Using systems biology to understand and routinely predict health and welfare traits in dairy cattle

Lead Research Organisation: SRUC
Department Name: Research

Abstract

The welfare of dairy cattle continues to gain importance, both nationally and internationally. However, welfare research has tended to focus on indicators of poor welfare such as disease or health status and longevity. More detailed studies of welfare on-farm have tended to be limited, using small numbers of animals or farms and of short duration. Recently, however, farmers are engaging with more detailed levels of on-farm recording, aided by farm management software and encouraged by farm assurance schemes they participate in, which has been shown to be of use in national genetic evaluations and/or benchmarking. Further, recent work by the partners have shown that that routine analysis of milk samples can predict the negative body energy balance in dairy cows, a trait related to metabolic stress and that immune function measures are correlated to health and welfare events such as mastitis, lameness and difficult calvings in dairy cattle.

This project will draw together the experience of partners to holistically explore animal health and welfare traits in dairy cattle, focussing on animals from the SAC Dairy Research Centre. The research herd is participating in ongoing genetic selection and feed experiments that produce detailed lifetime records for each animal, including production, health and welfare traits. This project will supplement these data with repeated analyses of immune and inflammatory measures in the blood and milk and weekly spectral analysis of milk. Mathematical models will be used to explore the biological relationships between the immune and inflammatory measures and defined health and welfare events in dairy cows. The health and welfare events include lameness, clinical mastitis, metabolic stress, calving difficulty (including Caesarean) and major reproductive illnesses (e.g., abortion, cystic ovaries). We will explore how the immune and inflammatory traits (supplemented by other key production/fitness data such as somatic cell counts) change before, during and after the defined health and welfare events. If successful, this modelling will result in predictive indicators that could lead to practical early warning systems for poor health and welfare traits in dairy cattle that could be implemented in the field to help explore/define new traits that relate to animal welfare.

Technical Summary

Using a systems biology approach we will explore the interactions that lead to and/or result in a poor health/welfare event in the dairy cow.

Assay. This project will routinely (bi-monthly for 2 years including a 6 month period of monthly sampling) assay the blood and milk of dairy cows for immunological parameters (natural antibodies, TNF-alpha, haptoglobin). These data will be collated with the routine collection of detailed data on MIR spectra (weekly) and other production (including product quality), health, welfare and fertility traits at the SAC Dairy Centre.

Integrate. Individual cow records collected on the farm include daily milk yield, live weight and body condition score, weekly milk fat and protein yield and milk somatic cell count, and thrice weekly feed and dry matter intake. Some of these data are routinely used as an indicator of welfare in farmed livestock (e.g., condition score). Also, these data will be collated in a SQL database to predict the ongoing body energy status of the dairy cow and therefore will be used to define the trajectory to negative body energy status (i.e., cow entering metabolic stress) and/or return to positive/neutral energy status. Health, welfare and fertility traits are also recorded under three main categories: (i) mastitis, (ii) reproductive problems (e.g., cystic ovaries, retained placenta, abortion), and (iii) lameness (e.g., sole ulcer, digital dermatitis, white line disease). Key fertility (e.g., calving interval, numbers of services) and reproductive (e.g., dystocia, stillbirth) parameters are also recorded.

Analyse. The data will be modelled to explore how temporal variation in the immunological parameters prior to welfare (including health) events could be used as early warnings of the subsequent event. Further, once sufficient samples are available, the milk MIR spectral data will be "trained" (SAC) to develop statistical predictions for the parameters that could be applied in routine milk recording.

