Cattle Practice October 2023

CATTLE PRACTICE VOLUME 31 PART 1 2023 95 Take home messages: • This research predicts the probability of a cow having an intra-mammary infection post dry-period, using a single model for both cows eligible for a cure or new-infection during this time period. • Management across the dry period was identified as a key feature for achieving better udder health results, both for cows eligible for dry-period cure or dry-period new infections. • Udder health remains a key area for continued improvement in the dairy industry and this model provides farmers with a tool to identify cows at high risk of an intramammary infection post-calving, which will inform decision-making on-farm. • The dairy industry is amassing large datasets, especially through milk recording. This farm and cow specific data can be used alongside machine learning algorithms for predicting future events.

CATTLE PRACTICE VOLUME 31 PART 1 2023 96 Outcomes following cow caesareans: a clinical audit Robinson, N., Henderson, A., Taylor, S., Julian, M., Dean, R., VetPartners Ltd, Spitfire House, Aviator Court, York, YO30 4UZ Cow caesareans are a common surgical procedure, and it is currently unclear whether the way in which they are carried out varies between clinicians, and how this may influence outcomes for both the dam and the calf. The aim of this quality improvement work was to determine how cow caesareans are currently carried out across a large group of practices, as well as tracking short-term survival following the procedure. A clinical audit was designed to collect data on cow caesareans performed across a large group of UK practices. A data collection form was designed through SurveyMonkey, which allowed collection of data on the surgical techniques used and the medications administered. QR codes were placed on surgical kits and autoclaves as a prompt to complete the data collection form for each caesarean performed. The vet performing the procedure was contacted 60 days after the procedure, to find out dam survival at 7 and 60 days post-procedure. Data were transferred into Microsoft Excel for data cleaning, processing and analysis. To continue the Quality Improvement cycle, data were reviewed after one year, and changes made to both the initial data collection form and follow-up questions, in order to gather further information going forward on the reason for caesarean, use of sedation, suturing techniques, survival of the calf, and any post-operative complications. To date, data have been collected on 394 caesareans, with follow-up data collected for 211 of these. Most cows were described as beef cattle (80%) with the remaining 20% described as dairy. Most procedures were performed standing (87%), with 9% recumbent and 4% a mix of standing and recumbent. Sterile gloves were worn in 9% of procedures, while sterile gowns were worn in 32%. Epidurals were used in 57% of caesareans, clenbuterol in 53% of and oxytocin in 65%. All cows received peri-operative systemic antibiotics and 17% also received local antibiotics on the uterus/in the abdomen or on the muscle layer. Almost all (99%) received peri-operative non-steroidal anti-inflammatories. Dam survival at 60 days was positive, with 88% alive at 60 days. Following review of and changes to the initial data collection, additional data were available for 42 caesareans. Of these, fetomaternal disproportion was the most common reason for caesarean (60%), followed by malpresentation (14%) then soft tissue obstruction (12%) with the rest having a caesarean for another reason (14%). After changes to the follow-up data collection, information on calf survival and postoperative complications were available for 47 caesareans. Amongst these, calf survival at 7 days was 73%. One or more post-operative complications were seen in 9 dams (19%), with the most common complication being wound infection (7 dams). A further 2 dams had both metritis and retained foetal membranes. Both dam and calf survival following the caesareans recorded so far are positive. In addition, virtually all cow caesareans are receiving analgesia in the form of non-steroidal anti-inflammatories. There is variation in some aspects of how the procedure was performed and the medications used, highlighting areas in which Quality Improvement activities could focus going forward. Over half of caesareans are carried out due to fetomaternal disproportion, suggesting this may be an area to focus preventative measures in the future.

CATTLE PRACTICE VOLUME 31 PART 1 2023 97 UK Beef Lameness; what we know, what we don’t know and where do we go? Floyd, T., Animal and Plant Health Agency, Pathology Department, Animal and Plant Health Agency, Woodham Lane, Addlestone, KT15 3NB This talk will provide an overview of the pathology associated with and the diagnostic approach to blindness in cattle, using data and examples from the Animal and Plant Health Agency’s scanning surveillance activities. Blindness may be the primary or sole presenting sign in cattle, or it may occur in combination with other neurological signs (e.g. depression or other changes in mentation, disorders of locomotion, seizures etc) or gross pathology (e.g. keratoconjunctivitis, cataracts etc), which may direct the course of diagnostic investigation. Investigation of these cases benefits from careful clinical and neurological examination of the affected animals, along with consideration of other clinico-epidemiological data, such as the onset and progression of signs, number of animals affected, age or stage of production, treatment history and so forth. From a pathogenetic perspective, blindness may be categorised as central (i.e. lesions of the brain) or peripheral (i.e. lesions of the eye or optic nerve). The aetiology of blindness in cattle is broad and varied, and may be divided into toxic, metabolic, degenerative, hereditary and infectious causes. If an accurate diagnosis is to be achieved, all parts of the optic system must be systematically examined and the resultant findings (or the absence of findings) considered in light of the aforementioned clinico-epidemiological data and results of appropriate ancillary testing. This talk will be illustrated by cases from the APHA’s Veterinary Investigation Diagnosis Analysis (VIDA) database, ranging from the common (e.g. cerebrocortical necrosis, CCN), through the less common but important (e.g. closantel toxicity), to the completely novel (e.g. congenital blindness and depression in calves with symmetrical porencephaly of the occipital cortex). We will discuss sampling of the optic system for pathological examination and appropriate sampling for and application of ancillary tests (e.g. bacteriology, virology, toxicology, etc), as may be required to establish a diagnosis.

CATTLE PRACTICE VOLUME 31 PART 1 2023 98 When even the simplest things go wrong – food and drink disasters Murphy, M.A., Animal & Plant Health Agency, West House, Station Road, Thirsk, North Yorkshire, YO7 1PZ This presentation will provide a review of several recent intoxication cases investigated by the APHA, following the exposure of cattle to different chemical agents. The route of exposure in each case was either feed or water. The incidents involve inadvertent ingestion by cattle of farm chemicals/agents used and regularly stored on farms. The clinical presentations and gross findings at post-mortem will be reviewed. In these case the morbidity amongst adult cows often reached 100% with losses of over 50 adult animals in some cases. Whilst uncommon they are striking in their impact for the clients and all those involved. Recommended therapies and interventions where appropriate will be discussed. The provision of advice by involving APHA and SRUC in these incidents ensures immediate and appropriate treatment can be provided to affected animals. There is also the need to address any potential risk to the food chain from residues in the surviving animals and if the involvement of other stake holders is required such as the environment agency. The number of animals involved in such cases can be substantial and rapid and immediate intervention if possible is critical. An awareness that intoxications/poisonings can occur is well established amongst livestock practitioners. However, when they arise the scale of the issue can be overwhelming. So, knowing who to seek expert advice from is important as well as addressing any additional concerns such as food safety and long-term health impacts on the stock.

CATTLE PRACTICE VOLUME 31 PART 1 2023 99 What can liver gene expression tell us about ketosis? Payling, L.1 , Acman, M.1 , Husband, J.2 , Romero, L.1 , 1 Biofractal, Caminho Poço das Pereiras 20, Casa Utopia, 8100-317, Loule, Portugal 2 Map of Ag, Suite 1A, Cumbria House, Gilwilly Road, Penrith, Cumbria, CA11 9FF INTRODUCTION Subclinical ketosis is estimated to cost £115 per case per year (Mostert and others 2018). The average prevalence in dairy cows in the first two weeks postpartum is high, with one large study finding 31% of cows in the UK affected (Berge and Vertenten 2014). At this prevalence, it would cost a 150-cow herd £5300 per year, largely due to prolonged calving intervals and reduced milk production (Mostert and others 2018). Further insights and solutions to this problem would therefore benefit the industry. The liver orchestrates the vast array of metabolic processes that occur during the development of ketosis which is characterised by an elevation in production of ketone bodies. This is achieved through altered expression of genes in the liver, coordinating a physiological response. Understanding the changes in liver gene expression during ketosis can provide precise insights as to the metabolic changes that occur and their consequences for health and performance. This information can improve our understanding of the development of ketosis and highlight novel opportunities for diagnosis, prevention, and treatment. METHODS In the current analysis, publicly available liver gene expression data from Wathes and others (2021) was analysed using pipelines that were curated to provide insights relevant to cow physiology. The data were from 103 Holstein Fresian dairy cows from 4 different farms. Cows were grouped into balanced, intermediate, or imbalanced metabolic status using plasma nonesterified fatty acids (NEFA), β-hydroxybutyrate (BHB), glucose and IGF1 concentrations. Liver biopsies were collected at 14 days in milk and the samples were used for RNA extraction, library preparation, and sequencing. Raw sequencing reads were quality control checked and pre-processed to remove poor quality portions of the reads and unwanted sequences using TrimGalore (Martin 2011). Then, data were aligned to the cow reference genome (Bos Taurus version ARS-UCD1.2) using Kallisto (Bray and others 2016), to provide gene abundances. Gene abundances were normalised to minimise technical variability between counts using DeSeq2. Next, differential gene expression was used in DeSeq2 (Love and others 2014) to quantify and statistically assess the changes in gene expression between intermediate and imbalanced cows compared to balanced cows. RESULTS Compared to balanced cows, there were more than 1,500 genes with altered expression in the liver of intermediate cows (p-adj <0.05). Furthermore, there were more than 1700 genes with altered expression in imbalanced cows compared to balanced cows (p-adj <0.05). Among these genes, those related to very low-density lipoprotein (VLDL), carnitine palmitoyltransferase (CPT), and antioxidant function had different levels of expression among the 3 metabolic groups (p-adj <0.05). Furthermore, known genes associated with ketosis resistance in Holsteins (Kroezen and others 2018) significantly differed in their expression between balanced, intermediate, and imbalanced cows (p-adj <0.05). Differentially expressed genes were related to biological pathways using Biofractal’s pathway activation algorithm based on the expression level and statistical significance of genes, and the pathway topology. In intermediate and imbalanced cows, pathways related to fatty acid metabolism, amino acid metabolism, mitochondrial energy production, and detoxification were activated; however, the catabolism of choline and tryptophan were inhibited compared to balanced cows. Distinct differences between intermediate and imbalanced cows compared to balanced cows were seen in pathways relating to oxidative stress, vitamin metabolism, and immunity. Compared to balanced cows, intermediate cows had activation in detoxification of reactive oxygen species, whereas imbalanced cows had activation in mitochondrial uncoupling, a mechanism to manage oxidative stress. Intermediate cows also showed activation in the metabolism of water-soluble vitamins and innate immunity, which was not present in imbalanced cows (p-adj <0.0001).

CATTLE PRACTICE VOLUME 31 PART 1 2023 100 CONCLUSIONS The analysis suggested a clear distinction in liver function between balanced, intermediate, and imbalanced cows. Both intermediate and imbalanced cows appeared to be utilising more fat and amino acids and less carbohydrate compared to balanced cows. However, intermediate cows showed activated innate immunity and watersoluble vitamin metabolism, which was not activated in imbalanced cows. Finally, intermediate and imbalanced cows appeared to employ different strategies for managing oxidative stress in the liver. The results demonstrated that the expression of some genes were positively correlated with the development of ketosis, and these could be good markers for diagnosis. However, other genes represented distinct physiology between intermediate and imbalanced cows, which may warrant different nutritional and management strategies for different stages of ketosis. REFERENCES Berge, A.C., Vertenten, G. (2014) A field study to determine the prevalence, dairy herd management systems, and fresh cow clinical conditions associated with ketosis in western European dairy herds. Journal of dairy science 97(4): 2145– 2154. https://doi.org/10.3168/jds.2013-7163 Bray, N.L., Pimentel, H., Melsted, P., Pachter, L. (2016) Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology 34(5): 525–527. https://doi.org/10.1038/ nbt.3519 Kroezen, V., Schenkel, F.S., Miglior, F., Baes, C.F., Squires, E.J. (2018) Candidate gene association analyses for ketosis resistance in Holsteins. Journal of dairy science 101(6): 5240–5249. https://doi.org/10.3168/jds.2017-13374 Love, M.I., Huber, W., Anders, S. (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15(12): https://doi. org/10.1186/s13059-014-0550-8 Martin, M. (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.Journal 17(1): 10. https://doi.org/10.14806/ej.17.1.200 Mostert, P.F., Bokkers, E.A.M., van Middelaar, C.E., Hogeveen, H., de Boer, I.J.M. (2018) Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model. Animal : an international journal of animal bioscience 12(1): 145–154. https://doi. org/10.1017/S1751731117001306 Wathes, D.C., Cheng, Z., Salavati, M., Buggiotti, L., Takeda, H., Tang, L., Becker, F., Ingvartsen, K.I., Ferris, C., Hostens, M., Crowe, M.A., GplusE Consortium (2021) Relationships between metabolic profiles and gene expression in liver and leukocytes of dairy cows in early lactation. Journal of dairy science 104(3): 3596–3616. https://doi.org/10.3168/jds.2020- 19165

CATTLE PRACTICE VOLUME 31 PART 1 2023 101 Bovine Respiratory Coronavirus: an important contributor to the Bovine Respiratory Disease Complex Burr, P.1 , Baxter-Smith, K.2 , 1 Biobest Laboratories Ltd, 6 Charles Darwin House, The Edinburgh Technopole, Milton Bridge, EH26 0PY 2 MSD Animal Health, Walton Manor, Walton, Milton Keynes, Buckinghamshire, MK7 7AJ In the UK Bovine Coronavirus (BCoV) has traditionally not been considered a significant contributing pathogen in the Bovine Respiratory Disease (BRD) complex, despite a growing body of evidence worldwide demonstrating both its presence and clinical importance in BRD. This published evidence, the frequent detection of BCoV in samples from calves with BRD, and perhaps recent experience with human coronavirus indicate that the reluctance to consider BCoV a primary respiratory pathogen deserves re-evaluation (Saif and Jung 2020). It is noteworthy that despite the different clinical syndromes associated with BCoV (calf diarrhoea, winter dysentery in adults and pneumonia in cattle of various ages) there is no consistent serological or genetic difference observed between viruses recovered from the different disease presentations (Oma and others 2016). The deletion seen in the evolution of porcine transmissible gastroenteritis virus into porcine respiratory coronavirus is not evident for BCoVs. BCoV has been shown to infect the upper respiratory tract (Soules and others 2022) and is frequently seen in association with other viruses such as BRSV and PI3 and as a precursor to secondary bacterial infection (Rahe and others 2022). Experimentally it has been demonstrated as a primary agent in Bovine Respiratory Disease and can produce clinical signs such as cough, depression, fever and increased respiratory rate. The virus is known to be endemic across European countries on all types of farms and is persistent in the environment and can be spread via fomites such as boots and tyres (WBC 2022). The availability of PCR as the tool of choice for pathogen detection in BRD has meant that (provided BCV is included in the test panel) the presence or absence of BCoV is determined and so its importance can be evaluated. We have undertaken an analysis of over 400 samples from cattle with clinical symptoms or death attributed to BRD submitted to Biobest over the last 2 years to understand the prevalence of this pathogen in clinical cases. BCV was found in 39% of these samples making it the most frequently diagnosed virus of those included in routine testing (IBR 5%, PI3 12%, RSV 22%). While properties of BCoV infection such as extended shedding may increase the potential for its detection above other viruses our results confirm that it is an important pathogen in the UK consistent with results worldwide. A more detailed statistical analysis revealed that key potential pathogens (BCoV, RSV, PI3 and Mycoplasma bovis) were found most frequently during the winter months. Statistically significant relationships (chisquared) were found between infection with Mycoplasma bovis and each of Pasteurella multocida (p<0.01); Histophilus somni (p<0.01), Bovine coronavirus (p=0.01) and Mannheimia hameolytica (p<0.01). Additionally, there were statistically significant relationships between infections with Mannheimia haemolytica and each of Histophilus somni (p=0.04), Pasteurella multocida (p<0.01) and Bovine coronavirus. BCoV was also significantly associated with Parainfluenza virus 3 (p<0.01) infection. As age increased the probability of BCoV and Mannheimia infection decreased. Increased understanding of the importance of BCoV in BRD will require new strategies for pneumonia control. Vaccination for respiratory BCV has previously not been available in the UK (although there has been some evidence that BCV vaccination of dams reduces pneumonia in calves). A new live attenuated intra-nasal vaccine which has been proven to reduce shedding, clinical signs and lung lesions caused by BCoV is expected to be available in the UK in Autumn 2023. This has the potential to be a useful addition to BRD control options (van Rooij and others 2023).

CATTLE PRACTICE VOLUME 31 PART 1 2023 102 REFERENCES Oma, V.S., Tråvén, M., Alenius, S., Myrmel, M., Stokstad, M. (2016) Bovine coronavirus in naturally and experimentally exposed calves; viral shedding and the potential for transmission. Virology Journal 13: 100 Rahe, M.C., Magstadt, D.R., Groeltz-Thrush, J., Gauger, P.C., Zhang, J., Schwartz, K.J., Siepker, C.L. (2022) Bovine coronavirus in the lower respiratory tract of cattle with respiratory disease. J. Vet. Diagn. Invest. 34(3): 482-488 Saif, L.J., Jung, K. (2020) Comparative Pathogenesis of Bovine and Porcine Respiratory Coronaviruses in the Animal Host Species and SARS-CoV-2 in Humans. J. Clin. Microbiol. 58(8): 23 Soules, K.R., Rahe, M.C., Purtle, L., Moeckly, C., Stark, P., Samson, C., Knittel, J.P. (2022) Bovine Coronavirus Infects the Respiratory Tract of Cattle Challenged Intranasally. Front. Vet. Sci. 9: 878240 van Rooij, M.H., Schmitz, M., Meessen, J.M.H., Wouters, P.A.W.M., Vrijenhoek, M.P., Makoschey, B. (2023) Vaccination of calves at day of birth with attenuated vaccines against bovine respiratory syncytial virus, bovine parainfluenza type 3 virus and respiratory bovine coronavirus. Veterinary Vaccine 2(1): 100014 WBC (2022) Prevalence, biosecurity and risk management of Bovine Coronavirus infections on dairy farms in Europe. Berge, Vertenten.

