Harbro Limited Public Funding

Coming Soon Bymetric is Launching Soon

Lameness can affect up to 20% of pigs in the UK and is one of the major welfare issues across the livestock industry. Animals which are lame may be in pain, require veterinary treatment and may not reach their full production potential. This project seeks to develop a pig management tool which will help identify pigs which are currently lame, or which are likely to become lame in the future and therefore should not be used for breeding. By utilising of recent advances in imaging technology, the consortium will be able to develop and exploit an affordable technological solution. Based on deviations from normal movement patterns, the technology will be able to flag up affected individuals to the farmer or his advisors e.g. veterinarians. It will also help genetic companies select for animals which are less susceptible to lameness to breed from. This will help reduce the costly impact of lameness on the industry, improving efficiencies and pig welfare, and promoting sutainable food the the benefit of all.

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.

"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."

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.

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.

Subclinical & clinical disease is the main factor responsible for pig system inefficiency & reduction in pro-ductivity and welfare. Currently disease detection is done through human observation or diagnostic sur-veillance, but monitoring continuously involves significant costs & effort.The project aims to develop & validate technology to automatically monitor performance and behaviour in growing pigs. Individual pig and group movements will be automatically captured and analysed using low cost camera installations and computer vision and learning techniques, thereby providing information about pig performance, behaviour and group dynamics so as to allow rapid intervention to improve health and welfare and increase farm efficiency. The consortium has skills in the design of software solutions, animal health & diagnostics, and pig management, with the academic partner being at the forefront of research in computer vision/recognition techniques and pig management & health.

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.

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.