Planned Impact

The future sustainability of the UK dairy industry relies on farmers being able to respond to key market signals and animal welfare is a key social (and economic) requirement. Key to addressing and responding to these signals is the ability to measure (or estimate), monitor and improve animal and production system attributes as they relate to animal welfare and other drivers (e.g., environment). This project offers a unique and innovative approach to preparing the UK dairy industry to address the challenges it will face to produce dairy products in a sustainable and socially acceptable manner. The partners have successfully worked together to begin to explore some of the key attributes of defining traits that relate to animal health and welfare and how these can be adopted by the industry. For example, SAC has delivered information on, and produced, practical dairy selection tools, particularly the inclusion of fertility, health, welfare and survival traits. These have helped UK dairy producers become more sustainable by adapting to a range of challenges, including consumer concerns; breeding for improved economic performance, animal health and welfare; and reduced environmental impact. Adoption of new indexes have improved animal health and welfare and economic performance compared to continued use of previous selection practices, and has cumulatively reduced greenhouse gas emissions per breeding animal by 1.4% (reduction in CO2 equivalents) per year in dairy systems. The overall annualised economic benefits of the genetic improvement that has taken place in the years 1980-2009 is worth £105.7 million/year to the UK dairy industry. A large proportion (~ 50%) has been realised by including health, fertility and longevity traits in UK dairy breeding goals.

As part of the project the partners will develop key knowledge transfer outputs, accessible to non-specialists. This will include developing display tools for participation in local public science events, includig the Doors Open Days, Knowledge Scotland, Edinburgh Science Festival and Royal Highland Show. These will also be available to policy makers linking to Centres of Expertise in Scotland, in which the partners are involved. Given the inter-disciplinary nature of this project, the impacts of the proposed work will go beyond the direct academic beneficiaries, having positive economic and societal impacts across a range of stakeholders including:
1. Policy makers and dairy industry will be able to use the outcomes from this project to help summarise the manner by which the UK dairy industry are actively working towards improving the social acceptability (and sustainability) of the dairy production chain. Animal welfare is generally viewed as a public good, but will likely be undersupplied by producers for a variety of reasons including the lack of appropriate indicators of welfare status. The results of this project will provide signals for both producers and government (who might need to regulate animal welfare).
2. Animal managers may be able to use outputs from this work to direct early intervention for improved animal welfare as well as exploring the impact of key management interventions such as feeding and breeding. By combining systems of data collection that are already in place to develop predictive models of welfare events this project will allow us to work with the dairy industry to implement such early warning systems.
3. The public will benefit from this project through having access to data allowing them to assess the cow health/welfare impacts of the dairy products they consume.
4. The UK overall will benefit through the linkages between the research innovation represented in the partners and those delivering knowledge and tools to the industry (e.g., Veterinary Surveillance Services); the outcomes will result in a shorter period from primary research through to on-farm implementation helping UK agriculture reap the benefits of this project.

Publications

10 25 50
 
Description Initial analysis on data has demonstrated that immune biomarkers recorded in this project are both heritable and repeatable.

Further analysis of immune traits in blood and milk has confirmed their heritability and repeatability. Analyses have also yielded strong phenotypic and genetic correlations between immune traits found in blood and those found in milk. Strong genetic correlations were observed between percent NKp46+ and stillbirth rate (0.61), and lameness episodes and percent CD8+ (-0.51). Results provide evidence that cellular immune-associated traits are heritable and repeatable, and the noticeable variation between animals would permit selection for altered trait values, particularly in the case of the T cell subsets. The associations observed between immune-associated, health, fertility, and production traits suggest that genetic selection for cellular immune-associated traits could provide a useful tool in improving animal health, fitness, and fertility. Moreover, results suggest natural antibodies found in milk are highly correlated with those found in blood, this is true at both the genetic and phenotypic level. A genome-wide association study carried out by our group also discovered 96 SNPs that were significantly associated with defined IA traits, most notably SNP on chromosome 17 and natural antibodies in a region previously linked with ptosis, intellectual disability, retarded growth and mortality (PIRM) syndrome in cattle. Moreover, 22 SNP were found to be common across 2 to 3 IA traits. A functional cluster analysis was carried out on significant SNPs and showed 9 clusters of genes linked to various immune response and inflammation genes as well as significant associations with biological pathways such as systemic lupus erythematosus and metabolic processes.

