Ischemic teat necrosis (ITN) is a growing problem in the dairy industry characterized by teat lesions, necrosis, pruritus and automutilation. Despite the economic and welfare consequences, there is no treatment, and the etiology of the disease remains poorly understood. The aim of this study was to investigate ITN by analyzing its clinical presentation, potential risk factors and microbial involvement. Methods included collection of milk and swab samples from affected cows over a period of one-and-a-half years and completion of questionnaires by veterinarians and farmers. Microbial testing included PCR testing for Treponema spp. and cultural testing by anaerobic and aerobic incubation on blood agar. The results showed a high and significant prevalence of Treponema spp. and Staphylococcus aureus in affected teats compared to non-ITN-affected control teats, indicating their potential role in the development of ITN. Other factors such as edema and milking practices also appear to contribute to the tissue damage. First-lactation and early-lactation heifers are particularly at risk. In conclusion, ITN appears to have a multifactorial etiology with both infectious and non-infectious factors playing a role. Further research is needed to better understand the complex interplay of these factors and to develop effective prevention and management strategies.

Mastitis is one of the most common diseases of dairy cattle. It has a high impact on farm economy, farmers\' working time, and antimicrobial usage (AMU). Selective dry cow therapy (SDCT) is an effective means of reducing AMU without negatively affecting udder health. The objective of our study was to evaluate the impact of SDCT implementation on farmer\'s income, working time, and AMU, using a bioeconomic model. A stochastic dairy simulation model (DairyHealthSim) based on a weekly model was used to simulate herd dynamics, reproduction, milk production, culling decisions, health outcomes, and the management of health events. A specific module was developed for the simulation of quarter-level intramammary infection (IMI) acquisition and elimination during the lactation and dry-off periods, and 25 different farm settings were defined to represent herds with various udder health situations. We then defined 20 scenarios of SDCT by combining both the use of different thresholds of somatic cell count and milk bacteriology for treatment allocation and the use of internal teat sealant (ITS). All SDCT protocols had a low impact on farmer\'s income, and we identified some protocols with a positive farm gross margin (up to 15.83 CA$/dried- cow). We also found that adding an ITS to all cows led to greater economic gain. The application of SDCT had a low impact on farmers\' working time, except when milk bacteriology was used for decision-making. Antimicrobial treatment to all cows above 200,000 cells/mL at last control, with the use of ITS on all cows, seems a good choice in most dairy farms. These findings could be used to convince farmers to adopt this strategy at dry-off.

Biosecurity plays a crucial role in preventing the introduction of infectious diseases to a herd as well as the spread of diseases within or between animals and herds. In particular, biosecurity measures are crucial for maintaining animal health and reducing the need for the application of antibiotic substances for fighting the rising antibiotic resistance. The object of this cross-sectional study was to investigate the presence of biosecurity measures and their association with milk quality parameters, with a special focus on somatic cell count (SCC) - an indicator for udder health -, in small-scale mountain dairy farms. Therefore, for the very first time, the CLASSYFARM system was considered, which is a computer platform integrated into the Italian national veterinary portal, that processes a significant amount of data from various sources collected in the field or from other information systems (e.g. animal welfare, health status, biosecurity, antimicrobial use, slaughterhouse information). A total of 169 dairy farms were included in the study. Biosecurity measures, based on 15 questions required in the CLASSYFARM welfare assessment protocol, as well as information about husbandry systems, milking systems and pasture practices were gathered and combined with milk yield data, provided by the South Tyrolean dairy association. Farms only scored 44.00 points on average in a scoring system from 0.00 to 100.00 points that was be able to summarize 15 different biosecurity measures in one index. Our results show a clear negative correlation (-0.713) between the biosecurity index and somatic cell score (SCS) indicating that a higher level of biosecurity, which reflects the presence of biosecurity measures within a farm, is associated with lower SCC levels. Furthermore, we found significant correlations between SCS and milk production (-0.629), confirming that udder health is linked to higher milk production. Fat, protein, and the fat-to-protein ratio showed a positive correlation with SCS (0.281, 0.146, 0.106), likely to be caused by a concentration shift effect (dilution effect). Husbandry system, breed, milking system, and pasture practices seem to have an impact as well, but the main factor was the biosecurity score. This study highlights the importance of implementing biosecurity measures for ensuring animal health and thus productivity and quality in milk production, even in small-scale farms, which are characterized by limited structure availability and smaller herds compared to big dairy enterprises in the lowlands.

