objective is to identify predictors of a few key common indicators for both environment and welfare aspects that can contribute to accepted farm assurance standards and reassure consumers. We will work with progressive dairy farms across the main UK dairying regions to ensure that relationships are robust and to provide a platform for demonstration and extension to other farmers. After BREXIT, the UK may have new opportunities to export or replace imports of high-value dairy products; development of such products is built on a solid foundation of verifiable quality in aspects such as environmental footprint and cow welfare.

Smallholder dairy farming systems contribute around 80% of milk production in Tanzania, with a significant role in improving the livelihood of farmers and poverty reduction through income generation and creation of employment. However due to the technical barriers they face, smallholder producers and processors do not attain the required standards for the regional and international milk markets. There is low usage of novel technologies and practices that would ensure high quality milk production, processing and marketing. The objectives of this project are: I) to develop and test mid infra-red spectrometer and mobile phone camera technologies to analyse milk quality in smallholder dairy production systems; II) to identify the optimal pattern for deployment of different levels of equipment (with different capabilities and costs) at milk collection centres, dairies and reference labs; III) to strengthen and facilitate adoption of milk quality diagnostic techniques by processors at milk collection centres and processing dairies; and IV) to develop an app and cloud-based data platform to promote information on milk safety standards and marketing along the dairy value chain.

This project addresses the adoption of precision livestock farming (PLF) technologies in sheep farming. PLF has been widely adopted in the management of high-value animals e.g. dairy cattle, but is not currently applied to those with lower economic value, e.g. sheep, despite the potential to increase production efficiency. In the UK, there are around 23.3 million sheep, including 14.7 million breeding ewes worth approximately £690 million to the economy. Since 2010, all individual sheep in the UK are equipped with EID (Electronic Identification) tags, further paving the way for use of PLF technologies. However, uptake is a major issue. A recent survey of European sheep farmers showed that only 38% of farmers have any EID equipment, which are rarely used for sheep management. Likewise, in the UK, a survey of PLF technology adoption showed that 55% of farmers did not have and did not intend to adopt EID technology for management purposes. The project consortium will engage with end-users (members of the farming community and farming advisors) early in the project, to co-design tools to increase the uptake of PLF on-farm. We will use one proven PLF tool; an existing pen-side tool to optimise lamb worming, using an algorithm for the early identification of under-performing lambs. This Targeted Selective Treatment (TST) has been developed at MRI and validated at MRI, SRUC and on commercial farms, including one facilitated by 5Agri. The adoption of TST reduces wormer use and labour, and the costs required. Importantly, it slows the development of wormer resistance. Farmers have described a clear need for this type of approach on farm. However availability to the farming community is currently hampered by the lack of a user-friendly method for farmers to access the algorithm. This project will facilitate the integration of the algorithm into a cloud-based platform, thereby making it easily accessible to farmers. Validation of the improved technology will be performed on 10 'innovative' and 2 research sheep farms across the UK, covering a range of geographical locations and using commercially appropriate sheep breeds to ensure evidence that is relevant to a wide range of sheep farms. Cost-benefit analysis and carbon foot-printing of implementing the new approach will be conducted. The results of this project will be disseminated through on-farm knowledge exchange events at strategic locations across the UK to demonstrate the ease, accessibility, cost-benefit and environmental benefit of using this integrated pen-side TST approach.

"Dunbia, a leading Beef and Lamb processor in the UK, together with our suppliers (farmers) and consortium partners (SRUC & Breedr), will drive significant improvements in production efficiency and productivity growth within the beef sector by over £500m in 5 years. Currently, there is a great degree of variability in the beef supply chain. This is largely due to a lack of consistent and accurate data collection and subsequent analysis leading to unacceptably high disease levels, poor business performance, and huge variability in product quality. The consortium proposes to radically drive agricultural productivity and environmental sustainability within the beef supply chain. The solutions developed in this project will allow the consortium to be a first mover in the UK and indeed globally. These solutions will involve multiple interventions across multiple segments of the supply chain. The platform developed will facilitate supply chain integration, and will deliver an economically and environmentally sustainable commercial beef supply chain."

"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."