Preliminary analysis of immune-asscociated traits and their concurrent milk spectra has yielded positive results. In particular, haptoglobin (Hp) concentration, an important acute phase protein, has been predicted using milk MIR spectra with an accuracy of 81%. Additionally, MIR predictions of monocytes, white blood cells that are largest of all leukocytes and part of innate immune system, are currently 79%.
Exploitation Route Heritable immune markers which are associated with increased resistance to disease could be used to select dairy cows which are more disease resistant. This would improve dairy cow welfare, improve the efficiency of milk production, and reduce the use of drugs such as antibiotics in the dairy industry. The development of a simple method to record immune parameters in cattle via infrared absorption represents now means we can record immune function in large numbers of cattle on a repeated basis at minimal cost. Such immune measurements may be used to either select for 'good' immune traits which are associated with improved health, productivity and welfare, or as biomarkers for the early identification of disease.

This demonstrates that the chosen immune biomarkers are useful for the purposes of genetic dissection of immune response. Discussed results with industry stakeholders engaged in genetic improvement.

The results have been presented at (inter)national conferences
Sectors Agriculture, Food and Drink

URL http://www.sciencedirect.com/science/article/pii/S002203021730067X
 
Description The results from this project have been presented in industry meetings where dairy industry stakeholders have been made aware that immune biomarkers vary across animals and in relation to key health and welfare states of animals. This had particularly focused on the potential to use milk mid infrared spectral analysis to predict key immune biomarkers within the farm.
First Year Of Impact 2015
Sector Agriculture, Food and Drink
Impact Types Economic

 
Description AHDB PhD Studentship
Amount £72,000 (GBP)
Organisation Agricultural and Horticulture Development Board 
Sector Public
Country United Kingdom
Start 10/2014 
End 10/2018
 
Description Agritech LateStage Award
Amount £115,000 (GBP)
Organisation Innovate UK 
Sector Public
Country United Kingdom
Start 08/2015 
End 01/2017
 
Description Allocation of Research Excellence Grant
Amount £46,198 (GBP)
Organisation Government of Scotland 
Department Scottish Funding Council
Sector Public
Country United Kingdom
Start 10/2017 
End 03/2018
 
Description Allocation of Research Excellence Grant
Amount £51,700 (GBP)
Organisation Government of Scotland 
Department Scottish Funding Council
Sector Public
Country United Kingdom
Start 04/2016 
End 04/2017
 
Description Horizon 2020
Amount € 7,000,000 (EUR)
Funding ID 727213-2 
Organisation European Union 
Sector Public
Country European Union (EU)
Start 05/2017 
End 04/2022
 
Description KTN/BSAS Summer Vacation Scholarship Award
Amount £2,500 (GBP)
Organisation Knowledge Transfer Network 
Sector Charity/Non Profit
Country United Kingdom
Start 06/2015 
End 08/2015
 
Description PredictinB statg Tus of dairy cows from mid infra-red spectral data using machine learning
Amount £244,024 (GBP)
Funding ID BB/S009396/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 01/2019 
End 01/2021
 
Description RESAS Strategic Reserach Portfolio
Amount £25,000,000 (GBP)
Funding ID Work package 2.3 Agricultural Systems 
Organisation Government of Scotland 
Department Scottish Government Rural and Environment Science and Analytical Services Division (RESAS)
Sector Public
Country United Kingdom
Start 04/2016 
End 04/2021
 
Title High-throughput cell phenotyping of bovine leukocytes 
Description A method was developed to rapidly phenotype bovine blood leukocytes using high-throughput flow cytometry. The technique requires a small volume (25ul) of whole blood and can be used to determine the proportion of helper T cells, cytotoxic T cells, Natural Killer cells, neutrophils and eosinophils within the sample. This allows the simultaneous phenotyping of whole herds of cattle. 
Type Of Material Technology assay or reagent 
Year Produced 2014 
Provided To Others? Yes  
Impact This methodology has been used to validate previous findings that particular cell phenotypes are associated with increased resistance to disease in cattle. By increasing the number of cattle which can be phenotyped in this manner, it has been possible to estimate the heritabilities of these cellular immune traits in dairy cattle. 
 
