Search Results (353)

Dairy cow body temperature is a key physiological indicator that reflects metabolic level, immune status, and environmental stress responses, and it has been widely used for early disease recognition. Infrared thermography (IRT), as a non-contact imaging technique capable of remotely acquiring the surface radiation temperature distribution of animals, is regarded as a powerful alternative to traditional temperature measurement methods. Under practical cowshed conditions, IRT images of dairy cows are easily affected by complex background interference and generally suffer from low resolution, poor contrast, indistinct boundaries, weak structural perception, and insufficient texture information, which lead to significant degradation in target detection and temperature extraction performance. To address these issues, a lightweight detection model named YOLOv11n-CGSD is proposed for dairy cow IRT images, aiming to improve the accuracy and robustness of region of interest (ROI) detection and body temperature extraction under complex background conditions. At the architectural level, a C3Ghost lightweight module based on the Ghost concept is first constructed to reduce redundant feature extraction while lowering computational cost and enhancing the network capability for preserving fine-grained features during feature propagation. Subsequently, a space-to-depth convolution module is introduced to perform spatial rearrangement of feature maps and achieve channel compression via non-strided convolution, thereby improving the sensitivity of the model to local temperature variations and structural details. Finally, a dynamic sampling mechanism is embedded in the neck of the network, where the upsampling and scale alignment processes are adaptively driven by feature content, enhancing the model response to boundary temperature changes and weak-texture regions. Experimental results indicate that the YOLOv11n-CGSD model can effectively shift attention from irrelevant background regions to ROI contour boundaries and increase attention coverage within the ROI. Under complex IRT conditions, the model achieves P, R, and mAP50 values of 89.11%, 86.80%, and 91.94%, which represent improvements of 3.11%, 5.14%, and 4.08%, respectively, compared with the baseline model. Using T_max as the temperature extraction parameter, the maximum error (Max. Error) and mean error (MAE. Error) in the lower udder region are reduced by 33.3% and 25.7%, respectively, while in the around the anus region, the Max. Error and MAE. Error are reduced by 87.5% and 95.0%, respectively. These findings demonstrate that, under complex backgrounds and low-quality IRT imaging conditions, the proposed model achieves lightweight and high-performance detection for both lower udder (LU) and around the anus (AA) regions and provides a methodological reference and technical support for non-contact body temperature measurement of dairy cows in practical cowshed production environments. Full article

Background/Objectives: Staphylococcus (S.) aureus is a major pathogen causing bovine mastitis and is often refractory to antibiotic therapies due to virulence factors and resistance mechanisms. In this pilot study, the safety and efficacy of an intramammary phage cocktail, in naturally S. aureus-infected dairy cows, were investigated. Methods: The initial part of the study on farm 1 confirmed tolerability and safety, as there were no observed systemic side effects of treatment. The subsequent efficacy study on farm 2 included 23 with S. aureus infected udder quarters, which were randomly divided into a treatment group (n = 16) and a control group (n = 7). The quarters in the treatment group received five intramammary infusions of the phage cocktail at 12-h intervals. Results: This resulted in a bacteriological cure rate of 81.3% (13/16) for the treatment group, compared to 28.6% (2/7) in the control group (p = 0.026). Conclusions: These results indicate that phage therapy is well-tolerated and may be a promising alternative to antibiotics for treating S. aureus mastitis, although confirmation in larger-scale, multicenter studies is required. Full article

Our genome-wide association study identified single-nucleotide polymorphisms (SNPs) associated with estimated breeding values (EBVs) for udder traits and longevity in Holstein-Friesian cows. While no SNP was individually associated with multiple EBVs, the functional profiles of the associated genes revealed overlapping biological processes across traits, including cell signaling, transcription regulation, immune response, metabolism, and cellular maintenance. Notably, nearby SNPs BTB-01738708 and ARS-BFGL-NGS-111478 were associated with EBV_longevity and EBV_udder and located near numerous genes, including GPR85, BMT2, IFRD1, and DOCK4, suggesting a potential for shared genetic influence on these traits. Our findings provide insights into the complex genetic architecture of these economically important traits and highlight the need for further research, including fine-mapping and functional genomics, to elucidate the specific variants and their effects. Full article