The use of antimicrobial treatments in agriculture is vital in protecting animal health and aiding the production of safe and nutritious food. However, previous overuse, and continued use of antibiotics in agriculture has been attributed to the rise in multi-drug resistance (MDR) bacteria, which can lead to ill-health and even death in humans if infected. MDR bacteria have been identified in large numbers of animals and raw food products, representing a major risk to public health and food system security. This is especially important in China and developing countries which rely heavily on animal products for nutrition and livelihoods, with chicken being the fastest growing protein source. GAMA Healthcare have developed an alternative antimicrobial treatment to conventional antibiotics by coupling a cancer medicine delivery system (microparticles) with a new class of short-lived antiseptic, which will be applied to reduce MDR bacteria in on chicken farms. The technology can be customised to meet the specific needs of the end-user, delivering a toxic payload to bacteria present within the animal and can be produced cheaply and safely, making it suitable for the agricultural/veterinary market.

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.

Only around half of UK-produced lambs meet target conformation and fat quality specifications resulting in waste at the farm and processor levels. This livestock genomics project addresses key issues in primary livestock production by collecting, analysing, and exploiting state-of-the art genomic and new phenotypic data from meat sheep on hard to measure (HTM) traits, combining carcass and disease for sustainable sheep improvement. New visual image assessments (VIA) of post-mortem lamb carcass quality, and novel, in-line meat hygiene records on individuals will be linked to genome-screening technology to identify superior bloodlines and genomic regions that are more productive and also more resistant to economically-important disease traits. This allows greater productivity to be acheived without compromising health and welfare, and explores the best method to deliver genomic solutions for increases in productivity and efficiency in tandem with improvements in animal health.

The consortium will develop an ear tag mounted geolocation tracking and monitoring device to catalyse improvements in production efficiency of sheep farming through reduced losses achieved due to early health interventions. The solution, aimed at extensive livestock systems, will enable producers in challenging physical environments to optimise their labour and equipment resources.

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.

To validate biological models predicting performance of cattle and to further improve these models to help generate unique software for ruminant diet formulation based on mechanistic principles.

Fertile suckler beef cows and low calf mortality are essential for profitable beef production systems. To improve cow fertility and calf survival national data will be used to develop genomic breeding values for fertility and survival. Genomic selection is a novel breeding tool which increases the rate of genetic improvement for traits that have traditionally been difficult to improve, like fertility and survival. As a result the overall efficiency of the UK beef industry can be improved as cows will be more fertile and produce more calves in their lifetime and more calves will survive. This will increase production, but just as important do it in a sustainable way that ultimately will reduce the greenhouse gas emissions per kg beef produced. This project is innovative as beef genomics is still in its infancy and there are currently no breeding tools available for the genetic improvement of survival.

Providing sufficient food to feed an increasing global population is challenging given limited resources. Soil is a key component of food production providing nutrition and organic matter. However, modern methods of crop production have resulted in degraded soil leading to reduced yields. This contributes to the so-called yield gap, the difference between yield in optimal conditions to that actually achieved. This project focusses on developing a test for soil quality that uses measures of soil biology, chemistry and physics. We profile soil nematode community DNA, similar to genetic fingerprinting, to inform the status of soil quality. Whereas soil chemical and physical measures are snapshot measures in time e.g. hours, nematode data is a reflection of weeks/months. The consortium partners will develop a tool for farmers to be used in a precision agriculture framework to identify fields in need of soil quality improvement.

The aim of this project is to explore options for implementing a new approach to assess feed conversion efficiency (FCE) in UK beef cattle. The longer-term aim is to use the new approach to breed for cattle with high FCE. It is important to maximize FCE because feed is the largest production cost in beef production and breeding for high FCE is a good long-term strategy that has worked well in the pig and poultry industries. The traditional approach to breed for FCE has been to measure feed intake and weight gain over long periods of time, but this is expensive for beef cattle and so has only been implemented for a few breeds in other countries. The project is based on testing for a novel biomarker and we will explore the practicalities of implementing this method alongside other on-farm testing of beef cattle and use the results to define options for future sampling and testing protocols.

This project addresses the key challenges facing dairy goat milk production by using new genetic and genomic technologies to improve the quality of milk production and disease management. The main challenge is to breed healthy goats with resistance to bacterial infections leading to mastitis, and to identify sires with daughters that have lower susceptibility to mastitis and generate genomic predictions of merit for this trait. The wider goat industry in the UK and abroad will access genomic predictions of enhanced mastitis resistance via new molecular technology from the creatipon of a low density (LD), lower cost customised single nucleotide polymorphism (SNP) array for UK goats. This allows for the use of more cost-effective molecular technology to predict ('impute') the information that was previously generated by the more expensive, more comprehensive SNP array and enabling more animals to be genotyped. The project will ensure sustainable breeding objectives for dairy goats in the long-term, by including routine collection of mastitis records as indicators of health and longevity, thereby helping to translate previous TSB-funded research into practice.