CATTLE PRACTICE VOLUME 31 PART 1 2023 103 Udder Cleft Dermatitis – a Practitioner’s eye view of the condition and approaches to treatment Kerby, M., Synergy Farm Health, The Transmission Hall, Rampisham Business Centre, Rampisham Down, Maiden Newton, Dorset, DT2 0HS UCD (Udder Cleft Dermatitis but also known as Bovine Ulcerative Mammary Dermatitis, Udder Foul, Udder Rot or Udder Intertrigo) is becoming an increasingly recognised skin problem in dairy cows affecting either the fore-udder attachment with the ventral abdominal wall and/or the skin between the two udder halves but particularly between the front two quarters. The lesions vary from mild erythema, small papules, pustules and crusts through to severe areas of skin affected with open wounds, necrotic and malodorous tissue, granulation tissue, pus and blood (Persson Walker and others 2014). Lesion scoring systems have been described (van Werven and others 2018, Ekman and others 2021). UCD may increase the risk of clinical mastitis (Persson Walker and others 2014, Ekman and others 2020) and embolic pneumonia (Millar and others 2017) with the latter featuring more frequently in the APHA Disease Surveillance reports in England and Wales (e.g. May 2021 report). Many practitioners will be familiar with the case presentation of haemorrhage from involvement and invasion of subcutaneous veins. The precise aetiology of UCD has not been elucidated but the lesions have been associated with mange mites (Allenstein 1991), Treponemes (Evans and others 2010) and bacterial colonisation (Sorge and others 2019, Beattie and Taylor 2000) though a Dutch study found no evidence of infection with Treponemes, fungi or mites but did detect the anaerobic bacteria Trueperella pyogenes and Bacteroides pyogenes more often in cattle with severe lesions (van Engelen and others 2021). Cow-related factors such as udder conformation and parity as well as herd-level environmental factors such as yield, type of cubicle base and length of cubicle have been shown to increase the risk and also the severity of UCD (Bouma and others 2016, Ekman and others 2018). UCD has been found on 80% of Dutch dairy farms , with herd prevalence’s ranging from 22 to 51% (Ekman and others 2018). The prevalence in the UK is currently unknown but personal observations in the field by the author using a mirror or iPhone on a stick in the milking parlour suggest figures similar to the Dutch findings. UCD-lesions heal poorly and show similarities to human pressure ulcers; both show delayed healing, which is a consequence of cellular and molecular imbalance in the wound. The size of the wound has an effect on the likelihood of improvement, it is therefore important to detect and treat lesions early, though these are poorly recognised by herdspeople and their potential importance not recognised. Scientific research into treatment options for UCD in dairy cows is limited. A randomised clinical trial by Van Werven and others (2018) reported no effect of treating mild lesions with a barrier film. Daily treatment of more severe lesions with an enzyme alginogel (used in human medicine) for 12 weeks resulted in a 3.4 times more likelihood to improve compared with an untreated control group, but less than 10% of lesions healed completely during the 12 week treatment period. A study in Swedish dairy herds by Ekman and others (2021) used a topical spray containing chelated copper and zinc for 14 days or 28 days depending on response but found no difference in improvement of UCD status on day 56 after treatment started compared to untreated controls. They did, however, see a higher proportion of treated cows that went from mild to severe during the first 2 weeks of the study compared with untreated controls and a numerically, but not statistically significant, higher proportion of treated cows that went from severe to mild or no UCD during the last 4 weeks of the study (between day 28 and day 56). In contrast , a non-peer reviewed Dutch study using the same topical spray in 2020 showed some efficacy: 18 out of 22 with mild UCD experienced complete healing of the lesion, with a median time to this observation of 4 weeks (range 1-11 weeks), whilst 10 out of 12 with severe UCD showed improvement, of which 1 animal completely healed. The median time to first improvement was 5 weeks, with a range of 1-10 weeks (Hesseling and Lammers 2020). Several studies using a liquid barrier dressing containing copper and zinc have been conducted in the last 18 months on 5 farms in the UK, 4 in the South-West and 1 in the East of England. A total of 31 dairy cows

CATTLE PRACTICE VOLUME 31 PART 1 2023 104 with UCD (6 graded mild, 14 graded moderate to severe and 11 graded severe) received weekly applications for a total of 5 weeks with weekly assessment of progress. Of the 156 weekly follow ups, 106 (68%) reported improvement, 27 (17%) showed no change and only 4 (3%) were worse with no observations recorded for 19 (12%). Marked improvements were recorded in malodour, exudate and depth of the lesion. Further studies are on-going looking at applications on Days 0, 2 and 7 followed then weekly until Day 42 and also include applications over both topical Oxytetracycline and topical 2.5% Iodine solution. Provisional results show good improvement rates so far. A full set of data should be available by early Autumn 2023. REFERENCES Allenstein, L.C. (1991) Mites case many of the smelly udder sores. Hoard’s Dairyman. 136: 507 APHA (2021) Disease Surveillancein England and Wales, May 2021 Report 5/12 June 2021. Vet. Rec. 99: 418-419 Beattie, K.G., Taylor, D.E. (2000) An investigation into intertrigo (necrotic dermatitis or "foul udder") in dairy cows Cattle Pract. 8: 377-380 Bouma, A., Nielen, M., van Soest, E.,Sietsma, S., van den Broek, J., Dijkstra, T., van Werven, T. (2016) Longitudinal study of udder cleft dermatitis in 5 Dutch dairy cattle herds J. Dairy Sci. 99: 4487-4495 Ekman, L., Nyman, A.K., Landin, H., Magnusson, U., Persson, Waller, K. (2018) Mild and severe udder cleft dermatitis – prevalence and risk factors in Swedish dairy herds. J. Dairy Sci. 101: 556-571 Ekman, L., Nyman, A.K., Persson Waller, K. (2020) Incidence of udder cleft dermatitis (UCD) in dairy cows and risk factors for transitions to UCD. J. Dairy Sci. 103: 11736-11749 Ekman, L., Nyman, A.K., Persson Waller, K. (2021) Recovery from udder cleft dermatitis in dairy cows. J. Dairy Sci. 104: 3532-3546 Evans, N.J., Timofte, D., Carter, S.D. , Brown, J.M., Scholey, R., Read, D.H., Blowey, R.W. (2010) Association of treponemes with bovine ulcerative mammary dermatitis. Vet. Rec. 166: 532-533 Hesseling, J., Lammers, G. (2020) Prevention of udder cleft dermatitis in dairy cows. 7th October 2020 issue Dairy Global Millar, M., Foster, A., Bradshaw, J.,Turner, A., Blowey, R., Evans, N., Hateley, G. (2017) Embolic pneumonia in adult dairy cattle associated with udder cleft dermatitis. Vet. Rec. 180: 205-206 Persson Waller, K., Bengtsson, M., Nyman, A.K. (2014) Prevalence and risk factors for udder cleft dermatitis in dairy cattle. J. Dairy Sci. 97: 310-318 Sorge, U.S., Binger, E.M., Schefers, J., Plummer, P.J. (2019) Short communication: Metagenomic evaluation of skin biopsies of udder sores in dairy cows. J. Dairy Sci. 102: 11470- 11475 Van Engelen, E., Dijkstra, T., Meertens, N.M., van Werven, T. (2021) Bacterial flora associated with udder cleft dermatitis in Dutch dairy cows. J. Dairy Sci. 104: 728-735 Van Werven, T., Wilmink, J., Sietsma, S., van den Broek, J., Nielen, M. (2018) A randomised clinical trial of topical treatments for mild and severe udder cleft dermatitis in Dutch dairy cows. J. Dairy Sci. 101: 8259-8268

CATTLE PRACTICE VOLUME 31 PART 1 2023 105 Maintaining our reputation, export market and consumer confidence in burgers, chops and steaks Jelley, M.1 , Lovatt, F.2,3, 1 Perkins Lodge Farm, Brington Road, Long Buckby, Northamptonshire, NN6 7NT 2 Flock Health Ltd, Balmer House, Balmer Lane, Eggleston, Barnard Castle, DL12 0AN 3 University of Nottingham, Sutton Bonington Campus, College Road, Loughborough, Leceistershire, LE12 5RD The threat of antimicrobial resistance (AMR) is real. AMR requires a uniform and harmonised approach from the human, environmental and veterinary perspectives if it is to be controlled and managed. Despite the huge progress that has been made with respect to stewarding the use of antibiotics within UK agriculture since 2016, antimicrobial resistance continues to be a threat to modern medicine. Livestock vets and farmers must continue to play their part to ensure responsible antibiotic use, while continuing to protect animal health. Antibiotic use is believed to be low in ruminant production, but without collating the data already held on farm, the sector has been unable to demonstrate this (RUMA 2022). Guidelines around effective antibiotic stewardship in the production of red meat is now commonplace in farm assurance schemes and herd and flock health plans, but there remains more work to do. Consumers are becoming increasingly interested how the meat they buy is produced, with the UK Food Security Report from 2021 showing that they expect it to be safe and accurately labelled. It is animal welfare and sustainability concerns that drive consumer perception (De Araújo and others 2022). With EU nations now mandated to collate antibiotic use in food producing animals, from an export and home market perspective, it has never been more important to increase engagement with farmers around antibiotic stewardship and to utilise all the tools at our disposal to demonstrate the evidence for that. To this end, a whole community of farm animal vets, farmers and practice teams have come together as part of the RCVS Knowledge-led collaborative initiative, Farm Vet Champions (RCVS Knowledge 2023a). Minimal sign-up gives all members of the practice team access to over 20 hours of free-to-access evidence-based CPD and access to the free SMART goals tool to set bespoke targets and monitor progress. Uploading herd and flock data to the Medicine Hub (AHDB 2023) is an essential activity to provide the evidence needed to maintain the reputation of the red meat industry and makes an ideal focus for setting SMART goals. Practice teams who have already made good progress on the journey of improving antimicrobial stewardship may be interested to apply for an Antimicrobial Stewardship Award (RCVS Knowledge 2023b); the deadline for entries is 12th January 2024. PRACTICAL TAKE HOME MESSAGES 1. Check out Farm Vet Champions free-toaccess CPD for all members of the practice team https://rcvsknowledge.org/fvc 2. Sign up farmer clients to the Medicine Hub www.medicinehub.org 3. Consider applying for an Antimicrobial Stewardship Award https://knowledge. rcvs.org.uk/grants/available-grants/amsawards/ RCVS Knowledge is grateful to the SPVS Educational Trust for supporting the BCVA Farm Vet Champion session. REFERENCES AHDB (2023) https://www.medicinehub.org.uk/ [Accessed 22/9/23] De Araújo, P.D., Araújo, W.M.C., Patarata, L., Fraqueza, M.J. (2022) Understanding the main factors that influence consumer quality perception and attitude towards meat and processed meat products. Meat Science 193: Article 108952 RCVS Knowledge (2023a) https://rcvsknowledge.org/fvc [Accessed 22/9/23] RCVS Knowledge (2023b) https://knowledge.rcvs.org.uk/ grants/available-grants/ams-awards/ [Accessed 22/9/23] RUMA (2022) Targets 2021–2024. Available from: https:// www.ruma.org.uk/wp-content/uploads/2022/11/RUMA-TTFReport-2022-FINAL-FINAL.pdf. [Accessed 22/9/23]

CATTLE PRACTICE VOLUME 31 PART 1 2023 106 In practice calf castration antimicrobial use clinical audit Simms, T., The Farm Vets, Hampden Partners Ltd, Anchor Lane, Aylesbury, HP20 1RP BACKGROUND OF THE AUDIT • Surgical castrates can be classed as cleancontaminated surgeries. While the procedure itself is clean, as performed on farm the environment is unavoidably dirty. Many concerns about farm practice are the conditions we are working in and the inability to create a sterile environment. Antibiotics are often used prophylactically in calf castration as a failsafe, rather than treating a current disease. • As an industry we are trying to refine antibiotic use through responsible prescribing. RUMA, Responsible Use of Antimicrobials in Cattle Production 2015. • As a team we identified that prophylactic use of antimicrobials in routine calf castration is inappropriate in some circumstances. • A standard operating procedure (SOP) and therapeutics policy for surgical calf castration (twist & pull) was written for the practice based on the current practice/industry views on therapeutic use while castrating. • RCVS Knowledge surgical checklist and auditing guides were used to assist with the auditing process. • The initial audit was performed to ascertain our current use of antibiotics and pain relief (non-steroidal anti-inflammatories: NSAIDs) while castrating calves. Through auditing we could identify if this is an area where we could potentially reduce antibiotic use. • A maximal level of antibiotic use was predecided prior to data collation, to assess compliance with the SOP (Table 1). • Our practice management system was interrogated for all use of the word “castrate”. The data was filtered to exclude species aside from bovine/calf. Both professional fees and clinical notes were consulted. • The audit was repeated 12 months later to assess further antibiotic use. RESULTS (TABLE 2 AND FIGURE 1) There is a significant difference in antibiotic use between a:b (chi-squared test p<0.05). Percentage Compliance Audit Conclusion Definition 0-25% Poor Compliance Little use of SOP. Little recording. 26-50% Some Compliance Some evidence of SOP use. 51-75% Moderate Compliance Demonstrable use of SOP, use of antibiotics may not be recorded or rationalised. 76-100% Good Compliance Good use of SOP, use of antibiotics rationalised and recorded. Table 1. 2021 2022 Number of “Castrate Visits” 98 81 Number of surgical castrates performed 719 929 Percentage of visits with sufficient clinical notes to analyse 96.94% 96.94% Percentage of castrates administered antibiotics 11.54%a 4.63%b Percentage of castrates not administered antibiotics 88.46% 95.37% Of those prescribed antibiotics, how many had clinical notes supporting the decision 47% 97.67% Percentage of castrates administered NSAIDs 99.86% 100% Compliance Good Good Table 2.

CATTLE PRACTICE VOLUME 31 PART 1 2023 107 TEAM FEEDBACK 2021 • Overall excellent compliance to the SOP, both with antibiotic use and particularly NSAID (99.86%) use. • There was considerable variation between vets in recording the decisions to use antibiotics in different clinical settings - improvements are needed in this area. • Most recorded use of antibiotics was due to use of ligation, for example if the calf was cryptorchid, or the environment was assessed to be “dirty”. • The team discussion led to amendment of the SOP to consider antibiotic use when ligating the spermatic cord in the case of haemorrhage or ligation. An uncomplicated case should not need antibiotic administration. 2022 • There was a large reduction in antibiotic use by 6.91% points compared to 2021. Analysed by the chi-squared statistical test, this reduction has a p value of <0.05, suggesting it could not have happened by random. • NSAID use increased to 100% of castrates. • Recorded reason for antibiotic use increased from 47% to 98% - an excellent improvement in clinical notation. • The most common reasons for antibiotic use were cryptorchid castration, ligation placement and “dirty environment”. • One vet in particular went from not recording data with sporadic antibiotic use to zero antibiotic use. Figure 1. • The 2022 data showed that vets were happier to perform more complicated castrates without antibiotics, such as cryptorchidism or larger castrates with ligation of the spermatic cord, as long as there was communication with the client as to the risks of post operative infection. DISCUSSION • I am immensely proud of my team. We have demonstrated that with knowledge of current levels of antibiotic use and discussion of our prescribing choices, we can make a tangible difference to the reduction and refinement of antibiotic administration. • The data and discussion empowered the team to give justification to farmers about their antibiotic choices, showing that breaking from the norm of “just in case” prophylactic administration is possible. If we are confident in our sterility, technique and success level we can confidently withhold antibiotics. • While we have run multiple farmer meetings on antibiotic use, demonstrating our ability as a team to significantly reduce the need of antibiotics provides a far more powerful message to farmers that antibiotics as a first line treatment is unnecessary. ACKNOWLEDGEMENTS I want to thank all my team for their enthusiasm and drive to want to refine antimicrobial use and their hard work in doing so. RCVS Knowledge is grateful to the SPVS Educational Trust for supporting the BCVA Farm Vet Champion session.

CATTLE PRACTICE VOLUME 31 PART 1 2023 108 Sustainable control of helminth parasites in cattle Williams, D., University of Liverpool, University of Liverpool, Leahurst Campus, Neston, Wirral, CH64 7TE/Control of Worms Sustainably (COWS), Stoneleigh, Kenilworth, CV8 2TL Resistance of bovine gastro-intestinal nematodes to macrocyclic lactones has been reported in UK and resistance to all three major anthelmintic classes including the benzimidazoles and levamisole is reported throughout Europe. Anthelmintic resistance is a major threat to the cattle industry, and it is important to preserve the efficacy of these products for as long as possible until new drugs or vaccines become available. Industry advisory bodies, including COWS (Control of Worms Sustainably https://www.cattleparasites.org. uk) advocate a test before you treat approach to worming young stock and adult cattle. This talk will focus on the best available, current advice around sustainable control of helminth parasites of cattle (gastro-intestinal nematodes, lungworm and liver fluke), new advances in diagnosing infection and what farmers perceive to be some of the major barriers to adopting sustainable control strategies.

