Assessment of Dairy Cow Welfare through Predictive Modelling of Individual and Social Behaviour
Lead Research Organisation:
Writtle University College
Department Name: Sport, Equine and Animal Science
Abstract
Dairy cow welfare is increasingly a subject of public concern. A recent European report of leading scientists concluded that lameness and mastitis of cows were the most important factors in reducing the welfare of dairy cows due to the pain associated with these conditions. Unfortunately, the Farm Animal Welfare Council in the UK also reports that the dairy industry has made little progress in addressing these problems, mainly due to a reduction in profitability affecting investment and the lack of welfare surveillance systems available. A major challenge in improving the welfare of food production animals is in developing methods of automating the detection of such welfare problems. Such detection systems should be able to operate as early warning systems and detect the early signs of disease or illness within dairy herds and individual cows.
Thanks to new technological developments there are potential solutions. Until recently, it has not been logistically possible to monitor the complex behaviour associated with animals kept in large social groups, such as sheep, pigs or cows. However, novel local positioning wireless sensors such as those designed by our project partner, Omnisense, can be deployed over large networks of animals and give accurate positioning information for individuals over long periods of time. For the first time we will be able to record large quantities of data regarding the behaviour and social interactions in a whole herd of dairy cows.
Research studies have shown that diseases such as lameness in dairy cattle can affect general behaviour, such as how long cows spend lying down. Similarly, social interactions between individual animals, such as how much time they spend close to each other or how closely they synchronise their behaviour, have been suggested as possible measures of animal welfare. However, it is a non-trivial problem to determine and quantify changes in individual and social behaviour and subsequently to use such changes to predict the onset of disease.
In this project we will be using automated data collection techniques to record patterns of space use, movement, and social interactions within commercial dairy herds. In the first year, the behaviour of animals with lameness, mastitis or metabolic disease will be compared with healthy animals to determine differences in behaviour. In year two, a full dairy herd will be monitored for an extended period from calving to measure changes in their behaviour with the natural onset of disease in order to identify early changes that might be used to subsequently predict disease occurrence. In year three, the study will be repeated on three other farms to test whether such predictions are still relevant on different intensive dairy units.
The behavioural data will be analysed using cutting-edge mathematical and statistical techniques. Using information about the observed changes in both individual cow behaviour and herd social structure we will develop a predictive model for the onset of disease and other welfare changes within individual cows. This will lead to the development of an on-farm automated 'early warning' system for disease detection. Such a system would be invaluable for improving the welfare and productivity of dairy cows.
Using the techniques we develop for predicting the onset of disease we will also determine if it is possible to use behavioural changes to identify other important welfare changes in dairy cattle, in particular the onset of oestrus and the time of calving.
Thanks to new technological developments there are potential solutions. Until recently, it has not been logistically possible to monitor the complex behaviour associated with animals kept in large social groups, such as sheep, pigs or cows. However, novel local positioning wireless sensors such as those designed by our project partner, Omnisense, can be deployed over large networks of animals and give accurate positioning information for individuals over long periods of time. For the first time we will be able to record large quantities of data regarding the behaviour and social interactions in a whole herd of dairy cows.
Research studies have shown that diseases such as lameness in dairy cattle can affect general behaviour, such as how long cows spend lying down. Similarly, social interactions between individual animals, such as how much time they spend close to each other or how closely they synchronise their behaviour, have been suggested as possible measures of animal welfare. However, it is a non-trivial problem to determine and quantify changes in individual and social behaviour and subsequently to use such changes to predict the onset of disease.
In this project we will be using automated data collection techniques to record patterns of space use, movement, and social interactions within commercial dairy herds. In the first year, the behaviour of animals with lameness, mastitis or metabolic disease will be compared with healthy animals to determine differences in behaviour. In year two, a full dairy herd will be monitored for an extended period from calving to measure changes in their behaviour with the natural onset of disease in order to identify early changes that might be used to subsequently predict disease occurrence. In year three, the study will be repeated on three other farms to test whether such predictions are still relevant on different intensive dairy units.
The behavioural data will be analysed using cutting-edge mathematical and statistical techniques. Using information about the observed changes in both individual cow behaviour and herd social structure we will develop a predictive model for the onset of disease and other welfare changes within individual cows. This will lead to the development of an on-farm automated 'early warning' system for disease detection. Such a system would be invaluable for improving the welfare and productivity of dairy cows.
Using the techniques we develop for predicting the onset of disease we will also determine if it is possible to use behavioural changes to identify other important welfare changes in dairy cattle, in particular the onset of oestrus and the time of calving.
