Cattle Practice October 2023

CATTLE PRACTICE VOLUME 31 PART 1 2023 45 Farmer and vet insights into the management of calf pneumonia – a place for rapid diagnostics? Potter, T.4 , Chambers, M.1 , Cooper, J.2 , Enticott, G.3 , Mehat, J.1 , La Ragione, R.1 , Reader, A.5 , Reboud, J.2 , Wakeham, A.6 , 1 University of Surrey, Guildford, Surrey, GU2 7XH 2 University of Glasgow, 464 Bearsden Rd, Glasgow, G61 1QH 3 University of Cardiff, Glamorgan Building, King Edward VII Avenue, Cardiff, CF10 3WA 4 Westpoint Farm Vets, Dawes Farm, Bognor Road, Warnham, Horsham, West Sussex, RH12 3ZG 5 Goldsland Farm, Wenvoe, Cardiff, Glamorgan, CF5 6BE 6 Global Access Dx, Technology Park, Thurleigh, Bedford, MK44 2YA Bovine respiratory disease (BRD) is a complex syndrome caused by multiple factors, including environmental and management-related stressors and a long list of viral and bacterial pathogens. In combination, these factors overwhelm and dysregulate host immunity and lead to disease. The financial costs and the negative impacts of BRD in both the dairy and the beef sectors are well documented; Bartram and others (2017) estimated the lifetime economic cost of a case of BRD in a dairy heifer to be £772 and 2019 data from abattoirs across England and Wales identified evidence of pneumonia/pleurisy in nearly 5% of post-mortem carcass inspections. Despite a significant body of research and clear advances in treatments, and preventatives there has not been a significant change in the morbidity attributed to bovine respiratory disease over the last 45 years (Smith and Woolums 2020) and in the CHAWG Report 2020 pneumonia remains in the top four health and welfare challenges facing the beef industry. So how do we address this continued challenge? Unfortunately, involvement in the management of BRD is often limited to reactive management of disease outbreaks. There are over 50 antimicrobial products licensed for the treatment of BRD in the UK and so whilst we have the tools available to manage a disease outbreak all too often by the time, vets get involved the damage has already been done. It is therefore important that vets endeavour to work with their clients to move to a more pro-active approach to BRD control with the focus on evidence-based prevention and targeted treatment. Recent developments in rapid molecular diagnostics, including loop-mediated isothermal amplification (LAMP) offer the possibility of delivering a platform technology considerably cheaper, quicker, and more sensitive than PCR for detecting some of the major pathogens associated with calf pneumonia, opening up the opportunity to use such a test for routine surveillance on-farm. This would enable early intervention and the development of specific treatment protocols, thus reducing antimicrobial usage and improving calf welfare. We present our insights into understanding the context into which such a test might be introduced. We present the results of a national survey of vets involved in calf management about their use of diagnostic tests with calves, their experience of managing calf pneumonia, current treatment practices and what kind of rapid tests they would like to have. These results are supplemented with insights from a participatory multistakeholder workshop to better understand the perceived challenges and opportunities of vets and farmers when managing calf pneumonia. The workshop also considered the role of diagnostics in the evidencebased management of calf pneumonia. This includes the barriers and challenges to their use, what rapid onfarm diagnostics would change about how the disease is currently addressed, and feedback on the desired attributes of a rapid test for calf pneumonia. This work was funded by the Biotechnology and Biological Sciences Research Council (BBSRC), project BB/ W020440/1 (https://gtr.ukri.org/projects?ref=BB%2FW020440%2F1). REFERENCES Bartram, D., Hogan, C., Penny, C.D. (2017) Estimating the Lifetime Total Economic Costs of Respiratory Disease in Beef and Dairy Calves in The UK. Value in Health 20: A399-A811 Smith, R.A., Woolums, A.R. (2020) Bovine Respiratory Disease Looking Back and Looking Forward, What Do We See? Vet. Clin. Food Anim. 36: 239-251

CATTLE PRACTICE VOLUME 31 PART 1 2023 46 Dairy beef calves – integration to succeed but what really lies beneath? Bell, D., SRUC Beef & Sheep Research Centre, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG The GB Dairy Calf Strategy 2020-2023 states the encouragement of a responsible breeding strategy for those in the dairying sector. One such method is the use of sexed dairy semen to produce dairy heifer calves, which would also reduce the number of dairy bull calves being born, with the fate of the dairy bull calves being of concern to the general public. Figures from AHDB show that there has been a year-on-year increase in the sale of sexed dairy semen. At the same time, there has been a steady increase in the number of beef cross calf births being registered from the dairy herd. The majority of these calves enter the dairy-beef production cycle. Although some of these calves will be retained and reared on the farm of birth, a substantial proportion of these calves will be sold in the pre-weaning period to another business for further rearing. These preweaned calves will be traded in a variety of ways such as farm to farm direct, through auction markets or through calf collection centres. Regardless of trading method, the next destination for these calves will be a unit with an unfamiliar environment and one in which there is the potential to be mixed with other calves. Therefore, calves will end up exposed to potential new health challenges. There were two stages to this project. The first involved conducting a series of interviews with key players across the dairy-beef supply chain and secondly, a feasibility study that was conducted with a non-aligned commercial calf rearing business in the UK. There were three groups across the supply chain that were interviewed: 1. dairy farmers (i.e. calf producers), 2. calf rearers, and 3. representatives from calf procurement companies. The analysis of the interviews from all the calf producers and calf rearers highlighted five main themes: genetics, terminology, reputation, communication and relationship. Many of the calf rearers were mentioning that they were now trying to select calves of specific sires as those calves suited their system. It was revealed that the flow of information between both parties was more often than not just an informal dialog with no record. Also, many of the calf producers expressed an interest in receiving feedback on the performance of their calves at the rearing unit. However, nobody was actively asking the rearers for this information. There was an overall aversion to referring to these calves as ‘surplus ’and there was growing consideration amongst the calf producers as well as the calf rearers as to the most suitable beef sires to use that fit the dairy-beef market. Overall, the interviews highlight some key areas for further development and improvement. The small feasibility study was conducted on a non-aligned calf rearing unit from early February to midMarch 2022. The 140 dairy-bred calves used in the study (age range: 10 to 67 days; mean age: 26 days) were directly sourced from 17 dairy farms and selected as per normal buying practice for that unit. They were weighed, Wisconsin health scored (WS), and lung ultrasound scanned and scored (LUS) on arrival to examine the effect of grouping calves based on their health status upon arrival at a rearing unit on their subsequent performance and health. For the scanning, lungs were scored from 0 to 5 where 0 represented ‘normal’ and 5 represented consolidation observed in 3 or more lobes. Using this information, calves were then assigned to one of five groups: 1. ‘High health’ (HH) (LUS 0/1 & WS ≤2), 2. ‘Low health’ (LH) (LUS ≥3 & WS ≥3), 3. ‘Intermediate health’ (INT) (LUS 2/3 & WS≤ 2), 4. ‘Mixed health’ (MIX) (a proportion of calves (50%) LUS ≤2 & WS ≤2 along with a proportion of calves (50%) with LUS 4/5 & WS ≥2), and 5. ‘Normal farm practice’ (NFP). The normal practice for grouping calves on that particular rearing unit was to keep calves from the same source farm together in the same pen wherever possible. Interestingly, this was the preferred method of grouping calves of the calf rearers that were interviewed. The same assessments were repeated after 22 days of the calves being on the rearing unit to coincide with when the calves were being next handled by the farm staff. From the weights, a daily liveweight gain (DLWG; kg/d) was calculated.

CATTLE PRACTICE VOLUME 31 PART 1 2023 47 The initial lung scanning of calves on arrival to the rearing unit found that 62% (87/140) of those calves had signs of lung consolidation (LUS ≥3; consolidation observed in 1 or more lobes). Calves with an arrival age of ≥32 days had a higher lung score than younger calves. The younger calves on arrival (≤17 days old), had a more noticeable increase in lung score after 22 days on the rearing unit compared to the older calves. Nearly all the groups had an increase in LUS from when they arrived on the rearing unit and 22 days later. In terms of performance, the NFP calves had the highest DLWG (0.65kg/d ±0.037 (SEM)) compared to calves in the other Groups (HH: 0.46kg/d ±0.085; LH: 0.61kg/d ± 0.059; INT: 0.52kg/d ± 0.034; MIX: 0.55kg/d ± 0.035; SEM). Of interest, calves in the LH Group had a higher DLWG than the calves in the HH Group. The LH Group had a higher proportion of farm recorded treatments for respiratory disease compared with the other Groups (No calves treated/Total number of calves in Group; HH 3/12 (25%); INT 9/34 (26%); LH 13/20 (65%); MIX 15/43 (35%); NFP 13/31 (42%)). Despite the number of replicates within the study being small in number and unbalanced it does raise questions surrounding seasonal affect on LUS obtained, the risks of calves from a ‘low challenge’ environment being brought into what can be classed a ‘high challenge’ environment as well as maximising performance.

CATTLE PRACTICE VOLUME 31 PART 1 2023 48 UK Beef Lameness; what we know, what we don’t know and where do we go? Tunstall, J., Fitzsimmonds, H., Torch Farm Vets Ltd, Clovelly Industrial Estate, Bideford, Devon, EX39 3HN It is widely accepted that lameness is a welfare problem for the national herd, including our beef herd with a mean farm level lameness prevalence of 8.3% (range 2.0 to 21.2%) in finishing cattle, increasing to a mean farm level prevalence of 14.2% (range 0.0 to 43.2%) for our sucklers. It has also been recently quantified as a production issue, with finishing cattle that have been lame once or more having a 240g reduction in average daily liveweight gain, increasing with a greater time spent lame. Themes including underreporting of lameness prevalence on farm, little knowledge of lesion types, challenges with the use of vets or professional foot trimmers and insufficient facilities to deal with lame animals are reported amongst others. Impressive gains have been made in dairy lameness in these areas; from evidence based mobility scoring and trained scorers at an industry wide standard, to veterinary practices across the country delivering farmer training on lesion identification and ‘foot first aid’ treatment. Whilst initial research has identified areas requiring further attention, our workshop would like to discuss with the wider veterinary profession about how we engage with beef producers on this topic, and what resources may need to be developed to support us to do so. Locomotion scoring is comparably reliable in beef as it is in dairy, and although further research is underway about reliability when performed by farmers, looking at feasible ways to undertake lameness detection for beef clients would be of great benefit.

CATTLE PRACTICE VOLUME 31 PART 1 2023 49 An assessment of KPI data for 50 suckler herds in the North West & Midlands of England Henderson, A., LLM Farm Vets, The Show Office, Agricultural Way, Bakewell, Derbyshire, DE45 1AH Key performance indicators (KPIs) are used routinely in business to assess performance, efficiency and as an aid to decision making, planning and future strategy. There would appear to be a dearth of publicly available KPIs on the performance of suckler herds in the UK. Whilst many examples of KPI targets exist in the UK and these should be achievable and realistic for our suckler clients, the lack of real-world data can make it difficult to provide context where clients fail to achieve these aims. Historically, AHDBs Stocktake report provided access to a range of KPIs on physical performance from a range of herds in severely disadvantaged areas, non-severely disadvantaged areas, spring calving herds and autumn calving herds for example. However, the last report was produced in 2016 (AHDB 2016) and I am not currently aware of other published data, which could be used as a helpful reference to veterinarians when providing advice to their suckler clients. The long-term prospects for the UK suckler industry appear challenging due to changing consumer habits, concerns regarding the environmental impact of suckler beef production, Brexit, changes to the subsidy system, the increasing costs of inputs and the apparent perceived or actual inefficiency in beef suckler production in the UK. However, suckler farming can be part of a sustainable food producing future. But only if KPIs are assessed to aid improvement and drive future efficiencies. This study aimed to collect KPI data from a range of suckler herds in the North-West & Midlands of England during TB tests and PD sessions to form the basis on an ongoing Suckler discussion group to create a forum for meaningful engagement between our veterinary practice and clients to allow the development of our client’s businesses and our business in the future. I will present the findings of our collection providing descriptive data on key KPIs of relevance to delegates. REFERENCES AHDB (2016) Beef and Lamb Stocktake https://ahdb.org.uk/ stocktake-and-farmbench-reports

CATTLE PRACTICE VOLUME 31 PART 1 2023 50 Sheep associated malignant catarrhal fever (SA-MCF): a series of cases on three farms in the UK Angell, J.W., Bentley, E.G., Stewart, J.P., Wern Vets CYF, Unit 11, Lon Parcwr Industrial Estate, Ruthin, Denbighshire, LL15 1NJ INTRODUCTION AND BACKGROUND Bison and buffalo are not commonly farmed in the UK, although they are considered an option for diversification due to the high value of the animal products. In the UK, a significant limiting factor for bison and buffalo production is the high susceptibility of these animals to sheep associated malignant catarrhal fever (SA-MCF) caused by ovine herpes virus-2 (OvHV-2) and strategies to limit this disease risk are essential to sustainable production. OBJECTIVES The aim of this project was to control SA-MCF in bison and buffalo in Wales, UK. Objective 1: determine the exposure of farmed bison and buffalo to OvHV-2. Objective 2: determine the presence/absence of OvHV-2 in species in contact with the bison/buffalo. Objective 3: determine whether the bison/ buffalo have been exposed to other infectious diseases that could potentially increase the risk of MCF following exposure to OvHV-2. Objective 4: utilise a novel vector vaccine (Macavax) as part of a control programme. MATERIALS AND METHODS Two farms were included in the project: 1. a mixed species farm with bison, cattle, sheep, poultry and deer; 2. a farm with buffalo and sheep. Blood/tissue samples were obtained from a sample of the bison, cattle, sheep and deer from farm 1 and blood samples were obtained from a sample of the buffalo and sheep from farm 2. qPCR was used to identify OvHV-2 on blood and tissue samples and commercial antibody tests were used to determine exposure to bovine viral diarrhoea virus (BVD), infectious bovine rhinotracheitis virus (IBR), Mycobacterium avium subspecies paratuberculosis, Neospora caninum and Mycoplasma bovis. Faeces were examined for the presence of gastrointestinal nematode eggs, Fasciola hepatica eggs and lungworm larvae. Trace element analysis was carried out using commercially available tests. Control strategies were deployed specific to the farms with a novel vector vaccine (Macavax) utilised on farm 1. The farms were monitored for 18 months to determine the efficacy of the control strategies. RESULTS Farm 1: no OvHv-2 was detected at the start of the project, however several deaths in the preceding years were confirmed as SA-MCF. The bison had evidence of previous exposure to IBR, N. caninum and Mycoplasma bovis, gastrointestinal nematodes and Fasciola hepatica. Copper, selenium and iodine deficiencies were also detected. The Macavax vaccine was administered twice to bison originating from the farm and once to new herd entrants that joined the herd after one year. No adverse events were observed. The health of the herd improved overall, however one death was recorded after 18 months with SA-MCF confirmed by postmortem and virus detection. Farm 2: 4/19 (21.1%) of the buffalo had OvHV2 detected by qPCR. 1/10 sheep also had OvHV2 detected by qPCR. The buffalo had evidence of previous exposure to IBR and Mycoplasma bovis, with marginal trace element deficiencies. No deaths associated with MCF were observed prior to or during the study period. CONCLUSIONS Bison and buffalo can be farmed successfully in the UK, provided their health and welfare needs are met appropriately. Various commercial strategies already in place for cattle may be used in a similar way in these species with appropriate amendments where necessary. Where possible the bison and buffalo should be kept as far away as possible from other species to reduce the risk of transmission of infectious diseases, especially OvHV-2. The novel vector vaccine (Macavax) was safe to use in bison, although further work as to the specific extent of its efficacy is needed.