CATTLE PRACTICE VOLUME 31 PART 1 2023 109 Why should we give a sh#t about dung beetles? Mann, D., Mann, C., 19 New Road, Bledington, OX7 6UU Dung beetles play an important role in agriculture, from improving soil health to reducing worm burden – with an estimated value in excess of £480 Million to the UK cattle industry alone, its about time we gave these beneficial insects some thought. The presentation will introduce dung beetles found in the UK, discuss their biology, ecology and conservation and consider the benefits of dung beetle activity in an agricultural setting.

CATTLE PRACTICE VOLUME 31 PART 1 2023 110 Bovine Tuberculosis: how do we engage farmers? Sellick, B., George Farm Vets, 18-20 High St, Malmesbury, SN16 9AU Overall trends suggest an improvement in Bovine Tuberculosis (bTB) incidence and prevalence across England and Wales, but for many the reality is somewhat more bleak. Roughly 50% of herds that regain Officially TB Free (OTF) status are non-OTF again within 3 years. This means that despite the changes that have been made to bTB policy over the years, many farmers still live under the constant threat of a bTB breakdown. The implications of this reach far and wide as the disease has a huge impact on mental health and wellbeing, animal health and welfare, financial security, sustainability prospects and much more. Many vets in private practice experience feelings of despondence and helplessness when faced with the issue of bTB. It is often difficult for vets to help their clients as they are challenged with a myriad of obstacles, from slow moving and obstinate government policy to suspicious and disillusioned farmers. This has meant for many years the main role of the private vet has been reduced to carrying out the ‘TB test’. The lack of autonomy for farmers and their private vets has contributed to this change in relationship. The farming community has been left to work with an increasingly under-resourced Animal Plant and Health Agency (APHA) which has resulted in a change in farmer mindsets dominated by frustration and scepticism. In recent years, countrywide initiatives like the TB Advisory Service (TBAS) and the BCVA Accredited TB Veterinary Adviser (BATVA) training have breathed new life into the role of the private vet. Fuelled by the knowledge exchanged through these services and the enthusiasm to make a difference, vets have the opportunity to engage their clients and agricultural communities like never before. This presentation will give attendees the opportunity to: • Examine the risk factors influencing bTB spread. • Review current policy . • Discuss changing farmer behaviours and engaging them with practical bTB control strategies. • Reflect on our role advising on bTB and how this may change in the future.

CATTLE PRACTICE VOLUME 31 PART 1 2023 111 Action plans to improve dairy herd health & welfare and reduce the need for antibiotic use: Examples and discussion Breen, J., Moorhouse, J., Cooper, R., Roberts, J., Baird, G., Husband, J., Map of Ag, Suite 1A, Cumbria House, Gilwilly Road, Penrith, Cumbria, CA11 9FF Dairy farms aligned to higher standards of dairy herd health & welfare are required to have a review from an independent veterinary surgeon with demonstrable expertise in dairy herd health at least annually. Targets and intervention levels are set for all areas of dairy herd health and performance, but particularly for those areas considered to be a “brand risk” for dairy such as calf and cow mortality, lameness prevalence and increased rates of culling and losses in early lactation. In addition, a focus on calf health, foot health, production diseases such as displaced abomasum events and udder health are all likely to impact herd antibiotic use and both this and brand risk topics are important for ALL dairy farms and the dairy industry, regardless of milk buyer. Herds that fall outside current scheme targets are required to engage with their veterinary surgeon and produce appropriate “action plans” to address non-compliances with the particular area(s) of herd health, and these action plans are used as evidence that the herd is working towards improving herd health and welfare. The independent veterinary advisor is tasked with providing some key pointers to both farm and the veterinary surgeon in practice during the audit as well as providing an opinion on the suitability of action plans that are produced. These workshops aim to provide veterinary surgeons with case material to illustrate appropriate approaches to creating action plans to address poor performance across various areas of herd health, particularly calf health, foot health, cow mortality and udder health. Action plans will be discussed in the light of the latest evidence from research wherever possible and the workshops will be informal to encourage discussion amongst attendees. Whilst particularly suited to those veterinary surgeons with clients aligned to higher welfare schemes, these herd health workshops are aimed at all producers.

CATTLE PRACTICE VOLUME 31 PART 1 2023 112 We need to talk about Red Cow Disease! Geraghty, T., SRUC Vet Services Aberdeen, Mill of Craibstone, Craibstone Estate, AB21 9TB Not sure how to advise your clients on managing Red Cow Disease? This workshop is for you! Do you ever find that ‘bug hunting’ leads to narrow conversations with your clients on risk managing infectious disease? In the extreme case it can become case of do we vaccinate or not? This session will open up the conversation to get a broader perspective. We will cover the basic epidemiology of Red Cow Disease* and the factors that influence the economic impact it can have on dairy and beef herds. The session will include consideration of: • Market forces • Strain variance • Risk of entry onto farms • Speed of spread • Detection and diagnosis • Animal resilience The workshop will ensure that delegates will have the required knowledge and understanding of Red Cow Disease to advise their clients on effective risk mitigation strategies in the broadest sense. Come along to find out more! *Red Cow Disease is a fictitious cow disease that represents ALL infectious diseases of cattle.

CATTLE PRACTICE VOLUME 31 PART 1 2023 113 0.396 Estimating prophylactic dry cow therapy use in GB dairy herds Introduction In January 2022, EU legislation banned the prophylactic use of antibiotics in the livestock sector across the EU. While the UK no longer falls under these laws, several UK industry bodies, such as the Responsible Use of Medicines in Agriculture Alliance (RUMA) have commented on the UK’s achievements so far on reducing antibiotic usage and welcome dialogue regarding future UK legislation which may mirror that of the EU. One example of prophylactic use of antibiotics can be seen with dry cow therapy (DCT) for treatment and prevention of intramammary infections. Blanket dry cow therapy (BDCT) involves treating all quarters of all cows with antibiotics versus selective dry cow therapy (SDCT), whereby only specific cows or quarters are treated, based upon evidence of infection, for example high somatic cell count (SCC). Mastitis is one of the most frequently occurring diseases affecting dairy cows in GB, with substantial economic and welfare consequences (AHDB, 2023). Subsequently, treatment and control of mastitis equates to a large proportion of antibiotics used in dairy herds (Boireau et al., 2018). Objectives • To investigate the level of prophylactic dry cow therapy (DCT) within dairy herds in GB. • Use bulk milk somatic cell count (BMSCC) data from NML samples and medicine record data from FarmAssist to calculate an estimated prophylactic dry cow tube usage. Methodology Calculating the prophylactic use of DCT for herds was carried out in two parts: 1. Calculating the number of cows treated with DCT using FarmAssist data (number of adult cows within the herd and dry cow tubes purchased) 2. There is a strong correlation between the BMSCC and the proportion of the herd with high SCC. To estimate the number of cows eligible for DCT we used figures from Hanks and Kossaibati, (2023) to produce the following parameters for the model: a. Adjusted the herd size by a cull rate of 26%. b. Estimated the number of mastitis cases at 25% (assumed 8.3% mastitis rate in last three months of lactation). c. Estimated the number of chronic cows with a repeat SCC >200,000 (based on correlation of high SCC cows and herd BMSCC). For example, a herd of 125 cows was adjusted to 92 after cull rate (26%), 8 cows were estimated as mastitis cases and a further 8 cows estimated as chronic high SCC (herd BMSCC 186,000). Giving 16 cows eligible for DCT. If the herd recorded 80 DC tubes (20 cows received DCT), then the estimated number of cows with prophylactic DCT is 4 (20-16) or 20% (4/20). Amy Blank & Eamon Watson MRCVS, NMR Key Findings Data were analysed for the years 2018 to 2022. The number of herds and cows varied between years from 274 herds in 2018 to 960 in 2022 as the number of herds utilizing the FarmAssist service increased. The average herd size ranged from 239 in 2019 to 262 in 2022 (Table 1). The estimated mean prophylactic use of DCT has remained consistent at approximately one third of cows within the herd receiving DCT prophylactically since 2018, with a slight increase from 2020 (Fig.2). This is reflected in the FarmAssist mean dry cow defined course dose (DCD) which remains stable (Fig.1). 2018 2019 2020 2021 2022 No. of herds 274 536 1,175 1,084 960 Total no. of cows 60,556 115,769 268,177 249,270 218,804 Average herd size 253 239 254 255 262 Table 1 Number of herds, cows, and average herd size by year, 2018 to 2022 Agriculture and Horticulture Development Board (AHDB). 2023. Mastitis is dairy cows. [Online]. AHDB. Available from: Mastitis in dairy cows | AHDB [Accessed 22 March 2023]. Boireau, C., Cazeau, G., Jarrige, N., Calavas, D., Madec, J., Leblond, A., Haenni, M. and Gay, E. 2018. Antimicrobial resistance in bacteria isolated from mastitis in dairy cattle in France, 2006–2016. Journal of Dairy Science, 101 (10), pp. 9451-9462. Hanks, J. and Kossaibati, M. 2023. Key Performance Indicators for the UK national dairy herd. [Online]. University of Reading. Available from: Cow Population Data (panlivestock.com) [Accessed 26 September 2023]. Figure 2 Distribution of estimated mean prophylactic dry cow therapy (DCT) use for herds recorded in FarmAssist by year, 2018 to 2022 Figure 3 Mean total dry cow DCD split into proportion of eligible versus prophylactic use for herds recorded in FarmAssist by year, 2018 to 2022 Figure 1 Mean total dry cow DCD use for herds recorded in FarmAssist by year, 2018 to 2022 Est. mean prophylactic DCT use 33% 33% 37% 36% 2018 2019 2020 2021 2022 Est. eligible proportion of DCT use Est. prophylactic proportion of DCT use 0% DCD 2018 2019 2020 2021 2022 0.0 0.1 0.2 0.3 0.4 0.5 2018 2019 2020 2021 2022 0.372 0.373 0.402 0.403 Over the past five years, antimicrobial usage within the dairy sector has seen a significant decrease, particularly in the use of the highest priority critically important antibiotics (HPCIA), a notable achievement within the industry. Although there has been a reduction in the use of antibiotic dry cow tubes since 2018, dry cow DCD has remained relatively consistent at 0.4 since 2020 (Fig.1). This study suggests there remains a proportion of prophylactic use of DCT. Figure 3 shows the distribution of dry cow DCD by proportion of DCT used in eligible cows versus prophylactic DCT. References 36% This suggests that on farm antimicrobial use may be further controlled by reducing the number of cows receiving prophylactic antibiotic dry cow tubes. On average, eliminating prophylactic use may reduce the dry cow DCD by approximately 36%. To aid in the reduction of prophylactic use, regular SCC testing can be used to help identify cows which do not require antibiotic DCT and where sealant use alone may be appropriate. This is a simplistic and generalised model offering an insight into DCT use and estimated prophylactic DCT. Further work is needed to refine and validate the model within individuals herds. DCD 0.0 0.1 0.2 0.3 0.4 0.5

CATTLE PRACTICE VOLUME 31 PART 1 2023 114 Evaluating the potential of untargeted lipidomic analysis of cow's milk to predict lameness Ana S. Cardoso1, Martin J. Green1, Dong-Hyun Kim2, and Laura V. Randall1 1School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, U.K. 2Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, U.K. Supported by the Biotechnology and Biological Sciences Research Council’s Doctoral Training Programme (BBSRC DTP) (grant number BB/T0083690/1) – Industrial Cooperative Awards in Science & Technology (iCASE) and Agriculture and Horticulture Development Board (AHDB). Conceptualization: A.S.C and L.R. Methodology: A.S.C., L.R, M.G, and D-H.K Investigation: A.S.C. and L.R Resources, D-H.K Formal Analysis, A.S.C and L.R Results Adequate analytical performance of the LC-MS was achieved after principal component analysis (PCA). Apparent trend of separation observed but no clustering identified in the lipidomic profiles of the samples from lame and non-lame cows using orthogonal partial least squares – discriminant analysis (OPLS-DA): Stability selection and Cox method shown to be adequate in identifying the strongest mass ions predictors of lameness compared to conventional regression approaches. Conclusion and Future Work This study provides an important contribution to understanding lipidomic differences between lame and nonlame dairy cows using milk samples, which is the easiest biofluid to collect in dairy farms. Further work is required to increase confidence in the annotation of the lipids identified as potential predictors of lameness. Introduction Lameness in dairy cows seriously affects welfare, production and reproduction indicators, leading to heavy losses for farmers per single case of lameness over a lactation. Cows that previously had a case of lameness face an increased risk of recurrence in the future of developing mild or even severe lameness. Aim To evaluate the potential of untargeted lipidomics analysis of cow milk samples to determine whether lipidomic signatures can be associated with lameness. [email protected] Visual inspection on 67 dairy heifers; AHDB 0-3 mobility scoring scale (scores < 2 were considered nonlame) 56 samples Snap frozen in liquid nitrogen, then stored at -80°C Untargeted lipidomics analysis LC-MS followed by data processing with Compound Discover 3.3 Statistical analysis: - Multivariate Analysis (MVA) - Stabiliser - Cox analysis Early lameness detection Comparing the metabolome of lame with nonlame cows Methods Samples were collected within 3 weeks of post-calving (POST) and at the time of the first case of lameness (AT) based on mobility score. Samples (n=56) were prepared using biphasic extraction for untargeted metabolomics and lipidomics. For this study, only the organic phases were used. LC-MS was performed in a single batch and a pooled quality control (QC) was prepared. Statistical analysis comprised MVA, model triangulation combined with stability selection and the Cox method to assess anomalies and calculate the correlation between all potential variables. R2X=0.489; R2Y=0.419; Q2=-0.237 R2X=0.359; R2Y=0.591; Q2=-0.0408

CATTLE PRACTICE VOLUME 31 PART 1 2023 115 Project FEET: Taking a whole team approach to recognising and treating lameness in dairy cows Emily Craven1, Jenny Stavisky1, Natalie Robinson1 and Rachel Dean1 VetPartners UK Background: Around one third of the national dairy herd is lame at any one time and estimates haven’t changed substantially over the last 20 years. Non-steroidal anti-inflammatory drugs (NSAIDs) have been shown to be helpful in addressing the pain of lameness, but we don’t know that much about how often they’re being used, and how treatment decisions are made. Conclusions: The extent and prevalence of pain due to lameness may be being underestimated and under treated Farmers potentially don’t worry about money as much as we think they do when it comes to lame cows Recognising and utilising the skills of all members of the on-farm foot health team could improve cow welfare and production Aim: To describe how the whole mobility team (farmers, foot trimmers (FTs), veterinary surgeons (vets) and veterinary technicians (VTs): 1. Perceive the pain associated with various conditions that cause lameness in dairy cows, and 2. Make choices about managing these conditions, including when and whether to use NSAIDs Methods: • Online questionnaire (surveymonkey.com) open January-September 2021 distributed widely to VetPartners farm team and beyond (thank you BCVA, NACFT, CEVA and other friends) • Demographic data and pain scoring (1-10) and preferences for using/ recommending NSAIDs for 16 different conditions associated with lameness • Statistical analysis in Excel and SPSS Version 28 (IBM) for further analysis. Mann-Whitney U used to examine differences in non-parametric variables. Significance set at p<0.05. Results: • 210 responses: 81 (38.6%) were farmers, 80 (38.1%) vets, 34 (16.2%) FTs and 15 (7.1%) VTs. • For most conditions, farmers scored pain lower and were less likely to use or recommend NSAIDs than others (Figure1) and farmers rated overall comfort of the cow significantly higher than vets predicted (Mann-Whitney U: 798, p<0.001) (Figure 2). • When considering factors impacting NSAID use farmers rated the importance of cost of drugs to farmers lower than vets though they would (Mann-Whitney U: 4495.5, p<0.001) (Figure 2). • When asked about the proportion of cows lame (AHDB mobility score 2 or 3) at their most recent assessment, most of the responding farmers (45/67, 67.2%) reported less than 10% lameness prevalence • Farmers most commonly reported carrying out mobility scoring themselves (29/79, 36.7%); however only 5% (4/79) reported being RoMS [Register of Mobility Scorers] accredited, as compared with 39.4% (13/33) of FTs and 73.3% (11/15) of VTs. Declarations: Funded by CEVA Animal Health and VetPartners. Ethical review by RCVS Ethical Review Panel, reference #2020 040 Dean Figure 2: Importance of factors in choosing whether to treat a cow with an NSAID Figure 1: Mean pain scores given for conditions/ procedures associated with lameness. IVRA = Intravenous Regional Anaesthesia; DD = Digital Dermatitis 0 2 4 6 8 10 Distal limb fracture Mobility Score 3 cow Digit amputation after IVRA Toe necrosis Foul of the foot White line abscess Sole ulcer Trimming fresh sole ulcer Debriding DD lesion Arthritis ActiveDD Interdigital growth Sole bruising White line bruising Mobility Score 2 cow Overgrown Mean score (1= least pain; 10= claw worst pain) Farmers Vets Foot trimmers Vet techs 0 1 2 3 4 5 6 7 8 9 10 I think it works/ perceived efficacy Overall comfort of cow I think the treatment improves productivity Degree of lameness attributed to condition Degree of perceived pain attributed to condition Milk withhold of drugs Repeated injections required Meat withhold of drugs Pressure from milk buyer Cost of drugs Injection route of drug e.. IM, IV. SC Mean score (1 = least importance/ 10 = most importance) Farmers Vets Vets' perceptions of farmers' priorities