Title High-throughput immune profiling of innate immune responsiveness in cattle 
Description A method has been developed to provide an estimate of immune responsiveness of bovine blood leukocytes to a range of innate immune stimuli including ligands for Toll-like Receptor (TLR) 1/2, TLR4, TLR5 and TLR7/8. Low volumes (100ul) of whole blood are stimulated with TLR ligands for 24 hours. Released cytokines are quantified by ELISA based methods. 
Type Of Material Physiological assessment or outcome measure 
Year Produced 2015 
Provided To Others? Yes  
Impact Using this method we have identified significant variation in the responsiveness of dairy cattle blood leukocytes to TLR stimulation. Responsiveness varies significantly with age but does not appear to be altered by selection for high productivity. This method will allow us to determine the implications of variation in innate immune responsiveness on dairy cow health, productivity and vaccine responsiveness. 
URL https://connect.innovateuk.org/documents/3285671/29811791/KTN_BSAS-Noronha_Report.pdf/9b66bfbf-5e29-...
 
Title Mid infrared spectral data based phenotype prediction tool 
Description A software workflow developed in Microsoft SQL for the storage, processing, calibration and preparation for reporting of mid infrared (MIR) -predicted phenotypes, implementing quality assurance checks, dynamic and flexible to the inclusion of additional traits and tailored for use in a commercial environment. Code has additionally been ported to the (open source) Python programming language and can be used on most operating systems. 
Type Of Material Improvements to research infrastructure 
Year Produced 2015 
Provided To Others? Yes  
Impact The tool is currently being used to advise farmers in the UK of cow energy traits within their herds. As the MIR spectral data is a byproduct of the routine milk recording process, the energy trait information can be generated in a completely non-invasive manner and hence, enable improvements in animal welfare. Moreover, the tool is being used to predict important immune-associated traits linked with health and fertility traits. 
 
Title Immune_Dairy Database 
Description The database incorporates measurements of a number of immune traits in a herd of dairy cattle over 15 sampling time points over an 24 month period together with health, production and reproduction traits. The immune traits have been measured in both blood and milk samples as part of the currently funded BBSRC grant and has been incorporated into an overall model to predict health events in dairy cattle. This database consists of 8 cellular immune traits, plus a number of paired immune measurements in serum and milk (cytokine, acute phase protein, natural antibody), with each trait being measured in a total of 3000 individual samples. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The database allows the matching of extensive phenotypic data to an individual cow's immune profile. Subsets of these data can be extracted and used in a wealth of data, statistical and mathematical analyses. 
 
Description Dairy Australia MoU 
Organisation Dairy Australia
Country Australia 
Sector Public 
PI Contribution This Memorandum of Understanding agrees to jointly work on the development of milk mid-infrared prediction tools to help dairy farmers manage and select their cows, combining of genomic information and the integration of genomic and milk mid-infrared data.
Collaborator Contribution The partners, by sharing of data, will help to further improve the impact of the original BBSRC project(s) after the projects have ended
Impact No outputs as yet. Not multidisciplinary
Start Year 2017
 