CATTLE PRACTICE VOLUME 31 PART 1 2023 51 Collecting data on farm for surveillance and improved biosecurity King, J., Wales Veterinary Science Centre, Y Buarth, Aberystwyth, Ceredigion, SY23 1ND Arwain DGC is a national collaborative programme funded through Welsh Government with the aims to deliver the objectives identified within the "Antimicrobial Resistance in Animals and Environment Five Year Implementation Plan for Wales (2019-24)". As part of this programme, Iechyd Da (Gwledig) Ltd have been developing technology to collect surveillance data and improve farm biosecurity. Through the Arwain DGC Project, a syndromic surveillance programme has been developed by Wales Veterinary Science Centre (WVSC), and piloted by several vet practices across Wales, with a view to becoming a blueprint for all practices across Wales. Additionally, a Biosecurity risk assessment tool (app) has also been developed by Iechyd Da (Gwledig) and trialled by seven practices on 20 farms across Wales to assess biosecurity status and opportunities for improvement. These initiatives are aimed to help vets and farmers to identify disease early and where possible avoid introducing disease on to the farm, resulting in improved health and reduced need to use antibiotics. SYNDROMIC SURVEILLANCE The importance of veterinary disease surveillance is widely recognised but there are several levels at which data can be collected. For the last ten years or more, the UK government has collected data from APHA, SRUC and partner postmortem providers (PPP) to update the Veterinary Investigation Diagnosis Analysis database (VIDA). This database is analysed and used to provide advice and information to stakeholders about new and potential emerging disease threats, to provide early warning messages and provide confidence in international trade. However, this data is only the tip of the surveillance pyramid (Figure 1) and collecting data further down the pyramid would provide a much better picture of what is happening on UK farms in reality. Syndromic Surveillance is the collection and analysis of the syndromes (clinical signs) that are observed and is becoming increasingly recognised in small animal veterinary sectors, and to a lesser extend in equine practice. It is still not common practice in farm animal work meaning there is a surveillance gap at the farm level however we know that it can be useful and the story of Schmallenberg Virus is a good example where an increase in adult cows with diarrhoea and deformed lambs had epidemiologists and veterinary scientists looking for a new disease. This presentation will provide a brief overview of a syndromic surveillance programme which has been designed to collect the syndromes being seen at practice level. It will include details of the plan itself and report on a pilot utilising two different methods of data collection. From a survey carried out before the project Figure 1. Adapted from the APHA Surveillance Pyramid - original source unknown. The Surveillance Pyramid

CATTLE PRACTICE VOLUME 31 PART 1 2023 52 began, it was clear that any system at practice level needed to be simple and not add much time to the veterinary surgeon’s busy schedule. As a result, the two different methods of data collection were both digital but utilised different methodologies. One system recorded the syndromes at the time of the visit (working with Vet Impress) whilst the other system (working with FAVSNET Liverpool University) was collected as the information was entered on the practice system for booking and invoicing. Syndrome data collected was based on the APHA submission form and included abortion, anorexia/ inappetence, clinical mastitis, diarrhoea, lameness, milk-drop, stillbirth and others. To provide clinical relevance to the data, other information about each case was also collected including part of the post code, the enterprise type, species, breed, stage of production and whether it was a group or individual problem were also collected. The data collected by WVSC remained anonymous to avoid any (sensitive) GDPR issues. BIOSECURITY APP This part of the Arwain DGC project involved the development and pilot the use of handheld technology to measure and manage biosecurity risks to prevent the spread of infectious disease by movement of animals on and off farms. There were seven practices and 20 farms piloting the survey across Wales. Working with their clients, vets carried out simple risk-based analysis of a farm’s biosecurity. The easy-to-use Biosecurity App helped identify the major weak spots in the farm’s biosecurity measures and enable the vet to give practical advice on improvements. Any changes made were then reviewed with the farmer during an interim visit after 3 to 6 months, with a full follow-up review visit six to nine months later to reassess the farm and measure the impact of changes made through changes in the score. The measurement of risk in this manner facilitates benchmarking of farms to further farmer engagement. Collected scores from farms in a geographical region (Wales-wide, regional, or more local) can be used to compare the risks applying to a particular farm compared to neighborhood farms, similar farm types or all farm on local, regional, or national scale. This benchmarking facility adds to the power of the tool. The collected data will also be useful to measuring how effective this type of programme is in encouraging farmers to adopt more effective ways of reducing the risks associated with disease transmission from farm to farm. The data will be of great interest to the relevant industry and government bodies. SUMMARY During the presentation there will be discussion of the pilot study results and suggestions as to how this data may be used moving forward. It will include discussion on the practical difficulties of setting up and running such systems in farm animal practice compared to other veterinary fields (such as small animal and equine practice). It will also explore how the pilots could be expanded across Wales and a brief look at how things could be done moving forward towards a national scheme. The presentation will include results, examples of the data collected, and outputs. Both of these activities are underpinned by other workstreams undertaken through the Arwain DGC Project, including; monitoring and benchmarking antibiotic use on over 4,000 farms, assessments of AMR in the farm environment on 50 farms and trialling innovative technologies and techniques to support farmers and vets to reduce the need to use antibiotics. More on these wider activities will be discuss during the talk.

CATTLE PRACTICE VOLUME 31 PART 1 2023 53 “I know prevention is better than the cure, but...”: Barriers and facilitators to implementing on-farm measures to reduce the risk of bovine tuberculosis Collinson, A., Tomlinson, S., Brennan, M., School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Nottingham, LE12 5RD The Bovine Tuberculosis Advisory Service (TBAS) offers bespoke advice to farmers on practical, cost-effective measures to reduce bovine tuberculosis (bTB) risks on their farm. TBAS advisors visit farms, assess current biosecurity and give four bespoke recommended measures from a list of 110 possible options, based on their findings. Data was gathered during follow-up visits undertaken within 6 months of the initial visit on which of the measures were enacted, and revealed that uptake of all four measures was uncommon. Reasons given for not completing a measure were most often linked to a lack of time, however even within this one category there could be various different explanations for the inaction, such as time of year. This study utilised a qualitative approach to understand the complexities behind uptake of measures, with the aim of enhancing the long-term success of the TBAS programme. Semi-structured interviews were conducted with six farmers who had participated in the TBAS initiative. The key messages taken away from the visit were discussed as well as which, if any, of the measures had been instigated including the reasons behind these decisions. Farmers’ perceptions of current bTB policy were also investigated, to understand how these might influence implementation of control measures. The interviews were transcribed and uploaded to NVivo for thematic analysis. Transcripts were initially coded inductively, and subthemes generated. The emerging subthemes were then mapped to the Capability, Opportunity, and Motivation Model of Behaviour (COM-B) using a deductive approach. Initial subthemes identified time, expense and not seen as practical or feasible as barriers to enacting the recommendations. Perceived other benefits to implementing the measure additional to bTB prevention, an existing relationship with the TBAS advisor, an existing or recent bTB problem on the farm and a perception that the recommendation had been a shared decision, were identified as facilitators. Measures that necessitated a significant change to the usual way of doing things or management policy could be either a barrier or a facilitator. The study identified that the TBAS visit was often regarded as a catalyst for action, however farmers continued to feel constrained and frustrated by the wider policies and legislation relating to bTB control, and felt that major changes were required in this to enable progress. It was considered that those making policy decisions were out of touch with the reality of dealing with the impact of those decisions on-farm, particularly the stress and mental health implications. The key findings presented within this paper highlight the relevance of capability (expense, time) and opportunity (feasibility, management norms) as barriers, and motivation (perceived benefits, trust in advisor, shared decision making) as a facilitator when considering uptake of the recommended measures. In order to encourage farmers to enact the recommendations it will be necessary to integrate this knowledge, including strategies for overcoming the barriers, into subsequent visits. This will be done by identifying behaviour change techniques that will address these factors, which will be used to develop training for TBAS advisors.

CATTLE PRACTICE VOLUME 31 PART 1 2023 54 A collaborative investigation of a new syndrome of gastroparesis in dairy heifers Swinson, V., APHA Thirsk, West House, Station Road, Thirsk, YO7 1PZ In the period between September 2022 and July 2023, there have been at least 20 submissions to the APHA postmortem provider network to investigate a syndrome of apparent gastroparesis in Holstein Friesian heifers. Eight of these submissions were carcase submissions for postmortem examination (PME) (12 carcases in total); and the remainder were postal submissions of EDTA blood samples. In the few months prior to these submissions, the APHA Cattle Expert Group (CEG) (which includes members from SRUC and partner postmortem providers) had been made aware of unusual gross PME findings in eight heifers from one herd. The heifers all had the same sire, and no heifers sired by other bulls were affected. The unusual PME findings, and the history, suggested to the wider surveillance network that further investigation of this was advisable. The cases were discussed at the monthly CEG surveillance meetings, and information was then disseminated via the APHA quarterly GB surveillance reports for Quarter 3 and Quarter 4 of 2022, an endemic disease alert via the EDAS alert system, a BCVA information note, and internal communications to APHA staff. The heifers typically presented with progressive abdominal distension and condition loss, became inappetant, were non-responsive to treatment, and had to be euthanased (or died from secondary complications such as abomasal rupture). No obvious dietary or management risk factors have been identified to date. At postmortem examination, the abdomen and the rumen were markedly distended, and the ruminal contents had a distinctive frothy texture. Abomasal impaction and/or ulceration was also a feature of some of the cases. One of the affected farms used a cow monitoring system, which recorded rumen function, and the outputs demonstrated markedly reduced, and eventually absent, rumen contractions at the time when the clinical signs became apparent and then worsened. The breeding company has been working with partners across the UK disease surveillance network, private vets, and a specialist genetic research team in France since May 2022. At the time of writing, the mechanism underlying this syndrome is uncertain. The gross pathological and histopathological findings of the cases have so far been inconclusive. The appropriate blood and tissue samples have been collected from affected and non-affected (control) animals. These are currently being analysed to try and uncover the precise genetic mechanism of the issue and, will hopefully aid better understanding of this syndrome. The working hypothesis is that the sire carried a de novo (new) mutation that is inherited in a dominant fashion. There appears to be mosaicism of the bull’s germ cells, where there is more than one genetic line of the germ cells (as the result of genetic mutation), and the condition appears to develop in approximately 25% of his offspring. It is thought that animals sired by this bull which are functioning normally beyond their first calving, are unlikely to have inherited the mutation, and therefore may remain healthy and possibly not transmit this fatal condition. The bull has been removed from AI service and his semen has been removed from the market. He does not have any sons in AI service. The breeding company have contacted customers directly who bought this bull’s semen. Farmers that suspect they have experienced cases, but that have not yet been approached by the breeding company, should contact the breeding company directly. The CEG, is still interested to hear about similar cases, so that it can continue to increase awareness, and develop greater understanding of this issue. This presentation will also discuss the recent work which has been undertaken to help enhance surveillance and dissemination of information for genetic disorders in the future. ACKNOWLEDGEMENTS With thanks to Cattle Expert Group colleagues, Ben Strugnell, the breeding company involved, and scientists at INRAE, France

CATTLE PRACTICE VOLUME 31 PART 1 2023 55 Counting Carbon; Does a smaller footprint leave less environmental impact? Defining sustainability in the dairy sector Middleton, M., Bishopton Veterinary Group, Mill Farm, Studley Road, Ripon, Yorkshire, HG4 2QR INTRODUCTION What is a carbon footprint? What it tells us and what it doesn’t’ tell us about sustainability. Over recent years increasing public awareness has been drawn to the threats of climate change and wider environmental sustainability concerns. Humans are consuming natural resources, transforming the landscape and generating waste at an entirely unsustainable rate (Hoekstra and Wiedmann 2014). Emerging in the nineties as an indicator of environmental sustainability relating to different products and industries, the environmental footprint and following this, the carbon footprint have become widely recognised by the public (Monfreda and others 2004). Footprints seek to express environmental impact of products from a life cycle perspective, this encompasses the upstream impacts of all the components and resources used throughout the entire supply line (Ridoutt and others 2015a). The widespread recognition of carbon footprints as a stand-alone indicator of environmental impact, due to it’s simplicity in communicating results, has allowed it to become the single focus of many contemporary debates around environmental sustainability. (Finkbeiner 2009, Laurent and others 2012, Laurent and Owsianiak 2017). Before discussing carbon foot-printing further, debating its merits and limitations, it is imperative that we better understand and define what a carbon footprint encapsulates, what it relates to and what it does not, what elements are included and what it tells us about the environmental impact and overall sustainability of agriculture. Agricultural GHG National inventory and Global warming potential (GWP) 2006 saw the integration between agriculture and land use, land-use change and forestry by the Intergovernmental Panel on Climate Change (IPCC). “This integration removes the somewhat arbitrary distinction between these categories in the previous guidance,” (IPCC 2006b). This development expanded the scope of national emissions inventories attributable to agriculture. This document sets out the principals of measuring and attributing Greenhouse Gas (GHG) emissions. Life Cycle Analysis (LCA) Environmental footprints are based on LCA, a footprint seeks to convey information about a specific environmental criteria, in a simple form, accessible to the public and non-technical stakeholders (Ridoutt and others 2016). LCA is one of the most commonly used methods across all industries to allocate GHG emissions as well as other pollutants to any specific product encompassing the entire production cycle (Teixeira 2015). LCA aims to standardise accounting in order to facilitate comparison both between different products and similar products produced within differing production systems, in contrast IPCC method quantifies GHG emissions using a national sector-based approach primarily for the purpose of producing national inventories (Schils and others 2005, O’Brien and others 2012). LCA was internationally standardised by the International Standardization Organisation, ISO 14040 and 14044 (ISO 2006a, 2006b). These ISO standards were used to develop sector specific guidelines for LCA analysis in the dairy sector by the International Dairy Federation (IDF) in 2010 and later amended within a revised document published in 2015 (IDF 2015). This document was produced in collaboration with a series of international stakeholders including the ISO, The British Standards Institution, Food and Agriculture Organisation (FAO), IPCC, Carbon Trust, World Business Council for Sustainable development and The World Resource Institute. However, despite efforts for standardisation, LCA still lacks a fully harmonised approach, choices and hypothesises made by different authors as well at the data used can affect the results and comparability of different studies despite comparable subject matter (Pelletier and others 2015, Ridoutt and others 2015b).

CATTLE PRACTICE VOLUME 31 PART 1 2023 56 Systems boundaries (Table 1) Functional Unit (FU) According to ISO14044 only products with standardised FU can be compared using LCA (ISO 2006b). FU should equilibrate the nutritional content of milk and allow comparison between milk of differing fat and protein content. However standardisation of this unit is not well established and two main correction formulae predominate within the literature (Baldini and others 2017a) (Table 2). Both these equations give the same weighting to a standard litre of milk at 4% fat and 3.3% protein, but the different equations produce slightly different weightings as milk solids diverge from the standard (Yan and others 2013). It is unfortunate that the IDF suggests Fat and Protein Corrected Milk (FPCM) but gives the equation relating to energy corrected milk (ECM) potentially creating inconsistency within the literature (IDF 2015). LCA Modelling Principals The LCA method (ISO 2006a, 2006b) permits two different principals to be applied in life cycle inventory modelling, attributional modelling (ALCA) and consequential modelling (CLCA) (Pelletier and others 2015, Baldini and others 2017b). CLCA seeks to establish a causal link between changes in demand generated by increased production and consequential increased supply of a given input. For example, increasing production of milk creates an increased demand for grain which creates additional demand for arable land etc. Inversely if milk production fell, demand for grain would also fall, the carbon footprint of the marginal supplier of said product is imputed into the cost of milk (Dalgaard and others 2014). So in this example it would be additional grain produced to meet the additional demand created by the expansion of the dairy sector, an author may deem that the marginal suppliers of grain exist at the agricultural frontiers and that new arable lands are created from previously unfarmed areas to meet the growing demand for additional grain. ALCA allocates inputs and outputs based on a normative value, where possible the system should be divided into two or more sub-processes, or if this is not possible expand the system to include the additional functions related to the co-products. For example, in dairy this implies that beef produced by the dairy farm ‘fulfils the same consumer need’ and therefore substitutes beef produced within cowThe FAO describes the sources of emissions which should be included are: (i) on-farm livestock emissions including enteric fermentation, slurry storage and application and manure deposition on pasture by grazing animals (ii) feed and forage production including application of mineral fertiliser, soil cultivation, crop residue decomposition and related upstream manufacturing processes of inputs such as fertiliser (iii) on-farm energy consumption related to all elements of livestock production (iv) Direct and indirect land use changes (LUC) induced by the production of feed (excluding grassland and grazing) (v) indirect energy related to the construction and manufacture of buildings, plant and farm machinery. (FAO and GDP 2018) Note that this source makes no reference to sequestration within grassland. Table 1. FU Formular Source Fat and Protein corrected milk (FPCM) kg milk x [0.337+(0.116x fat%) + (0.06 x protein%)] (FAO 2010) Energy corrected milk (ECM) kg milk x [0.25 + (0.122x fat%) + (0.077x Protein%)] (Sjaunja and others 1990) Table 2.