Technical Summary
The aim of the project is to develop an automated system that uses behavioural observations to predict the onset of diseases such as lameness and mastitis within a commercial dairy herd. The project is highly timely: the latest automated wireless sensors provided by our project partner will allow us to collect an unprecedented amount of data on the behaviour of large herds of cows (140+ individuals) over months at a time.
With an automated system the true behavioural states of each individual cow are not known but instead an observed output state is determined from the positional and activity data collected automatically using the wireless sensors. This is an ideal scenario to use Hidden Markov Models (HMM). HMMs are a flexible statistical tool that allow one to model and analyse sequences of behaviour and have not previously been used in this context. In particular we will use HMMs to identify atypical cow behaviour and we hypothesise that this will be a useful predictor of disease state.
Social Network Analysis (SNA) is a powerful framework which provides metrics that quantify social structure at different levels of organisation. These metrics can be used to test hypotheses regarding the relationship between an individual's social network position and its attributes such as disease status. A highly novel aspect of this project will be to use SNA of the behavioural data to make predictions about changes in welfare of individual cows within the herd.
Using computer learning techniques such as artificial neural networks we will combine the results of the HMM and SNA analysis together with other indicators of welfare to predict disease onset in individual cows. This will lead to the development of an on-farm automated 'early warning' system for disease detection. We will also apply the methodology to try to predict two other important aspects of cow welfare: the onset of oestrus and the time of calving.
With an automated system the true behavioural states of each individual cow are not known but instead an observed output state is determined from the positional and activity data collected automatically using the wireless sensors. This is an ideal scenario to use Hidden Markov Models (HMM). HMMs are a flexible statistical tool that allow one to model and analyse sequences of behaviour and have not previously been used in this context. In particular we will use HMMs to identify atypical cow behaviour and we hypothesise that this will be a useful predictor of disease state.
Social Network Analysis (SNA) is a powerful framework which provides metrics that quantify social structure at different levels of organisation. These metrics can be used to test hypotheses regarding the relationship between an individual's social network position and its attributes such as disease status. A highly novel aspect of this project will be to use SNA of the behavioural data to make predictions about changes in welfare of individual cows within the herd.
Using computer learning techniques such as artificial neural networks we will combine the results of the HMM and SNA analysis together with other indicators of welfare to predict disease onset in individual cows. This will lead to the development of an on-farm automated 'early warning' system for disease detection. We will also apply the methodology to try to predict two other important aspects of cow welfare: the onset of oestrus and the time of calving.
Planned Impact
Veterinary and animal science research has had a longstanding partnership between academia and industry. The main beneficiaries for this research are the 15,000 dairy farms in the UK with their 1.8 million cows. Disease is a common occurrence in dairy cows with 15-39 per cent of cows suffering from lameness (with up to 79 per cent of cows on a single farm) with an individual case costing an estimated £240. A direct end-user for the research findings will be our industry collaborator DairyCo who represent the UK dairy industry and will disseminate findings through their 'Cow Signals' programme, a national knowledge transfer initiative that directly engages and informs farmers about the importance of animal behaviour in welfare monitoring. We will also engage directly with producers through our collaboration with Milk Link who are owned by over 1500 UK dairy farmers. Milk Link employs over 1200 people at eight processing and packaging facilities in the UK and has an annual turnover of £586 million (2010/11).
This research will also have significant international impact, as exemplified by the fact that lameness and mastitis have been highlighted as the most important factors in a survey on the consequences of poor welfare in cows by the European Food Safety Authority. The results of our research will be relevant to all high producing nations maintaining intensive dairy units.
Better systems for understanding the link between behaviour and welfare have the potential to have significant impact on other sectors of the food production industry that rear animals in social groups (e.g. beef cattle, sheep and pigs). Our research will also be of significant interest to those seeking to have more informed welfare standards including the leading supermarket chains and animal welfare charities. The general public are increasingly interested in the welfare of farm animals as evidenced by the popularity of food produced through Farm Assurance schemes. The research will have a significant impact on our project partner, Omnisense Limited, enabling them to develop and test novel technology that could be used for a commercial 'early warning system' for on-farm disease detection.
This research will also have significant international impact, as exemplified by the fact that lameness and mastitis have been highlighted as the most important factors in a survey on the consequences of poor welfare in cows by the European Food Safety Authority. The results of our research will be relevant to all high producing nations maintaining intensive dairy units.
Better systems for understanding the link between behaviour and welfare have the potential to have significant impact on other sectors of the food production industry that rear animals in social groups (e.g. beef cattle, sheep and pigs). Our research will also be of significant interest to those seeking to have more informed welfare standards including the leading supermarket chains and animal welfare charities. The general public are increasingly interested in the welfare of farm animals as evidenced by the popularity of food produced through Farm Assurance schemes. The research will have a significant impact on our project partner, Omnisense Limited, enabling them to develop and test novel technology that could be used for a commercial 'early warning system' for on-farm disease detection.
