Search Results (328)

This cross-sectional study aimed to (a) determine the apparent prevalence of mastitis pathogens and (b) to identify risk factors for intramammary infections (IMIs) at the herd level in dairy herds in Bavaria, Germany. A stratified random sample of 305 herds was selected based on herd size, administrative district, and season. During the farm visits between July 2023 and July 2024, management data were recorded, quarter milk samples (QMSs) from 14,700 lactating cows were collected aseptically and analyzed, and the somatic cell count (SCC) at the quarter level was determined. Risk factors for the within-herd prevalence of Staphylococcus (S.) aureus, Streptococcus (Strep.) uberis, Strep. dysgalactiae, and non-aureus staphylococci (NAS) were analyzed by negative binomial regression, while risk factors for the presence of Escherichia (E.) coli and Strep. agalactiae IMIs on dairy farms were identified by logistic regression. The most frequently detected pathogens were NAS, found in 5.0% of all QMSs (n = 57,251), followed by Strep. uberis (1.9%) and S. aureus (1.8%), Strep. agalactiae (0.2%), and E. coli (0.1%). At the herd level, NAS, Strep. uberis, S. aureus, and Strep. dysgalactiae were found in 92%, 69%, 67%, and 57% of farms, respectively. Risk factors for increased within-herd prevalence included automated milking systems (NAS), organic production (Strep. uberis, S. aureus), straw bedding (Strep. uberis), and lack of bedding or mattress cubicles (Strep. dysgalactiae). The odds for a herd to be positive were increased with audible liner slips (E. coli) and the irregular cleaning of water troughs (Strep. agalactiae), and without a maintenance agreement for milking equipment (Strep. agalactiae). These results provide valuable insights into options for the targeted prevention of IMI. Full article

The DHI data is crucial for monitoring the udder health of dairy cows during the breeding process. This study aimed to investigate the factors influencing milk production in dairy cows throughout this period. We analyzed DHI data from Holstein dairy cows in the Heilongjiang region, alongside the incidence of mastitis. The findings revealed that high-yielding cows demonstrated significantly higher peak milk yield days, peak milk yield, urea nitrogen levels, 305-day milk yield, and persistency (p < 0.0001) compared to their low-yielding counterparts. Conversely, high-yielding cows exhibited lower protein rates, fat-to-protein ratios, and milk fat rates (p < 0.0001). Additionally, the somatic cell count (SCC) in high-yielding cows was significantly lower than that in low-yielding cows (p < 0.0001). The multivariate linear regression analysis of the DHI data indicated that parity was the primary determinant affecting both milk yield and SCC. Statistical analysis of cows with clinical mastitis revealed that those experiencing a single episode of clinical mastitis during the lactation period were predominantly in their first and second parities, while recurrent cases were primarily observed in the second and third parities. These results suggest that as the number of lactations increases, the SCC also rises, reflecting the cumulative impact of parity on the udder health of dairy cows. Full article

Mycotoxins are common feed contaminants that can affect the health, immune function, and productivity of ruminants by causing oxidative stress and organ dysfunction. In this field study, the effects of a phytogenic multicomponent mycotoxin detoxifier on oxidative status, liver function, udder health, and productive parameters were investigated in dairy ewes. One hundred clinically healthy ewes were randomly assigned to either a control group or a treatment group, with the latter receiving 1.5 kg/ton of the detoxifier over a 90-day period during lactation. The detoxifying agent contained adsorptive clays as well as phytogenic ingredients such as silymarin and curcumin, which are known for their hepatoprotective and antioxidant properties. Blood, milk, and colostrum samples were collected and analyzed for oxidative stress markers (TBARS and protein carbonyl (CARBS)), total antioxidant capacity (TAC), liver enzymes (ALT, AST, and ALP), and milk quality parameters (fat, protein, and solid content). Clinical assessments included mastitis scoring, udder inflammation, and fecal consistency. The treated ewes showed a statistically significant reduction in blood plasma and milk oxidative stress markers and liver enzyme levels while at the same time improving the fat and solid content of the milk. The incidence and severity of mastitis, udder reddening, and lactation abnormalities were lower in the treatment group. Brix refractometry indicated improved colostrum quality in the treated ewes. These results suggest that the detoxifier improved the oxidative balance, liver function, and overall health and productivity of dairy ewes under field conditions, supporting its use as a practical nutritional measure. Full article