CATTLE PRACTICE VOLUME 31 PART 1 2023 57 calf suckler systems leading to an ‘avoided burden’ that forms a credit for the dairy system (Flysjö and others 2011). If allocation could not be avoided it should be based on a physical relationship between products, the IDF (2015) suggested a method centred on feed energy requirements to produce a kg of beef or a kg of milk. Finally, if any other relationship cannot be found the IDF (2015) suggest allocation of emissions based upon economic value of the output. The IDF rules 2010 and 2015 represent a subset of ALCA with some specific rules. In the UK national guidelines called PAS2050 published in 2011 through collaboration between the British standards Institution, Defra and The Carbon Trust, (British Standards Institution 2011) similarly represent a subset of ALCA, again with some specific rules (Dalgaard and others 2014). Application of LCA and factors leading to intrinsic inconsistency Dalgaard and others (2014) compared the outcomes of four different LCA methods of calculating the carbon footprint of milk production, ALCA, CLCA, the IDF and PAS2050. These four methods were applied to Danish and Swedish milk production based on national life cycle inventory for each country obtained through data collected by ARLA and through national statistics and inventories. Switching between different modelling systems resulted in significant differences in the carbon footprint attributed to milk production, increasing from 1.15kg CO2 e on Swedish dairy farms using CLCA to over 1.7kg CO2 e using the IDF model. These differences where in large part due to the way that both direct Land Use Change (dLUC) and indirect land use change (iLUC) are calculated within the different models. Land Use Change There are two types of land use change that result in GHG emissions, direct land use change, which occurs as a result of changing land management practice on a dairy farm, for example changing cultivation systems resulting in changes in soil carbon. While indirect land change use, which occurs either through intensification of cropland or clearing forest to make way for cropland, to supply additional crops, to meet additional demand (Schmidt and others 2015). There are several different types of models for allocating iLUC with significant deviation in output between each method, this was demonstrated within the dairy sector by (Dalgaard and others 2014) but similar discrepancies have also been described within the biofuels industry (Searchinger and others 2008). Schmidt and others (2015) asserts that current land use reflects current land demand, consequently any increase in demand for land will ultimately increase land use. Any crop displaced by another crop will need to be produced elsewhere (Kløverpris and others 2007, Schmidt 2008). While Audsley and others (2009) asserts that, given agriculture is a primary driver for deforestation, the LUC emissions for this deforestation should be distributed equally over all land occupied for commercial agriculture, resulting in a LUC factor of 1.4T CO2 e Ha-1 irrespective of land quality (Audsley and others 2009). Schmidt and others (2015) refines the allocation of LUC emissions by differentiating differing land classifications based on land type, and potential. Land is classified into ‘markets’ such as arable land, grass land and range land. Global LUC emissions are calculated for each ‘land market’. And these emissions for LUC are distributed within that land market. An interesting consequence of this method is that the underutilisation of highly productive land leading to low yields, will result to higher iLUC emissions per unit of output (Flysjö and others 2012). The PAS2050 method models iLUC by applying a 20 year amortisation period. (British Standards Institution 2011). LUC emissions are applied directly to the products of deforested land and iLUC incurred through Brazilian soya bean meal equates to 740T CO2 Ha-1 for conversion of rainforest to cropland, divided by 20 and attributed to the crop is 7.7kg CO2 e per kg of soya bean meal (FAO 2010). Flysjö and others (2011) compared the implications of these differing methods for allocating iLUC upon confinement and organic dairy herds in Sweden. Organic herds invariably use more land per kg ECM but confinement herds use more soya bean meal. The choice of method used to calculate iLUC made significant differences to the relative emissions intensity of ECM. Co-Product Allocation The handling of co-products is one of the most debated and unresolved issues surrounding LCA in the agri-food sector (Notarnicola and others 2015). The IDF (2015) stated that allocation of emissions between feed co-products should be based upon economic value. The allocation of GHG emissions to beef originating from the dairy sector causes significant variation within the reported emissions of milk. The effect of this variation is exaggerated in grass-

CATTLE PRACTICE VOLUME 31 PART 1 2023 58 based systems due to the lower milk yield per cow resulting in a higher ratio of beef production for each kg ECM (Flysjö and others 2011). There is no convergence on ‘the best method’ of allocating emissions to co-products although economic allocation is the most commonly adopted, however this method is not compliant with the ranking criteria set out by the ISO (Baldini and others 2017). GHG Emissions From The Dairy Sector Life cycle GHG emissions per kg of FPCM vary significantly across different dairy farms, (Henriksson and others 2011, OBrien and others 2014b, O’Brien and others 2014a) from as low as 0.6kg CO2 e/kg FPCM to as high as 2.13kg CO2 e/ kg FPCM (O’Brien and others 2014a, O’Brien and others 2015). Methane and Nitrous oxide emissions are by far the most significant GHG emitted from dairy farms (Rotz 2018). Anthropogenic CO2 caused through use of fossil fuels and use of electric on farm composes only a small part of the overall carbon footprint of dairy (McGeough and others 2012), however energy use incurred through the production of fertiliser does make a more significant contribution on many farms (Casey and Holden 2005). Enteric Emissions Invariably on almost any dairy farm, anywhere in the world, today as has historically been the case, on farm methane emissions form the largest part of any carbon footprint based on kg CO2 e/kg FU (Capper and others 2009, Henriksson and others 2011, McGeough and others 2012, Morais and others 2018, Rotz 2018, Lorenz and others 2019). Typically, CH4 exceeds half of all GHG emissions contained within LCA with the majority, over 80% of methane emissions resulting from enteric fermentation and the remainder the result of manure breakdown (Flysjö and others 2011, McGeough and others 2012, Aguirre-Villegas and others 2022). Enteric emissions per functional unit output are generally lower on high yielding confinement systems than on grazing and more extensive systems (Flysjö and others 2011, OBrien and others 2014b, Rotz and others 2020). The amount of methane produced in the rumen is broadly driven by the dry matter intake (DMI) of cattle but also heavily influenced by the makeup of the diet in terms of digestibility and fibre type (Sabia and others 2020). There are differing methodologies that can be used for estimating enteric methane emissions, however, in the field of LCA, methane is usually estimated using IPCC guidelines (Aguirre-Villegas and others 2022), under this system different tiers represent advancing levels of methodological refinement (Table 3). Experimental evidence evaluating proxies for enteric methane emissions have shown DMI and digestible energy intake to be a “reasonably adequate” predictor of enteric emissions with an R2 of 0.64 (Negussie and others 2017). Many models have used linear relationships to correlate between DMI, digestible energy and methane emissions, however enteric production does not follow a linear process, generally emissions rates gradually approaches an upper and lower limit. Non-linear models that predict methane production as a function of digestible energy intake and starch-fibre-ratio has proven reasonably effective in predicting methane production (Stackhouse-Lawson and others 2012, Appuhamy and others 2016). Enteric fermentation is a complex process that cannot be easily represented by an equation (Rotz 2018), given the high overall contribution of enteric methane to the carbon footprint of dairy relatively small inaccuracies in calculating enteric methane production can have a relatively large effect on the final carbon footprint of milk. Modelling has demonstrated that short lived Methane enteric emission calculations. Tier 1 Simply adopts a default emission factor, 121kg/year CH4 for North American Holstein cows which is reduced to 81kg/ year for smaller New Zealand type grazing animals. Tier 2 Methane emissions are proportional to gross energy intake of feed and specific methane conversion factors. This method is adopted by many studies and is recommended by the IPCC. Tier 3 These methods are based on more complex modelling systems and are country specific, they consider feed characteristics known to effect enteric fermentation. (IPCC 2006a, Rotz 2018, Guzmán-Luna and others 2021) Table 3.

CATTLE PRACTICE VOLUME 31 PART 1 2023 59 GHGs such as methane behave as ‘flow pollutants’ in contrast to ‘stock pollutants’ such as N2 O and CO2 (Allen and others 2018). The author proposes the GWP method where, for flow pollutants, future climatic forcing effect of emissions depends upon the recent change in emissions. However this implies the ‘grand-parenting’ of national methane ‘quotas’. The Paris agreement requires a 24-47% reduction in biogenic methane emissions by 2050 and how national budgets are allocated to different nation states is a matter of contention which may be challenged on the basis of ‘international fairness’ (Prudhomme and others 2021). Manure Handling and on Field Losses On farm Nitrous oxide losses through manure storage, spreading and application of artificial fertiliser typically account for around 25-35% of total GHG emissions associated with dairy farming. (McGeough and others 2012, O’Brien and others 2014a). Nitrous oxide has a very large CO2 equivalence of 298kg CO2 e. This means that even relatively small quantities contribute significantly to the carbon footprint of dairy production (Rotz and others 2010). Ammonia (NH3 ) losses from slurry while it is stored and spread are also a significant problem, up to 50% of nitrogen within slurry taking the form of urea which is broken down into NH4 subsequently forming dynamic equilibrium between NH4 and NH3 , if NH3 is allowed to escape into the atmosphere as it volatilises the equilibrium will be pulled toward the creation of more NH3 . Ammonia emissions are significant because they can be transformed in the environment into Nitrous oxide and other nitrogen compounds resulting in indirect GHG emissions. In addition to causing air pollution and eutrophication of natural ecosystems (Rotz and others 2014). Losses of both methane and nitrous oxide from manure have been shown to be significantly lower in grazing herds than in confinement systems (O’Brien and others 2014a), this is because manure is applied directly to pasture without any storage or spreading process. Soil Carbon Sequestration within LCA Within the sphere of LCA, carbon sequestration by soils on dairy farms is applied inconsistently and is not included within the majority of LCA assessments (Knudsen and others 2019). The amount of carbon held within soil always moves toward equilibrium, this equilibrium point is affected by management processes such as cultivation and application of manure. Conversion of land from cultivation to permanent pasture can result in significant increases in soil carbon over a 20-30 year time period, equating to around 0.46kg CO2 e/kg ECM (Rotz 2018). These gains are lost if the land reverts to cultivation. It is recommended that soil carbon sequestration is excluded from LCA as guidelines from IPCC (2006b) assume soil carbon reaches equilibrium after twenty years. According to (ISO 2006a), sequestration should be calculated separately and applied as an offset. However, it has been demonstrated that it is possible for managed grassland to continue to sequester carbon (Soussana and others 2007, 2010) Soil carbon sequestration was found to be capable of offsetting between 5%-18% GHG emissions from grassland dairy systems (Knudsen and others 2019). Soil carbon sequestration has the potential to make a significant difference to conclusions around differences in GWP impact of different management systems (OBrien and others 2014b). The issue of soil carbon sequestration and iLUC, represent another area of conflict and opportunity for divergence within LCA, while (Soussana and others 2010, Knudsen and others 2019) assert that conversion of cropland into grassland creates a carbon credit through sequestration, Audsley and others (2009) would assert that the displacement of the arable crop results in indirect LUC emissions. The application of either of these positions will have a significant effect upon the final emissions calculation. Relationship between CF and Farm Profitability O’Brien and others (2015) showed a correlation between carbon footprint and economic performance of dairy herds in Ireland. This was attributed to biological efficiencies in higher preforming herds resulting in more efficient utilisation of pasture, longer grazing periods, more milk per cow and lower use of concentrate per cow. Although not related to financial performance many of these variations were supported by Henriksson and others (2011). Summary A consistent criticism of footprints has been the narrow focus, although strictly this is by design (Ridoutt and others 2016). However, applying this lens to a complex and convoluted biological system with multiple outputs and that utilise a myriad of bye products from other industries, leads to a relatively abstract measure, that through

CATTLE PRACTICE VOLUME 31 PART 1 2023 60 methodological choices can be tailored to support the desired conclusions of the author. “Net GHG emissions or CF has often been used to quantify the sustainability of a product. Sustainability is a much broader term though, including many other environmental impacts along with social and economic factors. More needs to be done to integrate these other factors into a full life cycle assessment. Use of GHG emissions as a sole measure of sustainability is not appropriate.” (Rotz 2018). “The risk is high that researchers and stakeholders misunderstand and/or inadvertently misuse foot printing results. An unfortunately large number of studies in the scientific literature and in popular media evidence occurrences of such situations, for example many studies using carbon footprint results to support claims about ‘environmental sustainability’, ‘green products’ or ‘environmental friendliness’ – carbon footprint can not act as acceptable proxies for systematically capturing the broad spectrum of environmental problems, thus making those claims inappropriate” (Laurent and Owsianiak 2017). To varying degrees, ruminant livestock systems can generate both positive and negative impacts upon local ecology and the wider environment. They can potentially form a key element of delivering ecosystem services but can also inflict significant damage, these outcomes are poorly captured by a carbon footprint (Von Greyerz and others 2022). There exists significant tension around the discourse of sustainability within agriculture and the vision of a sustainable future for food production (McNeill 2019). Given the limitations of a carbon footprint at describing sustainability, this study will investigate the opinions of a broad range of stakeholders and seek to capture their views around how we should define, attempt to measure and address sustainability within the dairy sector. METHOD An online questionnaire exploring themes of sustainability with the dairy sector, agriculture and wider food production was created. Participants were selected based on specialism in the field and/or as a key stake holder within the industry. The survey aimed to encompass a broad range of stakeholders from across the breadth of dairy farming, food production, local government and other organisations with an environmental interest (Figure 1). Participants were invited from different countries across the globe. Selection criteria also Figure 1. Make up of respondents according to self-assigned category, pertaining to primary role, location, area of focus and highest academic obtainment.

