Search Results (50)

Mastitis, a disease associated with milk production with multiple etiologies, causes significant economic losses among dairy farmers worldwide. This study aimed to detect mastitis using thermal images of the udder obtained during the milking phase from 500 Holstein dairy cows with the aid of an Artificial Neural Network (ANN). Mastitis levels were classified based on the California Mastitis Test (CMT) scores using somatic cell count (SCC) as the output variable. The dataset was divided into training (70%), validation (15%), and test (15%) subsets. RGB (Red, Green, Blue) thermal images were used to construct the input matrices. The model achieved correlation coefficients (R) of 0.91, 0.97, and 0.97 for the training, validation, and test datasets, respectively. The close agreement between validation and test performances indicates the absence of overfitting and demonstrates strong generalization capability of the proposed model. These findings suggest that artificial neural networks combined with thermal imaging can provide high-quality and reliable results for mastitis detection. Full article

Hafnia alvei, which belongs to the Enterobacteriaceae family, has been occasionally documented in animal infections but is still not well characterized in the context of bovine mastitis. This research examined the prevalence and antimicrobial resistance characteristics of H. alvei in dairy cows suffering from subclinical mastitis in South Africa’s Free State Province. In the Thabo Mofutsanyana District, a total of 174 milk samples were obtained from cows on six different dairy farms. The California Mastitis Test (CMT) was used to screen for subclinical mastitis, and somatic cell count was used to confirm it. Standard culture methods were used for bacterial isolation, and presumptive Enterobacteriaceae isolates were identified through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Out of the 174 samples, 84 (48.2%) tested positive for CMT, and 68 (39.1%) met the SCC criteria for subclinical mastitis at a cow level, while 96/336 (28.5%) were infected at a quarter level. Of the 100 presumptive Enterobacteriaceae isolates, 33 (33.0%) were identified as H. alvei (p = 0.0034). Antimicrobial susceptibility testing showed that 50% of the isolates were resistant to penicillin, followed by tetracycline and erythromycin with 25% and 10%, respectively. Furthermore, the results showed that 17 (51.5%) isolates exhibited multidrug-resistant profiles. The results suggest that H. alvei could be a contaminant in raw milk associated with bovine subclinical mastitis in this area, necessitating additional epidemiological research that includes healthy matched controls. Full article

A comparative cross-sectional study was undertaken in organized and unorganized dairy sectors to evaluate the prevalence of bovine mastitis and the antibiotic resistance in Staphylococcus spp. of dairy animals and their associated personnel. A total of 391 households (HH) consisting of 211 and 180 HHs from organized and unorganized sectors, respectively, were selected based on 30-cluster sampling methodology in southern and northeastern regions of India. From 391 HHs, a total of 1920 milking cows (organized dairy—533; unorganized dairy—1387) were screened for subclinical and clinical mastitis by the California Mastitis Test (CMT). Out of 1920 milk samples, 1002 milk samples, 362 associated personnel hand and nasal swabs, and 27 milking machine swabs were sourced. The samples were subjected to Staphylococcus spp. by isolation and identification by multiplex polymerase chain reactions (mPCRs) and antibiotic sensitivity testing (ABST) to determine antimicrobial resistance (AMR) profiles. CMT results showed high mastitis prevalence (54.65%) in unorganized farms compared to organized ones (45.78%), with a significant association of mastitis to dairy sectors (p = 0.0004). On speciation, S. aureus isolates were comparatively less than those of coagulase-negative staphylococci (CoNS) (3.5% and 7.7%, respectively) in the organized dairy sector, and the same was recorded for the unorganized dairy sector (0.85% and 13.19%, respectively). In both the dairy sectors, the highest antibiotic resistance for Staphylococcus spp. was observed against the β-lactams (penicillins and cephalosporins) group (71.36% and 76.59%) and the lowest for nitrofurans (3.5% and 3%), oxazolidines (0.7% and 5.1%), and rifamycin (0.7% and 5.1%), respectively. In both the sectors, human isolates had comparatively high mecA positives (15.70% and 15.96%) compared to the animal isolates (8.36% and 12.94%). Based on mPCR, a smaller number of methicillin-resistant S. aureus (MRSA) isolates (3.95%) than methicillin-resistant coagulase-negative Staphylococci (MRCoNS) was detected in milk samples (6.05%), and the same was observed for associated personnel samples (MRCoNS (14.63%) compared to MRSA (1.05%)). In four HHs, mecA positives were detected in both animal and human samples, and this highlights the transmission dynamics of mecA between animals and humans in households. The resistance of Staphylococcus spp. to β-lactams highlights the need for cautious antibiotic use to prevent AMR. Full article