This project addresses key challenges facing the sustainable intensification of dairy goat milk production by using new genetic and genomic technologies to improve the efficiency of milk production and continuity of supply.This project will identify sires with daughters that readily breed out of season and generate genomic predictions of merit for this trait. The exploitation of such ability by the wider commercial goat industry in the UK and abroad will be enabled via genomic predictions for this and a range of other key traits via the development of a low density (LD), lower cost customised single nucleotide polymorphism (SNP) array for UK goats. This allows the imputation from LD to the higher density SNP arrays and a greater proportion of the outer herd nucleus to be genotyped, thereby creating greater uptake and impact to a the wider UK goat population and beyond.

The goals of the project are: (i) to develop animal-mounted sensor systems that capture beef cattle feeding behaviour patterns and integrate this information with a feeding systems that accurately estimates feed intake at the individual animal level and (ii) to develop techniques for monitoring, in a commercial environment, the performance efficiency of individual animals. The aim is to integrate both input (feed) and output (growth/yield) measurements at the individual animal level, allowing beef farmers to make appropriate management decisions to improve the overall efficiency of beef production. The decision support platform will inform the livestock producer of the correct and balanced amounts of nutrients to be administered to individual beef animals in order to maximise production and profitability.

There are considerable animal health challenges in modern dairy farming, all with a profound impact on production output and efficiency. The early detection of metabolic diseases such ketosis, acidosis and lameness and intervention at the pre-clinical stage provides valuable information upon which the farmer can decide on the most appropriate interventions. Thus the project will integrate a number of new dairy livestock sensing systems in real-time, including animal-mounted and product in-line monitoring, to provide a robust decision support system for metabolic disease detection at pre-clinical stages. The solution will be capable of integration within existing technologies on commercial farms to enhance the value of the farmer's investment, and the information presented to the livestock-keepers will be in an easily accessible and digestible fashion delivered over multiple channels viz. smartphones, tablets or PCs.

This project addresses the sustainable intensification of sheep meat through the exploration of genomic selection for disease resistance. With pure- and crossbred Texel sheep, genome-screening technology and bioinformatic procedures will be used to identify genomic regions and bloodlines of sheep that are more resistant to mastitis. The project will put in place the computational and data recording protocol infrastructures so that farmers can include new measures of mastitis alongside their other breeding goals (such as aspects of lamb growth and meat quality) in the future. The project will also investigate if cheaper alternatives to the new genomic technology can provide similar information without losing accuracy, to identify the more resistant animals for breeding. New methods for identifying animals with clinical or subclinical mastitis will combine farmer records with on-farm milk testing and lab test indicators of disease to determine which method is most likely to be used routinely in the future.

This project will develop new methods to reclaim waste energy from different forms of refrigeration plants, and in parallel, use this energy to also assist in conditioning waste water to potable standard water. In both cases waste heat will be recycled to be used again in other localised manufacturing processes and water will be re-cycled . This will reduce costs in the food processing sector (including perishables). It will do this by reducing energy and water use costs as well as reducing the environmental footprint of the commodities produced. These novel technologies will have application in various processes in a diverse range of UK and international industries

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project will measure new lamb carcass and meat quality (MQ) traits simultaneously, using non-inva-sive state-of-the-art technologies in live animals and in meat cuts, including computed tomography (CT) and Near Infrared spectroscopy, and use the data in a breeding programme, alongside carcass traits measured routinely in the abattoir, but not currently accessible on an individual lamb basis. Relation-ships between new CT- / NIR- and MQ traits will be investigated. A routine way to measure these traits efficiently on a large number of crossbred lambs will be developed, enabling contemporaneous selec-tion for higher taste/healthier meat/ lower waste using accurate crossbred estimated breeding values. The optimal way to incorporate these new traits into sheep breeding programmes will be investigated. British lamb has a 12-16% market share of red meat consumption. Improving eating quality and production efficiency of home-grown lamb will have a significant impact on the future of the industry.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This project aims to develop a non-intrusive system which will allow beef finishing units to identify the optimal time to market finished cattle. The system will combine innovative; animal handling; automated weighing; image capture; and analysis software to provide realtime objective feedback on animal condition, market value and optimal time to take to market.Optimising cattle finishing times allows farmers to achieve maximum marketable yield and profit, by a reduction in variable costs such as feeding and bedding, and by improving the efficiency of capital resources such as animal housing. Further benefits accrue by reducing the requirement for farm visits by supply chain customers. Environmental impact will be from a reduction in animal greenhouse gas (GHG) emissions through faster finishing times and reducing resources used and requirements for farm visits by abattoirs. The consortium is David Ritchie (Implements) Ltd, The Harbro Group Ltd, Innovent Uk Ltd, Wm Morrison Supermarkets Ltd, Scotbeef Ltd and SRUC.