CATTLE PRACTICE VOLUME 31 PART 1 2023 61 included accessibility and willingness/time to complete the anonymised survey. In many of the cases participation in the survey followed on or preceded a face-to-face meeting although this was not exclusively the case. Of the people selected only 21% submitted a completed questionnaire. The questionnaire was closed once thematic saturation had been reached. Twenty-three participants responded, the responses were analysed using thematic analysis methods set out and guided by (Braun and Clarke 2006). Given the overlapping nature of the questions, responses were analysed as a whole, rather than on an individual question basis. Primary themes are recorded in Table 4. The total number of times each of them is mentioned or touched upon by participants is recorded in row A. In addition to this, respondents frequently focused on a particular theme, discussing this at length, a separate row B records the instances where this happened (Table 4). Responses were then organised into secondary themes clustered around preservation of natural capital, the importance of resilient social structures to support farming as well as themes around the often intensive nature of dairy farming resulting in a higher risk of environmental harm and lack of public acceptance. RESULTS AND DISCUSSION When asked about the merits and challenges of carbon foot printing, eighteen of the respondents picked up one or more of the themes already discussed within this essay. Five respondents suggested that carbon foot printing was in many ways a better gauge of efficiency, than a measure of sustainability. Given that enteric methane emissions represent more than half of GHG emissions on dairy farms and is directly related to the efficiency of feed conversion into milk (Aguirre-Villegas and others 2022) this assertion is supported. Moreover, Tier 2 methodology set out by the IPCC (2006a) to calculate enteric methane emissions, bases this figure as a direct product of gross energy intake. Given firstly, that enteric emissions make up such a large proportion of overall emissions and that secondly, carbon footprints are reported on a per standard unit of output basis, simple logic informs us of a strong association between carbon footprint and feed conversion efficiency. While it is misguided to state that efficiency and sustainability are unrelated, they should not be conflated. Natural capital erosion The most common theme that respondents picked up throughout the survey focused upon agricultural systems that are self-perpetuating and can last in perpetuity without eroding the natural capital upon which they, and wider society depend upon to function. This natural capital has been described and defined as encompassing soil, clean water and biodiversity (Goodland 1997). Respondents inferred that systems that progressively deplete anyone of these resources are ultimately unsustainable. Soil health is defined as the capacity of soil to function as a living system that sustains biological productivity, maintains environmental integrity and promotes plant, animal, and human health (Doran Table 4. Natural Capital and soil management Protects Water Biodiversity Nitrogen efficency Resilience (Environmental) Resilience (cultural) Rural Society Financial Geographically variable Arable integration Extensify/Reduce Input dependency Social / Public acceptance Animal Welfare CF is simple/simplistic CF is efficency CF leads to intensification CF methodology inconsistency Technological advancement Methane Reduction Broad/ Holistic Term A) mention 18 13 16 6 7 5 6 12 2 4 12 2 6 10 5 4 4 6 2 8 B) Focus 10 4 10 3 1 3 1 2 7 1 1 Secondary Themes Natural Capital Rural Society Intensification challenges Limitations of CF

CATTLE PRACTICE VOLUME 31 PART 1 2023 62 and Zeiss 2000). “Soil health” cannot be directly measured thus quantifying the health of a soil is not straight forward (Karlen and Obrycki 2019) different measures including soil organic carbon (SOC), water-stable aggregates (WSA), microbial biomass carbon (MBC), earthworm activity, water holding capacity, pH amongst others are all important to holistically assess the health of a soil, and while these factors are all linked, they do not necessarily neatly correlate (Karlen and Obrycki 2019, Mcclellan Maaz and others 2023) Soil organic carbon is a measure of soil health frequently discussed within the scientific and grey literature, however there is currently no agreed standard approach to which methodology should be used to measure and compare soil organic carbon. Measurements vary significantly depending upon season, soil temperature and a multitude of other external factors (Sabia and others 2020). These uncertainties are cited as a reason that changes in soil organic carbon in managed soil is excluded when assessing GHG emissions (Knudsen and others 2019). Despite difficulties in consistent assessment, soil organic carbon shows strong correlation with other soil health indicators (Mcclellan Maaz and others 2023). Using a multitude of soil health indicators, overall soil health was deemed to be better in pasture systems than arable land, unmanaged land and indeed comparable with soils surveyed in woodlands (see Figure 2) (Mcclellan Maaz and others 2023). The authors noted that samples were taken at a depth of 15cm and that this was not necessarily representative of soil health across a broader range of depths. Other studies have shown improved soil health indicators in pasture when compared to soils taken from forest (Saviozzi and others 2001). The theme described by survey respondents of a system that can self-perpetuate without eroding natural capital or exceeding its natural limits is an idea that broadly aligns with the concept of planetary boundaries. First described by Rockström and others (2009) and further developed by Steffen and others (2015) the concept sets out different dimensions or Earth system processes within which humanity must operate. These include climate change, Biodiversity loss (Biosphere integrity), ozone depletion, freshwater use and biochemical flows of nitrogen and phosphorous amongst others. For each Earth system process, the authors seek to define a “safe operating space” within which humanity can continue to develop and thrive. Planetary boundaries define the limits of these safe operating spaces and transgressing any of these boundaries incrementally increases the risk of disrupting the capacity of the earth to exist within a Holocene-like state, moving from the zone of uncertainty through to a high risk of serious impacts. According to Steffen and others (2015) the Earth system processes where planetary boundaries are currently being exceeded to the greatest extent are those of biosphere integrity; loss of genetic diversity and biochemical flows of excessive nitrogen and phosphorous (see Figure 3). These two key areas of sustainability mirror two of the remaining key areas focused upon by survey respondents. Figure 2. Distribution of single level soil health indices, scored by the clustered single level model, across different current land uses and management categories. Conventional cropland had lower soil health indices than other land uses (p<0.05) (Mcclellan Maaz and others 2023). Soil Health Index (0 = Minimum score, 1 = Maximum score) Conventional cropland Organic cropland Pasture Tree-based (orchards, agroforestry, forests) Unmanaged, previously Intensive agricultural lands Current land management 0.9 0.6 0.3 0.0

CATTLE PRACTICE VOLUME 31 PART 1 2023 63 Nutrient use efficiency, and effect on water quality and natural biodiversity. Nitrogen use and nutrient losses to the environment was one of the key focuses of seven of the twentythree respondents, of the remaining respondents over half mentioned this as an area of consideration. All livestock systems are limited to some degree in their ability to incorporate nutrients into products, due in large part to inherent inefficiencies of nutrient metabolism within both cattle as well as the plants they consume (Powell and others 2010), leading unavoidably to losses into the environment which have the potential to cause negative impacts at both a local and global level. (Clark and others 2007, Einarsson 2017). While nitrogen losses can make a significant contribution to GHG emissions, the environmental impact of excess nutrients is far more wide ranging. Nitrogen and phosphate inputs in the dairy sector are dominated by inorganic fertiliser and purchased concentrates, the major outputs of these nutrients are embodied within milk and animal sales, (Mihailescu and others 2014, Löw and others 2020, Flach and others 2021) Nutrient utilisation is most commonly assessed using two indicators, Nutrient Balance (NB) and Nutrient use efficiency (NUE) (Dentler and others 2020). Nutrient Balance is the difference between nutrient inputs and nutrient outputs, including phosphate and nitrogen embodied in feed, fertiliser as well as those in bedding, livestock purchases, seed and exported manure along with atmospheric deposition and biological fixation. Results can be expressed either in terms of per unit of land (kg/ha) or in terms of unit output (kg/L) (Einarsson 2017). Where the amount of input nutrient exceeds that of output nutrient it is often referred to as a ‘Nutrient Surplus’, where a surplus exists there is a risk of surplus nutrients being lost to the environment. Nutrient Use Efficiency (NUE) is a dimensionless indicator of the ratio between the aggregated input nutrients and output nutrients. NUE does not provide direct information on environmental impacts but informs on the efficiency with which nutrients are captured within the system (Gerber and others 2014). Of the respondents interviewed six identified either NUE or nitrogen surplus as important metrics of sustainability eluding to how excessive nutrient surpluses can adversely affect biodiversity. Only one respondent proposed that a maximum Nitrogen surplus per hectare should be considered as an indicator key metric of sustainability. Flach and others (2021) asserted that nitrogen surplus of less than 50kg/ha are acceptable and can be incorporated into the soil as organic matter. EU guidance suggests the maximum desirable nitrogen surplus should not exceed 80kg/ha and exceeding this level presents an elevated risk of excessive losses to the environment (EU Nitrogen Expert Panel 2015). The guidance describes how at higher stocking rates and higher farming intensity NUE must be higher to avoid breaching this threshold. However Schulte and others (2006) describes how these levels are not absolute and are affected by local climatic conditions such as rainfall and soil type. Excessive loss of nutrients into the environment is directly linked to biodiversity loss (EU Nitrogen Expert Panel 2015). The same source also described how movement of nutrients from Figure 3. A graphical representation of planetary boundaries taken from (Steffen and others 2015). Current status of the control variables for seven of the planetary boundaries. The green zone is the safe operating space, the yellow represents the zone of uncertainty (increasing risk), and the red is a high-risk zone. The planetary boundary itself lies at the intersection of the green and yellow zones (Steffen and others 2015).

CATTLE PRACTICE VOLUME 31 PART 1 2023 64 terrestrial ecosystems into water occurs within natural systems and within these systems a natural nutrient surplus is a requirement to sustain all ecosystems, it describes how agricultural systems with a NUE of greater than 90% are at risk of what it describes as ‘nutrient mining’ and depleting the soil of nutrients which are required for a functioning eco-system (See Figure 4). There is an optimal level of nutrient surplus, however these levels are frequently exceeded within the dairy sector with studies showing surpluses of 255kg/ha(Cherry and others 2012), 191kg/ha (Oenema and others 2012) and 318kg/ha (Bassanino and others 2007). Agricultural intensification has been touted as one of the most promising ways to meet growing demand while minimising environmental impacts (Tilman and others 2011), in the dairy sector this means increases in output both per acre and per cow, using predominantly confinement systems, invariably combined with increased use of concentrate feeding and typically inorganic fertiliser. Broadly, studies show that per unit of output, high out-put systems produce milk lower at emissions intensity than more extensive systems of dairy production, due in large part to the dilution effect of additional output on enteric methane emissions (Lorenz and others 2019). However multiple studies demonstrate that more intensive dairy systems, with higher levels of nutrient input reduce the overall efficiency with which nutrients are utilised. A law of diminishing returns resulting in a decline in NUE and an increasing nutrient surplus per ha (Knudsen and others 2019, Dentler and others 2020, Sabia and others 2020, Flach and others 2021). Nitrogen use efficiency and nitrogen surplus for extensively managed dairy farms was 0.41 and 41.6kg/ha (Dentler and others 2020) 0.44 and 37.9kg/ha (Flach and others 2021). A study of twenty one, intensively managed grazing systems in Southern Ireland found a mean nitrogen surplus of 175kg/ha and a mean NUE of 0.23, the study showed that higher nitrogen input per hectare in the form of inorganic fertiliser and concentrate feeding correlated with higher nitrogen surpluses (Mihailescu and others 2014), based on other studies this trend extrapolated into confinement systems, where output per hectare is much higher leading to lower NUE and a higher nutrient surplus (Knudsen and others 2019, Dentler and others 2020). The authors concluded that low input, low output systems represented a more efficient use of external inputs, leading to lower nutrient losses into the environment and lower environmental pressure. Farm management and between farm variation in efficiency within the production system also had a significant effect on overall performance (Mihailescu and others 2014). These conclusions are consistent with other studies (Chobtang and others 2017, Einarsson 2017, Figure 4. Conceptual framework of the Nitrogen Use Efficiency (NUE) indicator. The numbers shown are illustrative of an example system and will vary according to context (soil, climate, crop). The slope of the diagonal wedge represents a range of desired NUE between 50% and 90%: lower values exacerbate N pollution and higher values risk mining of soil N stocks. The horizontal line is a desired minimum level of productivity for the example cropping system. The additional diagonal represents a limit related to maximum N surplus to avoid substantial pollution losses. The combined criteria serve to identify the most desirable range of outcomes (EU Nitrogen Expert Panel 2015).

CATTLE PRACTICE VOLUME 31 PART 1 2023 65 Knudsen and others 2019, Flach and others 2021). A theoretical maximum utilisation of nitrogen within ruminant production of between 0.45 and 0.5 (Dijkstra and others 2013) demonstrates inherent and unavoidable nutrient inefficiencies of dairy farming. Dentler and others (2020) demonstrated that in addition to declining utilisation efficiency of nutrients with increasing milk yield, high input systems relied much more heavily on feeding human edible feed stuffs, ten out of twelve high input dairy farms consumed more human consumable protein than they produced making them net consumers of human edible protein and energy, implying that these systems create additional demand for arable land. The study discussed how increased nutrient surpluses generated by high input systems generated an elevated risk of impacting marine, freshwater and terrestrial ecosystems leading to pollution and loss of biodiversity, these assertions were mirrored by the respondents of the questionnaire. BIODIVERSITY Biodiversity loss was the mentioned more frequently than any other theme, with ten of the respondents choosing this as a major focus of discussions. In some instances biodiversity loss was directly linked to nutrient surpluses, while in others, the connection was made indirectly through discussion around the challenges of intensive land use and chemical inputs leading to biodiversity loss. Thirteen respondents advocated for more extensive systems which it was implied would improve biodiversity. All of these discussion points are supported by the literature and this link between high dependency on external inputs such as nitrogen fertiliser and purchased concentrates, leading to elevated nutrient surpluses and the subsequent risks of impacting water quality and biodiversity emerged as a key overarching theme of the study. In terms of metrics of sustainability, biodiversity was the most popular response to this question with respondents indicating that this metric served as a sentinel indicator for broader environmental harm. Biodiversity can be defined as the genetic variability among organisms, both within species and between species living within an environment. Agricultural practices may damage biodiversity (Sabia and others 2020) and different methods exist to quantify this damage to biodiversity. Biodiversity damage score measures the number of species detected within an occupied area and compares this to a baseline figure, the baseline figure is assumed to be natural forest because it is suggested that this is the land type that would arise without human distortion (Tuomisto and others 2012, FAO 2015). Several survey respondents asserted that appropriately managed grasslands can enhance biodiversity beyond that of unmanaged ‘natural’ ecosystems. This is supported by the FAO (2015) and by data gathered in the UK by (Schryver and others 2010). The study demonstrated organic fertile grassland to have a greater abundance of biodiversity than the baseline of ‘natural woodland’. The study showed that as land use intensification increased, biodiversity declined. Also biodiversity was higher in organic systems vs non-organic. The study also suggested that where grassland borders arable land, biodiversity is enhanced, a position also articulated by survey respondents who advocated the incorporation of livestock systems into arable rotations. A study by Sabia and others (2020) evaluating the effect of concentrate feeding on environmental impacts, high concentrate systems were again shown to deliver the greatest efficiency in terms of carbon footprint per kg of FPCM, with biogenic methane contributing 75% of the carbon footprint in low concentrate systems compared to 57% for high input systems. However, the high concentrate systems resulted in far higher nutrient surpluses and demonstrated much a higher impact on biodiversity (Sabia and others 2020). Delaby and others (2020) discussed that although careful management of nutrient surpluses was essential to minimise wider environmental impacts, within dairy systems biodiversity can best be promoted by improving the quality and abundance of adjoining habitat, created strategically within the farm holding. Extensification of dairy systems One third of respondents discussed in depth the challenges of intensive dairy systems or that a move towards more extensive dairy systems accompanied by a reduced dependence on the externalities of red diesel, compound fertiliser and imported feed, would both make dairy systems more environmentally sustainable and lead to a more resilient dairy sector, better able to meet the demands of a changing climate. Kleijn and others (2009) demonstrated that the relationship between nitrogen application and biodiversity is non-linear. In the broadest terms, only very small improvements in plant biodiversity where observed as nitrogen use fell from 250kg/ ha to 75kg/ha, plant biodiversity increased more

CATTLE PRACTICE VOLUME 31 PART 1 2023 66 rapidly below this threshold, although the study also demonstrated significant complexity within this assertion. Moreover, this study only looked at the biodiversity effects within the farmed area and did not take account of the wider effects of terrestrial and freshwater eutrophication which can be associated with high nutrient surpluses. Knudsen and others (2019) compared differing production systems at varying levels of land use intensity. Organic farms showed lower levels of biodiversity damage as well as lower levels of ecotoxicity. UK, organic, grass-based systems, with an average stocking rate of 1.2ha/cow across the sampled farms showed an improvement in species biodiversity relative to the baseline of natural deciduous woodland, expressed as a negative biodiversity damage score of -0.28. The group of conventional, UK, grassland systems had an average stocking rate of 1.09ha/cow and were found to have a median biodiversity damage score of 0.37 although over two thirds of this damage was associated with the imputed damages of producing the imported feed. Output in FPCM kg/cow was 7,411 and 6,193 for UK, grass based conventional and organic systems respectively. Of the systems studied Danish, conventional, confinement systems producing average yields of 9,599kg FPCM/cow/ year with an average stocking rate of 0.88ha/ cow were shown to present the highest risk of ecotoxicity and have the highest biodiversity damage score of 0.48. These farms also showed the highest levels of resource depletion in terms of fossil fuel use per kg FPCM, both directly and through costs associated with artificial fertiliser. In addition they where also found to be lower in terms of soil organic carbon which is positively correlated with the amount of grass fed since soil carbon sequestration is higher in grass land than in arable (Mogensen and others 2014). The confinement system did however use less land per kg FPCM than any other system, although on examination it appears that the figures presented include only land used within the holding itself and do not include the land used to produce the arable crops needed to sustain the system. While there is an emerging acceptance that protection of natural capital as a concept, is an integral element of sustainable agriculture, there is contested discourse as to how it can be measured, regulated and recognised at an industry level. Tension exists as to whether universal assessment criteria can be implemented at a national or international level or whether assessment must be tailored to meet local circumstances (Fleming and others 2022). Rural Society Respondents discussed how systems need to be resilient in a multitude of different dimensions in order to overcome environmental, climatic and geopolitical shocks and stressors, this includes social dimensions. The ability of farming systems to thrive and adapt is dependent upon farms and farmers being embedded within thriving rural communities with broad societal investment within agriculture and diverse systems of farming bespoke to the local climatic, geographical and cultural context. Healthy ecosystems, farm livelihoods and functioning rural communities are integral to food security (Chappell 2019). While strategies around sustainable intensification seek to maximise productivity while manging narrowly defined environmental impacts, these endeavours frequently rely on capital intensive solutions that can exacerbate social and environmental vulnerabilities, consolidate production and lead to a concentration of power (Gliessman and others 2018). Resilience can be viewed as the adaptive capacity of an agricultural systems to respond to climatic, environmental and economic challenges. Agricultural systems are complex social-ecological entities with reciprocal interactions between people, communities and the environment. These interactions operate at individual farm level, locally within communities and on a regional level (Petersen-Rockney and others 2021). Since the second world war, agriculture has seen a seismic and ever accelerating shift towards larger, higher yielding, more specialised farming systems with greater dependency on nonrenewable resources, purchased inputs and capital assets (Capper and others 2009). This has been accompanied by market consolidation, both up and down-stream of the farmer. This uniformity of markets, labour practices and advancement of technologies has allowed the expanding scale of modern farming (Busch 2010). By many measures, including that of carbon footprint, these changes have driven improved efficiency (Capper and others 2009). These farming systems can offer financial rewards to farmers who can embrace new advancements first, typically larger farmers and others that can access capital-intensive technologies, inputs and resources first, giving them a temporary market advantage while the rest of the industry catches up or exits, before the next cycle (Busch 2010). This process drives continual consolidation of farms and land ownership where farms take on increasing