Description Genomes Canada - Efficient Dairy Genome Project 
Organisation University of Alberta
Country Canada 
Sector Academic/University 
PI Contribution SRUC, has made an in-kind contribution in terms of sharing of data on a) daily feed intake, monthly weights for four yrs in UK and b) Individual animal cost to measure emission in a 24hr assessment with Laser methodology. SRUC will oversee the international work on the development of new milk mid-infrared prediction equations for novel traits and thus add to the value of the data/activity in this and linked project. SRUC will contribute genotype and sequence data on a subset of cows with milk mid-infrared phenotypes to enhance potential genomic predictions for novel traits.
Collaborator Contribution International demand for dairy products is set to expand in concert with the middle-class of emerging economies, the need for high quality milk protein in developing countries and world population expansion. Already, the Canadian dairy industry generates $16.2 billion to this country's GDP (2011). The current proposal looks to address increasing demand, and the global competitiveness of Canada's dairy cattle industry both on-farm and in exporting Canadian dairy genetics. Canadian industry stands to gain $100M annually by improving two key traits in cattle: 1) feed conversion (feed efficiency) toward increased milk production, and 2) reduced methane emission. This project offers the means for effective selection of advantageous feed efficiency and reduced methane emission traits for a more secure and sustainable supply of competitive Canadian dairy products. Using genomics-based approaches to define natural variation between animals, cattle will be selected for higher feed efficiency and lower methane emissions. Canadian dairy producers will have access to bulls whose daughters are more efficient at converting feed into milk and have lower greenhouse gas emissions with the same level of production. As feed is currently the largest expense in milk production, improving cow efficiency will substantially benefit industry members financially. More efficient animals also produce less manure waste, further contributing to a decreased environmental footprint for industry. Presently, it is very difficult and expensive to collect the data (phenotypes) required for genetic improvement of feed efficiency and methane emissions. To date, there has been no large-scale direct selection for these traits in breeding dairy cattle. The latest genomic approaches offer an opportunity to address this, but accurate phenotypes are required for genetically-representative animals from the Canadian population. Therefore, this project focuses on using genomics to collect important data for calculating individuals' genetic merit. Industry breeding strategies can then incorporate these two traits in developing optimal populations, even for young animals without phenotypes. Involvement of international research partners and industry networks ensures standardization of necessary new data, and broad application of project outputs for the benefit of Canada's dairy industry and global food security and sustainability.
Impact There are no direct impacts from this work to date. The project is multidisciplinary involving livestock genetics researchers, bioinformaticians, ruminant nutritionists and socio-economists
Start Year 2015
 
Description Genomes Canada - Efficient Dairy Genome Project 
Organisation University of Guelph
Department Department of Animal Biosciences
Country Canada 
Sector Academic/University 
PI Contribution SRUC, has made an in-kind contribution in terms of sharing of data on a) daily feed intake, monthly weights for four yrs in UK and b) Individual animal cost to measure emission in a 24hr assessment with Laser methodology. SRUC will oversee the international work on the development of new milk mid-infrared prediction equations for novel traits and thus add to the value of the data/activity in this and linked project. SRUC will contribute genotype and sequence data on a subset of cows with milk mid-infrared phenotypes to enhance potential genomic predictions for novel traits.
Collaborator Contribution International demand for dairy products is set to expand in concert with the middle-class of emerging economies, the need for high quality milk protein in developing countries and world population expansion. Already, the Canadian dairy industry generates $16.2 billion to this country's GDP (2011). The current proposal looks to address increasing demand, and the global competitiveness of Canada's dairy cattle industry both on-farm and in exporting Canadian dairy genetics. Canadian industry stands to gain $100M annually by improving two key traits in cattle: 1) feed conversion (feed efficiency) toward increased milk production, and 2) reduced methane emission. This project offers the means for effective selection of advantageous feed efficiency and reduced methane emission traits for a more secure and sustainable supply of competitive Canadian dairy products. Using genomics-based approaches to define natural variation between animals, cattle will be selected for higher feed efficiency and lower methane emissions. Canadian dairy producers will have access to bulls whose daughters are more efficient at converting feed into milk and have lower greenhouse gas emissions with the same level of production. As feed is currently the largest expense in milk production, improving cow efficiency will substantially benefit industry members financially. More efficient animals also produce less manure waste, further contributing to a decreased environmental footprint for industry. Presently, it is very difficult and expensive to collect the data (phenotypes) required for genetic improvement of feed efficiency and methane emissions. To date, there has been no large-scale direct selection for these traits in breeding dairy cattle. The latest genomic approaches offer an opportunity to address this, but accurate phenotypes are required for genetically-representative animals from the Canadian population. Therefore, this project focuses on using genomics to collect important data for calculating individuals' genetic merit. Industry breeding strategies can then incorporate these two traits in developing optimal populations, even for young animals without phenotypes. Involvement of international research partners and industry networks ensures standardization of necessary new data, and broad application of project outputs for the benefit of Canada's dairy industry and global food security and sustainability.
Impact There are no direct impacts from this work to date. The project is multidisciplinary involving livestock genetics researchers, bioinformaticians, ruminant nutritionists and socio-economists
Start Year 2015
 