An outbreak of mastitis caused by Staphylococcus aureus occurred in a commercial dairy goat herd during kidding season, resulting in fatal gangrenous mastitis in approximately 30% of the herd. S. aureus was recovered from milk, mammary tissue, and other organs in does subjected to necropsy. The S. aureus milk culture-positive rate among does in the hospital pen was 58.3%, while whole-herd milk cultures of clinically normal mature does identified S. aureus in 15.0% with an additional 15.0% positive for coagulase-negative Staphylococcus (CNS), yielding a total culture-positive rate of 30.0%. The prevalence of CNS in subclinical animals was consistent with previous reports from U.S. dairy goats; in contrast, S. aureus isolation rates substantially exceeded previously reported prevalences. Poor milking hygiene and milking machine dysfunction were identified as major factors contributing to the spread of the S. aureus from goat to goat. California Mastitis Test (CMT) scores were significantly higher in culture-positive does compared with culture-negative animals (p < 0.05), demonstrating the value of CMT as a practical on-farm tool for early treatment decision making. Interventions focused on addressing milking hygiene and milking machine maintenance, as well as segregation and vaccination of replacement females. S. aureus dropped to undetectable in the next two kidding seasons, whereas the CNS culture rates remained unchanged, suggesting other factors may be contributing to CNS infection. This case highlights the role of subclinical intramammary infection and milking practice factors in transmission and control of contagious mastitis pathogens like S. aureus. Full article

Background: Bovine mastitis is a leading cause of economic loss in dairy farming and is increasingly complicated by antimicrobial resistance (AMR), posing challenges to treatment and public health. Objectives: This study aimed to investigate the prevalence, bacterial etiology, and AMR patterns of mastitis pathogens in dairy herds from the Banat region of Romania. Materials and Methods: A retrospective analysis was conducted on 420 dairy cows from five localities. Mastitis diagnosis involved clinical examination, indirect tests (California Mastitis Test (CMT), R-Mastitest), and bacteriological culture. Antimicrobial susceptibility was assessed using the VITEK^® 2 system. Results: Out of 420 cows, 120 (28.6%) were diagnosed with mastitis. The predominant pathogens were Staphylococcus aureus (33.3%) and Streptococcus agalactiae (22.5%). Most infections were monomicrobial (70%) and affected a single under quarter (77.5%). Beta-lactam resistance was widespread among both Gram-positive and Gram-negative isolates, particularly against penicillin and ampicillin. Multidrug-resistant (MDR) strains were identified in 33.3% of all isolates, with 100% of Gram-negative isolates exhibiting MDR profiles. Conclusions: The high prevalence of S. aureus and S. agalactiae, along with widespread beta-lactam resistance and frequent MDR phenotypes, highlights the urgent need for routine AMR surveillance and targeted antimicrobial therapy in bovine mastitis control programs. Full article

Historically, methods to detect subclinical mastitis have been used to aid treatment decisions. The limitations of these tests have led to the exploration of the use of differential somatic cell count (DSCC). The objective of this study was to evaluate the relationship between DSCC and antibiotic success in subclinically infected cows. Cows were pre-screened to confirm an SCC ≥ 200,000 cells/mL and a positive bacterial culture. At enrollment, aseptic quarter milk samples were collected for culturing and evaluated using SCC, DSCC, the California Mastitis Test (CMT), and electrical conductivity. Enrolled quarters were treated with an intramammary antibiotic and resampled 7-, 14-, 28-, and 35-days post-treatment and retrospectively classified as “Cured” or failed to cure (Failed) based on a bacteriological cure. The overall cure rate was 51.5%. Pre-treatment SCC, total leukocyte count (TLC), neutrophils, and CMT were lower in Cured quarters compared to Failed. Meanwhile, macrophage percentage was greater in Cured quarters compared to Failed. No difference was found between lymphocyte percentage and conductivity. When evaluating the use of multiple threshold optimizations to predict cure outcome, TLC tended to have the highest ranking for the metric of interest; however, SCC tended to numerically perform as well in sensitivity and specificity outside of the optimized parameter. Full article

Mastitis remains a major constraint to dairy production in Bangladesh, particularly in high-demand regions. This study investigated the prevalence, risk factors, and antimicrobial resistance patterns of major pathogens associated with bovine mastitis in Northern Bangladesh. A total of 488 milk samples from 122 randomly selected milking cows were tested through clinical inspection and the California Mastitis Test (CMT). Positive samples were subjected to bacterial culture and antimicrobial susceptibility testing using the disc diffusion method. The overall cow-level prevalence was 35.24%, with 27.86% sub-clinical and 7.37% clinical cases. At the quarter level, prevalence was 21.72%. Among 166 bacterial isolates, Staphylococcus spp. (41.56%) was predominant, followed by Streptococcus spp. (23.49%), E. coli (17.47%), Klebsiella spp. (12.65%) and Bacillus spp. (4.82%). Gentamicin (100%) and Streptomycin (92.20%) were the most effective antibiotics, whereas Cefixime (100%) and Amoxicillin (87.40%) showed the highest resistance rates. Major risk factors included late lactation stage, high milk yield, previous mastitis history, and poor hygiene. In contrast, breed, age, and parity were not significant. These findings highlight a high prevalence of mastitis, predominance of Staphylococcus spp., and rising antimicrobial resistance, identify associated risk factors, and rising antimicrobial resistance profiles in Northern Bangladesh. 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