CATTLE PRACTICE VOLUME 31 PART 1 2023 67 levels of debt to support increasingly capitalintense farming systems (Petersen-Rockney and others 2021). Through capital interest, depreciation and asset costs these systems carry increasing levels of fixed costs, this drives the necessity to pursue maximum output even at very low marginal profitability and frequently, in terms of nitrogen, at very low marginal efficiency, in order to cover these elevated fixed costs. CONCLUSIONS Carbon footprints are presented within the contemporary media, commercial entities and frequently by government agencies as a proximate measure for sustainability. In the dairy sector, due to highly complex biological production systems, multiple outputs and use of co-products as primary inputs, there is significant opportunity for methodological divergence when calculating carbon footprints of milk. Layered on top of this are debates around accounting for soil carbon sequestration, the application of carbon off-setting as well as the carbon equivalence of short lived GHGs. Through its very nature the fact that a) enteric methane emissions account for over half of the carbon footprint, which in turn is calculated using gross energy of feed, and b) that carbon footprint is expressed per unit of production, implies that carbon footprint is primarily a metric of efficiency. Given this it is unsurprising that there is strong correlation between carbon footprint and profitability amongst dairy farms. The drive for improved efficiency has had a profound effect on the nature of the dairy sector, leading to the consolidation and intensification of dairy farming creating challenges around the management of environmental impacts. While grazing livestock can have a beneficial effect upon environmental outcomes, at high stocking rates supported by high levels of supplementary feeding these benefits can be very difficult to realise. The quest for ever advancing levels of technical efficiency place a significant burden of investment upon dairy farmers. This frequently leads to heavily capitalised systems of production with high fixed costs. These high fixed costs in turn promote the necessity for the pursuit of marginal production, while achieving this marginal production is facilitated by high levels of technical efficiency. However, the pursuit of this marginal production generally leads to lower overall resource use efficiency in terms of nutrient use and purchased feeds. High intensity systems exhibit a high stocking rate and frequently a high dependency on purchased fertiliser, concentrate feeds and red diesel. In addition to the associated environmental risks, high levels of dependency on external inputs, as well as the inflexibility afforded by high fixed costs, may impair the resilience of intensive dairy systems in the face of a changing climate and accompanying political and social upheaval that may emerge as a result. There exist examples of low input dairy systems, operating with minimal reliance on fossil fuels, chemical fertiliser and purchased feeds. These systems build natural capital and by many definitions of environmental sustainability, produce industry leading outcomes. They also offer an entry point for new entrant farmers. They also offer a means to harness the biological efficiency of dairy over beef systems, without building in the fixed costs that necessitate the pursuit of marginal production. Unfortunately, many of our current metrics, including carbon footprint penalise these systems. In a world with growing demand for food, but with limited land and challenges to the availability of the resources required to produce food, it is imperative that the productivity of existing farmland is maximised. However, it is clear that this must be done in a way that preserves the integrity of the land for future generations. The use of metrics that incentivise the trading of nutrient efficiency for carbon efficiency while increasing the risk of environmental damage and increasing dependency upon marginal arable output, is of limited value. Defining sustainability is a question almost rhetorical in nature. It pertains to an almost spiritual relationship between people, animals and the land, unique to each locality, born of the climate, the geography and the culture. Where local tradition and religion once set the boundaries for these relationships, global institutions grapple with the granularity of these issues. With respect to Agriculture, the use of carbon foot printing as a primary gauge of sustainability, has profound limitations. While efficiency and sustainability may not be concepts diametrically opposed, the two should not be conflated. RECOMMENDATIONS It is imperative that a more nuanced view is taken around the interpretation of carbon footprints with

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CATTLE PRACTICE VOLUME 31 PART 1 2023 70 jclepro.2014.02.023 Monfreda, C., Wackernagel, M., Deumling, D. (2004) Establishing national natural capital accounts based on detailed Ecological Footprint and biological capacity assessments ARTICLE IN PRESS. Land Use Policy 21: 231–246. https://doi.org/10.1016/j.landusepol.2003.10.009 Morais, T.G., Teixeira, R.F.M., Rodrigues, N.R., Domingos, T. (2018) Carbon Footprint of Milk from Pasture-Based Dairy Farms in Azores, Portugal. Sustainability 10(10): 3658. https:// doi.org/10.3390/SU10103658 Negussie, E., de Haas, Y., Dehareng, F., Dewhurst, R.J., Dijkstra, J., Gengler, N., Morgavi, D.P., Soyeurt, H., van Gastelen, S., Yan, T., Biscarini, F. (2017) Invited review: Largescale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions. 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CATTLE PRACTICE VOLUME 31 PART 1 2023 72 Approaches to reducing enteric methane emissions in dairy cows using a feed additive Walker, N., Packington, A., DSM Nutritional Products, Wurmisweg 576, 4303 Kaiseraugst, Switzerland Enteric methane (CH4 ) from ruminant livestock accounts for 30% of global anthropogenic CH4 emissions. Due to the relatively short atmospheric half-life of CH4 and its high global warming potential, reducing CH4 is regarded as the single most effective strategy to keep the goal of limiting warming to 1.5˚C within reach. Since the Global Methane Pledge was launched at COP26, 150 countries have signed-up to the collective goal of reducing global CH4 emissions by at least 30% of 2020 levels by 2030. In the UK, reducing emissions across all livestock sectors by 64% by 2050 is required to meet National Inventory goals. However, current technologies can only deliver a 23% reduction, thus alternative innovations are required to meet the shortfall. The UK Dairy Roadmap highlights a range of evidence-led targets towards carbon zero for dairy producers and processors, setting out a delivery programme to support their achievement. CH4 mitigation strategies at farm-level can be classified into 3 broad categories: 1. Improved management and genetics; 2. Nutrition and feed management; 3. Feed additives. Emissions reduction can be achieved by combining genetic and management approaches, reducing incidence of infectious or metabolic disease, and improving fertility, cow management and environment. Targeting the transition period and improving fertility will ultimately decrease culling rate, mortality and increase cow productivity and lifetime performance, thereby reducing the number of replacement heifers required, leading to further emissions reductions. A recent UK survey showed the average AFC was 29 months, well above the target of 24 months. Improving nutrition and feed management combined with dietary manipulation can be a highly effective CH4 mitigation approach. Better forage quality typically lowers emissions intensity due to enhanced animal productivity. Adopting other best practice feed management practices can improve dietary intake and feed efficiency. Higher starch diets promote propionate production which acts as an alternative major [H] sink to CH4 as well as providing energy for the cow. Numerous studies have shown low levels of lipid supplementation can decrease CH4 production, although results are variable. Feed additives which have the potential to reduce enteric CH4 emissions work by either specifically inhibiting methanogenesis or modifying the rumen environment such that CH4 production is reduced. Specific Methanogenesis Inhibitors include 3-nitrooxypropanol (3-NOP), bromoform, nitrate, urea, Seaweeds e.g., Asparagopsis). Rumen modifiers include Probiotics, Plant ‘secondary metabolites’ (e.g., essential oils, tannins, saponins, garlic); Propionate Precursors (e.g., fumaric acid, malate, aspartate); Antimicrobials or Ionophores. A recent independent scientific report published key findings, ranking the ten leading compounds being proposed as methane mitigators. Only two additives (3-Nitrooxypropanol and dried Asparagopsis (red algae)) have consistently delivered over 20% mitigation of enteric CH4 . Dietary nitrate is ranked third delivering 10% or more mitigation when consumed. Rumen modifiers tend to deliver less than 10% mitigation. The most extensively researched inhibitor 3-Nitrooxypropanol (3-NOP) was approved in the EU in 2022 for use in dairy cows and cows for reproduction. It was deemed highly efficacious and safe for the animal, worker, consumer, and environment. This was the first zootechnical additive approved in the functional group “substances which favourably affect the environment (reduction of enteric methane production)”. A similar authorisation is expected to be granted by the UK Food Standards Agency (FSA) in the first half of 2023. The compound 3-NOP is a highly specific and effective CH4 inhibitor which has a molecular shape like that of methyl-coenzyme M, the substrate of the enzyme coenzyme M reductase (MCR). MCR is found only in archaea and is involved in the last step of methanogenesis. 3-NOP selectively binds to the active site of MCR in a position that places its reducible nitrate group in electron transfer distance to Ni(I) and inactivates MCR by oxidising the active site nickel +1 in co-factor F430. Additionally, the nitrate group of 3-NOP is reduced to nitrite in the process, and in this form further inactivates MCR. 3-NOP does not impact the growth of other rumen microbes. Unlike some CH4 inhibitors, no evidence of reduced efficacy due to rumen adaptation has been reported.

CATTLE PRACTICE VOLUME 31 PART 1 2023 73 A condition of regulatory approval is to demonstrate efficacy and safety. With a typical mixed forage and concentrate T/PMR diet fed to high-yielding dairy cows, 3-NOP will reduce CH4 by approximately 30% when included at the minimum authorised dose (60mg/kg 3-NOP per kg DM). A recently published prediction equation allows farm specific CH4 mitigation calculations from dietary NDF, fat and 3-NOP concentration. Further research is investigating the effect of 3-NOP supplementation with other feed additives and feed ingredients to further reduce CH4 . Trial results and meta-analysis show that 3-NOP has no significant effect on intake, milk production, composition or processability (cheese and yoghurt manufacture). No effects were reported on rumen health or cow health, including disease incidence, fertility, or cow behaviour. 3-NOP is rapidly broken down into carbon dioxide and hydrolysed to naturally occurring 3-hydroxypropionic acid (HPA) and inorganic nitrate. No detectable residues are found in plasma, milk, meat or manure. 3-NOP is available as Bovaer® 10 to premix manufacturers in dry powder form. This is further blended and diluted for use by feed manufacturers for supplementation of concentrate feeds. Dairy TMR minerals can also be supplemented. Alternatively, a 3-NOP farm pack dilution may be used. Since EU approval, 3-NOP has been adopted as a CH4 mitigation strategy by numerous European dairy and processing companies. Due to the lack of milk production response, these companies incentivise farmers to use 3-NOP as part of a value chain. In 2022, the Flanders Government paid a subsidy to farmers to supplement cows with 3-NOP. When Bovaer® is approved in the UK, dairy processors will likely follow a similar strategy of adopting this zootechnical feed additive as part of a carbon zero strategy. As well as safeguarding animal health and welfare, farm vets have a role to collaborate with environmental initiatives relating to sustainable animal agriculture.

CATTLE PRACTICE VOLUME 31 PART 1 2023 74 Sustainability for cattle practitioners: A review of recent literature Britten, N., Synergy Farm Health Ltd, The Transmission Hall, Rampisham Business Centre, Rampisham Down, Maiden Newton, Dorset, DT2 0HS Sustainability is an increasingly pressing issue for the agricultural industry, with the livestock sector responsible for approximately 16.5% of emissions globally. Ruminants are significant contributors to total livestock emissions given the methanogenic properties of their digestive processes, so demand for ruminant products with lower emissions intensities is increasing. In addition to carbon emissions sustainability is also concerned with land usage, soil health, biodiversity, pollution (not carbon) and responsible use of medicines. Animal welfare can also be considered an issue of sustainability. This literature review draws from recent research on the sustainability implications of ruminant management practices that cattle vets are likely to encounter when giving advice on farm. Included are modelling of the carbon emission consequences of endemic diseases of cattle, the sustainability advantages of grazing compared with housing, grazing sustainably and feeding for improved sustainability. The practices outlined are of benefit to carbon emissions, soil health, local environmental pollution and animal welfare. Trade-offs between sustainability, welfare and production are discussed where they arise. Future opportunities to improve sustainability using genetics, precision livestock farming and other technologies are identified. This should equip cattle practitioners with the current state of research into sustainability and farming practices, facilitating the inclusion of sustainability as a consideration alongside animal health and welfare when giving veterinary advice.

CATTLE PRACTICE VOLUME 31 PART 1 2023 75 The impact of youngstock health and systems on carbon footprint Dent, H., Kite Consulting, The Dairy Lodge, Dunston Business Village, Dunstan, Staffordshire, ST18 9AB This presentation/workshop will look at the impact of youngstock health and improving dairy youngstock systems on carbon footprint of milk. This will include: • Introduction to carbon foot-printing and carbon emissions from agriculture (in particular dairy.) • Breakdown of where the average carbon footprint from dairy comes from i.e. enteric fermentation, manure, feed, fertiliser, energy etc. • Break down carbon footprint of a herd to show milking cows emissions against youngstock: i.e. what proportion of the dairy carbon footprint comes from bringing a cow into the herd. • Explore a case study on a 180-cow unit looking at impact of farm investment into youngstock housing which reduced pneumonia rates and improved growth rates and what that does to the overall dairy carbon footprint. • Discuss a case study for an intensive 300-cow unit and an smaller 12-cow organic unit looking at age at first calving as a key area to reduce carbon emissions. • Explore the relationship between age at first calving and carbon footprint per kg of milk, running through example scenarios. • Look at good youngstock health and relationship to production in later life can impact carbon footprint of milk. Overall, the aim of this presentation/workshop is to appreciate the large factor of emissions which come from the youngstock portion of the herd and appreciate how that can be used to reduce carbon footprint inline with political and retailer targets.