The kinetics of milk release is influenced by several factors, including the milking facility, which affects the milk emission profile and quality. In dairy goats, the typical working vacuum level is 41–44 kPa; higher levels negatively impact health, quality, and milkability traits. This study, which was conducted on a commercial dairy farm located in the Latium region (central Italy), evaluates the impact of two vacuum levels (38 kPa and 42 kPa) on the milk emission profile and somatic cell content in Saanen goats. Statistical analysis (one-way ANOVA) of 400 milk flow curves recorded from 100 goats in four different afternoon milking sessions (200 at 42 kPa and 200 at 38 kPa) showed no significant differences in terms of milk yield, total milking time, or bimodal curve percentage when using two different operating vacuum levels. However, the milk emission time was longer at 38 kPa (1.86 vs. 1.71 min), while the peak flow rate (1.04 vs. 0.96 kg/min) and blind time (0.32 vs. 0.24 min) were higher at 42 kPa. Somatic cell content decreased significantly as the working vacuum level decreased (2470 vs. 2167 × 1000 cells/mL). This is in line with current studies which suggest that high vacuum levels increase the risk of udder injury and intramammary infection. In conclusion, adjusting the milking machine to a working vacuum level of 38 kPa, and performing proper maintenance and routine checks, significantly improves somatic cell content, and, consequently, milk quality, in goats. Full article

This study aimed to examine the relationship between a high somatic cell count (SCC) in cows and milk quality during the hot season in different breeds. Milk samples from 500 cows in the hot season and 431 in the cold season of 2022 were collected across 39 farms in Santa Catarina, Brazil. The samples were analyzed for SCC, milk composition, and physical attributes. Cows were also evaluated for udder depth, udder clearance, teat-end condition, and leg and udder cleanliness. Based on the SCC levels, cows were categorized as low (≤200,000 cells/mL), medium (>200,000 and ≤615,000), or high (>615,000). Data were analyzed by ANOVA with a statistical model that included the effects of the SCC class, season, days in milk, parity, genetic group, and the interaction of the SCC level and season. The results showed that cows with a high SCC produced less milk with lower component levels but higher chloride content. Milk from the hot season had lower acidity and reduced component levels. The impact of SCC on the physical traits of milk did not vary with season. Furthermore, cows with deeper udders and lower udder clearance were more likely to have a high SCC, regardless of genetics. Both a high SCC and hot temperatures independently compromised milk yield and quality, thereby increasing the risk of culling. Therefore, improving udder conformation and avoiding cows with deep udders may help to reduce SCC levels. Full article

Mastitis is a significant challenge in the buffalo industry, affecting both milk production and animal health and resulting in economic losses. This study presents the first fully automated AI-driven thermal imaging system integrated with robotic milking, specifically developed for the real-time, non-invasive monitoring of udder health in Italian Mediterranean buffalo. Unlike traditional approaches, the system leverages the synchronized acquisition of thermal images during milking and compensates for environmental variables through a calibrated weather station. A transformer-based neural network (SegFormer) segments the udder area, enabling the extraction of maximum udder skin surface temperature (USST), which is significantly correlated with somatic cell count (SCC). Initial trials demonstrate the feasibility of this approach in operational farm environments, paving the way for scalable, precision diagnostics of subclinical mastitis. This work represents a critical step toward intelligent, automated systems for early detection and intervention, improving animal welfare and reducing antibiotic use. Full article

The somatic cell count (SCC) and differential somatic cell count (DSCC) are proxies for the udder health of dairy cattle, regarded as the criterion of mastitis identification with healthy, suspicious mastitis, mastitis, and chronic/persistent mastitis. However, SCC and DSCC are tested using flow cytometry, which is expensive and time-consuming, particularly for DSCC analysis. Mid-infrared spectroscopy (MIR) enables qualitative and quantitative analysis of milk constituents with great advantages, being cheap, non-destructive, fast, and high-throughput. The objective of this study is to develop a dairy cattle udder health status diagnostic model of MIR. Data on milk composition, SCC, DSCC, and MIR from 2288 milk samples collected in dairy farms were analyzed using the CombiFoss 7 DC instrument (FOSS, Hilleroed, Denmark). Three MIR spectral preprocessing methods, six modeling algorithms, and three different sets of MIR spectral data were employed in various combinations to develop several diagnostic models for mastitis of dairy cattle. The MIR diagnostic model of effectively identifying the healthy and mastitis cattle was developed using a spectral preprocessing method of difference (DIFF), a modeling algorithm of Random Forest (RF), and 1060 wavenumbers, abbreviated as “DIFF-RF-1060 wavenumbers”, and the AUC reached 1.00 in the training set and 0.80 in the test set. The other MIR diagnostic model of effectively distinguishing mastitis and chronic/persistent mastitis cows was “DIFF-SVM-274 wavenumbers”, with an AUC of 0.87 in the training set and 0.85 in the test set. For more effective use of the model on dairy farms, it is necessary and worthwhile to gather more representative and diverse samples to improve the diagnostic precision and versatility of these models. Full article