Description Linking to OptiMir Project 
Organisation OptiMIR
Country Belgium 
Sector Public 
PI Contribution This InterReg project is exploring how milk mid infrared spectra can be used to predict novel traits in dairy cattle. Researchers on this project are broadening the data used in this and the OptiMir project to expand predictive capacity of the results generated
Collaborator Contribution Researchers have been engaged in the collaborative pooling of data and undertaken detailed statistical modelling of energy status in dairy cattle across EU research organizations (France, UK and Germany)
Impact n/a to date
Start Year 2010
 
Description SRUC - NMR collaboration 
Organisation National Milk Records
Country United Kingdom 
Sector Private 
PI Contribution Storage and analysis of MIR spectral data. Creation of prediction pipeline to predict a variety of economically important phenotypes often to difficult or expensive to measure manually.
Collaborator Contribution Collection and analysis of milk samples generating mid infrared (MIR) spectral data and corresponding animal-herd information.
Impact Biotechnology and Biological Sciences Research Council (BBSRC): BB/S009396/1 - PredictinB statg Tus of dairy cows from mid infra-red spectral data using machine learning (£ 244024; 2019 - 2021); Scottish Government Rural and Environment Science and Analytical Services Division (RESAS): Work package 2.3 Agricultural Systems - RESAS Strategic Reserach Portfolio (£ 3000000; 2016 - 2021); Scottish Funding Council (SFC) - Research Grants Council (RGC): - Allocation of Research Excellence Grant (£ 46198; 2017 - 2018); Denholm SJ, Smith SL, Banos G, Ferrand M, Gele M, Brun-Lafleur L, Wall E. (2015). Predicting hard to record body energy traits using a merged phenotypic dataset and Mid Infra-Red (MIR) spectral analysis of milk samples; Denholm SJ, Smith SL, McNeilly TN, Hicks V, Wall E. (2016). Investigating the use of Mid Infrared spectral data to predict dairy cow cellular immune traits; Improvements to research infrastructure - Mid infrared spectral data based phenotype prediction tool (2015); Associations of immune-associated traits with nutrient levels in dairy cow milk and serum;
Start Year 2013
 
Description The influence of trace element levels on immunity and health in dairy cattle 
Organisation University of Aberdeen
Country United Kingdom 
Sector Academic/University 
PI Contribution Serum samples collected from dairy cattle with known health, production and immune trait data have been supplied to the research partner for trace element analysis to determine if levels of trace elements are associated with variation in health, production and immune status.
Collaborator Contribution The partner has measured 15 trace elements in the supplied serum samples and the results incorporated into the Immune_Dairy database..
Impact The data arising from this collaboration are currently being analysed.
Start Year 2014
 
Description British Cattle Breeders Club meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Poster presentations highlighting results of the genetic analysis of immune-associated traits as well as results from using mid infrared spectroscopy of milk samples to predict immune-associated traits. Prompted questions and discussion.
Year(s) Of Engagement Activity 2016,2017,2018,2019
 
Description British Society of Animal Science Annual Conference 2017 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Presented a paper discussing relationships of cellular immune-associated traits with health, fertility and production traits in dairy cows. Talk generated question sand discussion.
Year(s) Of Engagement Activity 2017
URL https://www.cambridge.org/core/journals/advances-in-animal-biosciences/issue/9FCE40A5DF9AA24026CD18B...
 
Description British Society of Animal Science Annual Conference 2018 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Paper presented discussing Immune-associated traits measured in milk as proxies for blood serum measurements in dairy cows. Questions and discussion post presentation
Year(s) Of Engagement Activity 2018
URL https://www.cambridge.org/core/journals/advances-in-animal-biosciences/issue/9FCE40A5DF9AA24026CD18B...
 
