State Dairy Farms Research Articles

Supporting the implementation and monitoring of selective dry cow therapy (SDCT) on NY State dairy farms

Selective dry cow therapy (SDCT) is both a cost-saving and an­timicrobially conscientious approach to the critical time of dry off in a dairy cow’s lactation. Guidance regarding proper imple­mentation is crucial to the success of a SDCT program, and farm and cow-level selection parameters should be carefully followed. The objective of this project was to create a formal program in which eligible dairy farms in New York State would receive guidance in the form of SDCT protocol development, software use, dry-off procedure training and data monitoring regarding udder health and milk quality parameters through the entire enrollment period. Here we describe the program and farm performance after implementation thus far.

MILK YIELD AND COMPOSITION OF DAIRY CATTLE DURING DRY SEASON IN SELECTED DAIRY FARMS IN KANO STATE, NIGERIA

The aim of the study was to assess the milk yield and composition of dairy cattle of different locations during dry season in selected dairy farms in Kano state. One hundred and twenty lactating cows (different stages of lactation) include Bunaji, Bokoloji, Fresian x Bunaji were used, ten from each twelve dairy farms to assess milk yield and composition. Daily milk yield was recorded for two months. Five milk samples from each farm were analysed for its composition. Danbatta farm was the best in average daily milk yield (ADMY) of 3.86l, Dantube farm was the lowest of 2.49l which differ (p<0.001), Imawa arewa, Asibitin tafasa and Lautaye farms didn’t vary other farms differ. Fat(%) did not vary in all the farms, TS(%) Total solid, TA(%) Titrable acidity, CP(%) Crude protein, Ash(%), SNF(%) Solid non fat differ (p<0.001). Tsaunin fulani farm was the best in Fat(%) 4.26, Asibitin tafasa farm was the lowest of 3.84. Lautaye was the best in TS(%) 57.2, Dakatsalle was the lowest of 38.8. Imawa arewa was the best TA(%) of 0.38, Dakatsalle, Kuki and shinkafi farms are the lowest of 0.29. Imawa arewa, Danbatta and Kwanar dumawa farms are the best in CP(%) 4.24, Kuki farm was the lowest of 3.46. Dantube farm was the best in Ash(%) of 0.54, Dakatsalle, Kuki are the lowest of 0.32. Lautaye was the best in SNF(%) 52.96, Dakatsalle farm was the lowest of 34.6. Fat(%) differ (p<0.05), TS(%) (p<0.001) among the breeds while their ADMY, TA(%), CP(%), Ash(%), SNF(%) did not vary. Bunaji was the best in Fat(%) of 4.22, TS(%) 50.2, SNF(%) 45.74 with ADMY of 2.74l. Fresian x Bunaji was superior in CP(%) 4.24, lowest in Fat(%) 3.88, Ash(%) 0.44, TS(%) 39.2, SNF(%) 35.32 with the best ADMY of 4.01l. Bokoloji was superior in Ash(%) of 0.47 lowest in TA(%) 0.31 with ADMY of 2.67l. Therefore, Danbatta farm, Fresian x Bunaji with the best milk yield, Tsaunin fulani farm with the best Fat(%), Lautaye farm TS(%), Imawa arewa TA(%), Imawa arewa, Danbatta and Kwanar dumawa farms CP(%), Dantube farm Ash(%), Lautaye farm SNF(%), Bunaji breed with the best Fat(%), TS(%), TA(%), SNF(%), Bokoloji breed Ash(%), Fresian x Bunaji CP(%) was recommended. Milk yield and composition varied between dairy breeds, herds of the same breed and even between individual cows of a breed.