Bovine mastitis is a multifactorial disease defined by the inflammation of the udder in cattle. It can be caused by different factors, but contagious or environmental pathogens play a major role in the onset of this disease. The main treatment for this condition is the administration of antibiotics, either parenterally or via the intramammary route. The samples were processed by the National Reference Centre for Bovine Milk Quality (CRNQLB) and bacteriologically examined by the IZSLER Primary Production Department (BS, Italy) over the period from 2015 to 2024. Moreover, this study presents the minimum inhibitory concentrations (MICs) obtained from all the bacterial pathogens isolated in the last three years of the study (2022–2024). This study aimed to describe the main frequencies recorded during the decade, in order to provide an enumeration of pathogens circulating in the IZSLER jurisdiction and to estimate trends in antimicrobial resistance, highlighting increases or decreases in observed resistance levels. Results show an increased prevalence of Streptococcus uberis, Escherichia coli, and Enterococcus faecium, with a decrease in Prototheca, yeasts, Staphylococcus aureus, and Streptococcus agalactiae. The general increase in antimicrobial resistance to trimethoprim needs to be highlighted to express the need for a targeted therapy based on accurate diagnosis to limit the spread of resistance in dairy farms. Full article

Routine milk-recording data may provide valuable insights into dairy cow welfare, although their ability to accurately reflect herd-level welfare outcomes remains unclear. This study explored the associations between routinely collected milk biomarkers and farm-level welfare status using a comparative machine learning approach. Using the Welfare Quality^® (WQ^®) protocol, 43 commercial dairy farms were classified as Enhanced, Acceptable, or Not Classified. Farm-level milk variables included somatic cell count (SCC), differential somatic cell count (DSCC), fat-to-protein ratio (FPR), fat, protein, casein, lactose, urea, β-hydroxybutyrate (BHB), acetone, total plate count (TPC), and morning milk yield. Kruskal–Wallis tests revealed significant differences among welfare classes for DSCC, SCC, lactose, and milk yield (False Discovery Rate-adjusted p < 0.05). Six machine learning algorithms were trained using 10-fold stratified cross-validation. The Elastic-Net (ENET) model showed the highest mean performance (Accuracy = 0.72 ± 0.19; Kappa = 0.56 ± 0.31), followed by Random Forest and Multilayer Perceptron (Accuracy = 0.70). Model accuracy exhibited substantial variability across cross-validation folds, reflecting the limited sample size and class imbalance. Across models, the most influential variables were SCC, DSCC, lactose, milk yield, FPR, fat, and urea. Overall, the findings provide preliminary and exploratory evidence that routine milk biomarkers capture welfare-relevant patterns at the herd level, supporting their potential role as complementary indicators within data-driven welfare assessment frameworks. Full article

Hyperketonemia (HYK), defined by blood beta-hydroxybutyrate (BHB) ≥ 1.2 mmol/L, is described as a significant risk factor for cows developing postpartum (pp) diseases and impaired reproductive performance. The goal of the present study was to observe metabolic challenges in transition cows and to identify systemic markers reflecting HYK associated with lessened reproductivity. Fifty-four Simmental cows were monitored, revealing approximately 30% prevalence of HYK at the early pp period on 7, 14, or 28 days in milk (DIM). We assessed the dry matter intake, rumination time (RT), serum liver activity index, non-esterified fatty acids (NEFAs), acute phase proteins, and uterine and oviductal health. Elevated NEFA and reduced RT 14 days antepartum were a good predictor for HYK at 7 DIM. Hyperketonemia at 14 DIM resulted in higher milk yield compared with controls. We could neither detect differences in uterine health nor in reproductive key performance parameters between hyperketonemic and control cows, whereby the proportion of polymorphonuclear neutrophils in oviductal epithelia was significantly lower in hyperketonemic cows 14 DIM. We conclude that elevated concentrations of BHB in HYK 7, 14, or 28 DIM indicated energy supply to support physiological metabolic adaptations and lactation and that, in the absence of excessive inflammation during the transition period, HYK was not a risk factor for impaired fertility. Full article