This study analyzes the use of a lightweight image-based deep learning model to classify dairy cows into low-, medium-, and high-milk-yield categories by automatically detecting the udder region of the cow. The implemented model was based on the YOLOv11 architecture, which enables efficient object detection and classification with real-time performance. The model is trained on a public dataset of cow images labeled with 305-day milk yield records. Thresholds were established to define the three yield classes, and a balanced subset of labeled images was selected for training, validation, and testing purposes. To assess the robustness and consistency of the proposed approach, the model was trained 30 times following the same experimental protocol. The system achieves precision, recall, and mean Average Precision (mAP@50) of 0.408 ± 0.044, 0.739 ± 0.095, and 0.492 ± 0.031, respectively, across all classes. The highest precision (0.445 ± 0.055), recall (0.766 ± 0.107), and mAP@50 (0.558 ± 0.036) were observed in the low-yield class. Qualitative analysis revealed that misclassifications mainly occurred near class boundaries, emphasizing the importance of consistent image acquisition conditions. The resulting model was deployed in a mobile application designed to support field-level assessment by non-specialist users. These findings demonstrate the practical feasibility of applying vision-based models to support decision-making in dairy production systems, particularly in settings where traditional data collection methods are unavailable or impractical. Full article

Neonatal calves possess an immature and naïve immune system and are reliant on the intake of maternal colostrum for the passive transfer of immunoglobulins. Maternal antibodies delivered to the calf via colostrum, are crucial to prevent calfhood diseases and death. Failure of transfer of passive immunity (FTPI) is a condition in which calves do not acquire enough maternal antibodies, mostly in the form of IgG, due to inadequate colostrum quality or delayed colostrum feeding. The diagnosis and risk factors for FTPI have been widely studied in dairy cattle; however, in beef calves, the research interest in the topic is relatively recent, and the most adequate diagnostic and preventative methods are still in development, making it difficult to define recommendations for the assessment and prevention of FTPI in cow–calf operations. The objective of this scoping review is to identify the published literature on best practices for colostrum management and transfer of passive immunity (TPI) in neonatal beef calves. The literature was searched using three electronic databases (CAB Direct, Scopus, and PubMed) for publications from 2003 to 2025. The search process was performed during the period from May to July 2023, and was repeated in January 2025. All screening processes were performed using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia). A total of 800 studies were initially identified through database searches. After removing duplicates, 346 studies were screened based on their titles and abstracts, leading to the exclusion of 260 studies. The remaining 86 studies underwent full-text screening, and 58 studies were considered eligible for data extraction. Hand-searching the references from published review papers on the subject yielded an additional five studies, bringing the total to 63 included articles. The prevalence of FTPI has been estimated to be between 5.8% and 34.5% in beef calves. Factors studied related to colostrum management include quality and quantity of colostrum intake, the timing and method of colostrum feeding, and the microbial content of the colostrum. Studies on risk factors related to the calf include the topics calf sex, twin status, calf vigor, weight, month of birth, cortisol and epinephrine concentrations, and the administration of nonsteroidal anti-inflammatory drugs to calves after difficult calving. The dam-related risk factors studied include dam body condition score and udder conformation, breed, parity, genetics, prepartum vaccinations and nutrition, calving area and difficulty, and the administration of nonsteroidal anti-inflammatory drugs at C-section. Most importantly for beef systems, calves with low vigor and a weak suckling reflex are at high risk for FTPI; therefore, these calves should be given extra attention to ensure an adequate consumption of colostrum. While serum IgG levels of < 8 g/L or < 10 g/L have been suggested as cutoffs for the diagnosis of FTPI, 16 g/L and 24 g/L have emerged as cutoffs for adequate and optimal serum IgG levels in beef calves. Several field-ready diagnostics have been compared in various studies to the reference standards for measuring indicators of TPI in beef calves, where results often differ between models or manufacturers. Therefore, care must be taken when interpreting these results. Full article