Technical note: Method for improving precision of in-parlor milk meters and adjusting milk weights for stall effects

Milk yield is a fundamental observation in most dairy experiments and is commonly determined using integrated milk meters that measure milk weight as the cow is being milked. These meters are heavily used in a harsh environment and often are not regularly calibrated, so calibration errors and mechanical problems may create artificial variation in milk weight data. Additionally, direct calibration by collection of milk in a bucket is difficult and imperfect because the use of the bucket may affect yield recorded by the milk meter. The objective of this work was to define a method to easily check parlor meter precision and adjust milk weight values for variation between individual stalls in a parlor. Because most cows are milked in a different stall at each milking, it has been proposed that stall deviations that represent the fixed effect of stall on milk weight could be statistically determined. Individual milk weights from 14 milkings across 7 d from approximately 200 cows were collected from the Penn State dairy farm, which is equipped with a double-10 herringbone parlor with an Afimilk 2000 milking system (S.A.E. Afikim, Afikim, Israel). Milk yield was measured automatically by in-line flow through milk meters (Afi 200; S.A.E. Afikim). The effect of stall on milk weight was modeled using a mixed model that included the fixed effect of stall and the random effects of day, milking time, and cow. First, stall deviations were calculated as the stall least squares means (LSM) minus the average LSM to identify malfunctioning meters requiring service (e.g., deviation exceeding 1 kg). A correction factor for each stall was then generated by dividing the LSM of each stall by the average LSM. Milk yields were then corrected by multiplying the meter weight value by the correction factor. To determine the effect of the correction, raw and corrected meter values were compared with weight of milk collected in a bucket (n = 3/stall). The corrected values had a 5% greater coefficient of determination than raw meter values (0.89 vs. 0.84) and had a lower average percent difference from the bucket milk weight compared with raw meter values (12.6% vs. 13.5%). The method was then used in 3 experiments with 121, 140, and 683 milk yield observations. In all data sets, correcting milk weights slightly improved model fit and had minimal effect on model term standard errors. However, this validation was completed in a parlor where the method was routinely used to identify stalls requiring service; the effect of stall corrections is expected to be larger in parlors without frequent monitoring. Stall deviations are expected to be due predominantly to calibration of the meter but also could be due to differences in pulsation or other stall-specific factors that result in a change in milk yield. It is important to account for these other sources of milk weight variation that are unrelated to treatment. Modeling the effect of stall is a simple, convenient, and low-cost method to monitor and improve milk meter precision and functionality and can be used to reduce artificial variation and experimental error.

Distribution of Lactococcus spp. in New York State dairy farms and the association of somatic cell count resolution and bacteriological cure in clinical mastitis samples

We investigated the distribution of pathogenic non-agalactiae gram-positive, catalase-negative cocci (GPCN) in a convenience sample of New York State dairy farms. Our primary objective with the clinical mastitis (CM) GPCN samples was to evaluate somatic cell count (SCC) resolution and bacteriological cure of Streptococcus dysgalactiae or Streptococcus uberis versus Lactococcus lactis or Lactococcus garvieae in cows that received an approved intramammary treatment. In phase I, we assessed the distribution of the GPCN and SCC resolution. In phase II, we evaluated the SCC resolution and bacteriological cure in CM samples from the 4 farms with the highest prevalence of L. lactis or L. garvieae in phase I. In phase I, 8,868 CM and subclinical mastitis (SCM) milk samples were received from 143 farms. The GPCN samples identified by culture were confirmed with MALDI-TOF. From the 473 MALDI-TOF-confirmed GPCN samples, 155 were S. dysgalactiae (33%); 150, S. uberis (32%); 112, L. lactis (24%); 16, L. garvieae (3%); and 40, other GPCN (8%). From these, 277 were CM samples and 127 were eligible for the evaluation of SCC resolution, which was defined as SCC ≤200,000 cells/mL in a composite sample 15 to 60 d post-diagnosis. The odds of SCC resolution in CM samples was evaluated with multivariable logistic regression, and the odds were 6.1 [95% confidence interval (CI):2.7-13.9] times higher for S. dysgalactiae or S. uberis compared with L. lactis or L. garvieae. In phase II, a total of 1,662 CM and SCM samples were evaluated with microbiological methods as in phase I, of which 211 samples were confirmed by MALDI-TOF: 39% were S. dysgalactiae (n = 61) and S. uberis (n = 21); 55%, L. lactis (n = 114) and L. garvieae (n = 2); and 6%, other GPCN (n = 13). In total, 168 CM samples were eligible for analysis and 118 were included in the final SCC resolution model. Similar statistical methods as in phase I were performed, and the odds of SCC resolution were 2.4 (95% CI: 1.1-5.5) times higher for S. dysgalactiae or S. uberis compared with L. lactis or L. garvieae. Bacteriological cure was defined as having a different or negative culture on a quarter sample taken 14 to 28 d after initial diagnosis. The odds of bacteriological cure (n = 121) were 8.0 (95% CI: 2.5-25.6) times higher for S. dysgalactiae or S. uberis compared with L. lactis or L. garvieae. Differences in SCC resolution and bacteriological cure between these groups may dictate a different management approach.