BACKGROUND: Intramammary infection is the result of invasion and multiplication of microorganisms in the mammary gland and commonly leads to mastitis in dairy animals. Although much has been done to improve cows\' udder health, mastitis remains a significant and costly health issue for dairy farmers, especially if subclinical. In this study, quarter milk samples from clinically healthy cows were harvested to detect pathogens via quantitative PCR (qPCR) and evaluate changes in individual milk traits according to the number of quarters infected and the type of microorganism(s). A commercial qPCR kit was used for detection of Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis. Quarter and pooled milk information of 383 Holstein, 132 Simmental, 129 Rendena, and 112 Jersey cows in 9 Italian single-breed herds was available.
RESULTS: Among the cows with pathogen(s) present in at least 1 quarter, CNS was the most commonly detected DNA, followed by Streptococcus uberis, Mycoplasma bovis, and Streptococcus agalactiae. Cows negative to qPCR were 206 and had the lowest milk somatic cell count. Viceversa, cows with DNA isolated in ≥ 3 quarters were those with the highest somatic cell count. Moreover, when major pathogens were isolated in ≥ 3 quarters, milk had the lowest casein index and lactose content. In animals with pathogen(s) DNA isolated, the extent with whom milk yield and major solids were impaired did not significantly differ between major and minor pathogens.
CONCLUSIONS: The effect of the number of affected quarters on the pool milk quality traits was investigated in clinically healthy cows using a commercial kit. Results remark the important negative effect of subclinical udder inflammations on milk yield and quality, but more efforts should be made to investigate the presence of untargeted microorganisms, as they may be potentially dangerous for cows. For a smarter use of antimicrobials, analysis of milk via qPCR is advisable - especially in cows at dry off - to identify quarters at high risk of inflammation and thus apply a targeted/tailored treatment.

UNASSIGNED: Subclinical mastitis in camels, an inflammation of the udder without visible signs, can reduce milk quality and raise bacteria levels. Regular monitoring of camel milk is crucial for consumer safety.
UNASSIGNED: A cross sectional study was conducted in Jigjiga city, Ethiopia to investigate the prevalence and characteristics of subclinical mastitis in she-camels. The study included 244 lactating she-camels from three privately-owned camel dairy farms, and a questionnaire survey was conducted with 60 camel owners.
UNASSIGNED: The overall prevalence of subclinical mastitis in she-camels was 10.6% (26/244), with no significant difference among the studied dairy farms. Risk factors that influenced the result of California Mastitis Test (CMT) included age and udder and leg hygiene. The study revealed that S. aureus was the most prevalent bacterium among the isolated bacteria, with a prevalence rate of 34.5%. This was followed by S. agalactiae, S. dysgalactiae, and Pasteurella multocida, with prevalence rates of 29.8, 19.4, and 16.2%, respectively. Among the isolated bacteria, 84.5% were sensitive to Erythromycin, 60% to Streptomycin, 44.7% to Oxytetracycline, and 36.7% to Tetracycline. Interviews with camel owners revealed that 66.7% used mixed herd grazing methods and reported feed shortage. Treatment practices for sick camels included modern veterinary drugs, traditional medicines, or a combination of both. The owners of camel dairy farms did not maintain proper hygiene practices during milking, such as not using soap when washing hands.
UNASSIGNED: Addressing camel mastitis necessitates access to alternative drugs, comprehensive herder training, and enhanced management practices.