Description Final OptiMIR Scientific & Expert Meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation given discussing the use of MIR spectral data for the prediction of cow body energy status. Q & A session and discussions afterwards. Further collaborations.

Body energy predictions now implemented as part of routine milk recording by National Milk Records.
Year(s) Of Engagement Activity 2015
 
Description Hosting an internationally renowned scientist (Edinburgh) 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Other audiences
Results and Impact Invited and hosted Prof Temple Grandin for 3 days. Organised seminars, working groups and discussions with students (undergrad + postgrad). Discussed BBSRC project over her stay. Over 250 attendees at a special seminar.
Year(s) Of Engagement Activity 2017
 
Description Midlothian Science Festival 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? Yes
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact Children and adults alike were informed of work at SRUC and how science impacts day to day life and decision making

Generated heightened interest in animal science and agriculture from both adults and children
Year(s) Of Engagement Activity 2015
URL http://midlothiansciencefestival.com/event/easter-bush-campus-open-day-2015/
 
Description NC3Rs BBSRC joint meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Type Of Presentation paper presentation
Geographic Reach National
Primary Audience Other audiences
Results and Impact Interest generated in the use of immune traits as markers for dairy cow health and welfare

Increased requests for further information
Year(s) Of Engagement Activity 2015
 
Description Oral presentation at the 66th EAAP meeting 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation paper presentation
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The talk generated questions and further discussion and the possibility of future collaborations

After my presentation I received an email from a PhD student working in a similar area requesting further information
Year(s) Of Engagement Activity 2015
 
Description Oral presentation at the 67th EAAP meeting 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Discussing investigations of the use of Mid Infrared spectral data to predict dairy cow cellular immune traits - Q & A session afterwards
Year(s) Of Engagement Activity 2016
 
Description Poster presentation at the British Society for Immunology Annual Congress 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation poster presentation
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Interesting questions received

Generated interest in potential of immune traits as markers in dairy cattle
Year(s) Of Engagement Activity 2014
 
Description Presentation (BSAS) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Talk resulted in Q&A session.

Interest generated in project.
Year(s) Of Engagement Activity 2015
 
Description Presentation (poster - WCGALP) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Poster generated significant interest and questions. Handouts with further information given out.

Requests for further information requested by academic peers.
Year(s) Of Engagement Activity 2014
URL https://asas.org/docs/default-source/wcgalp-posters/539_paper_9649_manuscript_854_0.pdf?sfvrsn=2
 
Description Press release to launch project 
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 The article was reproduced in BBSRC Business Mag

The press release sparked interest from the Dartington Cattle Trust and discussions on the potential impacts of the project.
Year(s) Of Engagement Activity 2013
URL http://www.bbsrc.ac.uk/news/food-security/2013/130613-pr-funding-for-predicting-health-of-dairy-cows...
 
Description Royal Highland Show 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? Yes
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact The stand generated much interest from school children (from primary through to S6), farmers, the press and the general public. As this was an open event there were many opportunities for discussion and knowledge transfer.

Discussions with farmers highlighted the usefulness of such a tool that could come out of the current area of research. School children and the general public gained a better understanding of animal science techniques and the ability to conduct animal research without the requirement of invasive sampling.
Year(s) Of Engagement Activity 2015
URL http://www.sruc.ac.uk/srucrhs
 
Description School Visit (Kelso - Royal Highland Trust) 
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 Ran workshop teaching school children about dairy genetics work carried out at SRUC, highlighting new tools such as immune markers and mid-infrared prediction technologies. resulted in heightened interest and questions.
Year(s) Of Engagement Activity 2015
URL https://www.rhet.org.uk/in-your-area/rhet-scottish-borders-ci/
 
Description World Congress on Genetics Applied to Livestock Production 2018 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Presentation given in the "Biology - Disease Resistance" session which was joint with the International Committee for Animal Recording (ICAR). Discussion of genome-wide associations of immune-associated traits in dairy cows.
Year(s) Of Engagement Activity 2018
URL http://www.wcgalp.org/