Use of a culture-independent on-farm algorithm to guide the use of selective dry-cow antibiotic therapy

An algorithm using only computer-based records to guide selective dry-cow therapy was evaluated at a New York State dairy farm via a randomized field trial. DairyComp 305 (Valley Ag Software, Tulare, CA) and Dairy Herd Improvement Association test-day data were used to identify cows as low risk (cows that might not benefit from dry-cow antibiotics) or high risk (cows that will likely benefit). Low-risk cows were those that had all of the following: somatic cell count (SCC) ≤200,000 cells/mL at last test, an average SCC ≤200,000 cells/mL over the last 3 tests, no signs of clinical mastitis at dry-off, and no more than 1 clinical mastitis event in the current lactation. Low-risk cows were randomly assigned to receive intramammary antibiotics and external teat sealant (ABXTS) or external teat sealant only (TS) at dry-off. Using pre-dry-off and postcalving quarter-level culture results, low-risk quarters were assessed for microbiological cure risk and new infection risk. Groups were also assessed for differences in first-test milk yield and linear scores, individual milk weights for the first 30 d, and culling and mastitis events before 30 d in milk. A total of 304 cows and 1,040 quarters in the ABXTS group and 307 cows and 1,058 quarters in the TS group were enrolled. Among cows to be dried, the proportion of cows that met low-risk criteria was 64% (n = 611/953). Of cultures eligible for bacteriological cure analysis (n = 171), 93% of ABXTS cured, whereas 88% of TS cured. Of the non-cures, 95% were contributed by the minor pathogens coagulase-negative staphylococci (n = 19/20). These organisms also accounted for 57.5% of new infections (n = 77/134). We found no statistical differences between treatment groups for new infection risk (TS = 7.3% quarters experiencing new infections; ABXTS = 5.5%), milk production (ABXTS = 40.5 kg; TS = 41.2 kg), linear scores (ABXTS = 2.5; TS = 2.7), culling events (ABXTS, n = 18; TS, n = 15), or clinical mastitis events (ABXTS, n = 9; TS, n = 5). Results suggest that the algorithm used decreased dry-cow antibiotic use by approximately 60% without adversely affecting production or health outcomes.

An evaluation of anaerobic co-digestion implementation on New York State dairy farms using an environmental and economic life-cycle framework

Anaerobic digestion systems on dairy farms in New York State rely on gate-fee revenues from co-digestion to ensure economic viability. Yet, because gate fees are paid on a volumetric (or weight) basis, farmers have been compelled to accept large waste volumes. When these wastes are co-digested at rates exceeding the design capacity of the digester, potentially significant technical, environmental, and economic consequences may arise. To better understand these trade-offs, we performed a combined environmental life-cycle and economic assessment with uncertainty analysis. We used the Anaerobic Digestion Model #1 to simulate the co-digestion process for 10 potential co-substrates that were hypothetically mixed with dairy manure throughout a range of loading rates. These simulation results demonstrated the need to include a robust anaerobic digestion model to capture complex process dynamics and loading limits. Results also showed that while higher loading rates were more economically favorable, they caused considerable reductions in the degree of waste stabilization during the digestion process, which dramatically increased downstream methane emissions (e.g., >450%) on the farm compared to manure-only digestion. Regardless, most co-digestion scenarios led to a net reduction in total life-cycle emissions compared to manure only and not digesting the co-substrate due mainly to greater electric power production and synthetic fertilizer replacement. Economically, gate-fee revenue was the most important contributor to profitability, substantially outweighing the revenue from electric power production, while also compensating for the increased handling costs of the added waste volume. Ultimately, the model clearly demonstrated the important environmental and economic implications arising from current anaerobic digestion implementation practices and policy in New York State. In addition, the model highlighted key stages in the system life-cycle, which was used to instruct and recommend immediately actionable policy changes.