CATTLE PRACTICE VOLUME 31 PART 1 2023 116 FIGURE 1. Percentage of calves testing antibody positive to different respiratory pathogens (n=255). FIGURE 2. Percentage of farms with calves testing antibody positive to different respiratory pathogens (n=51). FIGURE 3. Percentage of farms returning multiple (0-5) positive antibody responses (n=51). FIGURE 4. Proportion of farms with pathogen seropositivity by geographical area (n=51). FIGURE 5. Proportion of farms with pathogen seropositivity by season (n=51). AUTHORS’ AFFILIATION * MSD Animal Health, Walton Manor, Milton Keynes, MK7 7AJ REFERENCE 1. Barrett, D., Veterinary Record (2000) 146 545-550. Bovine Coronavirus, Mannheimia haemolytica and Parainfluenza 3 were the most common pathogens for antibodies to be detected against on farms in Great Britain. 84% of farms had calves with antibodies against three or more different pathogens. There was little geographical variation in seropositivity against the tested pathogens. Serological prevalence of five common Bovine Respiratory Disease (BRD) pathogens in Great Britain BOVINE RESPIRATORY DISEASE (BRD) INTRODUCTION Bovine Respiratory Disease (BRD) is one of the leading causes of calf morbidity and mortality, estimated to cost the UK farming industry £80 million per year.1 It is recognised to be a multifactorial disease requiring a multifaced approach to control. After infection with respiratory pathogens a positive serum antibody response can be detected after 4-6 weeks. Liz Cresswell*, Alexandra Ashworth*, Kat Baxter-Smith*, Rebecca Cole*, Eleanor Rawson* OBJECTIVE To identify the prevalence of seroconversion to different BRD pathogens in order to understand their proportional contribution to BRD in British cattle herds between November 2020 and November 2022. MATERIALS AND METHODS • 255 calves were sampled on 51 different farms selected by convenience sampling across Great Britain. • Five blood samples were taken per farm from unvaccinated calves between 3-6 months of age who were not in the acute stages of respiratory infection. • Enzyme Linked Immunosorbent Assay (ELISA) testing (IDEXX) was undertaken for antibodies against Bovine Coronavirus (BCV), Bovine Respiratory Syncytial Virus (BRSV), Mannheimia haemolytica (MANH), Mycoplasma bovis (MB) and Parainfluenza Virus 3 (PI3). MSD Animal Health Copyright © 2023 Merck & Co., Inc., Rahway, NJ, USA and its affiliates. All rights reserved. UK-NON-230800012 RESULTS Positive antibody responses were most commonly detected against BCV, PI3 and MANH (Fig 1 and 2). 84% of farms returned positive antibody responses to three or more pathogens (Fig 3). There was little variation in the distribution of serological positivity by geographical area (Fig 4). There was some seasonal variation in seropositivity against different pathogens, although low numbers of farms make analysis difficult and further data collection is ongoing (Fig 5). Bovine Coronavirus seropositivity remained high throughout the year, with over 95% of farms tested in spring, summer and winter returning positive results. Bovine Coronavirus was most commonly detected with two other pathogens, with antibodies against MANH and PI3 respectively being detected on 91% of farms which also tested positive for BCV. 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% BCoV BRSV M. haem M. bovis PI3 Key 0 1 2 3 4 5 2% 0% 14% 39% 25% 20% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% BCoV BRSV M. haem M. bovis PI3 90% 100% 80% 70% 60% 50% 40% 30% 20% 10% 0% North (n=18) Scotland (n=10) South (n=8) Wales/Midlands (n=15) Key BCoV BRSV M. haem M. bovis PI3 90% 100% 80% 70% 60% 50% 40% 30% 20% 10% 0% Spring (n=12) Summer (n=3) Autumn (n=15) Winter (n=21) Key BCoV BRSV M. haem M. bovis PI3 4436 BCVA A4 Poster.indd 1 30/08/2023 14:07

CATTLE PRACTICE VOLUME 31 PART 1 2023 117 Predictive modelling of deviation from expected milk yield in transition cows on automatic milking systems Fergus P. Hannona, Martin J. Greena, Luke O’Gradya,b, Chris Hudsona, Anneke Gouwc , Laura V. Randalla a School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, United Kingdom LE12 5RD b School of Veterinary Medicine, University College Dublin, Belfield, Dublin 4, Ireland c Lely International N.V., Cornelis van der Lelylaan 1, 3147 PB, Maassluis, the Netherlands Background A reduction in early lactation milk yield is one of the most common and economically consequential effects of poor transition in the dairy cow. Statistical models capable of identifying transition cows likely to suffer negative deviations in yield, may allow producers to mitigate these losses through proactive management. Sensor data collected by automatic milking systems (AMS) provide a unique opportunity to build and assess such models. Evaluation of Random Forest Classification Results Data relating to milk yield, rumination and physical activity were retained in the final predictive model. Following external validation, YD was predicted across the test data set with a mean absolute error of 9%. Categorisation of animals suffering large negative deviations (RED group) was achieved with a specificity of 99%, sensitivity of 35%, and balanced accuracy of 67% (Figures 3 & 4). Our results suggest that milk yield, rumination and physical activity patterns expressed by transition cows from 1–3 DIM have utility in the prediction of deviation from expected 30-day cumulative yield. However, these predictions currently lack the sensitivity required to classify cows reliably and completely into groups which may facilitate improved transition cow management. Objective The objective of this study is first, to explore the accuracy with which deviation from expected 30-day cumulative milk yield (Figure 1), can be predicted at 3 days in milk (DIM) using production and behaviour data collected by AMS (Figure 2). And second, to assess the accuracy with which this predicted yield deviation can classify cows into groups that reflect transition health to facilitate improved management (Figures 3 & 4). Materials and Methods Production, rumination, and physical activity data from 31 commercial AMS herds in the UK and Republic of Ireland were accessed. A 3-step analytical procedure was then conducted. In Step 1, an expected cumulative yield for 1–30 DIM for each individual cowlactation was calculated using a mixed effect linear model. In Step 2, 30-Day Yield Deviation (YD) was calculated as the difference between observed and expected cumulative yield. Cow-lactations were then assigned to one of three groups based on their YD, RED Group (</= -15% YD), AMBER Group (-14% ̶0% YD), GREEN Group (>0% YD) (Figure 1). In Step 3, machine learning models were trained to predict YD using AMS sensor data gathered from 1–3 DIM . Model performance was subsequently evaluated by external validation. Figure 2. AMS behaviour and production data from 1–3 DIM used to predict deviation from expected milk yield at 30 DIM. Figure 1. Traffic light classification system based on each cow’s deviation from expected cumulative milk yield at 30 DIM. RED Group (</= - 15% YD), AMBER Group (-14% ̶0% YD), GREEN Group (>0% YD) Figure 3. Calibration plot for group membership in the test data set. Figure 4. Performance metrics for the random forest model evaluated on the test data set. PPV = Positive predictive value, NPV = negative predictive value Group RED RED + AMBER GREEN Prevalence (%) 13 43 57 Sensitivity 35 67 81 Specificity 99 81 67 PPV 91 73 76 NPV 90 76 73 Balanced Accuracy 67 74 74 AMS Sensor Data Rumination Milk Yield Milk Temperature Physical Activity Milk Conductivity Visit Behaviour Predicted Group

CATTLE PRACTICE VOLUME 31 PART 1 2023 118 EFFICIENTLY ACHIEVING 1000KG FOR SUSTAINABLE DAIRY PRODUCTION MAXIMISING MILK SOLIDS References: J Hanks, M. Kossaibati., 2023. Key Performance Indicators for the UK national dairy herd. [Online] Available at: https://cdn2.assets-servd.host/craft-web/production/documents/NMR-500-Herds-2022.pdf [Accessed 1 March 2023]. Glossary: DMI: Dry Matter Intake TMR: Total Mixed Ration PMR: Partial Mixed Ration CMR: Calf Milk Replacer Report kindly sponsored by A more efficient cow that can produce milk solids with fewer inputs is a more sustainable cow, leading to decreased emissions per kg of milk. UK average milk solids production is 675kg/cow/305 days (Hanks & Kossaibati, 2023) - but some herds are achieving 1000kg - what makes them stand out? CONCLUSION 1000 kg of milk solids per cow per year is an obtainable goal for AYR, predominantly housed systems as they face the challenges of price volatility and continuing environmental pressure. Genetics was found to be responsible for up to 50% of the cows’ milk solid performance. To maximise production efficiency, health, welfare and fertility also needs to be optimum. All farms in this report are far exceeding their genetic prediction for total solids production, with the average ranging from 890kg to 1060kg of combined fat and protein per cow per year. There were more similarities than differences between these farms and there were several key management and genetic factors that could be adopted by other dairy farmers. Authors: Rose Jackson (BVSc DBR CertVBM MRCVS) & Maimie French (BSc (hons) MSc) from Kite Consulting Farm ID Calving Pattern Feeding system Cow numbers Average total solids/cow/ year (kg) Range in 305d total solids production (kg) 1 AYR 1 TMR 212 990 680-1390 2 AYR 1 TMR 180 900 510-1320 3 AYR 1 PMR+ fed in robots 246 1030 695-1350 4 AYR 1 TMR 405 1060 690-1490 5 AYR 1 PMR + fed in parlour 424 890 580-1270 6A AYR 1 TMR 421 1020 650-1380 6B AYR 1 TMR 458 1000 690-1230 7 AYR 1 TMR 435 960 550-1210 Table 1 Summary of farm systems and total solids The study includes an overview of the following key areas: • Genetics • Nutrition • Environment • Business resilience • Recording systems • Health & Welfare • Process Management Genetic data was obtained from AHDB using their Herd Genetic Report function; milk recording data was collected from the relevant Milk Recording Organisation (MRO). Data were analysed using TotalVet (QMMS Ltd). KEY FINDINGS Genetics • All farms had a very clear and focussed breeding strategy; 6 out of the 7 farms were basing their breeding decisions on genomic data.  • They all ranked high for £PLI (top 15% and above) • Linear regression analysis identified that genetics was responsible for up to 50% of the cows’ milk solid performance. Environment and Management • All farms milked ≥3 times per day; the robotic herd milked cows 3.2 times per day • Sand bedding was used on 5 of the 8 units and 3 units had very well managed sawdust and mattresses. • Cow grouping varied between the units; only one farm had a “true fresh” group • 7 of the 8 units were on a two-row cubicle design – meaning feed space was optimal. Health and fertility Cows are only able to achieve these high levels of production if their health indices are excellent too: all farms were achieving better than average health performance overall. • Mastitis incidence ranged from 6 to 16 cases/100 cows/year • Lameness incidence ranged from 2 to 32 cases/100 cows/year • 3-month rolling 21-day pregnancy rate (as defined by TotalVet’s Fertility Efficiency rate) ranged from 15.4 to 30.0% Calf health The first 50 days of life are particularly important for influencing the future performance of a heifer. Environmental and nutritional conditions both prepartum and in the pre-weaning period, can modify expression of certain genes (Epigenetics) • Age at first calving (AFC) ranged from 685 to 757 days (UK average is 799 days, (Hanks & Kossaibati, 2023)) • Colostrum management was excellent on all farms • All farms were feeding appropriate rates of milk • ≥1000g CMR for 1000kg of milk solids! Nutrition Feed Efficiency (FE) is the key to sustainable milk production • FE ≥1.4kg ECM/kg DMI for all farms • Forage inclusion of >50%  • Single TMR/PMR to all cows • Similarities in terms of feed additives: • C16 fat to all cows • Choline and Protected methionine in transition diets  • DCAB diet for close-up Carbon Footprint • The average kg CO2e/litre ECM is 1.2 for UK dairy farms while the range reported here was 0.8 to 1.1 kg CO2e/litre ECM - a good indicator of environmental sustainability. Up to 50% of a cow’s ability to produce high milk solids is due to genetics Cows with high milk solid yields are profitable and have less impact on the environment Cows are consistently able to produce 1000kg of milk solids per year when provided with the right genetics and conditions 1000kg For full report please scan here

CATTLE PRACTICE VOLUME 31 PART 1 2023 119 ANTIMICROBIAL MONITORING ON UK DAIRY FARMS Methodology For each herd, the livestock numbers were collected from the producer and the antimicrobial purchases were collected from the vet practice. A set of validated reports were then created and sent out to the producer/vet to check all products were included and validate the accuracy of the report content. The Kingshay antimicrobial monitoring service has been running since 2017 and enables farmers, vets, and milk processors to readily access antimicrobial usage data in a highly visual and user-friendly format. WWW.KINGSHAY.COM ANALYSIS OF ANTIMICROBIAL USAGE BY ROUTE OF ADMINISTRATION Other Key Trends Kingshay analysed antimicrobial data from 1,044 herds being recorded in 2022 T. Potter , C. Ford , K. Rowland Westpoint Farm Vets, Dawes Farm, Bognor Road, Warnham, West Sussex, RH12 3SH Kingshay Farming and Conservation, Bridge Farm, West Bradley, Glastonbury, Somerset, BA6 8LU Download your FREE report The analysis of antimicrobial usage now represents a key part of the herd health planning process, enabling vets to work with their clients to reduce and refine their use of these important medicines. Analysis of usage by route of administration shows that injectable products contribute the largest amount to all herds’ overall usage figure and this should be a key focus area moving forward. Whilst 76.5% of dairy herds now have an annual usage of below RUMA’s previous target of 21 mg/kg PCU set in 2017, there are still improvements to be made, particularly in the highest users. Figure 1 - Antimicrobial usage by route of administration by quartile for UK Dairy Herds (n=1,044) The data also highlights the high usage of oral antimicrobials in dairy herds (see figure 1) within the highest 25% of users with herds using on average 4.3 mg/kg PCU, which is 4 times as much as herds in the 3rd quartile and 43 times as much as herds in the lowest quartile. The UK dairy sector has achieved significant reductions in antimicrobial usage over the last 5 years but there is further work to be done. Oral administration to groups of animals has been highlighted by the EMA as having the highest estimated impact on antimicrobial resistance and herds should work to avoid the need for prophylactic and metaphylactic group treatments by implementing management changes and preventing disease outbreaks. Across the 1,044 dairy herds analysed in 2022 the overall usage ranged from 0.26 to 87.17 mg/kg PCU. Highest Usage The analysis showed that the 25% of herds using the most antimicrobials contributed 49% of the overall antimicrobial usage and for the industry to continue to make progress against reduction targets it is essential for veterinary surgeons to engage with these clients. Routes of Administration Analysing the antimicrobial usage by routes of administration provides a useful insight into what is contributing to the total usage on farms. For all herds, injectable antimicrobials make up the largest proportion of their antimicrobial usage (ranging between 70% and 76%) and reductions in this area highlight the biggest opportunity for reducing overall herd usage. On farm, the usage of injectable antimicrobials will generally be for the treatment of individual animals, so to achieve reductions, these farms should focus on disease prevention and working closely with their veterinary surgeons to optimise product selection and treatment protocols. Results Any products that were not used in the period were adjusted as well as any products used on other enterprises, such as beef or sheep. 1 1 2 2 2 Conclusions The second annual Antimicrobial Focus Report summarises the antimicrobial purchasing trends from dairy and beef herds across the UK, highlighting key areas where there is potential for further improvement. The report goes into dairy herd level comparisons, dry cow therapy and year on year indepth evaluations, as well as analysis by region.