This study examined the effects of long-term Saccharomyces cerevisiae supplementation on feed intake, milk production, milk composition, and selected reproductive indicators in lactating dairy cows. Twenty-four multiparous Holstein–Friesian crossbred cows were blocked by parity and randomly allocated to three treatments: a control group without supplementation (CON; n = 7), live yeast supplementation for 60 days (YS-60; n = 10), and live yeast supplementation for 90 days (YS-90; n = 7). Dry matter intake and body weight gain were significantly higher in cows receiving live yeast, with the greatest responses observed in the YS-90 group (p < 0.05). Milk yield and energy-corrected milk were increased by supplementation, particularly in YS-90 cows (p < 0.01), along with higher milk fat and lactose concentrations. Somatic cell count was consistently lower in YS-90 cows throughout the 14-week experimental period. Body condition score differed among treatments (p < 0.01), with higher values observed in yeast-supplemented cows. Feed efficiency did not differ among treatments. Reproductive parameters, including estrus detection and pregnancy rate, were not significantly affected by live yeast supplementation, although plasma progesterone concentration was higher in supplemented cows (p < 0.05). Given the limited number of animals per treatment, reproductive outcomes should be interpreted cautiously. Overall, extended live yeast supplementation improved production performance and udder health, while its effects on reproductive performance warrant further investigation. Full article

This study investigates the reliability and potential genetic utility of data recorded by automatic milking systems by comparing them with official milk recording data. Analyses focused on phenotypic distributions, correlations, systematic differences, and heritability estimates for milk production and quality traits including milk yield, fat and protein percentage, somatic cell count, and electrical conductivity. Automatic milking system data and official milk recording data shared similar distributions. Correlations between the two systems were high for milk yield (r = 0.93), but moderate for fat (r = 0.52) and protein percentage (r = 0.48), and somatic cell count (r = 0.62), suggesting that while the former provides consistent data for quantity traits, quality-related ones may be less reliable. Systematic deviations between automatic milking systems and official milk recordings emerged across different lactation stages. Heritability estimates based on automatic milking system data were generally higher than the official control for production traits, supporting their use in genetic evaluations. Electrical conductivity displayed a similar heritability to somatic cell count, but its measure is insufficiently detailed and its use as an indirect indicator of udder health is not recommended. Automatic milking system data demonstrates potential for integration into genetic selection programs, although further refinement of sensor accuracy is recommended. Full article

Farming animals that are resilient to various instabilities could improve both animal welfare and system sustainability. We evaluated three resilience indicators (Var, LnVar, and r-auto) in Holstein cattle on Czech farms using a bio-economic approach. We considered 3655 cows based on their genetic predisposition as 25% most resilient (Q3), median (Q2), and 25% least resilient (Q1), as well as their performance characteristics from routine production testing. Most of the performance characteristics significantly differed (p < 0.05) among the defined resilience quartiles. Q3 cows had slightly lower milk yield, higher milk component content, better udder health, and shorter dry periods compared to Q2 cows. The longevity of Q3 cows differed according to the indicator used (this was higher in Var and LnVar, but lower in r-auto). The highest profitability was found for the Q2 group in Var and r-auto and for Q1 in LnVar. Across all three resilience indicators, Q3 cows were the least profitable. Milk yield, lactation persistence, longevity, and milk fat and protein content contributed most to farm profit change across the resilience groups. The generality and simulation accuracy confirmed that the bio-economic model is suitable for the comprehensive setting and economic evaluation of resilience indicators and cattle performance. Full article

Dairy cow longevity is a key driver of farm profitability, animal welfare, and environmental sustainability. Despite genetic progress in milk production, the average herd life has declined in many high-yielding dairy systems, raising concerns about early culling. This study analyzed data from 2057 Holstein–Friesian cows in Hungary to characterize the distribution and timing of culling events and to identify major risk factors affecting productive lifespan. We studied age, parity, milk yield, and culling reason using descriptive statistics, Kruskal–Wallis tests, multinomial logistic regression, and Kaplan–Meier survival analysis. Udder health problems were found to be the most frequent cause of culling (22.8%), followed by metabolic disorders (18.2%), locomotive problems (17.3%), and reproductive disorders (17.1%). Economic reasons such as low milk production contributed to a smaller proportion of culling. Most cows were culled after the second or third lactation, with survival probability dropping sharply within the first 1500–2000 days of life. Cows reaching four or more lactations represented a small but economically and genetically valuable subset of the herd. Our results indicated that in Hungary culling decisions are largely determined by health problems, which represent a greater limitation to the productive potential of dairy cows than economic factors. This research recommends that breeding programs prioritize genetic selection for robustness and that herd management adopts preventive health and reproductive strategies to prolong cow longevity, ultimately enhancing the efficiency and sustainability of dairy production systems. Additionally, prevention of animal wastage to foster animal welfare could be suggested as an additional advantage. Full article