Milk quality has a growing importance for farmers as component-based pricing becomes more widespread. Food quality and precision manufacturing techniques demand consistent milk composition. Udder health, general cow condition, environmental factors, and especially feed composition all influence milk quality. The large volume of routinely collected milk data can be used to build prediction models that estimate valuable constituents from other measured parameters. In this study, casein was chosen as the target variable because of its high economic value. We developed a multiple linear-regression model and a feed-forward neural network model to estimate casein content from twelve commonly recorded milk traits. Evaluated on an independent test set, the regression model achieved R² = 0.86 and RMSE = 0.018%, with mean bias = +0.003% and slope bias = −0.10, whereas the neural network improved performance to R² = 0.924 and RMSE = 0.084%. In silico microgreen inclusion from 0% to 100% of dietary dry matter raised the predicted casein concentration from 2.662% to 3.398%, a relative increase of 27.6%. To extend practical applicability, a simulation module was created to explore how microgreen supplementation might modify milk casein levels, enabling virtual testing of dietary strategies before in vivo trials. Together, the predictive models and the microgreen simulation form a cost-effective, non-invasive decision-support tool that can accelerate diet optimization and improve casein management in precision dairy production. Full article

Overmilking occurs when the teat cups remain attached to the udder during milking, even though there is little or no milk flow. This puts pressure on the teat tissue and reduces milk production due to longer milking times, meaning fewer cows are milked per hour. Therefore, the correct removal of the teat cup at the end of mechanical milking is crucial for the milking process. The aim of this study was to describe the factors influencing automatic teat cup removal (ATCR) at the end of mechanical milking and to demonstrate its importance for udder health, milk production and milk quality. There are considerable differences between milking system suppliers and countries regarding the minimum removal of the teat cup at the end of the milking process. However, to ensure good milk quality, prevent teat damage and reduce the risk of mastitis, it is important to shorten the working time of the milking machine on the udder in both automatic and conventional milking systems. For this reason, several studies have shown that increasing the milk flow switch point effectively reduces milking time, especially in automatic milking systems where dairy cows are milked more than twice a day. However, when the ATCR setting was increased above 0.5 kg·min⁻¹, milk production decreased, and the number of somatic cells in the milk produced increased. Therefore, the use of ATCR at a milk flow rate of 0.2 kg·min⁻¹ significantly increased milk production, improved milk quality and maintained udder health when a low vacuum level (34–36 kPa) was used in milking machines such as MultiLactor and StimuLactor (Siliconform, Germany). In conclusion, ATCR at a milk flow of 0.2–0.3 kg·min⁻¹ is a useful level to achieve various goals on dairy farms when a low vacuum of 34–36 is used in the milking machine. If the milking machine uses a higher vacuum, it is possible to program a higher ATCR at a milk flow of up to 0.5 kg·min⁻¹. Full article

Clinical mastitis in small ruminants is usually seen with an incidence of less than 5% and most cases, especially with hyperacute evolution, are not referred for hospital care. During the 5-year survey, 16 goats and 7 sheep, totaling 23 small ruminants, met the inclusion criteria with a definitive diagnosis of clinical mastitis. Clinical signs ranged greatly among cases, varying from septic state in hyperacute cases, and enlarged, pendulous udder associated with chronic pain and abnormal gait in chronic cases. Microbiological culture revealed a wide array of bacterial pathogens, including Staphylococcus aureus, Escherichia coli, Streptococcus spp., and Pasteurella spp. In vitro antimicrobial susceptibility profiles varied greatly among bacteria isolates, ranging from sensitive to all tested antimicrobials to a multi-resistant profile. Pathological features included hyperemia and dark red areas of necrosis in the skin, marked hyperemia of the affected gland at the cut surface, lactiferous ducts and gland cisterns filled by cloudy or suppurative fluid, abscesses, and hardness of the mammary gland parenchyma. This retrospective study highlights the multifactorial nature and clinical variability of mastitis in small ruminants, demonstrating its significant impact on animal health, welfare, and production. Full article