CATTLE PRACTICE VOLUME 31 PART 1 2023 76 A survey of foot disinfection practices for control of bovine digital dermatitis; evaluating solution depth, footbath hygiene, and the potential of footbaths as infection reservoirs for Treponema species. Gillespie, A.1 , Vanhoudt, A.2 *, Benedictus, L.2 , McAloon, C.3 , Logan, F.3 , Spaninks, M.2 , Viora, L.4 , 1 Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, L69 3BX 2 Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands; *Current affiliation Royal GD, Deventer, the Netherlands 3 School of Veterinary medicine, University College Dublin, Belfield, Ireland 4 School of Biodiversity, One health and Veterinary Medicine, University of Glasgow, Glasgow, G63 0AW Foot disinfection using footbathing is widely applied as a method for controlling bovine digital dermatitis (BDD) and other infectious claw diseases in dairy cows. Although opinions differ, broadly speaking current industry recommendations advocate the use of footbaths at least 3m long and 12cm deep, with total solution volume amounting to 1 litre per cow passage (Cook and others 2012, Cook 2017). Appropriate footbath dimensions ensure at least two immersions of each foot to above the coronary band, and that solution depth remains sufficient throughout use. Few studies have examined the application of industry recommendations or assessed their efficacy in maintaining good footbath hygiene. In addition, the efficacy of footbaths against the BDD causative Treponema bacteria has not been examined under field conditions. As well as describing current industry practices, our aim was to provide advice regarding the initial solution depth required to ensure adequate foot coverage for all cows passing through footbaths. In addition, we examined the hygiene of footbaths under field conditions in terms of organic matter content (g/L) (OMC), and used quantitative PCR to measure their efficacy against the putative BDD causative Treponema bacteria. METHODS Thirty-two dairy herds affected by BDD were recruited by a collaboration of veterinary researchers from the University of Glasgow School of Biodiversity, One Health and Veterinary Medicine (UG), the University College Dublin School of Veterinary Medicine (UCD) and the Farm Animal Practice of Utrecht University (FAPU). Data on footbathing practices was collected using a questionnaire. Researchers attended farms to measure footbath dimensions, and to measure solution depth and collect footbath content samples during use approximately every 50 cow passages. Firstly, footbath solution depth was assessed, as inadequate solution depth would lead to ineffective foot disinfection. Explanatory variables significantly associated with footbath solution depth using univariable linear regression (P<0.1), number of cow passages and footbath length, were offered to a final multivariable mixed effects model with the random effect of farm included. Footbath samples were used to measure OMC (g/L) as a proxy for footbath hygiene. Explanatory variables considered to affect foot hygiene were tested using univariable linear regression to assess associations with the outcome OMC. The significant variable (P<0.1), number of cow passes per litre of original footbath solution, was offered to a final multivariable model including the random effect of farm. A subset of samples from 15 farms was evaluated in duplicate using qPCR to measure total bacterial DNA and bacterial DNA from the Treponema genus. In addition, species-specific primers were used to measure quantities of three species of Treponema commonly associated with BDD (T. medium, T. phagedenis and T. pedis) (Evans and others 2008, 2009). Footbath samples collected by FAPU were plated on Columbia agar plates supplemented with sheep blood for 24 hours at 37o C and colonies counted. RESULTS Questionnaire answers showed that only one farm was using a footbath that complied with industry recommendations regarding footbath dimensions, solution depth, and litres of solution per cow passage before footbathing began; 18/32 (56%) footbaths were <3m, 26/32 (81%) were <12cm

CATTLE PRACTICE VOLUME 31 PART 1 2023 77 deep, and 15/32 (47%) footbathing regimes were not providing at least 1 litre per cow of footbathing solution. The depth of solution decreased throughout footbathing at the rate of 1.2cm per 100 cow passages. This resulted in 10/32 (31.3%) footbaths having depths of <7cm by the end of the session, risking poor coverage of the high-risk heel bulb area, however the random effect of farm was responsible for 76% of the variation in footbath depth. OMC exceeded 20g/L during footbath use on 16/32 farms, suggesting the biocide could become ineffective for the cows passing through the solution thereafter. Results from the multivariable mixed effects model showed that one cow per liter of original footbath solution was adequate to maintain OMC <20g/L, however the random effect of farm was responsible for 64% of the variation in OMC. The qPCR for Treponema spp. detected bacteria in one duplicate from the final footbath samples on two farms, however, T. medium, T. phagedenis and T. pedis were not detected in any footbath samples. Bacteriological cultures of the FAPU footbath samples on sheep blood agar were negative. Together these results suggest even footbaths contaminated above 20g/L OMC remain effective for removing BDD-associated bacteria. DISCUSSION Footbathing solution depths frequently fell below 7cm, risking poor biocide contact, even with the highest risk heel bulb region. Organic matter content in footbaths frequently exceeded biocide testing requirements of 20g/L, which raises concern regarding disinfectant efficacy, however, no BDDpathogenic treponemes were detected using qPCR, and no aerobic bacteria could be cultured from a subset of footbath samples. Our data suggest that footbaths are not an infection reservoir for BDDcausative Treponemes. Footbathing practices vary among dairy farms, with only 11/32 farms surveyed providing effective foot disinfection throughout footbathing (maintaining minimum solution depth of 7cm and OMC<20g/L). Farm-level factors were responsible for 64% of variation in contamination levels and 71% of variation in solution depth. Farmers in this study were not typically using veterinary surgeons or hoof trimmers as a source of advice regarding footbathing; there is an opportunity for veterinary surgeons and hoof health professionals to audit footbaths in-person during use as part of lameness control planning. REFERENCES Cook, N.B. (2017) A Review of the Design and Management of Footbaths for Dairy Cattle. Veterinary Clinics of North America: Food Animal Practice 33(2): 195–225. https://doi. org/10.1016/J.CVFA.2017.02.004 Cook, N.B., Rieman, J., Gomez, A., Burgi, K. (2012) Observations on the design and use of footbaths for the control of infectious hoof disease in dairy cattle. Veterinary Journal 193(3): 669–673. https://doi.org/10.1016/J. TVJL.2012.06.051 Evans, N.J., Brown, J.M., Demirkan, I., Murray, R.D., Birtles, R.J., Hart, C.A., Carter, S.D. (2009) Treponema pedis sp. nov., a spirochaete isolated from bovine digital dermatitis lesions. International Journal of Systematic and Evolutionary Microbiology 59(5): 987–991. https://doi.org/10.1099/ ijs.0.002287-0 Evans, N.J., Brown, J.M., Demirkan, I., Murray, R.D., Vink, W.D., Blowey, R.W., Hart, C.A., Carter, S.D. (2008) Three unique groups of spirochetes isolated from digital dermatitis lesions in UK cattle. Veterinary Microbiology 130(1–2): 141–150. https://doi.org/10.1016/j.vetmic.2007.12.019

CATTLE PRACTICE VOLUME 31 PART 1 2023 78 A new approach to lameness – introducing the Lameness Pattern Analysis Tool Manning, A.1 , Clifton, R.2 , Holsey, H.1 , Leach, K.1 , O’Grady, L.2 , Hyde, R.2 , Barden, M.2 , Can, E.2 , Green, M.2 , Bradley, A.1,2, 1 QMMS Ltd, Cedar Barn, Easton Hill, Easton, Wells, Somerset, BA5 1DU 2 University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD Lameness is an important welfare concern, and a potential brand risk for the UK dairy industry. The average prevalence of lameness in UK dairy herds is estimated at 30-35% (Barker and others 2010, Griffiths and Oikonomou 2017), though there is clear variation between farms. In recent years, the proportion of farms carrying out monthly or quarterly mobility scores has increased, driven largely by milk buyer demand. Currently these data are being used to satisfy milk contracts, but very little analysis is being carried out on the data. The aims of this project were to develop a Lameness Pattern Analysis Tool (LPAT), that could be used on all dairy farms with mobility score data, generate informative Lameness Pattern Analysis Reports, that would provide a means of monitoring lameness, and guide initial vet-farmer discussions on the subject. The Tool should use a similar approach to the Mastitis Pattern Analysis Tool, which uses clinical mastitis and somatic cell count data to inform the predominant mastitis epidemiology (Breen and Manning 2022). This MPAT was developed and released in 2022 and is available to all milk recording farms. Fifteen farms across the south of England were recruited to this project. Monthly mobility scores were carried out by one of two Register of Mobility Scorers (ROMS) trained scorers between June 2021 and May 2023. Internal validation between these scorers was carried out on a monthly basis, and during annual reaccreditation as part of ROMS. On some of the herds in this dataset, mobility scores had been carried out prior to 2021 by farm staff, and these data were also included in the study. In addition to mobility scores, data were collected from on-farm software and milk recording organisations: this included trim and lameness treatments, fertility data, and movements. Data were analysed using TotalVet and several new lameness metrics were created. Metrics were selected that had high inter-farm variation, and which were least influenced by the frequency of mobility scoring and recording of trims or lameness treatments. These include the proportion of heifers remaining sound during first lactation, proportion of lame and chronically lame by parity, new lame cure rate and days spent score 3. New lameness metrics will be presented as part of a new Lameness Pattern Analysis Tool. Case studies will be used to demonstrate different features of the Lameness Pattern Analysis Report. This report can be used on any UK dairy herd with mobility score data, and is enhanced with lameness and trim records. It is hoped that the new LPAT can support more vet-farmer discussion around lameness control. The earliest marker of ‘improvement’ is seen in 1st lactation animals, with a target of >85% of heifers remaining sound throughout their first lactation. REFERENCES Barker, Z.E., Leach, K.A., Whay, H.R., Bell, N.J., Main, D.C.J. (2010) Assessment of lameness prevalence and associated risk factors in dairy herds in England and Wales. J. Dairy Sci. 93(3): 932-41 Breen, J.E., Manning, A. (2022) Mastitis pattern analysis : epidemiology into practice. Livestock, 27(5): 202–208 Griffiths, B.E., Oikonomou, G. (2017) An epidemiological study into the prevalence of dairy cattle lameness and associated risk factors in England and Wales. Cattle Practice, 25(3): 257–258.

CATTLE PRACTICE VOLUME 31 PART 1 2023 79 Association between a genetic index for digital dermatitis resistance and the frequency of infectious foot lesions in Holstein cows Anagnostopoulos, A.1 , Barden, M.1 , Griffiths, B.E.1 , Bedford, C.1 , Winters, M.2 , Li, B.3 , Coffey, M.3 , Psifidi, A.4 , Banos, G.3 , Oikonomou, G.1 , 1 Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE 2 Agriculture and Horticulture Development Board, Stoneleigh Park, Kenilworth, CV8 2LZ 3 Animal & Veterinary Sciences, SRUC, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG 4 Department of Clinical Science and Services, Royal Veterinary College, North Mymms, Hertfordshire, AL9 7TA OBJECTIVES Digital dermatitis (DD) is a polybacterial disease endemic to most UK dairy farms and is often the most prevalent foot lesion recorded. It poses a major financial and welfare threat and is characterised by high incidence and recurrence rates. With a limited evidence base behind the efficacy of DD treatment and control protocols, the genetic background of resistance to DD could be potentially utilised. We aimed to investigate the association between the UK genomically estimated breeding value for resistance to digital dermatitis, the Digital Dermatitis Index (DDI), and the frequency of infectious foot lesions in a population of Holstein dairy cows. MATERIALS AND METHODS We enrolled and genotyped 2,352 cows from four farms. Foot lesion records were obtained by veterinary surgeons for each animal at four time points during a production cycle, starting at approximately two months before calving and ending in late lactation. These records were not used in the calculation of the animals’ DDI. Lesion records were matched to the animal’s own DDI (n=2,101) and their sire’s DDI (n=1,812). Digital Dermatitis Index values in our study population ranged from -1.41 to 1.2. The relationship between the DDI and the presence of digital dermatitis (DD), heel horn erosion (HE), and interdigital hyperplasia (IH) was investigated using logistic regression models, with farm and parity fitted as covariates. RESULTS The odds of an animal being affected by DD were 2.50 times greater for every one-point reduction in the animal’s DDI (95% confidence interval (CI) 1.92- 3.22). The adjusted probability of DD was 60% (95% CI: 53-68%) in cows with a DDI value of -1 while it was 20% (95% CI 16-25%) in cows with a DDI value of +1. Similar results were obtained using sire DDI; the odds of DD were 1.47 times greater (95% CI 1.23-1.75) for every one-point reduction in sire DDI. The odds of HE and IH were 2.56 times (95% CI 1.96-3.33), and 4.34 (95% CI 2.70-7.14) greater respectively for one point decrease in the DDI. The odds of HE and IH were 1.33 times (95% CI 1.11- 1.61), and 1.56 times (95% CI 1.11-2.22) greater respectively, for every one-point decrease in sire DDI. CONCLUSION The results of this study showed that the Digital Dermatitis Index could be utilised to select animals with better genetic resistance to DD, HE, and IH. We found a strong negative association between the presence of these lesions and the cows’ own Digital Dermatitis Index breeding values. Significant negative association was also found between lesion presence and their sires’ Digital Dermatitis Index breeding values. These results highlight the potential of claw-health genetic indexes to aid herd management of infectious foot lesions.

CATTLE PRACTICE VOLUME 31 PART 1 2023 80 Foot anatomy and structure and its association with the development of claw horn disruption lesions in dairy cattle Griffiths, B.E.1 , Barden, M.1 , Anagnostopoulos, A.1 , Bedford, C.1 , Higgins, H.1 , Psifidi, A.2 , Banos, G.3 , Oikonomou, G.1 , 1 Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE 2 Department of Clinical Science and Services, Royal Veterinary College, North Mymms, Hertfordshire, AL9 7TA 3 Animal & Veterinary Sciences, SRUC, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG OBJECTIVES Claw horn disruption lesions (CHDL), the collective term for sole ulcers, sole haemorrhage, and white line lesions, are regarded as the most important non-infectious lameness causing lesions. Anatomical characteristics of the foot such as sole thickness, digital cushion thickness and toe angle have previously been identified as important risk factors for CHDL development. The objective of this study was to examine the association between foot anatomy and structure and the development of CHDL. MATERIALS AND METHODS Across four commercial UK dairy farms, a cohort of 2,352 Holstein cows was prospectively enrolled and assessed at three timepoints: prior to calving (mean: -55 days, standard deviation (SD): 15), immediately post calving (mean: +5 days, SD: 3) and in early lactation (mean: +84 days, SD: 14). At each timepoint the presence of CHDL was assessed by veterinary surgeons, body condition score was recorded (Ferguson and others 1994), a thermographic image of the sole of each foot was taken using a FLIR E8-XT camera (FLIR Systems), and an ultrasound image of the left hind lateral claw was taken (a DRAMIŃSKI Vet 4 Mini). Additionally, at the post-calving timepoint, the foot angle and heel depth of the lateral claws of the hind feet were measured using a pair of callipers. After data collection had finished, sole temperature from thermographic images was measured using FLIR Tools software (version 5.13.18031.2002), and sole soft tissue thickness (SSTT, also known as digital cushion thickness) and sole horn thickness were measured from ultrasound images using ImageJ software (Schneider and others 2012). To characterise the association between preand post-calving foot anatomy and structure on the development of CHDLs in early lactation logistic regression models were fit in R (R Core Team, 2022). Four models were fit with two binary outcomes denoting the presence of either a sole lesion (sole ulcer or sole haemorrhage) or a white line lesion at the early lactation assessment, and explanatory variables from either the pre-calving or post-calving assessments. All variables of interest (SSTT, sole horn thickness, sole temperature, foot angle and heel depth) and potential confounders (farm, parity, body condition score and pre-existing lesions) were offered to the model. RESULTS A smaller SSTT post-calving (OR: 0.75, 95% CI: 0.65– 0.85 p<0.001) was found to increase the odds of cows having a sole lesion in early lactation, this may be a consequence of laxity in the soft tissues of the hoof after calving causing compression of the soft tissue underlying the pedal bone. On average, a smaller SSTT pre-calving also increased the odds of cows having a sole lesion in early lactation but there was an interaction with parity whereby first and second parity animals had a decreasing likelihood of sole lesions as SSTT decreased, but older cows had a weak trend in the opposite direction representing a slightly increased likelihood of sole lesions with a greater SSTT. The composition of SSTT changes with age and cases of previous CHDLs, therefore in older cows the overall depth of the sole soft tissues may be less influential on future sole lesion risk, and it is possible that less functional digital cushions may have a greater overall depth. No association was found between SSTT and the development of white line lesions. The odds of a sole lesion were slightly increased with higher sole temperatures post-calving (OR: 1.03, 95% CI: 1.02–1.05, p <0.001) and the odds of a white line lesion were increased with higher sole temperatures pre- (OR: 1.04, 95% CI: 1.01–1.07, p=0.016) and post-calving (OR: 0.97, 95% CI: 0.94–

CATTLE PRACTICE VOLUME 31 PART 1 2023 81 1.00, p=0.031). It should be noted that although the effect size was small, an interaction with parity was present in the pre-calving sole lesion model, whereby first parity heifers had the strongest trend, whereas older animals showed little change. This result may reflect how different management of heifers pre-calving compared to cows may result in greater increases in sole temperatures, and which are also associated with an increased risk of future sole lesions. Neither foot angle, nor heel depth immediately post-calving were associated with either lesion, which questions the importance of foot shape in prevention of CHDLs. In cows that did not already have a sole lesion, an increased sole horn thickness pre-calving was associated with reduced odds of cows developing sole lesions during early lactation; when a pre-exisiting sole lesion was present the trend was reversed and an increased sole horn thickness was associated with an increased odds of a sole lesion in early lactation. This finding may suggest a sufficiently thick sole has a protective effect in healthy claws, but increased sole horn thickness may be a consequence of reduced wear caused by previous lesions, and therefore this could also reflect the recognised risk of lesion recurrence. An increased sole horn thickness post-calving, regardless of lesion status, was associated with a reduced likelihood of developing a sole lesion (OR: 0.88, 95% CI: 0.83–0.92, p<0.001), highlighting the importance of maintaining adequate sole horn thickness when foot trimming cows prior to drying off. CONCLUSION The results presented here suggest that white line and sole lesions have different risk factors in terms of foot anatomy and structure, and this may indicates these lesions have a different aetiopathogenesis. This study has confirmed the association of the size of sole soft tissues with the development of sole lesions and has also challenged the belief that foot angle and heel depth are important conformation traits in the development of CHDL whilst highlighting the importance of sole horn thickness. REFERENCES Ferguson, J.D., Galligan, D.T., Thomsen, N. (1994) Principal Descriptors of Body Condition Score in Holstein Cows. J. Dairy Sci. 77: 2695–2703. doi:10.3168/jds.S0022-0302(94)77212-X. R Core Team. 2022. R: A Language and Environment for Statistical Computing. Schneider, C.A., Rasband, W.S., Eliceiri, K.W. (2012) NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9: 671–675. doi:10.1038/nmeth.2089.