Background: Pain after giving birth is commonly observed in horses, yet there has not been a specific tool developed for assessing this pain in postpartum mares. The goal was to adapt existing equine pain scales and to preliminarily validate a practical pain scale for use by veterinarians and caregivers after foaling. Methods: The pain scale was developed by adapting items from other pain scales, including established orthopedic and colic equine pain scales, and incorporating caregiver feedback. The final scale includes eight areas for assessing pain: behavior, facial expressions, vital signs, udder examination, gastrointestinal function, hoof temperature, response to food, and movement. Observations were conducted on ten heavy draft mares that experienced dystocia, with pain scores recorded twice daily for 1 to 4 days postpartum. Simultaneous saliva samples were collected to measure cortisol levels. Results: The pain scale proved feasible for use at the stall and allowed for partial scoring when certain assessments were deemed risky. Pain scores were highest on the first day after foaling and decreased as the mares recovered. In a case of clinical deterioration, a substantial increase in pain score was noted. Increased pain scores were associated with elevated cortisol levels, supporting the biological relevance of the scale. In clinical practice, if a pain score exceeded 40% of the maximum score, the mare was identified as a patient requiring analgesic treatment. Conclusions: This postpartum-specific pain scale provides a standardized method for assessing pain in mares after foaling and may assist in guiding appropriate pain management. Although the proposed pain scale shows promise as a clinical tool, the present results are preliminary and require confirmation in larger studies. Full article

SCC is a standard indicator of udder inflammation, but it reflects only part of the broader physiological changes occurring in the mammary gland. This study aimed to evaluate associations between SCC, in-line milk traits, and blood biochemical markers in Holstein dairy cows. Based on SCC and California Mastitis Test (CMT) results, 59 cows (20–100 DIM) were divided into three groups: Group 1 (SCC < 200,000 cells/mL; n = 20), Group 2 (SCC 200,000–500,000 cells/mL; n = 19), and Group 3 (SCC > 500,000 cells/mL; n = 20). The Lely Astronaut^® A3 system was used to record milk parameters and behavioral data, while blood samples were collected for biochemical analysis. While there were negative relationships with milk yield (r = −0.266, p < 0.05) and creatinine (r = −0.291, p < 0.05), there was a significant positive correlation between SCC and milk electrical conductivity (EC) (r = 0.330, p < 0.05), gamma-glutamyl transferase (GGT) (r = 0.424, p < 0.001), and lactate dehydrogenase (LDH) (r = 0.285, p < 0.05). Potassium and chloride concentrations varied between groups, indicating slight electrolyte imbalances linked to higher SCC even though they remained within physiological bounds. Receiver operating characteristic (ROC) analysis further showed that milk EC (area under the curve (AUC) = 0.770) and blood potassium (AUC = 0.707) demonstrated the highest diagnostic accuracy for distinguishing healthy and mastitic cows. These results show that integrating SCC data with automated in-line monitoring and blood biochemical profiling can help identify novel complementary indicators for the detection of mastitis in dairy cows and offer a deeper understanding of udder health. Full article

In recent years, donkey milk has gained growing interest for its nutritional and therapeutic properties, stimulating both research and commercial interest. Monitoring udder health is essential to reduce production losses and ensure animal welfare. Despite its importance, information about the ultrasonographic anatomy of teat structures in lactating jennies is limited, and normal reference values are not well established. This study aimed to describe the ultrasonographic appearance of the teat and provide reference measurements in healthy lactating standard dairy jennies. Twenty-eight subjects were examined using a 13 MHz linear transducer, and longitudinal and transverse scans were performed to assess teat canal length, teat canal diameter, and cranial and caudal teat wall thickness. All measurements were repeatable and showed high bilateral symmetry. Teat canal diameter was positively correlated with the month of lactation (p < 0.05), whereas no significant associations were found with age or body weight. These findings establish normative ultrasonographic parameters for teat structures in jennies and highlight the progressive adaptation of the teat canal during lactation. Standardized measurements can support early detection of mammary gland pathologies, guide preventive management of mastitis, and improve udder health monitoring in donkey dairy farming. Full article