CATTLE PRACTICE VOLUME 31 PART 1 2023 120 SRUC is a charity registered in Scotland, No. SC003712 ⚫ Calves ⚫ One hundred and forty-one dairy-bred calves in straw bedded group pens ⚫ Access to seven litres of milk replacer daily using an automatic milk feeder and ad libitum access to water, concentrate and straw ⚫ Calves left the trial at 26 days of age or after an episode of NCD ⚫ Daily health scoring including tail, perineum and hindleg cleanliness (CLEAN) (Table 1), skin tent elasticity and capillary refill time, Wisconsin calf health score (HEALTH) (2) and faeces score where possible (Table 1) ⚫ NCD was classified by as faeces score of ≥2 or a CLEAN score of ≥2 ⚫ Dehydration was classified by a return of the skin tent of >3 seconds ⚫ Saliva was collected on the day of recruitment and approximately weekly thereafter using the Salivette saliva collection system and saliva pH and conductivity measured using portable meters ⚫ Data analysis: ⚫ Non-diseased samples that were taken within two days of the development of NCD or where HEALTH was intermediate or diseased (≥4) were removed ⚫ Samples were classified as being ‘NCD without dehydration’ (NCDH), ‘NCD with dehydration’ (NCD-D) or ‘healthy’ ⚫ General linear mixed models tested the fixed effect: disease status, sex, sire breed type, age, the interaction between disease and age, age at inclusion into the group pen, and date Scoring criteria Score CLEAN Faeces 0 Clean calf or with a small amount of dried faeces on tail/perineum/hind legs Formed faeces 1 A large amount of dried faeces or some pasty faeces on tail/perineum/hind legs Pasty faeces 2 Wet Faeces on tail/perineum/hind legs Loose faeces that did not sift through bedding 3 A very wet tail/perineum or a large amount of faeces on tail/perineum/hind legs Liquid faeces that sifted through the bedding Beth Riley1,2, Marie Haskell1, Carol-Anne Duthie1, Colin Mason1, Alexander Corbishley2 1. Scotland’s Rural College, West Mains Road, Edinburgh, EH9 3JG, Scotland 2. Royal (Dick) School of Veterinary Studies & Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG. Scotland Email: [email protected] @riley_bethan Acknowledgements The authors wish to thank the farm and technical staff at SRUC Dairy Research & Innovation Centre, Crichton Royal Farm, Dumfries for their assistance. BRs PhD is funded by EASTBIO DTP and AHDB. SRUC receives funding from RESAS, Scottish Government. Methods Introduction Results (contd.) ⚫ Neonatal calf diarrhoea (NCD) affects an average of 48% of calves in the first 9 weeks of life (1) ⚫ This study aimed to assess the relationship between saliva parameters and naturally occurring dehydration in calves with NCD and the relationship between calf characteristics and saliva parameters ⚫ Saliva pH ⚫ Lower in NCD-H (p<0.01) and NCD-D (p<0.01) calves compared to healthy calves (Figure 1) ⚫ Lower in calves with NCD-D compared to NCD-H calves (p<0.05, Figure 1) ⚫ Higher in female calves than male calves (p<0.05, Figure 2) ⚫ Saliva conductivity ⚫ No effect of disease (P>0.1) ⚫ Tended to be lower in calves born in spring than those born in autumn (p<0.1) ⚫ Greater in calves that moved into the group pen at an older age (p<0.05) Conclusions ⚫ Saliva pH shows some promise as a pen side diagnostic for NCD with and without dehydration ⚫ Saliva conductivity had no relationship with NCD or dehydration The effect of neonatal calf diarrhoea with and without dehydration and calf characteristics on saliva pH and conductivity (1) Johnson et al, 2017, Vet Rec Open, 4, e000226 (2) McGuirk 2008, Vet Clin North Am Food Anim Pract, 24, 139-53 (3) Schwarzkopf et al, 2022, BMC Vet Res, 18, 102 References Results Table 1: The criteria for the tail, perineum and hindleg cleanliness (CLEAN) and faeces scores ⚫ Reduced saliva pH in NCD-H and NCD-D consistent with metabolic acidosis that increases as dehydration develops. ⚫ Thus, there is potential as a pen side test ⚫ Future technological developments may allow automatic testing at the teat of the automatic milk feeder ⚫ Unlike a previous study (3) there was no effect of age in this study Discussion Figure 2: The effect of sex on saliva pH. Differing letters indicates significance Figure 1: The effect of neonatal calf diarrhoea and dehydration on saliva pH. Differing letters indicates significance

CATTLE PRACTICE VOLUME 31 PART 1 2023 121 SRUC is a charity registered in Scotland, No. SC003712 Beth Riley1,2, Marie Haskell1, Carol-Anne Duthie1, Alexander Corbishley2, Colin Mason1 1. Scotland’s Rural College, West Mains Road, Edinburgh, EH9 3JG, Scotland 2. Royal (Dick) School of Veterinary Studies & Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG. Scotland Email: [email protected] @riley_bethan Methods Introduction Results (contd.) ⚫ Neonatal calf diarrhoea (NCD) affects an average of 48% of calves in the first 9 weeks of life (1) ⚫ This study aimed to assess the relationship between haematocrit and plasma total protein (TP) and naturally occurring dehydration in calves with NCD and the relationship between calf characteristics and blood parameters ⚫ Haematocrit ⚫ Increased in NCD-D calves (P<0.05, Figure 1A) ⚫ Reduced in male calves (p<0.05, Figure1B) ⚫ Reduced in dairy sired calves(p<0.001, Figure 1C) ⚫ TP ⚫ Reduced in NCD-H (p<0.01, Figure 2A) ⚫ NCD-D not significantly different from Healthy or NCD-H (p>0.1, Figure 2A) ⚫ Reduced in dairy sired calves (p<0.05 , Figure 2B) ⚫ Reduces as calves age (p<0.001 , Figure 2C) Conclusions ⚫ Vital that the clinician interprets haematocrit and TP together when diagnosing dehydration ⚫ TP may not increase as expected in NCD-D calves ⚫ Sex and breed of the calf should be considered The effect of neonatal calf diarrhoea with and without dehydration and calf level characteristics on blood parameters used to measure dehydration (1) Johnson et al, 2017, Vet Rec Open, 4, e000226 (2) McGuirk 2008, Vet Clin North Am Food Anim Pract, 24, 139-53 References Results Table 1: The criteria for the tail, perineum and hindleg cleanliness (CLEAN) and faeces scores ⚫ NCD was classified by as faeces score of ≥2 or a CLEAN score of ≥2 ⚫ Dehydration was classified by a return of the skin tent of >3 seconds ⚫ Blood samples were collected on the day of recruitment and approximately weekly thereafter using jugular venipuncture and haematocrit and TP measured ⚫ Data analysis: ⚫ Non-diseased samples that were taken within two days of the development of NCD or where HEALTH was intermediate or diseased (≥4) were removed ⚫ Samples were classified as being ‘NCD without dehydration’ (NCDH), ‘NCD with dehydration’ (NCD-D) or ‘healthy’ ⚫ General linear mixed models tested the fixed effect: disease status, sex, sire breed type, age, the interaction between disease and age, age at inclusion into the group pen, and date Figure 1: The effect of neonatal calf diarrhoea with and without dehydration, sex and sire breed type on haematocrit. Differing letters indicates significance. Figure 2: The effect of diarrhoea with and without dehydration, sire breed type and age on plasma total protein. Differing letters indicates significance. Acknowledgements The authors wish to thank the farm and technical staff at SRUC Dairy Research & Innovation Centre, Crichton Royal Farm, Dumfries for their assistance. BRs PhD is funded by EASTBIO DTP and AHDB. SRUC receives funding from RESAS, Scottish Government. ⚫ Calves ⚫ One hundred and forty-one dairy-bred calves in straw bedded group pens ⚫ Access to seven litres of milk replacer daily using an automatic milk feeder and ad libitum access to water, concentrate and straw ⚫ Calves left the trial at 26 days of age or after an episode of NCD ⚫ Daily health scoring including: tail, perineum and hindleg cleanliness (CLEAN) (Table 1), skin tent elasticity and capillary refill time, Wisconsin calf health score (HEALTH) (2) and faeces score where possible (Table 1) Scoring criteria Score CLEAN Faeces 0 Clean calf or with a small amount of dried faeces on tail/perineum/hind legs Formed faeces 1 A large amount of dried faeces or some pasty faeces on tail/perineum/hind legs Pasty faeces 2 Wet Faeces on tail/perineum/hind legs Loose faeces that did not sift through bedding 3 A very wet tail/perineum or a large amount of faeces on tail/perineum/hind legs Liquid faeces that sifted through the bedding

CATTLE PRACTICE VOLUME 31 PART 1 2023 122 As in previous years, culling for infertility remained the top reason for cows leaving the herd, at 25% of culls. Mastitis stayed in the second spot, with mastitis culls decreasing from 9.1% to 8.7%, which has helped keep mastitis cases lower than they would have been. The prolonged hot, dry summer of 2022 meant that many producers saw increased summer mastitis incidences, along with cows suffering more than usual from heat stress. The average cost of mastitis has been calculated to be £365 per case, based on 29 cases per 100 cows totalled £10,439 (see table 2): up on last year’s average of £10,020 (£334 per case) due to the higher milk prices. If a herd aims to lower their mastitis cases to less than 15 cases (to be in top 25%), then this would be a saving of £4,964 per year. This potential saving could be offset and “invested” in infrastructure or systems to future proof herd performance. The hidden loss of potential income from poor herd health, due to health incidences such as mastitis can add up, particularly with milk prices being the highest they have been in 20 years. Variable costs have risen significantly compared to last year according to Kingshay’s latest Costs of Production analysis. WWW.KINGSHAY.COM CULLING FOR MASTITIS Download your FREE report HEALTH TRENDS ON UK DAIRY FARMS ANALYSIS OF MASTITIS CASES, COSTS AND CULLING RATES Mastitis trends over the last 5 years Mastitis costs Summary Kathryn Rowland, Senior Farm Services Manager Kingshay Farming and Conservation, Bridge Farm, West Bradley, Glastonbury, Somerset, BA6 8LU Average mastitis levels have dropped from 39 cases per 100 cows in 2019, and 30 the previous year, to 29 cases in 2023. With the focus on producers to reduce antibiotic usage and somatic cell count, the continued reduction in mastitis cases is encouraging. See table 1. Table 1 - Trends in mastitis cases over the last 5 years Table 2 - Comparisons in costs per case for mastitis Figure 1 - Individual reasons for cows leaving the herd Kingshay analysed data from over 200 herds using Kingshay’s Health Manager service. The service links herd health issues & costs to dairy cow performance, with quarterly reports for a more targeted approach to your cow records. Many producers are looking to increase output to spread these higher costs over more litres to increase return on investment. With a shift towards higher yielding, larger herds, more pressure may be placed on cow health. One way to increase output is to address animal health issues such as mastitis, fertility and lameness which are major limiting factors to production. Mastitis is also one of the main reasons for cows leaving the herd, accounting for 8.7% of all culls. With milk prices averaging 46ppl, the cost of mastitis per case is the highest it has ever been. These costs need recalculating frequently as milk prices and costs shift, but cull cow values are still strong and this offsets some of this lost income. Kingshay’s Dairy Costings Focus Report 2023 includes analyses of herd performance, health costs and margin over purchased feed data ranked by a variety of different factors, such as production system and region, along with milk yield and herd size bands. The twelfth annual report also includes milk price and feed cost trends up to the year ending March 2023.

CATTLE PRACTICE VOLUME 31 PART 1 2023 123 Emma Taylor | Mohamad Kossaibati | James Hanks | Nick Taylor PAN Livestock Services, Veterinary Epidemiology & Economics Research Unit (VEERU) School of Agriculture Policy & Development Introduction Since 2010, the University of Reading has conducted annual analyses of herd performance for 500 Holstein Friesian dairy herds. Starting in 2010, each study covers >70 different parameters describing different aspects of fertility, production and health. The objectives of the studies are to provide farmers and their technical advisers with accurate and current descriptions of performance levels as the basis for discussion and target setting at herd level. QR code to previous KPI studies Methodology Data source: The source of data are the monthly milk records obtained by National Milk Records (NMR). The 500 herds used in the study all fully milk record on a monthly basis and account for approximately 10% of herds recorded by NMR. The herds are all predominantly comprised of Holstein, Holstein-Friesian, Friesian and have milk recorded for a minimum of two years prior to being included in the 500-herd selection. Benchmarking: For each parameter, the 1st quartile, median, 3rd quartile and interquartile range are calculated. The target value is the level achieved or bettered by 25% of the herds in the study. This value is the “better” of the first (25%) or third quartile (75%) values. Results (based on median values) Herd demographics ▪ Median herd size increased from 129 in 2010 to 178 in 2018, and since fluctuated around that value. ▪ The proportion of cows in lactation 1 increased from 26% in 2010 to 29% in 2012, and since fluctuated around that value. ▪ Median herd cull rates were higher than 2010 in most years, but with no consistent trend. Median herd cull rate was 24% in 2010 and 26% in 2022. ▪ Median herd productive life and age at exit both decreased from 2010 to 2021 (from 1,511 to 1,323 days and from 6.6 to 5.9 years), but recovered slightly in 2022 compared to 2021. How are fertility, production and health parameters changing in the national UK dairy herd? Trends in key performance indicators since 2010. Fertility ▪ Median herd age at first calving has decreased from 2.4 years in 2011 to 2014, 2.3 years in 2015 to 2020 down to 2.2 years in 2021 and 2022. ▪ The % served by 80 DPP increased from 46% to 60% between 2010 and 2017 and has since fluctuated between 58% and 61%. ▪ % service intervals 18-24 days has increased from 30% in 2010 to 41% in 2022. ▪ Calving to 1st service interval decreased from 105 days in 2010 to 81 days in 2017 and has since fluctuated between 79 days and 81 days. ▪ The % conceived by 100 DPP has increased from 26% in 2010 to 39% in 2022. ▪ From 32% in 2010, median herd conception rate decreased in 2011 and 2012 but has increased since 2016, reaching 38% in 2022. ▪ Calving interval has decreased from 424 days in 2010 to 394 days in 2022. Milk Production and Somatic Cell Count (SCC) ▪ Milk/cow/year increased from 7,665 kg in 2010 to 9,008 kg in 2021, but was slightly lower in 2022 at 8,708 kg. ▪ Lifetime milk/cow/day increased from 10.5 kg in 2010 to 13.1 kg in 2021, but was slightly lower in 2022 at 12.7 kg. ▪ Median herd average SCC decreased from 210,000 cells/ml in 2010 to 166,000 cells/ml in 2022. ▪ The median herd proportion of recorded cows with SCC >=200,000 cells/ml decreased gradually from 24% in 2010 to 16% in 2022. ▪ The median herd proportion of recorded cows with SCC >=500,000 cells/ml decreased in two steps from 9% in 2010 to 7% in 2015, where it stabilized ▪ The median herd proportion of recorded cows with chronic (repeat) SCC >=200,000 cells/ml decreased in stages from 14% in 2010 to 8% in 2022. Conclusions Since 2010, key performance indicators relating to fertility, milk production and somatic cell count have improved. However, the demographic of UK dairy herds have noticeably changed. Herd sizes have increased, and older cattle are more readily replaced for replacement heifers, although the motivations behind reduced longevity remains unclear. Figure 1. Percentage change in median herd size (number of cows) and median proportion of cows in lactation 1 (%) compared to herd values in 2010. Figure 2. Percentage change in median cull rate (%), median productive life (days) and median age at exit (years) compared to herd values in 2010. Figure 3. Percentage change in median fertility parameter values compared to values in 2010. Figure 4. Percentage change in median milk per cow per year (kg) and median lifetime milk per cow per day (kg) compared to herd values in 2010. Figure 5. Percentage change in median average SCC (cells/ml), and the median proportions of recorded cows with a SCC >= 200,000 or >= 500,000 compared to herd values in 2010. Contact Information/ Acknowledgements • Email: [email protected] | https://panlivestock.com/ | @InterHerdPlus • The authors are grateful to NMR for their assistance and cooperation and acknowledge the contribution of VEERU colleague Kulwant Channa for his technical support.

CATTLE PRACTICE VOLUME 31 PART 1 2023 124 Antimicrobial resistance in Escherichia coli from UK cattle farms C.J. Wooding*, S.M. Frosini* *Department of Pathobiology and Pathogen Sciences, Royal Veterinary College, Hatfield, UK Antimicrobial Resistance (AMR) is a major threat to modern human and veterinary medicine, and to UK cattle farming through economic losses and compromised welfare(1) . Past extensive prophylactic, metaphylactic, and growth promotor use have seen the farming industry come under heavy scrutiny in terms of antimicrobial use and resistance(2) . Higher antimicrobial use on dairy farms due to a higher production intensity has been linked to an increased resistance compared to beef(3,4) and currently, the most common antimicrobial classes used in UK cattle are β-Lactams, tetracyclines and aminoglycosides(5) . E. coli is one of the most prolifically resistant bacteria encountered, and the rise of multidrug-resistant (MDR) isolates, especially associated with AmpC, ESBL or CPE phenotypes is of particular concern(6) . Commonly cattle E. coli can show resistance to beta-lactams, tetracyclines, fluoroquinolones, trimethoprim-sulphonamide combinations, and phenicols(6,7) . Introduction Methods Aims Conclusion Results 1 2 3 CHARACTERISE RESISTANCE levels and distribution across farms COMPARE RESISTANCE between dairy and beef AND intensive and extensive farms CORRELATE RESISTANCE with antimicrobial use 7% Total Resistance Prevalence 10% 4% Prevalence on dairy farms Prevalence on beef farms No statistically significant difference in resistance levels between dairy and beef farms (p = 0.151) or between intensive and extensive farms (p = 0.476) • All samples yielded blue E. coli colonies on TBX agar giving a recovery rate of 100% • 6 samples, all from dairy farms, yielded E. coli colonies on MacConkey agar supplemented with cefotaxime • All 6 were confirmed to express the AmpC β-lactamase, but were negative for ESBL production • No E. coli growth was observed on any of the MacConkey with meropenem plates 3% Total AmpC Prevalence 6% 0% Prevalence on dairy farms Prevalence on beef farms No statistically significant difference in resistance levels between dairy and beef farms (p = 0.151) or between intensive and extensive farms (p = 0.257) • Resistance prevalence breakdown according to the individual antimicrobials tested and the prevalence of Multi-Drug Resistant (MDR) E. coli isolated per farm (including AmpC expressing E. coli as these were all confirmed to be MDR following AST). Literature resistance prevalence is taken from (5) for ampicillin, amoxicillin/clavulanic acid, enrofloxacin and tetracycline, and from (8) for TMPS and chloramphenicol. Number of antimicrobials used positively correlated with increased resistance (p=0.839) and presence of AmpC-expressing E. coli (p=0.845)) • Overall and individual antimicrobial class resistance prevalence was low compared to data presented in recent literature(5,8) • Hypothesised to relate to a relatively high disposable income in the area sampled(9), meaning farmers can afford to spend more on preventative healthcare and better infrastructure to reduce disease burden and thus reduce antimicrobial usage • No significant difference in resistance prevalence could be found between dairy and beef, or intensive and extensive farms sampled • Use of a larger number of antimicrobials leads to higher levels of AMR 0 5 10 15 20 25 ampicillin amoxicillin/clavulanic acid enrofloxacin tetracycline TMPS chloramphenicol MDR Resistance Prevalence (%) Antimicrobial Total Resistance Prevalence Dairy Resistance Prevalence Beef Resistance Prevalence Resistance Prevalence in the Literature n = 200 References: (1) Call. D. R, Davis. M. A, Sawant. A. A. Antimicrobial Resistance in Beef and Dairy Cattle Production. Animal Health Research Reviews. 2008;9(2): 159-167 (2) Tiseo. K, Huber. L, Gilbert. M, Robinson. T. P, Van Boeckle. T. P. Global Trends in Antimicrobial Use in Food Animals from 2017 to 2030. Antibiotics (Basel). 2020;9(12): 918 (3) Humphry. R. W, Henry. M. K, Reeves. A, Correia-Gomes. C, Innocent. G. T, Smith. R, Mason. C. S, Gunn. G. J, Tongue. S. C. Estimating Antimicrobial Usage Based on Sales to Beef and Dairy Farms from UK Veterinary Practices. Vet Rec. 2021;189(1): e28 (4) Davis. M. A, Hancock. D. D, Besser. T. E, Daniels. J. B, Baker. K. N. K, Call. D. R. Antimicrobial Resistance in Salmonella enterica serovar Dublin Isolates from Beef and Dairy Sources. Vet Microbiol. 2007;119(2-4): 221-230 (5) Hennessey. M, Whatford. L, Payne-Gifford. S, Johnson. K. F, Van Winden. S, Barling. D, Häsler. B. Antimicrobial & Antiparasitic Use and Resistance in British Sheep and Cattle: A Systematic Review. Prev Vet Med 2020;185: 105174 (6) Schwaber. M. J, Navon-Venezia. S, Schwartz. D, Carmeli. Y. High Levels of Antimicrobial Coresistance Among Extended-Spectrum-β-Lactamase-Producing Enterobacteriaceae. Antimicrob Agents Chemother. 2005;49(5): 2137-2139 (7) Veterinary Medicines Directorate. UK Veterinary Antibiotic Resistance and Sales Surveillance Report (UK-VARRS 2021) [Internet]. Addleston: Veterinary Medicines Directorate. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1126450/FOR_PUBLICATION_-_UK-VARSS_2021_Main_Report__Final_v3_-accessible.pdf (Accessed 23/09/2023) (8) De Jong. A, El Garch. F, Hocquet. D, Prenger-Berninghoff. E, De Wulf. J, Migura-Garcia. L, Perrin-Guyomard. A, Veldman. K. T, Janosi. S, Skarzyska. M, Simjee. S, Moyaert. H, Rose. M, ESSA Study Group. European-Wide Antimicrobial Resistance Monitoring inn Commensal Escherichia coli Isolated from Healthy Food Animals Between 2004 and 2018. J Antimicrob Chemother 2022;77(12): 3301-3311 (9) Office for National Statistics. Regional Gross Disposable Household Income, UK: 1997 to 2021. [Internet] Available at: https://www.ons.gov.uk/economy/regionalaccounts/grossdisposablehouseholdincome/bulletins/regionalgrossdisposablehouseholdincomegdhi/1997to2021#gross-disposable-household-income-for-itl3-local-areas (Accessed: 23/09/2023