This innovative project will integrate food industry waste with biorefining of a readily available non-food feedstock to overcome barriers for the production of high value chemicals with implications for the environment and rural economy. It will develop a process for the co-production of organic acid and chitin by co-fermenting the crab waste in combination with plant biomass using a microorganism which produces an organic acid resulting in solubilisation of protein and minerals and consequent buffering of the medium for an optimal fermentation. Protein degrading enzymes will be included for co-removal of proteins. Released minerals will reduce costs by enhancing production of the organic acids in the fermenting medium. The purified chitin will be assessed for its potential use as an agricultural bio-stimulant and as a raw material for producing both water treatment and personal and health care products. Economic models will be developed to determine the suitability of establishing full scale biorefineries in rural communities within the UK and will take into account the value of co-products including organic acids and protein.

Biomass produced from perennial energy crops, Miscanthus and short-rotation coppice, can reduce the carbon intensity of energy production. The UK Government has had incentive policies in place, targeting farmers and power plant investors to develop this market, but growth has been slower than anticipated. Market expansion requires farmers to select to grow these crops, and the construction of facilities to consume them. This project develops and uses environmental data linked to a model of biomass supply and demand to improve our understanding of the behaviour of the energy crop market in the UK. The project is led by a consulting company (Ecometrica) developing a data platform that will be available to potential market participants, based on scenario results from a market model developed by academic researcher (SRUC). Realistic market scenarios will be developed and tested using the decisions facing a major energy market participant (E.ON). The outcome will be a credible set of business scenarios of market development useful for both government and private investors, and information on the environmental impact, including the lifecycle carbon cost.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Considerable amounts of fresh beef are discarded before sale and in the home because of discolouration. The subject of waste and improving economic and environmental efficiency in meat supply chains is an area of utmost importance with major opportunities for improvement.. The proposal aims to enable innovations that will increase efficiency in processing and distribution and reduce wastage in the beef supply chain by improvements in eating quality, meat spoilage and increased colour shelf life. The project will adapt a participatory approach from retailer to primary production identifying critical control points which underlie waste in the beef supply chain.

Project Title: Gene pool fishing by out-crossing and back-crossing cycles in one terminal sire sheep breed -blueprint for terminal sire breeding in the UK and beyond. Project Number: 101085 Project Partners: H.R. Fell & Sons Ltd (The Meatlinc Sheep Company) Lead Partner Total Grant £42,460 Scottish Agricultural College Academic partner Total Grant £122,000 Project description: This project will provide a genetically improved terminal sire sheep breed and a demonstration on how to achieve substantial extra selection gains in one breed by exploiting genetic variance in others. It will use high accuracy (computed tomography [CT]) technology, available in the UK to sheep breeders, to comprehensively evaluate growth, composition, muscling and meat quality indicators of selection candidates produced by outcrossing, inter-se matings and repeated backcrossing. The aim will be to identify carriers of valuable genetic variants relating to production efficiency that have been carried over from the other breeds, then to increase their frequencies in the target terminal sire breed, therefore enriching their gene pool. CT is non-invasive and allows very accurate measurements of carcass quality in live animals. CT will serve as a "dense net in a gene fishing exercise" for suitable gene variants.

This project centres on exploring the potential to extract key new information from the spectral analysis gained through the mid Infra Red testing of individual cow milk samples. The scope exists to use the spectral data gained from such testing to estimate the quantity of a range of fatty acids in milk. Such information is valuable in terms of assessing cow health, fertility and nutrition status and also can be used to estimate the methane emissions of the cow. This project will focus on determining the potential to establish a number of new cow performance measures that will allow the dairy industry to optimise herd performance and maximise the lifetime yield of the herd. This in turn will not only boost the economic sustainability of dairying but also lessen the environmental impact of the sector. Another aspect of the project will be to assess the heritability of certain fatty acid traits. It is anticipated that heritability will be shown to be a key determinant of certain fatty acid types. If this can be demonstrated through the project, breeding programmes can be developed that take these traits into account such that the genetic pool within the dairy herd is strengthened in the right areas, delivering improved cow health and potentially improving the healthiness of dairy products for human consumption.