Lipopolysaccharide (LPS) endotoxin is a well-characterized microbe-associated molecular pattern (MAMP) that forms the outer membrane of both pathogenic and commensal Gram-negative bacteria. It plays a crucial role in triggering inflammatory disorders such as mastitis, acidosis, and septicemia. In heifers, an LPS challenge induces a dynamic stress response, marked by elevated cortisol levels, increased body temperature, and altered immune function. Research indicates that LPS administration leads to a significant rise in cortisol post-challenge. Building on this understanding, the present study aimed to estimate genetic parameters for serum cortisol response to LPS challenge in Holstein heifers and its linear associations with production, health, reproduction, and conformation traits. Additionally, a genome-wide association study (GWAS) was conducted to identify genetic regions associated with cortisol response. A total of 252 animals were evaluated for cortisol response, with correlations estimated between cortisol levels and 55 genomic breeding values for key traits. Genetic parameters and heritability for cortisol response were estimated using Residual Maximum Likelihood (REML) in the Blupf90+ v 2.57 software. Single-Step GWAS (ssGWAS) employing a 10-SNP window approach and 42,123 SNP markers was performed to identify genomic regions that explained at least 0.5% of additive genetic variance. Finally, candidate genes and QTLs located 50 kb up and downstream of those windows were identified. The cortisol response showed significant but weak linear associations with cystic ovaries, body maintenance requirements, lactation persistency, milk yield, and protein yield (p-value ≤ 0.05) and showed suggestive weak linear associations with udder texture, clinical ketosis, heel horn erosion, and milking speed (p-value ≤ 0.15). Cortisol response showed significant additive genetic variance, along with moderate heritability of 0.26 (±0.19). A total of 34 windows explained at least 0.5% of additive genetic variance, and 75 QTLs and 11 candidate genes, comprising the genes CCL20, DAW1, CSMD2, HMGB4, B3GAT2, PARD3, bta-mir-2285aw, CFH, CDH2, ENSBTAG00000052242, and ENSBTAG00000050498, were identified. The functional enrichment analysis allowed us to infer two instances where these gene products could interfere with cortisol production: the first instance is related to the complement system, and the second one is related to the EMT (Epithelium–Mesenchymal Transition) and pituitary gland formation. Among the QTLs, 13 were enriched in the dataset, corresponding to traits related to milk (potassium content), the exterior (udder traits, teat placement, foot angle, rear leg placement, and feet and leg conformation), production (length of productive life, net merit, and type), and reproduction (stillbirth and calving ease). In summary, the cortisol response to LPS challenge in Holstein heifers seems to be moderately heritable and has weak but significant linear associations with important production and health traits. Several candidate genes identified could perform important roles, in at least two ways, for cortisol production, and QTLs were identified close to regions of the genome that explained a significant amount of additive genetic variance for cortisol response. Therefore, further investigations are warranted to validate these findings with a larger dataset. Full article

In recent decades, Blanket Dry Cow Therapy (BDCT) has been regarded as a cornerstone strategy for the control of mastitis in dairy cows during the dry period. However, concerns regarding the rising incidence of antibiotic resistance and the associated zoonotic risks have prompted a paradigm shift, leading to intensified research into alternative management approaches. In response, many countries have adopted a more targeted approach, known as Selective Dry Cow Therapy (SDCT), which focuses on the therapeutic use of antibiotics, administered only to cows or quarters that are either infected or at high risk of infection during the dry period. This review provides a comprehensive synthesis of the scientific literature regarding the main methods for selecting animals for SDCT, the impact of this strategy on udder health, milk production, farm economics, and antibiotic consumption, as well as the factors that may influence its effectiveness. Over time, a range of methods have been developed to identify infected animals, including bacteriological culture, somatic cell count (SCC), differential somatic cell count (DSCC), and the California Mastitis Test (CMT), which are often used alone or in combination with clinical mastitis history and/or parity. Among these methods, SCC has proven to be the most economically viable and best suited for practical use, while its combination with DSCC has been shown to significantly enhance diagnostic accuracy. According to the studies reviewed, SDCT is a safe and effective strategy for maintaining udder health and farm profitability, as long as infected cows are accurately identified, and internal teat sealants are used in quarters not treated with antibiotics during the dry period. However, since udder health is influenced by herd characteristics, management practices, and regional pathogens, the findings cannot be universally applied and must be adapted to each herd’s specific conditions. Full article

Mastitis is a common condition in dairy cattle that causes huge losses globally. The inflammation is caused by the invasion of the teat canal by pathogens, including hard-to-control single-cell microalgae of the genus Prototheca. The aim of the study was the in vitro comparison of the antimicrobial properties of 10 selected essential oils (EOs) and amphotericin B (AMB) against Prototheca bovis strains (PRO3 and PRO7) from different regions in Poland. The antialgal effect was estimated by using toxicity tests. The chemical composition of the EOs was determined by using gas chromatography coupled with mass spectrometry. The tested EOs had significant cytotoxic effects on algal viability. A statistical analysis of the results revealed that the highest biocidal potential, at a concentration of 2%, was demonstrated by lavender, rosemary, and oregano oils, reducing the survival of the Prototheca bovis strains, on average, by 51.21%, 45.83%, and 45.15%, respectively. In comparison, AMB reduced algal viability by an average of 88% compared with the control groups. Further research into the utilization of the biocidal properties of lavender, rosemary, and oregano oil against Prototheca spp. may help to develop new forms of treatments against mastitis caused by this pathogen in the future. Full article