Publications
Barker ZE
(2018)
Use of novel sensors combining local positioning and acceleration to measure feeding behavior differences associated with lameness in dairy cattle.
in Journal of dairy science
Boyland N
(2016)
The social network structure of a dynamic group of dairy cows: From individual to group level patterns
in Applied Animal Behaviour Science
Chopra K
(2020)
Proximity Interactions in a Permanently Housed Dairy Herd: Network Structure, Consistency, and Individual Differences.
in Frontiers in veterinary science
Vázquez Diosdado J
(2015)
Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system
in Animal Biotelemetry
Vázquez Diosdado J
(2015)
Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system
in Animal Biotelemetry
Vázquez Diosdado JA
(2018)
Space-use patterns highlight behavioural differences linked to lameness, parity, and days in milk in barn-housed dairy cows.
in PloS one
Description | We aimed to develop an early warning system to detect health and welfare issues in dairy cows, through remote tracking of their movement and behaviour. We have found key differences in how animals use space, particularly relating to their disease status where lame cows will have a smaller range size in housing and be more likely to return to the same resting position. |
Exploitation Route | Analysis is still ongoing, but hope for important indicators for monitoring animal welfare and industry development of technology to monitor health and welfare. |
Sectors | Agriculture Food and Drink Environment |
URL | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0208424 |
Description | Project is still ongoing but aims to develop early warning system for detecting health and welfare problems in dairy cattle. We are also looking at applications in other species groups including zoo animals. |
First Year Of Impact | 2016 |
Sector | Agriculture, Food and Drink,Environment |
Impact Types | Societal Economic |
Description | Farm Animal Welfare Trust PhD Scholarship |
Amount | £45,000 (GBP) |
Organisation | Farm Animal Welfare Trust (FAWT) |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 08/2013 |
End | 09/2016 |
Description | Natural Environment Research Council (NERC): NE/P008011/1 - Novel animal-mounted sensor technology to improve efficiency and sustainability (£120000; 2017 - 2018) |
Amount | £250,000 (GBP) |
Funding ID | NE/P008011/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 02/2017 |
End | 08/2018 |
Description | Novel animal-mounted sensor technology to improve efficiency and sustainability |
Amount | £250,033 (GBP) |
Funding ID | NE/P008011/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 01/2017 |
End | 07/2018 |
Description | Omnisense Ltd project partner |
Organisation | Omnisense |
Country | United Kingdom |
Sector | Private |
PI Contribution | Project id developing new algorithms to be used within the Omnisense Ltd tracking system. |
Collaborator Contribution | Project uses Omnisense Ltd tracking technology to track dairy cows with the aim of detecting health and welfare issues. Omnisense provide direct ongoing technical support when running the system. A large discount was also offered on the initial costs of the tracking system. |
Impact | No direct outputs yet. |
Start Year | 2012 |
Description | AHDB dairy (Discover, innovate, grow) conference, Yew Tree Lodge, Kegworth. 1/3/16. |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | 20 minute presentation on 'Managing for optimal cow comfort' 125 farmers and advisors, with section which introduced paper by Zoe Barker on the used of biotelemetry sensors for welfare assessment and disease detection. |
Year(s) Of Engagement Activity | 2016 |
Description | BBC News / Radio 4 Interview and Video |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Media (as a channel to the public) |
Results and Impact | We were interviewed for BBC News and Radio 4 about our project for a story on the "Internet of Things". A web video about our project featured prominently on the BBC News website. We received more media and public interest in our project. |
Year(s) Of Engagement Activity | 2013 |
URL | http://www.bbc.co.uk/news/technology-23932259 |
Description | Big Bang @ Essex 2014 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Over 1000 schoolchildren and members of the public took part in our interactive Maths of Cows display at the Big Bang Fair at the University of Essex. |
Year(s) Of Engagement Activity | 2014 |
Description | Big Bang @ Essex 2015 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Over 1000 schoolchildren and members of the public took part in our interactive Maths of Cows display at the Big Bang Fair at the University of Essex. |
Year(s) Of Engagement Activity | 2015 |
Description | Big Bang National Science Fair |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Over 2500 schoolchildren and members of the public took part in our interactive "Maths of Cows" display at the Big Bang Fair at the NEC. Over 2500 people were directly engaged with and took part in activities related to our research project. |
Year(s) Of Engagement Activity | 2014 |
URL | https://www.thebigbangfair.co.uk/View/?con_id=4177 |
Description | Big Bang National Science Fair 2015 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Over 2500 schoolchildren and members of the public took part in our interactive Maths of Cows display at the Big Bang Fair at the NEC. |