Body temperature serves as a crucial indicator of dairy cow health. Traditional rectal temperature (RT) measurement often induces stress responses in animals. Body temperature detection based on infrared thermography (IRT) offers non-invasive and timely advantages, contributing to welfare-oriented farming practices. However, automated detection and temperature extraction from critical cow regions are susceptible to complex illumination, black-and-white fur texture interference, and region of interest (ROI) deformation, resulting in low detection accuracy and poor robustness. To address this, this paper proposes the EDC-YOLO-World-DB framework to enhance detection and temperature extraction performance under complex illumination conditions. First, URetinex-Net and CLAHE methods are employed to enhance low light and overexposed images, respectively, improving structural information and boundary contour clarity. Subsequently, spatial relationship constraints between LU and AA are established using five-class text priors—lower udder (LU), around the anus (AA), rear udder, hind legs, and hind quarters—to strengthen the spatial localisation capability of the model for ROIs. Subsequently, a Dual Bidirectional Feature Pyramid Network architecture incorporating EfficientDynamicConv was introduced at the neck of the model to achieve dynamic weight allocation across modalities, levels, and scales. Task Alignment Metric, Gaussian soft-constrained centroid sampling, and combined IoU (C_IoU + G_IoU) loss were introduced to enhance sample matching quality and regression stability. Results demonstrate detection confidence improvements by 0.08 and 0.02 in low light and overexposed conditions, respectively; compared to two-text input, five-text input increases P, R, and mAP50 by 3.61%, 3.81%, and 1.67%, respectively; Comprehensive improvements yielded P = 88.65%, R = 85.77%, and mAP50 = 89.33%—further surpassing the baseline by 2.79%, 3.01%, and 1.92%, respectively. Temperature extraction experiments demonstrated significantly reduced errors for $T_{Max}$, $T_{Min}$, and $T_{avg}$. Specifically, for the mean error of LU, $T_{Max}$, $T_{Min}$, and $T_{avg}$ were reduced by 66.6%, 33.5%, and 4.27%, respectively; for AA, $T_{Max}$, $T_{Min}$, and $T_{avg}$ were reduced by 66.6%, 25.4%, and 11.3%, respectively. This study achieves robust detection of LU and AA alongside precise temperature extraction under complex lighting and deformation conditions, providing a viable solution for non-contact, low-interference dairy cow health monitoring. Full article

Ultrasonography has been proposed as a complementary tool for the evaluation of udder health, yet limited information exists on its application for measuring the glandular cistern area during mastitis. This study aimed to investigate modifications of the glandular cistern area in clinical (CM) and subclinical mastitis (SCM) compared with contralateral healthy quarters, and to assess the reliability of manual and automated ultrasonographic measurements. A longitudinal study was conducted on 42 Italian Holstein cows, comprising 26 SCM and 16 CM quarters, each paired with contralateral healthy controls. Ultrasound examinations were performed at diagnosis (T0), 24 h (T1), and 5 days (T5). Cisternal areas were measured in transversal and longitudinal sections using both manual and ImageJ-guided methods. Intra- and inter-operator reliability was assessed using Intraclass Correlation Coefficients (ICCs). Statistical analyses included two-way mixed ANOVA with post-hoc Bonferroni correction. Mastitic quarters tended to show smaller cisternal areas compared with contralateral healthy quarters, with significant differences observed between contralateral healthy and CM quarters (p < 0.05), but not between contralateral healthy and SCM or between SCM and CM quarters. Temporal trends differed significantly among groups (interaction effect, p < 0.05). Both manual and automated measurements demonstrated excellent intra- and inter-operator reliability, with ICCs consistently > 0.95 across pathology groups and time points. Ultrasonography of the glandular cistern is a feasible, reproducible, and reliable method under field conditions. Clinical mastitis is associated with a measurable reduction in cisternal area, while changes in subclinical mastitis appear less evident. The high reproducibility of measurements, including automated analysis, supports the use of this technique may contribute to improve the use of ultrasound also for the udder heath. Full article