CATTLE PRACTICE VOLUME 31 PART 1 2023 82 Validation of a fully automated optical system for cattle lameness detection Siachos, N., Anagnostopoulos, A., Griffiths, B.E., Neary, J., Smith, R.F., Oikonomou, G., Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE OBJECTIVES Consistent monitoring and early intervention are key to lameness management in modern dairy herds. The objective of this study was to evaluate the performance of an automated lameness detection system (CattleEye Ltd) which is using a 2D surveillance camera placed over an exit race and generates mobility scores via a machine learning algorithm. MATERIALS AND METHODS Four experienced veterinarians (VETs) performed a total of 29 whole-herd mobility scoring sessions in 8 medium to large-size herds using the 4-grade (0-3) AHDB mobility scoring method. The weekly average score for each cow provided by the system (CE) was also stored and analysed after the end of the study. A total of 27,082 mobility scores were collected and matched to the weekly average CE scores. Agreement between CE and each VET was assessed for the binary transformed scores (non-lame: 0,1; lame: 2,3) using percentage agreement (PA), kappa (κ) and Gwet’s coefficients (AC). Moreover, the same VET was present in 17 foot trimming sessions in 3 farms and recorded the presence and graded the severity of any sole haemorrhage (SH), sole ulcer (SU), white line disease (WL), toe ulcer (TU), digital dermatitis (DD) and interdigital phlegmon (IP) cases in all four feet. Lesion records were then matched with the weekly average CE scores, resulting in a dataset of 991 cows. The same VET also mobility scored a subset of 340 cows in 2 farms 1-3 days before foot trimming. Accuracy (ACC), sensitivity (SE) and specificity (SP) were calculated for both CE and the VET; presence (binary) of at least one case of SU grade ≥ 2, WL grade 3, TU, stage M2 of DD and IP grade 2, was used as the gold standard. Finally, individual daily CE scores covering a period of 90 days prior to the trimming sessions were retrieved. Linear mixed models were used to retrospectively assess the association of the presence of at least one of the aforementioned lesions (PL) with the daily CE scores on a continuous scale (0-100). Binary PL, time, time × PL interaction and farm were fitted as fixed effects and the random effect of each cow was considered for the repeated scores. RESULTS The agreement between CE and VETs in binary mobility scores produced overall PA, κ and AC ranging from 81.5% to 86.3%, from 0.23 to 0.41, and from 0.76 to 0.83, respectively. ACC, SE and SP of CE and VET varied notably among farms, yielding an overall combination of 0.83, 0.40 and 0.88, and 0.80, 0.53 and 0.83, respectively. Finally, continuous CE scores were historically increased in cows with at least one “severe” lesion by an overall difference in estimated marginal means of 9.4 points (95% CI: 7.0-11.7, p<0.001) compared to the non-affected ones. CONCLUSIONS We demonstrated that the agreement between CE and VETs is within the moderate and substantial range, in concordance with that previously reported between experienced human scorers (Anagnostopoulos and others 2022, Linardopoulou and others 2022). Further investigation of farm and cow-level factors that potentially influence the predictive ability of CE in identifying cows bearing foot lesions is needed. The association of historical automated mobility scores with foot lesions creates an opportunity for early intervention before the development of severe pathologies. REFERENCES Anagnostopoulos, A., Griffiths, B., Neary, J., Smith, R., Oikonomou, G. (2022) Initial validation of an intelligent video surveillance system for automatic detection of lameness in dairy cattle. Proceeding of the 31st World Buiatrics Congress, Madrid, Spain, pp. 291-292. Linardopoulou, K., Viora, L., Fioranelli, F., Kernec, J., Abbasi, Q., King, G., Borelli, E., Jonsson, N. (2022) Time-series observations of cattle mobility: accurate label assignment from multiple assessors, and association with lesions detected in the feet. Proceeding of the 31st World Buiatrics Congress, Madrid, Spain, pp. 297.

CATTLE PRACTICE VOLUME 31 PART 1 2023 83 Farm animal careers and perception of ‘fit’ in undergraduate veterinary students: A mixed methods study Payne, E., Morton, E., Lally, C., Remnant, J., University of Nottingham, School of Veterinary, Medicine and Science, Sutton Bonington Campus, Loughborough, LE12 5RD Challenges associated with recruitment and retention of farm vets are reported in the sector. One of the areas to address to overcome these challenges is to the provision of steady supply of skilled veterinary graduates keen to pursue a career in the farm animal sector. Previous research has suggested that a feeling of “fit” is important to undergraduates when considering choosing working within farm animal practice. The aim of this research was to identify whether students feel that they ‘fit’ in farm practice and reasons for their answer. A mixed methods survey was distributed by email at all nine UK vet schools. The survey comprised of three sections: education information; attitudes towards a career in farm animal practice; demographic information. Thematic analysis was performed on the free text responses to the question ‘Taking into account the demographic information you have provided above, to what extent do you agree with the following question: I feel able to pursue a career in farm animal practice. Please explain your answer’. Regression analysis was performed on demographic variables. Thematic analysis identified six themes: career opportunities, nature of farm veterinary work, relationships and interactions, individual experiences, expectations and perceptions, and no perceived barriers. Females, marginalised ethnic groups and those from an urban/suburban background were all identified as having significantly (p<0.05) less agreement with the statement ‘I feel able to pursue a career in farm practice’. This study confirms that biases that exist within wider society do have an influence on veterinary undergraduates' intentions to pursue a farm animal career, with some groups of students being made to feel that they do not ‘fit’. These barriers help to fuel issues pertaining to recruitment and retention within the farm animal veterinary sector. Urgent action is required to address this and improve inclusivity in the farm animal veterinary sector. As a profession, we should be promoting acceptance, openness and an inclusive, diverse and accessible population of role models for our undergraduate to aspire to emulate.

CATTLE PRACTICE VOLUME 31 PART 1 2023 84 Veterinary student competence and confidence in calving cows after simulator training in a blended learning approach Orr, J.1 , Kelly, R.1 , Carmichael, M.M.2,3, 1 School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, G61 1QH 2 The Royal (Dick) School of Veterinary Studies, Easter Bush Campus, Midlothian, EH25 9RG 3 CVS Group, CVS House, Owen Road, Diss, Norfolk, IP22 4ER BACKGROUND New graduates are challenged by out of hours emergency calvings and thus may not consider farm animal practice. Case exposure and practice opportunities are limited during the veterinary undergraduate programme including Extra Mural Studies (EMS) (RCVS 2021). However, many of the veterinary accrediting bodies state that calving a cow is a Day One Competence (Molgaard and others 2018, ECCVT 2019, Salisbury and others 2019, RCVS 2022). Simulators to teach large animal reproductive skills have been successfully used in veterinary education (Baillie and others 2005, Nagel and others 2015, Ferreira and others 2021, Anderson and others 2021), but evidence for calving simulators and their successful integration into the curriculum together with online material representing a blended approach is very limited. AIMS • Establish what students are concerned about and what they look forward to when considering calving cows. • Investigate the success of a high-fidelity calving simulator (using a blended approach) on student confidence levels (CONF) and practical skill competence (COMP) in calving a cow, as well as students’ opinions on what would improve both. • Investigate the relationship between CONF and COMP. MATERIALS AND METHODS Over three academic years (2016-2018), and before any practical bovine obstetrical teaching, 300 fourth year veterinary students at the University of Glasgow were asked to complete a questionnaire containing: 1. Student characterisation questions (gender, age, continent of origin, calving experience levels and intention following graduation). 2. Calving CONF which was self-assessed on a scale of 1-5 (highest) for 13 specific calving tasks (e.g. assessing for room, extracting the calf). Free text response questions in relation to calving cows asking students what they were concerned about, what they looked forward to and what they felt would increase their CONF and COMP. Students were then allocated to one of four teaching groups: lectures only (delivered in previous years, LEC, n=60), online video material on calving using a high-fidelity simulator (computer assisted learning, CAL, n=59), calving practical for 1.5 hours with the high-fidelity simulator (SIM, n=96), and the blended approach, SIM with CAL preparation before the practical, (CAL&SIM, n=85). After teaching delivery, students completed a second questionnaire to again self-rate their calving skill CONF levels, and student COMP was assessed in a formative practical assessment in the format of a calving skill Observed Structured Clinical Exam (OSCE). Chi square, ANOVA, Mann-Whitney and multiple logistic regression statistical methods were used to determine any effects of teaching group and student characteristics on CONF and COMP. Free text responses were analysed using thematic analysis. RESULTS The student demographic was typical of a UK veterinary school (with international accreditation), 77.3% were female, and over half of the students were European (54%), 32% North American and 12% Asian. Sixty eight percent of students declared some or even lots of calving experience, while only 42% would be predicted to encounter a cow calving based on their career intention following graduation. Although students looked forward to calving as a rewarding experience, improving animal welfare or using practical skills, they had three main worries, themselves (lack of their

CATTLE PRACTICE VOLUME 31 PART 1 2023 85 own practical ability, making mistakes in decision making, often to do with size of calf), the animals (suffering, complications, causing harm), and the farmer (not getting help from the farmer or a negative farmer-vet interaction). For students in the LEC group there was no difference in the mean calving CONF score before and after the 3.5 week experimental period (before 34.8 (95% CI 32.6–37.0), after 33.5, 95% CI 31.3– 35.7, p>0.05). For students that were allocated to further teaching, mean calving CONF was 34.2 (95% CI 33.1-35.3) out of 65 before teaching, increasing to 41.3 (95% CI 40.2–42.3) after further teaching was delivered (p<0.05). Significant increases in the after teaching CONF score were seen for the SIM and CAL&SIM groups (SIM by 19% and CAL&SIM by 21%, p<0.05). Only the SIM practical, alone and particularly with the videos as preparation (CAL&SIM) enhanced the likelihood of being categorised as having some calving confidence (SIM odds ratio of 11, CAL&SIM odds ratio of 18.4 compared with LEC, p <0.05). In contrast, even the CAL increased the proportion of calving OSCE pass and excellent students compared with the LEC students (CAL 73%, LEC 40%, p<0.05) with further increases in the pass rate in the SIM (84%) and CAL&SIM (87%) groups. Only the teaching group and, to a much smaller extent, peer assessors or external staff as OSCE assessors increased the odds of passing the OSCE, with the greatest increase observed after the blended approach (CAL&SIM, odds ratio of 11.5 compared to LEC, p <0.05). Most students felt that additional practical experience would improve their CONF and COMP. In support of the important role of student confidence in carrying out calving tasks, results indicated that when students had not received SIM training but had self-rated as confident, they tended to have a higher OSCE pass rate (p<0.1). Experience of the practical abolished any effects of higher confidence. CONCLUSION Implementation of a SIM practical to teach students how to calve cows raises self-assessed student CONF and increases their COMP, particularly as part of a blended learning approach together with the demonstration videos. Video resources alone have a place for increasing COMP. The magnitude and significance of these SIM-induced CONF and COMP boosting effects during real calving scenarios, and impact on cow/calf health and welfare, still warrants further investigation, particularly as veterinary clinical students themselves identify exactly these themes as priorities and reasons for their training. This study highlights the importance of students being involved in calvings while on EMS to gain positive experiences both in relation to confidence and skills, crucial for practice choice upon graduation. REFERENCES Anderson, S.L., Miller, L., Gibbons, P., Hunt, J.A., Roberson, J., Raines, J.A., Patterson, G., Dascanio, J.J. (2021) Development and validation of a bovine castration model and rubric. Journal of Veterinary Medical Education 48(1): 96–104. https://doi.org/10.3138/JVME.2018-0016 Baillie, S., Crossan, A., Brewster, S., Mellor, D., Reid, S. (2005) Validation of a bovine rectal palpation simulator for training veterinary students. In Studies in health technology and informatics (Vol. 111). http://www.ncbi.nlm.nih.gov/ pubmed/15718694 ECCVT. (2019) List of subjects and Day One Competences. http://www.oie.int/en/for-the-media/onehealth/ Ferreira, M.F., de Araújo Sampaio Lima, R., de Souza Amaral, R. (2021) Practising with an obstetric box and a dummy improves students’ confidence in performing obstetric procedures involving large animals. Veterinary Record, 188(12): no. https://doi.org/10.1002/VETR.57 Molgaard, L.K., Hodgson, J.L., Bok, H.G.J., Chaney, K.P., Ilkiw, J.E., Matthew, S.M., May, S.A., Read, E.K., Rush, B.R., Salisbury, S.K. (2018) AAVMC Working Group on CompetencyBased Veterinary Education. Competency-Based Veterinary Education: Part 1 - CBVE Framework. Washington, DC: Association of American Veterinary Medical Colleges. Nagel, C., Ille, N., Aurich, J., Aurich, C. (2015) Teaching of diagnostic skills in equine gynecology: Simulator-based training versus schooling on live horses. Theriogenology, 84(7): 1088–1095. https://doi.org/10.1016/j. theriogenology.2015.06.007 RCVS. (2021) The Future of EMS - Report of Stakeholder Day - Professionals. https://www.rcvs.org.uk/news-and-views/ publications/the-future-of-ems-report-of-stakeholder-day/ RCVS. (2022) RCVS Day One Competences. https://www. rcvs.org.uk/news-and-views/publications/rcvs-day-onecompetences-feb-2022/ Salisbury, S.K., Chaney, K.P., Ilkiw, J.E., Read, E.K., Rush, B.R., Bok, H.G.J., Danielson, J.A., Hodgson, J.L., Matthew, S.M., May, S.A., Molgaard, L.K. (2019) Competency-Based Veterinary Education: Part 3 - Milestones.

CATTLE PRACTICE VOLUME 31 PART 1 2023 86 How WhatsApp client communication can save time, improve cash flow and reduce phone calls Samuel, S., Vets Digital, PO BOX 727, Fareham, PO14 9QT In this lecture, we will delve into the transformative power of digital communication in the farm veterinary sector. We will explore how the integration of popular platforms such as WhatsApp, Facebook Messenger, Instagram, Apple pay and Google Pay has revolutionised the way farm vets interact with farmers. We will share the most common use cases including seamless product orders, communication of lab results, streamlined visit organisation and digital payments. We will explore how this can be integrated with the Practice Management System (PMS). Digitising farm veterinary communications not only significantly reduce the reliance on traditional phone calls, but it also alleviates team stress and minimises administrative burdens. We will run through practical examples from our extensive first-hand experiences from farm vets currently using this system. We will share success stories, lessons learned, and the positive impact of leveraging digital platforms in farm veterinary practices. We will look at the latest advancements that can transform the way vets and farmers collaborate, enhancing efficiency, communication, and overall client satisfaction.