UK production of salmon, pigs and poultry is over-reliant on imported soy protein which has significant sustainability and supply concerns. Using air classification (AC) of UK grown faba beans we will develop two new products to partially replace imported soy. AC is a simple, low cost process requiring no addition of water, solvents or heating and will be used to produce bean protein concentrate (BPC, 56% protein and 5% starch) for use in salmon feeds and bean starch concentrate (BSC, 54% starch and 18% protein) for use in pig and poultry feeds. Dietary studies will assess the scope to replace soy by these products in the three animal species described. Bean varieties with improved qualities (higher protein, lower anti nutritional factors, and traits transferred into winter varieties) will be developed to further enhance the economic value of the process.

The consortium will develop a health and condition monitoring platform, a foundation to creating decision support applications in order to catalyse improvements in production efficiency and a concomitant reduction in waste and losses in the ruminant protein supply chain. The solution will encompass reliable and continuous monitoring and sensing of specifically defined, important variables and signals in beef and dairy cattle in commercial agricultural settings including challenging physical environments. As well as providing valuable management and labour saving tools, these solutions offer distinct efficiency advantages for commercial producers.

British Limousin Cattle Society (BLCS), Anglo Beef Processors (ABP) and Scottish Agricultural College (SAC) are partners in a three year £700,000 project to implement genomic selection for Video Image Analysis (VIA) carcass traits. The project is co-funded by the government-backed Technology Strategy Board and will combine abattoir VIA information on slaughter animals and high density genotypes from a number of Limousin sires to produce a UK Limousin SNP key. Once the SNP key is developed, Limousin genomic breeding values can then be accessed though a BLCS subsidiary company which can assist breeders in identifying which animals to genotype, facilitate the collection of DNA samples, and coordinate the transfer of genotype information and the resulting genomic breeding values. Genetic improvement of beef carcass traits in the UK currently uses traditional BLUP genetic evaluations for live weight and ultrasound measures recorded mostly on pedigree animals. Installing VIA machinery into the abattoir provides the opportunity to collect large amounts of high quality carcass information on slaughter animals at line speed in the abattoir. With the VIA carcass traits being measured late in life, in high volume and on animals outside the pedigree sector they are an ideal subset of traits to benefit from genomic selection. This project provides Limousin genomic breeding values for carcass traits that are measured on the actual beef carcass at the time of slaughter. The use of genomic selection also allows more accurate selection for carcass traits earlier – potentially at birth - in the animals life. These aspects combined will accelerate genetic improvement for carcass traits and provide a platform for genomic selection for future traits. Furthermore, market signals will be greatly strengthened in the supply chain with both the pedigree and commercial sectors using the same measurements of quality to assess their animals. This will enable clearer signals to be sent faster to the pedigree sector about the characteristics of animals that the market values and for which they should be breeding.

Free Living Nematodes (FLN) are emerging as a major problem for UK potato growers, exacerbated in the short term by removal of approved nematicides and in the long-term by expected population increases due to climate change. FLN cause direct damage by feeding on potato roots reducing yields and quality, and indirectly by transmitting Tobacco Rattle Virus (TRV). Relatively low levels of TRV infections can render entire crops unsaleable, both for the fresh and the processing industries. Current knowledge estimates the total loss to the UK potato industry to be >£13m p.a. FLN comprise a range of different taxonomic groups that are difficult to distinguish visually but vary significantly in terms of their distribution, pathogenicity and virus transmission frequencies, and have been to date under-studied in the UK. The problem is further compounded by beneficial and pathogenic FLN species co-existing, and thus accurate discrimination is essential. This project brings together a consortium of companies with a grower base of over 500 growers invloved in ware potato production seed both for use in the UK and export. In addition, a number of companies with potential methods for controlling FLN populations are included as partners. For the first time, a molecular diagnostic capable of distinguishing between the three main groups of FLN of interest will be developed, validated and deployed. This will be used to assess direct FLN feeding damage on a selection of commercial potato varieties as well as study effects on tuber quality and transmission of virus. In parallel, molecular markers will be developed to facilitate the breeding of new potato varieties with resistance to TRV.