Prevention of new intramammary infection (NIMI) during the dry period (DP) is essential to prevent the development of mastitis in dairy cows. To investigate risk factors for NIMI, 212 cows, comprising a total of 848 udder quarters, were examined in this study. Quarter milk samples were taken on the day of drying off and 7 ± 3 days after calving. Cow- and quarter-level associated risk factors were assessed at the beginning of the DP and after calving. In total, 7.1% of the udder quarters developed an NIMI between the samplings. Non-aureus staphylococci (40.4%) and Gram-negative pathogens (22.8%) were most frequently the cause of NIMI. The observed milk leakage prevalence was 16.7%, with a peak 24 h after drying off. Simultaneously, the udder pressure peaked 24 h after drying off. A significant correlation between milk yield on the day before drying off and milk leakage could be proven. Cows with quarters leaking milk produced an average milk yield of 28.32 kg on the day before drying off. Generalised linear mixed models and odds ratios were calculated to determine the significant risk factors for NIMI during the DP and early lactation. Quarters leaking milk had 3.4 higher odds for NIMI between the samplings compared to quarters without milk leakage. Quarters from cows with dirty udders had 3.1 higher odds of developing an NIMI between the samplings compared to quarters from cows with clean udders. The results of this study demonstrate the importance of dry cow management before drying off and during the critical period of active involution of the udder tissue.

There are no studies regarding the estimation of genetic parameters and genetic trends for reproductive traits and somatic cells in goats. Their knowledge allows optimization of selection schemes. The objective of this study was to estimate genetic parameters and genetic and phenotypic trends for age at first kidding (AFK), kidding interval (KIN) and somatic cell score (SCS). Analyses were conducted within and across seven US goat breeds, namely, Nubian (NU), Alpine (AL), LaMancha (LM), Toggenburg (TO), Saanen (SA), Nigerian Dwarf (ND) and Oberhasli (OB), and a set of all of these breeds (AB). The restricted maximum likelihood methodology and trivariate animal models were used. Genetic and phenotypic trends were estimated using regression models. The average and standard deviation of AFK, KIN and SCS for AB were 573.6 ± 178.5 days, 418.8 ± 125.5 days and 4.67 ± 2.23 Log2, respectively. The heritabilities (h2) and standard errors of AFK, KIN and SCS for AB were 0.28 ± 0.02, 0.04 ± 0.02 and 0.22 ± 0.01, respectively. The h2 ranged from 0.15 (SA) to 0.37 (NU) for AFK, from 0.04 (AB) to 0.10 (AL) for KIN, and from 0.11 (TO) to 0.26 (LM and ND) for SCS. Genetic correlations between AFK and KIN and between AFK and SCS for AB were positive and weak (0.07 and 0.12, respectively) but significant (P < 0.01). Genetic correlations between SCS and KIN were significant (P < 0.01) for all the breeds and ranged from -0.15 (NU) to 0.44 (AL). Genetic correlations between AFK and SCS in the NU and AL breeds were similar (approximately 0.21). A positive genetic trend was found for KIN in the SA breed, which caused an increase in the number of days between consecutive kiddings. The genetic trend of SCS for the NU, AL and ND breeds was negative and decreased annually, which is beneficial for producers. These first results show the intensity and direction of some favorable/unfavorable relationships between AFK or KIN and SCS Log2 in some U.S. goat genetic groups.

The dairy industry is reshaping itself and becoming commercialized in Pakistan due to the increased demand for milk to overcome the shortage. Exotic breeds such as Holstein Friesian, a high milk producing breed have started being reared more on farms in Pakistan. Along with other issues, mastitis does affects the milk production of this breed. The objective of this study was to evaluate the milk composition in terms of bacterial communities in Holstein Friesian reared in Punjab, Pakistan and alteration in microbial composition with healthy and mastitic udder. Milk samples (n = 36) from farms rearing Holstein Friesian were collected. Among these samples, 05 samples from each three groups, HHF(healthy), CHF (clinical mastitis) and SHF (subclinical mastitis), based on their udder health condition, were processed using the 16 S r=RNA gene based technique. Diversity assessment as carried out by alpha diversity indices showed that milk samples from the udder infected with clinical mastitis were the least diverse and those from the healthy udder were more diverse. Beta diversity across samples showed a scattered pattern suggesting overlap amongst bacterial communities across different groups samples as depicted by PCA plots of beta diversity indices. The taxonomic profile revealed that Proteobacteria Firmicutes, Bacteroidota and Actinobacteriota were the major phyla detected across all groups. Proteobacteria dominated the HHF and SHF group while abundance of Firmicutes was higher in CHF group. Differences at other levels including order, genus and species were also recorded. The overall picture concludes that diverse microbiota is associated with different udder health conditions.