CATTLE PRACTICE VOLUME 31 PART 1 2023 125 Evaluation of the difference between mobility score outcomes conducted before and after milking: A study on 5 UK dairy farms Blowers, B.J., Fishwick, J., Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, AL9 7TA INTRODUCTION Lameness describes any clinical condition that impairs locomotion regardless of cause (Archer and others 2010). The prevalence of lameness within the British dairy herd has been estimated at 30-32% (Griffiths and others 2018, Randall and others 2019). Lameness raises significant welfare concerns as well as increasing the environmental impact of dairy farming. The financial importance of lameness is considered only behind that of fertility and mastitis internationally (Bruijins and others 2010, Deger and others 2015). The cost of lameness on farm can range from £70-500 per case depending on the underlying pathology (Willshire and Bell 2009, Dolecheck and Bewley 2018). It can often be simpler to consider the cost of lameness in terms of lost productivity. Huxley (2013) summarised that lameness can decrease milk yield by 270-540kg per case, per lactation. Studies by Booth and others (2004) and Charfeddine and Pérez-Cabal (2017) demonstrated that lameness negatively affects cow longevity and fertility while increasing culling rates further impacting farm finances. Lameness is recognised as a painful condition, while cows’ stoicism has been recognised as a masking factor preventing early detection (O'Callaghan and others 2003, Laven and others 2008). With the average duration of lameness cases being estimated at 135 days (Whay 2002), a compromise of three of the five welfare needs can be expected. These are the need to exhibit normal behaviour, the need to be free from discomfort and the need to be free from pain injury and disease (Animal Welfare Act 2006). Leach and others (2012) demonstrated that when protocols to treat cows with an AHDB 0-3 mobility score of 2 (Table 1), within 48 hours of detection, were introduced on farms the prevalence of lameness significantly reduced within 4 weeks. This further highlights the importance of early detection and treatment of lameness as it will reduce the effects on yield and welfare concerns, making early detection and treatment the aim of many farmers. ABSTRACT Lameness is one of the three most important diseases affecting the dairy industry today, compromising animal welfare, productivity and economic viability of cattle. Early detection is considered a key factor in lameness management and a key to this is the appropriate and regular use of a mobility scoring systems to identify new cases of lameness. The literature currently suggests post milking as the optimum time to mobility score, however there is limited research assessing this directly. Mobility scoring was conducted on the high yielding groups of 5 UK dairy farms, using the Agriculture and Horticulture Development Board (AHDB) 0-3 method. These scores were conducted pre milking in the collecting yard and post milking as the cattle left the parlour during both morning and afternoon milking on consecutive days. In total 5,180 mobility scores were carried on 602 cattle across 11 days. Statistical analysis found there was a significant increase (p<0.001) in the number of AHDB score 1 cattle post milking (36.56% of cows scored) compared to the pre milking scores (24.05% of cows scored). There were no significant changes in the number of cattle scoring AHDB scores of 2 or 3 from pre milking scores to post milking scores. When assessed there was no significant difference between pre milking scores conducted during morning or afternoon sessions (p=0.2498). This was also seen when comparing morning and afternoon post milking scores (p=0.03208). One interesting outcome from this study was a clear trend of pre milking score 2 cattle to decrease scores post milking. On 4/5 of the farms 60% or more of pre milking AHDB score 2 cattle decreased a score post milking. The study concluded post may be the optimal time for mobility scoring. It has also raised questions about why there would be a decrease in mobility scores post milking highlighting this as an area for further research.

CATTLE PRACTICE VOLUME 31 PART 1 2023 126 The average dairy herd size in the UK has increased from an average of 75 head of cattle per farm to 166 head per farm between 1996 and 2021 (AHDB 2023). The increase in herd size has placed greater pressure on farmer time management and reduces the likelihood of regular mobility scoring (Blackie and Maclaurin 2019); resulting in an increased need for mobility scoring systems to have increased sensitivity and be less time consuming. Detection of lameness can be achieved by one of three methods: subjective visual mobility scoring, biomechanical kinematics and pressure plate recordings. These methods all have a degree of subjectivity with kinematics and pressure plates currently being reserved mainly for research purposes due to the cost and difficulty in analysing data (Flower and others 2005, Walker and others 2010). Pressure plates offer the most accurate and sensitive method for early lameness detection but requires a large amount of stored data for each cow. Alongside this, they are also expensive to install and maintain, currently making them impractical on farm (Walker and others 2010). Although visual scoring methods are highly subjective, they can be cheap and effective when the system is well designed. Whay (2002) defines the ideal visual scoring system as one that is easy to use and remember while not encouraging the collection of excess data. There are multiple visual methods of assessing mobility in cattle, with the benefits and limitations being summarised by Whay (2002). The only notable exception not discussed by Whay (2002) is the four point mobility scale defined by the UK Agriculture and Horticulture Development Board (AHDB) created after the study’s publication. There is a lack of literature reviewing the optimal time of the day to conduct mobility scores. Anecdotal evidence suggests that AHDB scores conducted pre and post milking produce differing results. Many veterinarian surgeons prefer to score during afternoon milking; due to improved visibility, more sociable working hours and not having to charge clients out of hours fees. Studies into the kinematics of bovine locomotion suggests that scoring post milking may be the optimum time (Flower and Weary 2006, Chapinel 2009). Kinematic lameness investigations use parameters such as stride height, length and duration as well as measuring the stance and swing phases of walking (Flower and others 2006). This data is collected using 60 frames per second video recording of cattle walking down test alleys which are then digitised and analysed (Flower and Weary 2005). This study showed that although there were statistically significant differences in the kinematic gait measurements pre and post milking, the visual score changes were not significantly different. These findings are thought to be due to increased walking pace post milking and reduced 3 limb support times, defined as time spent with three hooves on the ground. This creates more gait cycles per meter, thus making any variation in gait or lameness more obvious (Flower and others 2005). However, these may not be detectable changes when visually scoring mobility. In contrast, pre milking scores are complicated by gait changes caused by udder distention resulting in hindlimb abduction causing abnormal foot placement, which can be mistaken as lameness (Boelling and Pollot 1998, Chapinel 2009). These physiological changes to gait could therefore negatively affect the sensitivity of visual scoring systems. It is not just cow factors that can affect mobility scores without increasing the incidence of pathologies. Herd level factors such as standing times greater than 90 minutes and being held in the collecting yard before milking can increase mobility scores without underlying pathologies (O’Connor and others 2020). Cows that have mild lameness are more likely to be lower down the social hierarchy (Galindo and Broom 2000) so will be exposed to greater standing times during milking. This could exacerbate their lameness and cause an increased score post milking. There is some disagreement in the literature concerning factors such as path maintenance and distance walked with O’Connor and others (2020) finding no statistical significance while Chesterton and others (1989) found significant effects. All of the effects discussed above may influence mobility scores Score Description 0 Good mobility walks with even weight bearing and rhythm on all four feet with a flat back. Has long fluid strides where the environment allows. 1 Imperfect mobility walks with uneven rhythm or weightbearing, has shortened strides. The affected limb is not immediately identifiable. 2 Impaired mobility, uneven weight bearing on an immediately identifiable limb, or obviously shortened strides with an arch to the centre of the back. 3 Severely impaired mobility, unable to keep pace with the herd, lame leg is easily identifiable, limping, obvious back arch, may be unable to weight bare. Table 1. Description of the AHDB mobility scoring system. (Archer and others 2010, AHDB 2021).

CATTLE PRACTICE VOLUME 31 PART 1 2023 127 causing differences between scores depending on the timing. HYPOTHESES This study aimed to look at the optimal time to mobility score, by comparing AHDB 0-3 mobility scores (Table 1) collected pre and post milking and from both morning and afternoon milkings. It will also compare how individual cows’ scores change after milking. The current literature on the mechanics of cattle locomotion and anecdotal evidence suggest that post milking will provide more sensitive and specific results leading to the following hypothesis: 1. Mobility scoring conducted post milking will have a higher prevalence of AHDB scores 2 and above compared to scores conducted pre milking. 2. Cows identified as AHDB scores of 2 pre milking will be identified as scores of 3 post milking. METHOD Mobility scores were carried out on the high yielding cows of five dairy farms, across England and Wales, over multiple days. The criteria for farm selection was based on the convenience of access to the farms. Pre and post milking scores were conducted during both morning and afternoon milking sessions of the same day due to the scorer’s time constraints. Information on the farms production, housing and management systems were also collected to provide context of the scoring environment. The AHDB mobility scoring system, Table 1, was used for its simplicity, usability and the scorer’s familiarity with the system. The scoring was conducted by a final year veterinary student, as part of their final year research project, and had their scoring calibrated by their first session being conducted alongside a register of mobility (RoMs) accredited scorer. Due to the scope of the study, all scores were conducted by the same individual. On all the farms, pre milking scores were conducted as the cows entered the collecting yard and post milking scores as they left the milking parlour. Both pre and post milking scores were collected at each milking session. Where possible morning and afternoon scores were also collected on the same day for the scorer’s convenience. Cows with a mobility score of 2 or 3 had their freeze brand or ear tag number and leg/s they were lame on noted and shared with the farmer to allow them to assess and begin any necessary treatment. A tally was taken for cattle with a score of 1 to compare the prevalence of low grade lameness present pre and post milking. Statistical analysis was conducted using a combination of contingency tables and Chi squared calculations within GraphPad Prism 9.1.0. RESULTS The farms involved had between 70-170 animals scored with free stall sand housing being the most common housing system. All the farms had a predominance of Holstein-Frisian cattle. Farm 1 and 2’s herds were also comprised of a number of Brown Swiss and British Short horn and short horn crosses respectively. Milking times ranged from 90 minutes up to 3 hours. The farm tracks were generally in a good state of repair with only farms 2 and 5 being in a poor state. Of the farms visited three of the farms were continuously housed, and two were housed at night only (Table 2). In total 314 cattle were turned out during the day and 288 were continuously housed. All the herds were fed on TMR or grass and were supplemented with concentrates in parlour. Of the five farms visited, two had scores conducted during both morning and afternoon milking on two consecutive days. One farm was scored on three consecutive days, one farm was scored on the morning and afternoon of the first day then scored on the morning of the following day. One of the farms was scored during the morning on two consecutive days and during the afternoon on the first day (Table 2). Scoring sessions were conducted in this way due to each farms prior commitments and time restraints. In total 5,180 mobility scores from 602 animals were conducted across the five farms. The scores assigned pre and post milking scores are summarised in Table 3. Statistical comparison, using the Chi Squared test, showed that the decrease in cows scoring 0 and the increase in cows scoring 1 post milking were significant (p<0.0001) (Figure 1). This pattern was seen within the individual farms as well as the total population (Table 2). There were no significant differences in the number of cows assigned AHDB mobility scores of 2 or 3 pre and post milking. There was no statistically significant difference between pre milking scores conducted during morning or afternoon milking sessions (p=0.2498). This pattern was also observed in post milking scores conducted during the morning and afternoon milking sessions (p=0.3208). To assess how individual cow’s mobility scores changed between pre and post milking a single

CATTLE PRACTICE VOLUME 31 PART 1 2023 128 Farm Total Number of Mobility Scores (Pre Milking Score: Black, Post Milking Score: Purple) Number of cattle scored Scoring Sessions Housing Track Condition and Distance Walked to Collecting Yard Milking Duration Herd Composition Average Milk Yield (L/ Cow/ Year) 1 70 Morning and Afternoon scoring on 3 consecutive days Indoor, Deep Litter Shavings Good Condition, Flat Concrete, <50m 3 Hours Holstein-Frisian and Brown Swiss 8,800 2 170 Morning scoring on two consecutive days and afternoon scoring on three consecutive days Free Stall with Sand Bedding Over Night, Pasture During Day From Housing: Good Condition Flat Concrete From Pasture: Poor Condition Dirt track, Housing: <50m Pasture: 500m 3 Hours Holstein-Frisian and British Short Horn. 9,000 3 108 Morning and afternoon scoring followed by morning scoring on consecutive day Free Stall Shed, Sand and Mattress Bedding Good Condition, Flat Concrete, <50m 90 Minutes Holstein-Frisian 11,000 4 110 Morning and afternoon scorings on two consecutive days Free Stall Barn, Sand and Mattress Bedding Good Condition, Flat Concrete, <200m 3 Hours Holstein-Frisian 12,000 5 144 Morning and afternoon scoring on 2 consecutive days Free Stall Sand and Bedding Overnight Pasture in the Day From Housing: Good Condition Flat Concrete From Pasture: Poor Condition Dirt track, Housing: <50m Pasture: <500m 90 Minutes Holstein-Frisian 11,000 Table 2. Comparison between Pre (black) and Post (Purple) milking mobility scores for each individual farm, with accompanying farm management systems and scoring sessions conducted. The graphs show the amalgamated results from each scoring session conducted on each farm. The farm descriptions highlight factors that have been shown to influence mobility scores. The graphs and table demonstrate that regardless of the farm specifics all the farms visited followed the same pre and post milking scoring pattern.

