Reports on Seed Funding

Summary of the projects funded using the BBSRC Seeding Catalyst Awards. 

1. Automated welfare monitoring of dairy cows using 3-dimensional imaging and deep learning - Prof Melvyn Smith & Dr Mark Hansen.

This project was carried out with Agsenze, Westpoint Farm Vets and Agri-Epi Centre and aimed to improve lameness scoring performance and explore the feasibility of adding rumen-fill scoring to a low-cost automated system for on-farm health and welfare monitoring. Key impacts of the award include – a proof of concept that rumen fill can be captured in a practical way on the farm from a moving animal, opening up potential for future implementation; that in a deep learning approach, a new combination of animal characteristics (not just spine curvature but also movement related) has the potential to improve lameness detection; and that an on-going relationship aimed at taking this technology to the market and so realising a beneficial impact has been cemented between the academic and commercial partners. The results for their rumen fill and lameness detection work are being prepared for publication.

2. National roll out of an online lameness recording system for UK sheep farmers - Prof Laura Green and Dr Emma Monaghan

The academics worked with Border Software on this project aiming to provide sheep farmers with a method of collecting lameness treatment records that can be analysed to provide personalised reports and advice, thus enabling informed management decisions to minimise the impact of lameness on flock welfare and productivity. The funding has facilitated a successful collaboration between academics and industry bu providing a link between farmers collecting 'real data' on lameness treatments and the academic expertise. They were able to demonstrate the economic and welfare benefits of collecting lameness treatment information to the stakeholders that benefit from it the most. They are working on developing an iOS app for data collection and continue to recruit farmers to share data using this system. 

3. Non-invasive EEG for fish: an international industry-academic collaboration - Prof James Turnbull and Prof Toby Knowles

This funding was for a knowledge exchange project enabling the academics involved to collaborate with experts from Ace Aquatec, Silsoe Livestock Systems and academics from SLU Gothenberg. There were three major outcomes during the project. (1) A firm collaborative base was established between all the academic and industrial partners, including commercial processing sites. This included the exchange of a great deal of understanding, detailed discussions on: available resources, researchable constraints, IP and concrete plans for future cooperation. (2) Equipment was moved from Bristol to Stirling as part of a strategy to sustain fish EEG technology in the UK. This involved the physical transportation of the equipment and training in its use.  (3) The lack of robust field EEG sampling equipment was identified as a major constraint to current and future research. Outlines for the requirements for such equipment were put together as was preliminary development on prototype components. It would now appear realistic that we will be able to use non-invasive EEG to monitor the efficacy of commercial stunning of fish at slaughter at a pilot scale within the next year and at a commercial scale within 2 to 3 years.

4. Sandpit event to generate research and development ideas designed to improve the sustainability of the UK poultry industry whilst protecting and improving animal welfare - Dr Sarah Lambton and Stuart Blyth (CIEL)

A workshop was held on 14th January and attended by representatives from four research institutes, three industry bodies, thirteen companies as well as CIEL and Innovate UK. The workshop included presentations of past and present poultry research and government research priorities followed by a workshop teasing out the issues and research priorities for the poultry industry. From this four proposals were generated covering the transition of pullets from their rearing facilities to the laying house; simulating maternal care for chicks; defining the terms of reference for sustainability in the poultry industry and investigating links between the microbiome and health, welfare and performance. The objective was to chose one of these projects to be worked up into a full proposal for submission to the Innovate funding call by the end of February.  In the end three of the proposals reached the initial stages of development into a full application for the Innovate funding call, however none of them reached submission for a variety of reasons. Efforts are being made to find alternative suitable funding opportunities for these proposals and other ideas generated during the event. 

5. The roll-out of Qualitative Behaviour Assessment (QBA) in commercial livestock welfare management through mobile application technology - Prof Francoise Wemelsfelder and Mr Thomas Krzyzelewski

The academics worked with Sainsburys, Evidence Group and Medayo (an app development company) to translate QBA methodology into mobile application (Android and iOS). This was completed within the incredibly tight project timeline. The functionality of the resulting application was demonstrated to, and approved by, a new industry partner. An article was submitted to UK Vet Livestock on “Qualitative Behaviour Assessment as an indicator of animal emotional welfare in farm assurance” by Richard Cooper (Evidence Group) and Francoise Wemelsfelder. The review provides discussion of QBA’s main benefits and risks to farm assurance, suggests that investment in data information technology is required to facilitate/address these, and ends by acknowledging that the current award has enabled SRUC to make a start with this process. A commercial Licensing Agreement with a new UK industry partner for roll-out of the QBA app across their livestock business. The licence demonstrates the success of this project, producing a mobile delivery mechanism for QBA to contribute to major UK business initiatives aimed at promoting high welfare for livestock.

6. Factors affecting bird distribution in loose housed laying systems - Dr Kate Norman and Dr Siobhan Abeyesinghe

This project worked with Oakland Farm Eggs to investigate associations between environmental temperature, bird distribution and indicators of thermal comfort in commercial systems. Since hens can move across the house, up or down the temperature gradient, they tested the hypothesis that bird-distribution along the temperature gradient influences local stocking rate. A temperature gradient was recorded across the laying shed and it was found to positively correlate with the number of birds recorded on the litter area, sitting and dustbathing. Further investigations are required to identify if the increase in bird numbers resulted in higher temperatures or higher temperatures attracted more birds. These results are directly applicable for our industry partners and may also be applicable to a variety of laying systems, particularly with the increase in larger loose-housed systems. These results will be presented at industry meetings and conferences and are more in depth analysis is planned for publication in a peer-reviewed journal. 

7. Development of a Health & Welfare Index or broilers using vocalisation data - Prof Lucy Asher

Working with Agsenze and Applied Poultry / Hudson & Sanders, this was a proof of concept and knowledge exchange project to understand the feasibility of automated health and welfare detection for broiler chickens. During the project Agsenze have built a new low cost microphone platform, and working with NU have built in detection of specific acoustic parameters. This has led to development of a threshold level within these parameters which is expected to detect health and welfare compromise in young broiler chickens. This will be further tested in a future Innovate project. A combination of peer-reviewed commercial literature and consultation with poultry industry members was used to identify how different health and welfare problems could be detected using automated methods. They were able to collect some pilot work to test a number of these methods using the types of sensors within the AgSenze platform and detail which new technologies could be incorporated into the platform for added value.