About the Project
This studentship is an exciting opportunity to be involved in a large collaborative multi-disciplinary project comprising of experts in the following areas: beef production, carcass evaluation, animal health and welfare, smart-farming (precision livestock farming), advanced imaging techniques, sensing systems and advanced data analytics (specifically machine learning approaches).
There are two main market-driven challenges facing the UK beef sector:
1. Pre-farm gate: Currently, producers monitor performance and select cattle for slaughter through visual assessment and manual weights over weigh platforms. In 2017, 51% of prime beef carcasses in the UK did not meet target fat and conformation grades (AHDB, 2018). Animals are frequently over-finished leading to increased variable farm costs (feed, bedding and labour), reduced annual capacity of finishing units and increased primary processing costs. The cost to UK producers of sending over-finished cattle to slaughter has been estimated at £8.8 million per year. Over-finished cattle also have an environmental cost, with an estimated 100 year global warming potential of 230 kgCO2eq per animal (14 days over-finished) (AHDB, 2018).
2. Post-farm gate: Classification of beef carcasses in the UK is undertaken predominantly by visual assessment by trained assessors, who allocate EUROP fat and conformation grades. This forms the basis of payment from processor to producer but presents a number of challenges including cost (manual assessors and re-training), availability of trained staff and consistency. Lack of confidence in the reliability of classification makes it difficult to agree quality-based payment schedules that reflect the true carcass value.
This PhD will focus on the use of engineering solutions (advanced sensing and high-resolution imaging systems) on-farm and in the abattoir, coupled with advanced data analytics (specifically machine learning approaches), to provide more accurate and detailed measurements of the carcass and it’s individual components than currently available. A more comprehensive dataset with variables generated on-farm and in the abattoir, will allow for a better understanding of yield development at the individual animal level, and drive improvements in product quality and consistency through enhanced decision support (optimised nutrition, farm advisory services (business management, health and welfare), optimised slaughter selections).
The successful student will work with the Beef and Sheep Research Centre team at SRUC. The student will register at the University of Edinburgh where they will have access to the training environments of both SRUC and the University of Edinburgh. Both institutions are committed to the training of PhD students in both specific and transferable skills. The student will receive mentoring and training in the following areas specific to this PhD project: beef production systems, precision livestock farming developments, product quality (carcass) and advanced data analytics (specifically machine learning techniques).
The student will receive further support from two participating SME’s offering access to expertise, facilities and experience of working in a professional environment including engagement with end-users. Innovent Technologies, an agri-technology company, will provide access to expertise in advanced imaging, data science and decision support for livestock applications. Agri-Epi, one of four UK government AgriTech Innovation Centres, brings expertise in precision farming applications.
Expected start date is the 1st October 2020.
Funding Notes
The student will receive an annual student stipend of £15,285 at 2020/21 rate. This studentship will fund to pay the tuition fees at home fees rate only. International students must provide evidence of sufficient funds to cover the higher international student tuition fee level (approximately £19,093 per year would be required).
Students should have at least a BSc 2:1 degree (or equivalent) in a biological subject such as animal science, agriculture, or related subject. If English is not an applicant’s first language, see https://www.ed.ac.uk/news/covid-19/prospective-students/entry-requirements/english-language-tests for more details.
References
To apply for this studentship, please complete the application and equal opportunities monitoring forms by clicking on the ’Institution website’ icon on the right. Send your forms to pg.research@sruc.ac.uk, alongwith a copy of your CV.