CATTLE PRACTICE VOLUME 31 PART 1 2023 129 day was randomly selected on each farm where the morning and afternoon mobility scores were collated. During the collation of the morning and afternoon scores, cows that changed scores during both morning and afternoon scoring sessions were only included in the data once. The results of this are summarised in Table 4. Across all the farms a similar trend was seen; between 21-84% of AHDB score 2 cattle pre milking decreased their scores post milking. The percentage of score 1 cattle increasing scores post milking ranged between 3-22%. A clear trend was seen on farms 1,2,3 and 5 of the majority (>60%) of pre milking AHDB 0-3 score 2 cattle decreasing a score post milking. Farm 4 was the only farm where less than 60% of pre milking score 2 cattle decreased scores post milking (21% n=17). DISCUSSION The purpose of this study was to assess the effects of milking on mobility scores conducted on dairy cattle from each farm’s high yielding groups. With over 5,000 scores conducted and 602 individual cows, this is one of the larger studies looking at how mobility scoring is affected by milking. When assessing the current literature, there are few studies specifically comparing changes in mobility scores pre and post milking. The results of this study show a statistically significant difference between scores carried out pre and post milking (Figure 1, Table 2). Table 4 shows a clear trend of AHDB pre milking score 2 cattle decreasing a score post milking. The total number score of 2 cattle post milking was comparable to pre milking (Figure 1). This is due to the number of score 0/1 cattle increasing scores post milking. This poses questions as to when the best time to mobility score is and why so many cattle considered to be lame (AHDB Score 2) pre milking can change to being considered clinically sound (AHDB Score 0/1) post milking. With the increase in the number of score 1 cattle post milking (Figure 1) and the number of pre milking score 2 cattle reducing to score 0 or 1 post milking (Table 4), it could be suggested that post milking scores are more appropriate for a general assessment of herd mobility. This is due to the increase in score 1 cattle post milking providing a more accurate picture of the herd’s lameness status. As well as reducing the risk of missing post milking score 2 cattle and the risk of counting cattle only achieving an AHDB score of 2 due to factors such as natural udder distention (Flower and Weary 2006). The pre milking mobility scores were carried out as the herd moved toward the collecting yard. Therefore, factors such as cow turbulence and feed motivation, which is known to decrease lameness Pre Milking (%) Post Milking (%) Score 0: Good Mobility 58.49 44.95 Score 1: Imperfect Mobility 24.05 36.56 Score 2: Lame leg identifiable 16.22 17.18 Score 3: Unable to keep pace with herd 1.24 1.31 Table 3. Table showing the percentage of all pre and post milking mobility scores taken across all 5 farms. Across all of the scoring sessions 58.49% (n=1515) pre milking and 44.95% (n=1164) of post milking scores were AHDB mobility score 0, pre milking 24.05% (n=623) and post milking 36.56% (n=947) were score 1. Pre milking score 2’s comprised 16.22% (n=420) and post milking 17.18% (n=445) of all scores taken. Only 1.24% (n=32) and 1.31% (n=34) of scores were attributed to AHDB scores of 3. Figure 1. Graph showing the number of scores within each AHDB group pre (black) and post (purple) milking across all farms and all milking periods included in the study. The graph highlights the significant changes, P<0.0001, (Red*) in the number of cattle with scores 0 and 1 when comparing pre and post milking scores. While also showing that there are no significant differences between the number of cattle scoring 2 and 3 pre and post miking. Generated through GraphPad Prism 9.1.0.

CATTLE PRACTICE VOLUME 31 PART 1 2023 130 Table 4. Table summarises the changes in AHDB mobility scores of individual cows pre and post miking on each farm. One full day of scoring was selected randomly on each farm where morning and afternoon scores where collated. Any cow that was identified as changing scores during morning and afternoon scoring was only included once. The percentages are the number of cattle from that pre milking AHDB mobility score that either increased score, decreased score or stayed the same. The interpretations and descriptions of each graph are also included in this table alongside the number of cattle scored. Change In Cow Mobility Scores Post Milking in Comparison to Pre Milking Scores Description of Results Number of Cattle Scored Morning and Afternoon The graph shows how animals scored pre milking were scored post milking. Only 3% (n=3) of pre milking score 0/1 cattle changed score post milking, all increasing to score 2. While 85% (n=11) of pre milking score 2 cattle decreased score post milking. There were no score 3 cattle on this farm on this day. Morning: 70 Cattle Afternoon: 70 Cattle Total: 140 Cattle The graph shows how animals scored pre milking were scored post milking. Only 6% (n=21) of pre milking score 0/1 cattle changed score post milking, all increasing to score 2. While 77% (n=10) of pre milking score 2 cattle decreased score post milking. There were no score 3 cattle on this farm on this day. Morning: 170 Cattle Afternoon: 170 Cattle Total: 340 Cattle The graph shows how animals scored pre milking were scored post milking. Only 18% (n=33) of pre milking score 0/1 cattle changed score post milking, all increasing to score 2. While 60% (n=19) of pre milking score 2 cattle decreased score post milking. There was no change in score the cattle scoring 3 pre milking. Morning: 102 Cattle Afternoon: 108 Cattle Total: 210 The graph shows how animals scored pre milking were scored post milking. Only 22% (n=38) of pre milking score 0/1 cattle changed score post milking, all increasing to score 2. While 21% (n=17) of pre milking score 2 cattle decreased score post milking. There was no change in score the cattle scoring 3 pre milking. Morning: 110 Cattle Afternoon: 110 Cattle Total: 220 Cattle The graph shows how animals scored pre milking were scored post milking. Only 14% (n=32) of pre milking score 0/1 cattle changed score post milking, all increasing to score 2. While 78% (n=32) of pre milking score 2 cattle decreased score post milking. For pre milking score 3 cattle 50% (n=1) decreased to score 2 post milking. Morning: 144 Cattle Afternoon: 140 Cattle Total: 188 Cattle

CATTLE PRACTICE VOLUME 31 PART 1 2023 131 in poultry (Wylie and Gentle 1998), may have contributed to the low number of score 1 cattle pre milking. The effect of cow turbulence and bunching during the pre milking scoring will have reduced the time available to score each cow as they moved into the collecting yard. This could potentially lead to an underestimation of the number of score 1 cattle pre milking. This is in comparison to post milking scores where the cows were more often moving in single file out of the parlour providing a clearer window and more time to mobility score them. For score 2 cattle, the lame leg was identified during both pre and post milking scores to try and mitigate against underestimate. There are several possible explanations for the increase in post milking score 1 cattle recorded (Figure 1). Some of which are discussed above, cow turbulence and reduced scoring time associated with scoring in the collecting yard. Other possible factors that may contribute to increased post milking scores include cows experiencing standing times greater than 90 minutes (O’Connor and others 2020). In this study, all of the farms had milking times of 90 minutes to 3 hours. There was no significant difference noted in the number of score 2 cattle recorded pre and post milking, although the cows assigned these scores did change (Table 4). This was an unexpected finding in relation to the first hypothesis. Practically this suggests that scoring time in relation to milking has little effect on mobility scoring for the prevalence of lameness. However, there was a trend where the majority of pre milking score 2 cattle across 4 of the farms decreased to a score of 0/1 post milking (Table 4). This suggests that the timing of scoring in relation to milking may have a role in the successful identification of lameness on many farms, however more work is needed to replicate these findings on a larger scale and across varying management systems. There are several factors that could explain the drop in post milking scores for individuals. One explanation could be the reduction in udder weight and fill post milking. Around 89% of the udder weight is carried through the hind limbs, which is where most hoof pathologies are found (Murray and others 1996, Sadiq and others 2021). Post milking the weight of the udder can decrease by 3% of the cow’s body weight (Flower and Weary 2006) putting less force through the hoof pathology post milking, reducing the pain felt and the subsequent effect on cow gait. The effects of udder distention and width on gait will also decrease post milking (Boelling and Pollott 1998). There was no significant change in score 3 cattle pre and post milking with 32 cattle scoring 3 pre milking and 34 scoring 3 post milking. Whereas 21- 84% of AHDB pre milking score 2 cattle decreased a mobility score post milking. These differences can be explained by the definition of AHDB score 3; Unable to keep pace with the herd with an easily identifiable lame limb and back arch (AHDB 2021, Table 1). This definition gives the scorer a clear feature to focus on: the ability to keep pace with the herd, reducing the degree of subjectivity in the score. Only farm 4 saw a decrease in post milking mobility score 2’s of less than 60% (21%). The cause of this is uncertain if it is likely due to farm specific factors such as which lesions are predominantly causing lameness on farm. It is also possible that the milking herd has a well established social hierarchy leading to lame cows being exposed to increased standing times (3 hours) (Arave and Albright 1981, Von Keyserlingk and others 2008). No significant increase in the numbers of cattle progressing from AHDB score 2 to 3 post milking was another unexpected finding. Scores were expected to increase post milking due to increased standing times (O’Connor and others 2020). However, as discussed above the effect of reduced udder weight post milking putting less pressure through hoof pathologies may counteract the effects caused by increased standing preventing cattle moving from AHDB score 2 pre milking to score 3 post milking. As mentioned in the result section there was no significant difference between scores collected in the morning or the afternoon. This suggests no benefit, in relation to mobility scoring, to selecting a specific milking session to score during. Meaning morning or afternoon milkings are as suitable as each other for mobility scoring. This lack of difference was not unexpected due to cattle having similar lying times during the day and night before milking sessions (Blackie and Maclaurin 2019). It is unlikely that there will be any differences in the severity of pathology between morning and afternoon when scores are conducted on the same day. This is due to the duration of pathologies causing lameness lasting between 1.5 and 6.7 weeks when early treatment occurred (Schulz and others 2016). Meaning it is unlike that the severity of the pathology will change within a day even when treated. The study by Flower and Weary (2006) currently appears to be the main paper looking specifically at how milking affects mobility scoring in cattle. Flower and Weary (2006) similarly concluded that post milking mobility scoring is more appropriate than pre milking scores. As described in the introduction, Flower and others found that milking affected the kinematic gait analysis without causing

CATTLE PRACTICE VOLUME 31 PART 1 2023 132 significant changes in subjective mobility scores. The fact that subjective scores did not change pre and post milking is contrary to the findings in this study. Flower and Weary (2006) only looked at 48 cattle which may not be a large enough sample size to compensate for the effects of intrarater variability, potentially explaining the lack of significance. This study involved 602 cattle which was hoped to be a large enough sample size to offset the effect of intra-rater variability. Mobility scoring is highly subjective with cows of score 1 being the most open to individual interpretation due to cows’ stoic nature (O'Callaghan and others 2003, Raundal and others 2014), leading to a high degree of both inter and intra observer variability (Raundal and others 2014, Garcia and others 2015). This intra rater variability goes some way to explaining the difference between pre and post milking scores, especially in relation to score 1 cattle. It has been documented that experienced cattle veterinarians only have 65% intra-rater agreement (Garcia and others 2015). While veterinary students were found to have a higher interrater variability (variation between scorers) with an 82% agreement (SchlageterTello 2014, Garcia and others 2015). The scoring in this paper was conducted by a final year veterinary student. Their lack of experience was mitigated by them conducting their first scoring session alongside an RoM’s accredited scorer to calibrate their scoring. The intra-rater agreement demonstrated by Schlageter-Tello (2014) suggests that their scoring should stay consistent after being calibrated. The scores being conducted by a single scorer over several consecutive sessions provides limitations due to concerns about scorer fatigue and bias developing as familiarity with the cattle develops. Due to the scope of the study it was not possible to have multiple scorers or to spread the scores out over more days. This limitation needs to be taken into context when assessing the results of this study. The results of this study along with the current literature suggest mobility scoring post milking as the optimal time to mobility score. These findings could have ramifications on how milk contracts consider how they want scoring conducted as both the Red Tractor Assurance scheme and private milk processing contracts have placed a greater focus on lameness and regular mobility scoring. To minimise environmental effects on mobility scores the pre milking scores were conducted as the cows entered the collecting yard and post milking scores just after they left the milking parlour. This was to minimise the effects that the type and quality of pathways may have had on mobility scores (Chesterton and others 1989, Whay 2002). Collecting yards and milking parlours across the UK follow the same basic principles for their design and construction (Samer and others 2008) with the majority using the same construction materials creating a relatively uniform scoring environment within the collecting yards across farms. Although this gave a uniform area to score, the rest of the farm’s conditions were highly variable and may have influenced mobility scores. Several scoring systems were considered for this study such as the Sprecher Back Arch Scoring (Sprecher and others 1997) and the Manson and Leaver (1988) Scoring system but these were rejected in favour of the AHDB system. This was based on both the scorer’s familiarity with the AHDB system and its current standing as the industry standard scoring system. Whay (2002) suggests the ideal scoring system should not encourage the collection of more data than is needed. They also highlight the fluidity of movement, willingness to walk and claw placement amongst other factors that are key for successful scoring, which the AHDB system appears to focus on when compared to other available scoring systems. It is important to recognise that no mobility scoring system is able to accurately differentiate between abnormal mobility and true lameness (Grimm and others 2018). This is due to the aspects considered in mobility scoring being present in both lameness and gait abnormalities. One of the limitations of this study is that due to time restraints the observer was unable to take any breaks between farms. Due to this, by the end of the study, fatigue may have affected the scorer’s perception of scores. Another limitation encountered was by scoring the same farm multiple times a day over multiple days, it is possible that the observer was scoring with previous biases based on the memory of the cattle’s previous scores. This may have led to some scores conducted on the later visits being impacted by the scorer’s memory bias. It was not possible to mitigate this risk with the scope of the study, meaning it needs to be considered when analysing the results. For future studies, it would be advisable to make use of multiple RoM’s trained mobility scorers to assess cows pre and post milking and to score farms spread out over several days opposed to consecutive ones. CONCLUSION Both initial hypotheses were found to be incorrect. There was no significant difference in the number of cattle being assigned AHDB mobility scores 2

CATTLE PRACTICE VOLUME 31 PART 1 2023 133 and 3 pre and post milking. Contrary to the second hypothesis the majority of pre milking AHDB score 2 cattle decrease scores post milking. As discussed, the results highlight post milking as an optimal time to conduct mobility scores, while there are no clear clinical reasons to prioritise morning or afternoon scoring. This could have an influence on when the industry decides to mobility score for milk contracting. Further work is needed to see if these results are repeatable across a wider range of dairy and cattle systems. REFERENCES AHDB UK and EU Cow numbers (2023) https://ahdb.org.uk/ dairy/uk-and-eu-cow-numbers. Accessed March 28, 2023 AHDB Mobility Scoring (2021) https://ahdb.org.uk/ knowledge-library/mobility-scoring-how-to-score-your-cows. Accessed March 17, 2021 Animal Welfare Act (2006) https://www.legislation.gov.uk/ ukpga/2006/45/contents. Accessed March 22, 2021. Archer, S., Bell, N., Huxley, J. 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CATTLE PRACTICE VOLUME 31 PART 1 2023 134 Tierärztliche Praxis Ausgabe G: Großtiere/Nutztiere 44(01): 5-11 Sprecher, D.E.A., Hostetler, D.E., Kaneene, J.B. (1997) A lameness scoring system that uses posture and gait to predict dairy cattle reproductive performance. Theriogenology 47(6): 1179-1187 Von Keyserlingk, M.A.G., Olenick, D., Weary, D.M. (2008) Acute behavioral effects of regrouping dairy cows. Journal of Dairy Science 91(3): 1011-1016 Walker, A.M., Pfau, T., Channon, A., Wilson, A. (2010) Assessment of dairy cow locomotion in a commercial farm setting: The effects of walking speed on ground reaction forces and temporal and linear stride characteristics. Research in veterinary science 88(1): 179-187 Willshire, J., Bell, N.J. (2009) An economic review of cattle lameness. Cattle Practice 17(2): 136-141 Whay, H.R. (2002) Locomotion scoring and lameness detection in dairy cattle. In Practice 24: 444–449 Wylie, L.M., Gentle, M.J. (1998) Feeding-induced tonic pain suppression in the chicken: reversal by naloxone. Physiology & behavior 64(1): 27-30