Background/Objectives: Subclinical mastitis is a common and economically significant infection in dairy cows. This study aimed to assess the prevalence and antimicrobial susceptibility of bacteria causing subclinical mastitis in dairy cows in the Upper Cheliff Region, Northern Algeria, and to investigate the effects of subclinical mastitis on milk production and reproductive performance. Methods: A total of 263 cows from 23 farms were screened for subclinical mastitis using the California Mastitis Test (CMT) and sampled for isolation and identification of bacteria by MALDI-TOF MS. Antimicrobial susceptibility testing (AST) was performed using the Vitek 2 system and disk diffusion method. Methicillin resistance in staphylococci and mammaliicocci was confirmed by mecA/mecC detection. Results: The results revealed a prevalence of subclinical mastitis of 58.9% at the cow-level and 31.1% at the quarter-level. The most prevalent microorganisms identified were Enterococcus faecium (E. faecium) (24.4%) and Enterococcus faecalis (E. faecalis) (20.5%), followed by non-aureus staphylococci (NAS) (16.9%), Escherichia coli (E. coli) (7.9%) and Staphylococcus aureus (S. aureus) (7.08%). Risk factors significantly associated with the prevalence of subclinical mastitis included parity, lower milk production (<12 L/day), poor animal cleanliness and a history of previous mastitis. Reproductive performance was significantly impaired in cows with subclinical mastitis, cows with longer calving-to-first-service intervals (130 vs. 102.7 days; p < 0.0001), more services per conception (2.5 vs. 1.9; p < 0.0001) and a lower pregnancy rate at first service (24.5% vs. 48.1%; p < 0.0001). Furthermore, 43.2% of cows with subclinical mastitis required three or more inseminations to achieve pregnancy. AST showed a low resistance rate for the antimicrobial agents most commonly used in human and veterinary medicine. Coagulase-negative staphylococci (CoNS) showed remarkable rates of methicillin-resistance (22.2%), as well as resistance towards fosfomycin (37.8%) and tetracycline (31.1%). A substantial proportion of E. coli isolates exhibited resistance to piperacillin (40%) and ciprofloxacin (15%). All S. aureus isolates were classified as MSSA without detection of mecA and mecC genes. Conclusions: The results of this study demonstrated that subclinical mastitis is prevalent in the Upper Cheliff region and is associated with reduced milk production and reproductive performance. The detection of pathogenic and resistant microorganisms in milk is alarming and requires effective management strategies to control subclinical mastitis and improve dairy farm productivity. Full article

To study behavioral and productive factors to detect changes that may indicate and predict clinical mastitis cure, Holstein dairy cows (n = 60), in an automatic milking system (AMS) and equipped with behavioral monitoring collar, were monitored from the diagnosis of clinical mastitis (D0) until clinical cure. The parameters collected through sensors were feeding activity, milk electrical conductivity (EC), milk yield, Mastitis Detection Index (MDi), milk flow, and number of gate passages. Clinical mastitis cases (n = 22) were monitored and divided into cured cases (n = 14) and non-cured cases within 30 days (n = 8), paired with a control case group (n = 28). Cows were assessed three times per week, and cure was determined when both clinical assessment and California Mastitis Test (CMT) results were negative in three consecutive evaluations. Mixed generalized linear regression was used to assess the relationship between parameters and clinical mastitis results. Mixed generalized logistic regression was used to create a predictive model. The average clinical cure time for cows with clinical mastitis was 11 days. Feeding activity, gate passages, milk yield, milk flow, EC, and the MDi were associated with cure. The predictive model based on data from D0 showed an Area Under the Curve of 0.89 (95% CI = 0.75–1). Sensitivity and specificity were 1 (95% CI = 1–1) and 0.63 (95% CI = 0.37–0.91), respectively. The predictive model demonstrated to have good internal sensitivity and specificity, showing promising potential for predicting clinical mastitis cure within 14 days based on data on the day of clinical mastitis diagnosis. Full article