Year(s) Of Engagement Activity | 2015 |
URL | https://www.thebigbangfair.co.uk/View/?con_id=4382 |
Description | CNBC TV programme contribution for "The Cloud Challenge" aired 28th February 2017 |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Interview with Dr Zoe Barker from Cow Tracking Project team at Sturgeons Farm, Writtle University College. CNBC interested in connectivity and use of the internet/cloud in agricultural management. Dr Barker talked through application of the OMS500 sensors from our partners, Omnisense, in the management of dairy cows. |
Year(s) Of Engagement Activity | 2017 |
URL | http://cnbc.com |
Description | Cattle Lameness Academy launch event |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Vets, foot trimmers and farmers from all around GB attended launch event for the Cattle Lameness Academy, held in Somerset. Several International and National levels speakers covered a range of topics. Title of presentation releavnt to this award was: Automatic lameness detection- 2020. |
Year(s) Of Engagement Activity | 2016 |
Description | Essex Food and Farming event |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | 3000 key stage 2 children attended the Essex Food and Farming Event to see a range of displays and presentations relating to farming. The BBSRC project was presented as an interactive display accompanied by video and posters to demonstrate the potential for behaviour monitoring to detect disease and therefore the potential for use of technology. Hugely positive feedback from all schools, particularly in areas of livestock farming engagement. |
Year(s) Of Engagement Activity | 2008,2009,2010,2011,2012,2013,2014,2015 |
URL | http://www.essexag.co.uk/ |
Description | Farming conference presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Title of presentation was: What impact can Health and Welfare planning have? Presented at Oxford Real Farming Conference 7th January 2016 - 60 farmers |
Year(s) Of Engagement Activity | 2016 |
Description | IMA@50 Festival of Mathematics |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Over 1000 schoolchildren and members of the public took part in our interactive "Maths of Cows" display at the IMA@50 Festival of Mathematics in Manchester. Over 1000 people directly engaged with our research project. |
Year(s) Of Engagement Activity | 2014 |
URL | https://twitter.com/imafest |
Description | Knowledge Transfer Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | Approximately 30 PG students and researchers attended a knowledge exchange workshop at the end of the main research project. The meeting was hosted at the University of Essex and had a day of teaching novel methods and tools for data analysis and modelling followed by a day of research seminars linked to the project. |
Year(s) Of Engagement Activity | 2016 |
Description | Livestock Trade show (The Livestock Event) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Raised awareness of farmers to the potential for monitoring behaviour and time-budgets of commercial dairy cows A farming press media article on a related topic |
Year(s) Of Engagement Activity | 2014 |
Description | Presentation to farmers |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Industry/Business |
Results and Impact | Title of presentation: Welfare assessment - what can we do on farm and how useful can it really be? West Sussex grassland society February 14th 2016 |
Year(s) Of Engagement Activity | 2016 |
Description | Radio 4 Farming Today Interview |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Media (as a channel to the public) |
Results and Impact | We were interviewed by Anna Hill for R4 Farming Today about our BBSRC funded project to monitor dairy cow welfare. Higher national interest in our project. |
Year(s) Of Engagement Activity | 2013 |
URL | http://www.bbc.co.uk/programmes/b01qw9f9 |
Description | SET for Britain |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Our research group presented a poster at the Houses of Parliament as part of the SET for Britain event in 2014. We directly explained the scope of our project to parliamentarians. |
Year(s) Of Engagement Activity | 2014 |
URL | http://www.setforbritain.org.uk/2014event.asp |
Description | Stakeholder Impact and Networking Engagement meeting (July 2018 at the University of Essex) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | An impact and networking meeting to engage with and disseminate project results to Industry and other stakeholders was held in July 2018 (funded and hosted by the University of Essex). Follow-up meetings were also held with stakeholders who couldn't make the meeting on the day. Industry representatives from Noldus, Omnisense, UFAW, Innovation for Agriculture, AHDB, ZSL, and academic collaborators form the Universities of Essex, Nottingham, Sheffield and Writtle University College were all involved. |
Year(s) Of Engagement Activity | 2018 |
Description | What's Your Angle at the London Science Museum |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Over 2500 schoolchildren and members of the public took part in our interactive Maths of Cows display as part of the What's Your Angle mathematics festival at the London Science Museum and supported by the London Mathematical Society. |
Year(s) Of Engagement Activity | 2015 |
URL | http://blog.sciencemuseum.org.uk/whats-your-angle/ |