Milk recording is a critical tool in dairy farming, providing individual cow information. When used effectively, this data contributes to on-farm productivity, herd health management decisions and supports prudent veterinary prescribing of antimicrobials. Although an industry and government priority, uptake has been relatively slow in Ireland. This multi-methods, three-part study aimed to gain a comprehensive understanding of the benefits to farm performance, and factors driving uptake of milk recording on Irish dairy farms. It involved an economic analysis of N=516 farms from 2008-2019, a workshop with N=26 stakeholders and an online survey of N=197 non-milk-recording farmers. Quantitative and qualitative data were analysed using econometric models and thematic analysis respectively. Results were synthesised using the COM-B model to gain a deeper understanding of what drives the target behaviour. The study revealed that agricultural education, farm location, farm specialisation in dairy and membership of a farmer discussion group were the main factors influencing uptake of milk recording. Milk recording was associated with a €39.04/cow increase in gross margin, a 177.58 litres/cow increase in milk yield and a reduction of 13,450 cells/ml in bulk milk tank somatic cell count readings. Infrastructural constraints, cost, lack of benefits and workload were the most reported perceived barriers to milk recording by farmers. The Behaviour Change Wheel illustrates how to utilise findings and systematically develop future interventions to increase milk recording uptake. This study highlights the importance of a multi-methods approach to agricultural technology adoption and the need for evidence-based methodology when developing behaviour change interventions.

Early detection of intramammary infection (IMI) can improve animal health and welfare in dairy herds. The implementation of sensors and automatic milking systems (AMS) in dairy production inherently increases the amount of available data and hence also the potential for new approaches to mastitis management. To utilize the full potential of data from AMS and auxiliary sensors, a better understanding of physiological and pathological changes in milking traits associated with different udder pathogens may be imperative. This observational study aimed to investigate pathogen-specific patterns in milking traits recorded in AMS. The milking traits included; online somatic cell count (OCC), electrical conductivity (EC), milk yield (MY), and average milk flow rate (AMF). Data were collected for a study period of 2 years and included 101 492 milkings from 237 lactations in 169 cows from one farm. Measurements of OCC were recorded at cow-level and data on EC, MY, and AMF were obtained at quarter-level. In addition to the data obtained from the AMS, altogether 5756 quarter milk samples (QMS) were collected. Milk samples were obtained monthly for bacteriological culturing. We included findings of 13 known mastitis pathogens to study pathogen-specific patterns in milking traits. These patterns were compared with those in a baseline group consisting of cows that did not have any positive milk culture results throughout the lactation period. Patterns of the milking traits are described for all positive samples both across 305 d in milk (DIM), and in the 15-d period before a positive bacteriological sample. The association between a positive sample and the milking traits (ln(OCC), EC-IQR; the ratio between the quarter with the highest and the quarter with the lowest level of EC, and MY) for the 15 d before the detection of a pathogen was assessed using mixed effects linear regression models. All pathogens were associated with alterations in the level and variability of ln(OCC) relative to lactations with no positive bacteriological samples. A positive sample for Staph. aureus was associated with increased values for MY during the 15 d before a positive diagnosis. It is biologically plausible to interpret changes in OCC and EC-IQR as consequences of an intramammary infection (IMI), while higher MY in bacteriologically-positive cows is most likely linked to the increased risk of infection in high-yielding cows. In this study, the most notable changes in the traits (OCC and EC-IQR) were observed for Staph. aureus and Strep. dysgalactiae, followed by Strep. simulans, Strep. uberis, and Lactococcus lactis. Even if we did not detect significant associations between positive bacteriology and EC-IQR, visual assessment and descriptive statistics indicated that there might be differences suggesting that it could be an informative trait for detecting infection when combined with OCC and possibly other relevant traits using machine learning algorithms.