Subclinical mastitis (SCM) is a stealthy but devastating challenge in the dairy industry, leading to economic losses and hindering efforts to achieve milk self-sufficiency. This study investigated the prevalence of SCM, antimicrobial resistance, and virulence profiles of Escherichia coli. A total of 174 milk samples were analyzed using the California mastitis test (CMT), somatic cell counts (SCCs), bacteriological culture, MALDI-TOF MS, and polymerase chain reaction (PCR). The findings revealed that the SCM prevalence was 68/174 (39.08%) based on CMT and SCC. Among SCM-positive samples, 60/68 (88.23%) were identified as E. coli, confirmed by MALDI-TOF MS and PCR assay. The most frequently detected serogroups were 0113 (11.6%) and 0113 (3.3%). Additionally, the genes for Stx1 and Stx2 were also detected in nine (15%) and one (1.7%), respectively. Antimicrobial susceptibility tests showed widespread resistance, with E. coli isolates demonstrating resistance to penicillin in 43 (71.6%), followed by ciprofloxacin in 42 (70%) and gentamicin in 18 (30%). A larger proportion of the E. coli strains (100%) harbored the bla_VIM gene, while 23 (38.3%), 20%, 20%, and 1.47% contained bla_KPC, bla_NMD, suli1, and msrA. Thirty (50%) isolates were considered multidrug-resistant (MDR). These findings underscore the urgent need for enhanced surveillance and antibiotic stewardship in dairy farming. The presence of MDR E. coli in SCM poses a dual threat of potential transmission to humans and treatment failures in mastitis management. This study highlights the importance of proactive control strategies to mitigate the spread of antimicrobial resistance in livestock and beyond. Full article

Bovine mastitis is a significant disease affecting dairy cattle worldwide, impacting milk quality and farm profitability. Understanding pathogen distribution is crucial for effective disease management. This study analyzed 319,634 individual cow milk samples submitted to the UC Davis Milk Quality Laboratory between 2009 and 2023 to assess pathogen prevalence, seasonal variations, and long-term trends. Routine microbiological cultures identified major and minor mastitis pathogens, with additional testing for Mycoplasma spp. Statistical analyses evaluated annual and seasonal trends in bacterial isolation rates. Results indicated that environmental pathogens, particularly non-aureus staphylococci and coliforms, were most frequently isolated, while contagious pathogens (Staphylococcus aureus, Streptococcus agalactiae, and Mycoplasma spp.) were less prevalent. Seasonal trends revealed higher contamination rates in Winter and increased no-growth samples in Summer. The study also observed a decline in sample submissions in recent years, possibly reflecting evolving dairy management practices. These findings provide a comprehensive perspective on mastitis pathogen dynamics in California’s Central Valley, supporting improved milk quality control measures and tailored mastitis prevention strategies. Full article

Subclinical mastitis is a critical disease affecting camel health and milk quality. However, research on shifts in milk bacterial communities following subclinical mastitis in camels is limited. We evaluated changes in bacterial communities following subclinical mastitis in Bactrian camels. Three portions of California Mastitis Test (CMT)-negative milk and five portions of CMT-positive milk were collected from each Jimunai County and Keping County using the CMT, and the bacterial community composition of the camel milk was analyzed using amplicon sequencing of the v34 region of the 16S rRNA gene. Subclinical mastitis induced genus-level differences in the core bacterial microbiota of Bactrian camel milk. To our knowledge, Delftia was identified in camel milk for the first time, predominantly in Jimunai County. Bacterial abundance in camel milk from Keping County was increased and altered. Alpha diversity analysis revealed that subclinical mastitis induced lower and higher bacterial abundance in milk from Jimunai County and Keping County, respectively, compared to that of healthy camels. Therefore, these findings provide direction for future research on pathogenic microorganisms for the prevention and control of subclinical mastitis in Bactrian camels. 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

Subclinical mastitis (SM) is the most economically damaging yet often visually undetectable disease of dairy cows. Early detection and treatment can reduce the loss caused by the disease; thus, the continuous improvement of SM diagnostic methods is necessary. Although milk’s somatic cell count (SCC) is commonly measured for diagnostic purposes, its direct determination is not widely used in everyday practice. The primary objective of our work was to investigate whether the predictive value of SM diagnostics can be improved by training artificial neural networks (ANNs) on data generated using typical conventional milking systems. The best ANN classifier had a sensitivity of 0.54 and a specificity of 0.77, which is comparable to performances of various California Mastitis Tests (CMT) found in the literature. Combining two diagnostic tests, ANN and CMT, we concluded that the positive predictive value could be up to 50% higher than the value provided by the individual CMT. While implementing CMT is a labor-intensive process on herd-level, in milking machines where milk properties or milk yield data can be measured automatically, similar to our work, SCC-increase predictions for all individuals could be obtained daily basis. Full article