CATTLE PRACTICE VOLUME 31 PART 1 2023 87 How your website and digital platforms can help you with recruitment Aveston, H., Vets Digital, PO BOX 727, Fareham, PO14 9QT In this lecture, we explore the potential of digital marketing in facilitating recruitment efforts for farm vets. Farm veterinary practices face unique challenges when it comes to attracting vets, and this session aims to shed light on how digital marketing strategies can be a game-changer with this. We will look at a range of digital marketing techniques that can effectively enhance farm veterinary recruitment efforts. Attendees will discover the power of social media platforms like LinkedIn, Facebook, and Instagram as valuable tools for showcasing the practice. Through engaging content creation, targeted advertising, and strategic networking, digital marketing can significantly expand the reach and impact of recruitment campaigns. The lecture also highlights the value of leveraging online job boards, professional networking platforms, and industry-specific platforms. The session provides insights into crafting compelling job listings and optimising their visibility on digital platforms. To further empower attendees, the lecture introduces the concept of employer branding and its impact on recruitment success. Building a strong employer brand through digital channels not only helps attract top talent but also fosters employee retention. Attendees will explore effective strategies for showcasing their practice's values, unique company culture, and professional development opportunities to appeal to prospective candidates. In summary, this lecture illuminates the immense potential of digital marketing in revolutionising farm veterinary recruitment. By harnessing the power of social media, online job boards, and employer branding, attendees will leave with actionable insights and strategies to effectively navigate this challenging problem.

CATTLE PRACTICE VOLUME 31 PART 1 2023 88 BVD diagnosis – that’s always straightforward! What could possibly go wrong? McCormick, I., Carty, H., SRUC Vet Services, Greycrook, St Boswells, Roxburghshire, TD6 0EQ The Animal Health and Welfare Pathway is now being rolled out to farms in England, starting with Annual Health and Welfare Reviews - funded vet visits focusing on BVD management. The path to BVD eradication is not always straightforward in terms of the diagnostic challenges that can present; what could English vets learn from Scotland’s BVD Eradication Scheme and the progress of the current phase 5 of the scheme? After a period of voluntary testing, Scotland introduced a compulsory BVD eradication scheme in 2013. At this point, the BVD level was estimated at 40 per cent (BVD Not-Negative herds). 8.8 per cent of holdings are now classified as BVD Not Negative, which shows how progress can be made using a compulsory eradication scheme to decrease an endemic cattle disease such as BVD. This workshop will cover the diagnostic challenges that can prevent progress with BVD eradication on both beef and dairy farms. We will cover some of the common stumbling blocks with BVD diagnostics and give tips on addressing them with some interactive case scenarios. We will also cover the progress of phase 5 of the eradication scheme. What barriers have been encountered to reducing the number of PIs to zero? How to help non-engaging clients. What are the dangers of invertedly purchasing a ‘Trojan Cow’, and how is best to advise our farm clients if this happens? How did other countries eradicate BVD, and what barriers did they encounter? Ninety minutes of BVD fun with two of SRUC’s experienced VIOs with 43 collective years’ worth of BVD experience!

CATTLE PRACTICE VOLUME 31 PART 1 2023 89 A Client’s calves have pneumonia again – why? Swinson, V., Florea, L., APHA Thirsk, West House, Station Road, Thirsk, YO7 1PZ Bovine respiratory disease (BRD) continues to be a common diagnosis despite increased knowledge for this disease syndrome, the increased use of vaccines, and the ongoing advice to farmers on prevention and herd health planning. BRD also continues to be one of the main drivers of antimicrobial use, particularly in the beef sector; in addition to impacting productivity and the carbon footprint of the cattle sector. This workshop will give an overview of BRD investigation and will discuss investigation of the possible reasons behind, and management for, long-term BRD issues on farms. This workshop will describe, and encourage discussion on: 1. The most effective methods of investigating respiratory disease – to cover: • blood sampling (single vs paired) • swabbing (nasopharyngeal vs nasal) • bronchioalveolar lavage (BAL) • postmortem examination • equipment/sampling kit • media • culture 2. Getting the most from testing (in acute phase vs historical). 3. Laboratory testing – choice of tests and test packages. 4. Wider picture – are there other disease processes involved in this animal? How does the investigation of your client’s case fit into the wider picture? 5. Histopathology – how does this add value? 6. How the information gained from investigation can be used to help in discussions about herd health planning with clients – vaccination and management. 7. Antimicrobial stewardship in relation to respiratory disease – whether the use of antimicrobials is appropriate, and discussion of susceptibility testing. 8. Respiratory tract microbiomes – are there other microorganisms that might affect susceptibility to the primary pathogens. 9. New or less well recognised pathogens – recent work on bovine mycoplasmas and viral pathogens. 10. Other considerations for grazing cattle – such as lungworm, fog fever, interstitial pneumonia, chronic carriage of pathogens.

CATTLE PRACTICE VOLUME 31 PART 1 2023 90 Using REMEDY to Model Dairy Enterprise Carbon Footprints Can, R,1 , Hyde, R.1 , Clifton, R.1 , Thompson, J.1 , Barden, M.1 , Glover, I.1,2, Manning, A.2 , Bradley, A.J.1,2, Green, M.J.1 , O’Grady, L.1 , 1 School of Veterinary Medicine & Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD 2 Quality Milk Management Services Ltd, Cedar Barn, Easton, Wells, Somerset, BA5 1DU Modern dairy herds have access to increasing amounts of information about their cows, their productivity and health status, but the ability to process, optimise and maximise the value of this data is often compromised by a lack of time, necessary skills and appropriate software platforms. This workshop will introduce delegates to the new on-line platform (REMEDY - REal time DairY), developed with support from InnovateUK, which will allow farmers and their advisers to use the latest, self-updating machine learning algorithms to model and predict both cow and herd level outcomes. The project has engaged a number of industry partners and a group of approximately twenty co-developing farmers with the aim of developing a platform to fill perceived inadequacies in dairy data handing and processing. This workshop will have a particular emphasis on the use of REMEDY for assessing and modelling carbon footprints. We will outline the approach to Life Cycle Analysis (LCA) in diary enterprises and using actual herd examples demonstrate how the platform can be used to model the impact of management decisions and animal health on carbon footprint and farm efficiency and sustainability. Delegates will be able to interact with the platform and question those involved in its development

CATTLE PRACTICE VOLUME 31 PART 1 2023 91 Bridging the gap – thinking big picture to improve the effectiveness of your veterinary services go? Reyneke, R., University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD The aim of every practitioner is to work to help improve the health, welfare and productivity of the animals on our farms. Unfortunately, we are frequently faced with circumstances where we offer relevant, evidencebased advice, sometimes repeatedly, yet this advice is sometimes not actioned resulting in few changes on farm. However, it is not just our clients that are guilty of failing to make changes; there are likely to be many examples where we ourselves are aware of what we ‘should’ be doing but are failing to change our own behaviours. How many of us as members of the public can say that we follow the evidence-based recomendation of eating at least five portions of fruit and vegetables a day? The challenge is human behaviour change. Traditionally, when we have looked to influence on farm practices, the focus has been on education and knowledge transfer. Whilst this can be valuable, it is not surprising that knowledge transfer alone is insufficient in many circumstances – changing behaviour is complex and relies on more than simply knowing or understanding the correct behaviour. This gap between ‘knowing’ and ‘doing’ is recognised in many fields, including human healthcare. It is from here the field of implementation science was created with the intent to bridge this gap - to improve the uptake of evidence-based practices in order to improve health (Eccles and Mittman 2006). Since its inception almost two decades ago, implementation science has been successfully used in human healthcare and has also been adopted by other fields such as education and criminal justice (Gleicher 2017, Moir 2018). Despite its clear potential, it is currently underutilised in veterinary medicine. This workshop will provide an introduction to the potential offered by utilising existing theories, models and frameworks to improve the uptake of recommended practices. Attendees will leave not only with the understanding of the potential scope of this approach, but most significantly will be familiar with examples of frameworks and practical approaches to using these tools to overcome the challenges faced in going from ‘knowing’ to ‘doing’. Following a brief introduction, there will be an interactive discussion which will focus on taking attendees through examples of these frameworks. Attendees will breakout into small groups to discuss potential circumstances for applying this approach and to work through the practical application of a framework. A final whole group discussion will bring these learnings together and provide practical ideas and strategies of where and how these frameworks could be utilised. Attendees will be in a position to return to practice and apply the principles learned to improve uptake of evidence-based practices, as well as be aware of the wider potential offered by the field. Attendees will also have the opportunity to learn about the ongoing research in this area focusing on using these approaches on farm, with the potential to become more involved if of interest. REFERENCES Eccles, M.P., Mittman, B.S. (2006) Welcome to Implementation Science, Implementation Science 1: 1 Gleicher, L. (2017) Implementation science in criminal justice: How implementation of evidence-based programs and practices affects outcomes [Online]. Available: https://icjia. illinois.gov/researchhub/articles/implementation-sciencein-criminal-justice-how-implementation-of-evidence-basedprograms-and-practices-affects-outcomes [Accessed 25 May 2022]. Moir, T. (2018) Why Is Implementation Science Important for Intervention Design and Evaluation Within Educational Settings? Frontiers in Education 3: doi:10.3389/ feduc.2018.00061

CATTLE PRACTICE VOLUME 31 PART 1 2023 92 Interpreting results from automatic lameness detection systems Randall, L., Hyde, R., University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD Early detection and prompt effective treatment has been highlighted to be critical to the management of lameness in dairy herds by dramatically improving cure rates (Groenvelt 2014; Leach 2012). It is therefore key that methods used to detect lameness in dairy cows can not only achieve this early on in the development of lameness, but this can also be achieved reliably. Whilst visual assessment using mobility scoring is currently the mainstay of lameness detection, automated lameness detection methods are also commercially available such as the use of computer algorithms paired with CCTV cameras to automatically diagnose lameness. With the adoption of automated lameness detection methods on dairy farms the opportunity arises to utilise the data generated in different ways which raises questions around how we use and interpret lameness data. Using worked examples this workshop will aim to address questions relating to assessing the performance metrics of lameness detection methods and how to use and interpret data generated by automated systems. There are great opportunities for the modern farm animal veterinarian to leverage advances in technology to improve animal health, welfare and production through the use of automatic lameness monitoring systems. To provide a quality service to their farmers, it is crucial that production animal veterinarians are able to understand and interpret the results from automatic lameness monitoring systems, and this workshop aims to provide veterinarians with these critical skills. Topics covered will include; • The rationales for the importance of early detection and prompt effective treatment. • Background to lameness detection methods. • Background to performance metrics and interpretation using worked examples. • Discussions relating to using and interpreting lameness data including data generated by automated systems. REFERENCES Groenevelt, M., Main, D.C., Tisdall, D., Knowles, T.G., Bell, N.J. (2014) Measuring the response to therapeutic foot trimming in dairy cows with fortnightly lameness scoring. Vet. J. 201(3): 283-8. doi: 10.1016/j.tvjl.2014.05.017. Epub 2014 May 16. PMID: 24881511. Leach, K.A., Tisdall, D.A., Bell, N.J., Main, D.C., Green, L.E. (2012) The effects of early treatment for hindlimb lameness in dairy cows on four commercial UK farms. Vet. J. 193(3): 626- 32. doi: 10.1016/j.tvjl.2012.06.043. Epub 2012 Aug 11. PMID: 22884565.

CATTLE PRACTICE VOLUME 31 PART 1 2023 93 Getting started with Dynamic Health Planning in practice Geraghty, T., SRUC Vet Services Aberdeen, Mill of Craibstone, Craibstone Estate, AB21 9TB Dynamic Health Planning is a structured process of optimising health risk management on seasonal beef and sheep farms. The core elements of Dynamic Health Planning are: • A pro-active process working to achieve defined economic output targets. • A team activity with collective responsibility for success and completion. • A continuous improvement process with periodic review ahead of each key risk period. The benefits of Dynamic Health Planning to the farm are increased output and reduced health risk exposure. For vet practices, the process aims to be a very time-efficient method that meets mandatory ‘health plan’ requirements (e.g. from Red Tractor, QMS or others) while increasing sales of preventative products and services and delivering better outcomes for clients engaged with health planning. Over the production year 2022-23 we have been trialling Dynamic Health Planning in practice with the help of Lee-Anne from The Fold Farm Vets (Northumberland), Ed from Thrums Vets (Angus) and Ali from The Stewartry Vet Centre (Castle Douglas). This workshop will cover the principles and practicalities of Dynamic Health Planning for busy practitioners. Come along to find out if this process could be of benefit to you and your beef and sheep clients.

CATTLE PRACTICE VOLUME 31 PART 1 2023 94 Can we predict the probability of a cow calving in with a high SCC? Thompson, J.1 , Green, M.1 , Hyde, R.1 , Bradley, A.2 , O’Grady, L.1 , 1 School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD 2 Quality Milk Management Services, Cedar Barn, Easton Hill, Wells, BA5 1DU INTRODUCTION Udder health is crucial to the productivity and longevity of dairy cows. Antibiotic usage, economic losses and pain can all be reduced by preventing mastitis on farm, which therefore remains a priority for the dairy industry. The dry period provides an opportunity to manage udder health by curing existing intra-mammary infections. However, it can also be a high-risk time for new intra-mammary infections. Preventive strategies, for example the Mastitis Control Plan, have aided improvements to herd health through understanding epidemiological patterns using clinical mastitis events and milk recording data. Electronic recording of data is intensifying in dairy systems and becoming more accessible. The use of Machine Learning (ML) has created the opportunity to extract greater value from cow-level data to inform decision-making. The aim of this research was to use routinely collected farm data to construct a machine learning model that makes probabilistic predictions at drying off for an individual cow risk of a raised somatic cell count post-calving. MATERIALS AND METHODS This research was undertaken with ethical approval from the University of Nottingham. Anonymised data were obtained as a convenience sample from 108 UK dairy herds which undertook regular milk recording. Data included anonymised farm and cow identifiers, parity, dry-off and calving dates, milk recording dates, somatic cell counts (SCC), milk parameters (yield/fat%/protein%), dry-off dates and clinical mastitis event records. Data were cleaned to remove incomplete or erroneous data. Predictor variables were engineered based on biological plausibility and of potential importance for prediction of SCC status post-calving. The outcome measure evaluated was presence of a raised somatic cell count in the 30 days postcalving. A machine learning gradient boosting algorithm, XGBoost, was set up on a 56-farm training dataset. Mean Absolute Calibration Error, Scaler Brier Score, and calibration plots were used to evaluate model accuracy and fit. External validation was undertaken on a separate 28-farm test dataset and on a separate dataset of poorer quality (24 herds with substantial missing data). RESULTS A machine learning algorithm has been developed to produce probabilities for the risk of a cow calving in with a raised SCC in the 30 days post-calving, with a high degree of calibration certainty. A key variable that contributed to the prediction was historic herd level new dry period IMI rates but infection status prior to dry off was poorly predictive. This suggests that management across the dry period should be a key focus area for achieving better udder health, whether that be for cows eligible for curing over the dry period or for potential dry-period new infections. The three main SCC parameters from the lactation prior to outcome which impacted upon model probability predictions were median SCC, the mean of the first three SCCs, and the percentage of SCCs less than 50,000cells/ml. Statistical assessment of calibration for the external dataset returned a Scaled Brier Score of 0.095 and a Mean Absolute Calibration Error of 0.009. Models tested on both training and test datasets calibrated well, indicating that the risk of a raised somatic cell count post-calving was well differentiated between cows. From the final models it was evident that the herd new intramammary infection rate during the dry period was a key driver of the probability that a cow had a raised SCC post-calving. CONCLUSION In conclusion, this research has determined that probabilistic classification of the risk of a raised SCC in the 30 days post-calving is achievable with a high degree of accuracy, using routinely collected farm data. These predicted probabilities provide the opportunity to aid farmer decision-making by allowing different management strategies for cows immediately after calving, according to their likelihood of infection.