CATTLE PRACTICE VOLUME 31 PART 1 2023 135 REDUCTION IN ANTIBIOTIC USE IN 800+ GB HERDS SUPPLYING 11 PROCESSORS FROM VETERINARY PRACTICE SALES DATA AND CHANGES IN FARMER BEHAVIOUR Analysing antibiotic use on farm is one piece of the jigsaw to striving for efficient food production from healthy animals. Robust data on antibiotic use is routinely collected from vet practices on behalf of participating milk processors through FarmAssist in conjunction with Kite Consulting. The programme has now seen data collected for five years and during this time a programme of targeted change management has seen significant results. These results have been achieved by a combination of factors: a sustained change management programme, aimed at farmers and their vets, run by Kite Consulting in conjunction with milk processors, as well as changes in Red Tractor Standards on the usage of antibiotics on farm and veterinary surgeons support. The change management programme drew on Kite Consulting’s experience in the area to combine technical information, seminars, on-farm events, peer to peer learning and the sharing of best practise. Through discussion and knowledge transfer dairy farmers have fully understood the need for antibiotic reduction on farm as a wider issue for society and acknowledge it is ‘the right thing to do’ and agree with the Red Tractor Standards. Dairy farmers now see the collection and review of antibiotic usage data as a normal part of their farm data capture. This programme demonstrates the value of benchmarking the technical data against RUMA targets, as an aid to behaviour change. Benchmarking financial data has long been used to generate change in the farming sector but the sharing of technical information in this way in conjunction with industry support, has helped to create demonstrable behavioural change. KEY FINDINGS 1. Robust farm level data is available from the dairy industry. 2. A reduction in antibiotic use has been seen over the recording period. 3. Herd size is not related to antibiotic use. 4. HP-CIA use has been reduced substantially. METHODOLOGY With consent from the producer, antibiotic sales data (both dispensed and prescribed) were collected from the producer’s vet practice. Data are collected and managed through FarmAssist (National Milk Records). The FarmAssist service calculates antibiotic use using standard European Medicine Agency methodology for mg/PCU, defined daily and course dose (DDD and DCD) measures. The data from FarmAssist can be reviewed as an individual farm, as a vet practice or milk processor cohort of farms (as here) or as a ‘national’ dataset. We acknowledge the support of milk processors and vets to provide these data and for their use in this work. References: 1. FarmAssist National Summary 2017-2021 – FarmAssist NMR, in press 2. AHDB. GB producer numbers. https://ahdb.org.uk/dairy/GB-producer-numbers. Published 2022 Authors: Kate Matthews (Kite Consulting), Ali Haggerty (Kite Consulting), Eamon Watson (FarmAssist NMR), Amy Blank (FarmAssist NMR) , Victoria Hicks (Kite Consulting) Glossary: HP-CIA: Highest Priority Critically Important Antibiotic CIA: Critically Important Antibiotic RUMA: Responsible Use of Medicines in Agriculture Alliance Year Farm (n) Mean Herd Size Mean mg/PCU HP-CIA Injectable (mg/PCU) HP-CIA Intramammary (DCDvet) Intra mammary tube – dry cow (DCDvet) Intra mammary tube – lactating cow (DCDvet) RUMA TARGET n/a n/a 21.00 0.461 0.166 0.43 0.62 2018 884 227 22.64 0.93 0.18 0.46 0.63 2019 656 233 22.17 0.23 0.05 0.45 0.53 2020 869 229 20.08 0.05 0.01 0.43 0.54 2021 878 233 20.28 0.03 0.00 0.41 0.45 2022 638 229 20.13 0.02 0.00 0.41 0.46 Total 1484 230 21.06 0.27 0.65 0.43 0.53 Table 1. Average antibiotic use against RUMA industry target for farms between 2018-2022 The overall trend from 2018 to 2022 has been a reduction in mg/PCU to below the RUMA target of 21mg/PCU. HP CIA use has dramatically reduced. Power BI Desktop Average Mg/PCU use by antibiotic classification 0 5 10 15 20 Year Mg/PCU 2018 2019 2020 2021 2022 1.1 2.5 2.3 2.2 1.9 1.4 19.0 19.6 17.8 18.3 18.7 22.64 22.17 20.08 20.28 20.13 Average of HP CIA Mg/PCU Average of CIA Mg/PCU Average of Non CIA Mg/PCU Power BI Desktop Average Mg/PCU use by antibiotic classification 0 5 10 15 20 Year Mg/PCU 2018 2019 2020 2021 2022 1.1 2.5 2.3 2.2 1.9 1.4 19.0 19.6 17.8 18.3 18.7 22.64 22.17 20.08 20.28 20.13 Average of HP CIA Mg/PCU Average of CIA Mg/PCU Average of Non CIA Mg/PCU Figure 2. Range of mg/PCU by year Figure 3. Average of HP CIA MG/KG, Average of CIA MG/KG and Average of Non CIA by Year Power BI Desktop Range in Mg/PCU by Year 2018 2019 2020 2021 2022 0 20 40 60 80 100 120 140 160 180 200 220 Mg/PCU Figure 1. Herd size vs Mg/PCU Power BI Desktop Herd Size v Mg/PCU 0 50 100 150 200 Herd Size Mg/PCU 0 500 1000 1500 2000 Year 2018 2019 2020 2021 2022 Pearson correlation coefficient 0.08 There is no relationship between herd size and antibiotic use, r value of 0.08, this is an important message for the veterinary industry, farming community and general public. There has been large reductions in the range of antibiotic use over the 5 year period, as well as a reduction in the mean mg/PCU. HP CIA use (Category B) has reduced substantially every year, and in 2022 93.6% of farms recorded no HP CIA use on farm compared to 21.0% in 2018. INTRODUCTION AND OBJECTIVES Antimicrobial resistance is recognised as a global threat to modern medicine and human health. There is now a continued focus on antibiotic use in agriculture and food producing animals (FPA). Public perception of antibiotic use in FPAs means supply chains need to be able to demonstrate a responsible attitude. Antibiotics are key medicines to help protect animal health and welfare. Zero use in not advocated. In order to identify areas where improvements could be made the first step is to monitor antibiotic usage over time and to engage farmers to stimulate behavioural change at the farm level. The objectives of this work were: 1. Describe antibiotic use in a subset of the GB dairy population 2. Compare results with industry level RUMA targets 3. Explore trends in antibiotic use 4. Demonstrate how change management programmes engage farmers in important issues and promote change at the farm level The top and bottom flat lines are the highest and lowest values, the box shows the interquartile ranges, the line in the center is the median and the dot being the mean.

CATTLE PRACTICE VOLUME 31 PART 1 2023 136 Colin Penny1 , Mark Crawshaw2, Jennifer Hutchison2, Hannah Schubert3, Steve Raphael4 1Zoetis UK Ltd, First floor, Birchwood Building, Springfield Drive, Leatherhead KT22 7LP . 2MBM Veterinary Group, 21 Hill Street, Kilmarnock, Ayrshire KA3 1HF. 3Torch Farm Vets, 15 Habat Enterprise Park, Clovelly Road industrial Estate, Bideford, Devon EX39 3HN. 4 Academy Vet Centre , 6 Academy Street, Stranraer DG9 7DR. Effect of GnRH Injection at AI in Winter Housed Dairy Cows • Up to 20% of cows have been shown to have delayed ovulation (> 40hrs) relative to the start of observed oestrus (Walker and others 1996) and these cows, if inseminated using the normal AM/PM rule, can be less fertile due to semen quality deterioration prior to ovulation. • Administering GnRH around the time of oestrus/AI following naturally occurring heats has also been shown to improve conception rates by around 12% or more in some studies however the effect is variable depending on the selection of cows submitted for treatment (Morgan and Lean 1993, Lopez-Gatius and others 2006). • Some studies have also shown higher progesterone levels in the period after AI in GnRH treated cows which could also enhance fertility (Ullah and others 1996; Kaim and others 2003). • A recent Canadian study (Burnett and others 2022) showed an improved conception rate of 6% in GnRH treated cows with the effect being greatest in cows that had poor oestrus expression as measured by activity monitors. • In contrast, a recent study by Hubner and others (2022) found no benefit in routine use of GnRH at AI for either increasing pregnancy rate or progesterone levels 7 days after AI. • 7 Holstein dairy herds were enrolled by 3 UK Vet practices during the period Nov 2020 - March 2021. • During this period cows were selected based on even /odd management number to receive GnRH (100 micrograms Gonadorelin; Acegon®, Zoetis UK Ltd) at the time of AI, or no treatment (control). • Cows observed in heat without any prior drug interventions were AI’d based on the AM/PM rule and given GnRH at AI. • Overall, 1218 cows received GnRH treatment at AI and 1337 acted as untreated controls. • A basic analysis of conception rate (CR) was done based on PD or service return data for all services that occurred during the study period. • In this limited field study there was no significant effect on CR when cows were given GnRH at the time of AI with no prior selection criteria applied. • As most cows will ovulate within 24 hrs of GnRH injection, treatment at, or prior to AI may benefit “delayed ovulator” cows by ensuring that LH surge and ovulation occurs within the window of semen survival, which may be around 24 hours at best for conventional semen. • Optimal timing for GnRH injection is likely to be around 4-10 hours after the start of standing oestrus with AI occurring 12-24 hours after oestrus detection. • GnRH injection at the time of AI is a compromise approach which may be less effective when sexed semen, with reduced lifespan relative to conventional semen, is being used. • The results of this study do not support the use of GnRH at the time of AI as a blanket approach to all services during the winter housing period in UK dairy herds, however a targeted approach may still be justified based on the risk of delayed ovulation in repeat breeder cows, cows with poor oestrus expression (Burnett and others 2022) and cows during periods of heat stress (Lopez-Gatius and others 2006). REFERENCES : Burnett, T.A., Madureira, A. M. L., Bauer, J.W., Cerri, R.L.A. (2022) Impact of GnRH administration at the time of artificial insemination on conception risk and its association with estrous expression. Journal of Dairy Science. 105:1743–1753 Hubner A.M, Canisso F, Peixoto P, Conley A.J., Lima F.S. (2022) Effect of gonadotropin-releasing hormone administered at the time of artificial insemination for cows detected in estrus by conventional estrus detection or an automated activity-monitoring system. Journal of Dairy Science 105:831–841 Kaim M., Bloch A., Wolfenson D., Braw-Tal R., Rosenberger M., Voet H., Folman Y (2003). Effect of GnRH administered to cows at the onset of oestrus on timing of ovulation, endocrine responses and conception. Journal of Dairy Science. 86:2012-2021 Lopez-Gatius F., Santolaria P., Martino A., Deletang F., De Rensis F.(2006) The effects of GnRH treatment at the time of AI and 12 days later on reproductive performance of high producing dairy cows during the warm season in north eastern Spain. Theriogenology 65:820–830 Morgan W.F., and Lean I.J.(1993) Gonadotrophin-releasing hormone treatment in cattle: a meta-analysis of the effects on conception at the time of insemination. Australian Vet Journal 70:205209 Ullah G., Fuquay JW., Keawkhong T., Clark BL., Pogue DE., Murphey EJ.(1996) Effect of gonadotrophin-releasing hormone at estrus on subsequent luteal function and fertility in lactating Holsteins during heat stress. Journal of Dairy Science 79:1950-1953 Walker WL., Nebel RL., McGilliard ML. (1996) Time of ovulation relative to mounting activity in dairy cattle. Journal of Dairy Science 79:1555–61 Apical sole area trimmed off PM to expose necrotic pedal bone The aim of this field study was to explore whether giving GnRH injection at the time of AI to all cows during the winter breeding period would enhance conception rate Results of treatment/control cow numbers and conception rates (CR) • No effect of treatment was observed, with the treated group having overall CR of 39% and control cows 40%. • There was considerable between-farm variation in the effect observed. INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSIONS

CATTLE PRACTICE VOLUME 31 PART 1 2023 137 Mastitis surveillance - data sharing and collaborations Swinson, V.1 , Biggs, A.2 , Bruno-McClung, L.3 , 1 APHA Thirsk, West House, Station Road, Thirsk, N Yorks, YO7 1PZ 2 Vale Veterinary Group, Cullompton, Devon, EX15 1TG 3 APHA Worcester, County Hall, Worcester, WR5 2LQ The last 20 years or so has seen significant changes in the methods of investigation and control of bovine mastitis. Twenty years ago, the predominant method of investigation was the submission of a milk sample to a commercial laboratory for culture and antimicrobial susceptibility testing (AST). The current picture involves a much more diverse range of investigation methods, which still includes culture at a commercial laboratory but, which also includes the use of milk recording data, onfarm mastitis testing, culture within a practice lab setting, and culture, PCR, or MALDI-ToF testing by a veterinary laboratory. The changes in investigation methods have been driven by various factors, with the main ones being: • Decreasing antimicrobial usage (1). • Improving the test turnaround time for results. • Receiving advice from a mastitis specialist. • Monitoring for antimicrobial resistance (AMR). Figure 1. Surveillance pyramid and the main new or re-emerging threats for which APHA undertake surveillance. All the investigation methods have pros and cons, and good progress has already been made in reducing antimicrobial usage within the cattle industry (2)(3). As with most disease investigations, it is important to assess the most suitable method of investigation on a case-by-case (or herd-by-herd) basis. One potential issue with the use of diverse methods of investigation is that this makes ‘seeing the bigger picture’ for mastitis more difficult. This could result in a delay in detecting trends for mastitis pathogens, or a delay in detecting unusual or concerning antimicrobial resistance. The Animal and Plant Health Agency (APHA) - Surveillance Intelligence Unit (SIU), is responsible for overseeing the scanning surveillance done by APHA. Scanning, or passive, surveillance looks to detect new, unusual, or changed patterns of disease. It involves the collection, analysis, and interpretation of data. For some diseases, with mastitis being one of them, it is important that data is gathered across multiple levels of the Surveillance Pyramid (Figure 1).

CATTLE PRACTICE VOLUME 31 PART 1 2023 138 During 2021 and 2022, APHA SIU has undertaken three pilot projects with the Veterinary Medicines Directorate (VMD), to investigate potential collaborations for mastitis bacteriology and antimicrobial susceptibility testing. These were: 1. On-farm mastitis testing: collaborations with private veterinary practices, to compare the results obtained by on-farm mastitis testing with those obtained by APHA bacteriology lab culture and to investigate the AST profiles. 2. Private veterinary laboratory (PVL) data sharing: discussions with PVLs about the potential for data sharing of test data, and other potential bacteriology collaborations. 3. Further investigation of unusual isolates or, isolates with concerning AMR: exploring collaborations with private vet practice labs, and commercial labs, to further investigate isolates that are of concern [from herds where mastitis cases were not responding well to treatment, or unusual isolates had been detected, or cases where there have been unusual or severe mastitis cases, or a sudden outbreak of mastitis (particularly at drying off (4))]. The results of these pilot projects are being analysed during 2022. The conclusions so far include: 1. On-farm testing: there is potential for reducing antimicrobial usage using the on-farm testing kits; there is potential for a shorter sampling to treatment interval, and therefore possibly quicker resolution of the mastitis; a wide variety of onfarm test kits are used; there is wide variation in the efficacy of this method of mastitis assessment, and testing, and consequent decision making; care should be taken with handling and disposal of the kits after the test is completed; and careful selection of farm clients for use this method is very important. The most common results reported using the on-farm tests were Streptococcus spp. (20%), Escherichia coli (15.19%), Streptococcus uberis (14%), and Staphylococcus spp. (10%). Excluding no growth and contaminated results, the percentages of gram-positive and gram-negative results were 70% and 30% respectively. Antibiotic choices varied depending on on-farm test result. When the on-farm test result was Escherichia coli, 50% were treated with antibiotics, 42% with NSAIDs, and 8% were given no treatment. When the on-farm test result was a gram-positive spp., 79% were treated with antibiotics. Overall, the most used antibiotic was procaine penicillin (66%). For the APHA testing, the most common isolates reported were Streptococcus uberis (20.3%), Staphylococcus aureus (13.5%), Escherichia coli (10.8%), and Bacillus licheniformis (6.76%). Excluding no growth and contaminated results, the percentages of gram-positive and gram-negative results were 71% and 29% respectively (but these did not all coincide with the results for on-farm testing). For the 58 isolates with both on-farm and APHA results reported, 24 matched to the level of identification given for the farm result (accuracy 41.4%). Thirteen result types (bacterial identification or no growth) were obtained for onfarm culture, compared to 25 for APHA testing. 2. Private veterinary laboratory (PVL) data sharing: there are several different incentives for labs to share their data; there are several different barriers to labs sharing their data; the test data is stored and transferred in different formats; and specifically for mastitis/AMR - not all bacteria are identified to species level, different diagnostic tests are used for bacterial identification, different methods of antimicrobial susceptibility testing (AST) are used, different antimicrobial panels are used, and different cut-off values are used for disc diffusion within the same AST method (5). Some preliminary data analysis has been undertaken to look at how the data could be used in the future. This could include assessment of the different mastitis pathogens detected (as a percentage of the total), and the percentages of a particular pathogen that were non-sensitive to an antimicrobial. Examples of these analyses were included in the 2020 and 2021 VARSS reports (6). 3. Further investigation of unusual isolates or, isolates with concerning AMR: both projects described above (1nandn2) have increased surveillance for bovine mastitis pathogens and their AMR profiles. If an atypical, or unusual, pathogen is detected, or one with concerning AMR, it usually will have further investigation such as by 16s sequencing, or whole genome sequencing, undertaken at APHA. APHA and VMD are monitoring for isolates of concern, such as MRSA. There is a large variation in dairy herd prevalence of livestock-associated MRSA between countries (7) (8). It is important that MRSA control measures are quickly introduced if it is diagnosed, as within-herd prevalence is linked to milking hygiene practices. The potential implications of MRSA within a herd are - for humans, the zoonotic implications for those handling the livestock; for cows, the MRSA is generally resistant to beta-lactam cephalosporin compounds; and for calves, it may have implications

CATTLE PRACTICE VOLUME 31 PART 1 2023 139 for calf health if they are fed waste milk. The findings of the pilot projects will be used to inform future initiatives, collaborations, and data sharing for mastitis, and potentially for other diseases or disease syndromes as well. APHA uses extended panels for AST, which include antimicrobials that are significant from a ‘One Health’ perspective, as well as those that are relevant for the treatment of the mastitis itself. As we move to systems where we are using less antimicrobials, it is still important to monitor mastitis trends, and ensure that we are not missing any new or re-emerging threats. Please contact Vanessa Swinson at: Vanessa. [email protected] for more information. LINKS 1. RUMA – Responsible Use of Medicines in Agriculture Alliance; https://www.ruma.org.uk/ 2. Farm Vet Champions - RCVS Knowledge; https:// knowledge.rcvs.org.uk/forms/register-your-interest-tobecome-a-farm-vet-champion/ 3. Arwain Vet Cymru: a National Veterinary Prescribing Champion Programme for Welsh Veterinary Practices — University of Bristol; https://research-information. bris.ac.uk/en/projects/arwain-vet-cymru-a-nationalveterinary-prescribing-champion-progr 4. Protocols for drying off can be found at https://ahdb. org.uk/knowledge-library/drying-off-dairy-cows 5. EUCAST - (European Committee on Antimicrobial Susceptibility Testing) New definitions of S, I and R can be found at: https://www.eucast.org/ newsiandr#:~:text=I%20%2D%20Susceptible%2C%20 increased%20exposure*%3A,at%20the%20site%20 of%20infection 6. Veterinary Antimicrobial Resistance and Sales Surveillance 2021 - GOV.UK (www.gov.uk); https:// research-information.bris.ac.uk/en/projects/arwainvet-cymru-a-national-veterinary-prescribing-championprogr 7. Frontiers | Livestock-Associated MethicillinResistant Staphylococcus aureus From Animals and Animal Products in the UK (frontiersin.org); https://www.frontiersin.org/articles/10.3389/ fmicb.2019.02136/full 8. LA-MRSA (publishing.service.gov.uk); chromeextension://efaidnbmnnnibpcajpcglclefindmkaj/https:// assets.publishing.service.gov.uk/government/uploads/ system/uploads/attachment_data/file/479015/LAMRSA.PDF

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