Award details

13TSB_AgriFood: Automated screening for pathologies at abattoir through computer vision- based inspection of pig carcasses

Reference	BB/L017423/1
Principal Investigator / Supervisor	Professor Stephen McKenna
Co-Investigators / Co-Supervisors
Institution	University of Dundee
Department	Computing
Funding type	Research
Value (£)	21,394
Status	Completed
Type	Research Grant
Start date	31/01/2014
End date	31/10/2017
Duration	45 months

Abstract

The aim of the proposed project is to develop an automated system, based on visual image analysis that detects a number of public health hazards on pig carcasses through carcass inspection at abattoir, and to screen pig carcasses at slaughter for conditions indicative of subclinical diseases. The technical objectives of the proposal are to: (1) develop and deploy multi-camera recording infrastructure that enables capture of images of carcasses; (2) acquire image data sets and have experts annotate pathologies in these images; (3) develop and refine algorithms/software that can automatically recognise pathologies; (4) validate these algorithms on large scale datasets, and disseminate results to relevant users. These aims align with the TSB competition aim of 'Data capture and integration through the value chain'. The automated capture of data associated with subclinical diseases will be fed to pig producers through the activities of BPEX Pig Health Scheme; producers will then be able to make decisions about improving the health of their herd. As such, the proposal is also directly aligned to the competition aim of 'Management decision making'.

Summary

Visual inspection of carcasses is an important factor for ensuring the quality of meat products. However, manual inspection puts a strain on meat inspector resources, which effectively prevents detailed screening as, for example, for the purposes of health schemes. The aim of this project is to develop an automated system for visual screening at abattoir. The system will analyse images taken at abattoir in order to detect a number of health hazards on pig carcasses, and to screen them at slaughter for indications of underlying subclinical diseases. The project will: (1) develop a system for capturing images of carcass; (2) acquire image data sets and have experts annotate pathologies in them; (3) develop software that learns to recognise pathologies automatically; (4) validate the system on large scale datasets for the detection of routine health hazards, and disseminate results to relevant users, incl. providing feedback to farmers. The project brings together market leaders in meat production (Tulip) and supplier for abattoirs (Hellenic), pig levy board (BPEX), the UK's leading centre for research into pig science (Newcastle Univ.), and experts in computer vision and pattern recognition (Newcastle Univ. and Univ. of Dundee). It will enhance confidence in detecting health hazards in pig carcasses, aiming towards automated detection of underlying subclinical disease. Feeding this back to pig farmers will increase productivity and improve efficiency on farms through preventing further diseases. Producers will be able to make decisions about improving the health of their herd through the information they receive from the abattoir. The project will thus contribute towards sustainability and competitiveness of the UK pig Industry.

Impact Summary

Impact on pork industry Meat inspection is a significant cost to the industry, and regardless of the size of the abattoir these costs are still incurred. The introduction of the proposed automated system into the abattoir inspection systems will reduce such costs. Outside the participating Industry, the primary beneficiaries of this research will be the wider food production industry that does not participate in the project: the broader Pig Sector, the Government and Government Agencies, the Academic community and the Wider Public who will benefit as a consequence of successful implementation. Industry partners in the consortium will be in the unique position of exploiting the outcomes of the project for the benefit of their businesses. This will confer major competitive advantages, especially as outcomes will be applicable to the wider pig sector, and potentially beyond. In the first instance Tulip's abattoir in Spalding, which will serve as development facility, will benefit from the automated analysis system. Subsequently the system can be rolled out to all Tulip facilities, which will result in automatic screening of effectively ~30% of the UK's pig kill. With moderate site-specific modifications the proposed technology can be deployed in most abattoirs (world-wide). The system could be potentially installed in all pig abattoirs in the UK and the European Union, provided that it obtains approval from the (E)FSA. Wider governmental and societal impact BPEX involvement in the project will ensure potential adoption of the product by all abattoirs that slaughter pigs in the UK. The current mechanisms of BPHS for disseminating information on the incidence of pathologies to pig producers will ensure that the generated information will reach the majority of UK pig producers. In general the outcomes of the project will be of particular relevance to policy makers, especially to those that aim to ensure production of safe and high quality meat products. In general, thereis increased public interest in the safety of livestock products, including authentication and incidence of zoonotic diseases. Processors and retailers are the conduit for such concerns. Part of the project outcomes will be the production of safer pork products, which is of interest to retailers and public alike. FSA publishes reports about the incidence of such pathologies on its websites and retailers are very keen to disseminate information about the safety of their products. Academic Impact Academic partners will benefit from the application of their skills to pig production systems, and the challenges this brings, and the consequent enhancement of their on-going research. Potentially the algorithms developed for the detection of pathologies in pig carcasses could be extended to detect pathologies in other livestock carcasses. This will significantly expand the scope of the research of the academic partners. The application of the developed algorithms to pig pathologies will be subject to communication at the latter stages of the project. Exploitation and Application Project outcomes are expected to confer competitive advantages on the industry partners involved. Information generated on the incidence of specific pathologies will directly benefit Tulip-associated pig producers and eventually all BPHS associated pig producers. The application of the automated system will increase the number of carcasses inspected and thus enhance the value of the BPHS. Hellenic Systems would be expected to market the automated recording systems to UK abattoirs, including those associated with Tulip. Clearly the impact of the product developed by the project would be enormous if the system is adopted by (European) FSA. The impact activities will be primarily undertaken by BPEX, Tulip and the academic Institutions; all of them have considerable relevant KT experience and successes as outlined above.

Committee	Not funded via Committee
Research Topics	Animal Health, Microbial Food Safety, Technology and Methods Development
Research Priority	X – Research Priority information not available
Research Initiative	Innovate UK (TSB) [2011-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BB/L017385/1 13TSB_AgriFood Automated screening for pathologies at abattoir through computer vision based inspection of pig carcasses

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