Longitudinal assessment of dairy farm management practices associated with the presence of psychrotolerant Bacillales spores in bulk tank milk on 10 New York State dairy farms

The ability of certain spore-forming bacteria in the order Bacillales (e.g., Bacillus spp., Paenibacillus spp.) to survive pasteurization in spore form and grow at refrigeration temperatures results in product spoilage and limits the shelf life of high temperature, short time (HTST)-pasteurized fluid milk. To facilitate development of strategies to minimize contamination of raw milk with psychrotolerant Bacillales spores, we conducted a longitudinal study of 10 New York State dairy farms, which included yearlong monthly assessments of the frequency and levels of bulk tank raw milk psychrotolerant spore contamination, along with administration of questionnaires to identify farm management practices associated with psychrotolerant spore presence over time. Milk samples were first spore pasteurized (80°C for 12 min) and then analyzed for sporeformer counts on the initial day of spore pasteurization (SP), and after refrigerated storage (6°C) for 7, 14, and 21 d after SP. Overall, 41% of samples showed sporeformer counts of >20,000 cfu/mL at d 21, with Bacillus and Paenibacillus spp. being predominant causes of high sporeformer counts. Statistical analyses identified 3 management factors (more frequent cleaning of the bulk tank area, the use of a skid steer to scrape the housing area, and segregating problem cows during milking) that were all associated with lower probabilities of d-21 Bacillales spore detection in SP-treated bulk tank raw milk. Our data emphasize that appropriate on-farm measures to improve overall cleanliness and cow hygiene will reduce the probability of psychrotolerant Bacillales spore contamination of bulk tank raw milk, allowing for consistent production of raw milk with reduced psychrotolerant spore counts, which will facilitate production of HTST-pasteurized milk with extended refrigerated shelf life.

Bovine Tuberculosis Prevalence, Potential Risk Factors and Its Public Health Implication in Selected State Dairy Farms, Central Ethiopia

Bovine Tuberculosis Prevalence, Potential Risk Factors and Its Public Health Implication in Selected State Dairy Farms, Central Ethiopia

Optimally achieving milk bulk tank somatic cell count thresholds

High somatic cell count in milk leads to reduced shelf life in fluid milk and lower processed yields in manufactured dairy products. As a result, farmers are often penalized for high bulk tank somatic cell count or paid a premium for low bulk tank somatic cell count. Many countries also require all milk from a farm to be lower than a specified regulated somatic cell count. Thus, farms often cull cows that have high somatic cell count to meet somatic cell count thresholds. Rather than naïvely cull the highest somatic cell count cows, a mathematical programming model was developed that determines the cows to be culled from the herd by maximizing the net present value of the herd, subject to meeting any specified bulk tank somatic cell count level. The model was applied to test-day cows on 2 New York State dairy farms. Results showed that the net present value of the herd was increased by using the model to meet the somatic cell count restriction compared with naïvely culling the highest somatic cell count cows. Implementation of the model would be straightforward in dairy management decision software.

1220 Facilities, management, and animal factors associated with primiparous cows postpartum herd exit risk in New York state dairy farms

1220 Facilities, management, and animal factors associated with primiparous cows postpartum herd exit risk in New York state dairy farms

1221 Facilities, management, and animal factors associated with calf losses in New York state dairy farms

1221 Facilities, management, and animal factors associated with calf losses in New York state dairy farms

1219 Facilities, management, and animal factors associated with heifer culls in New York State dairy farms

1219 Facilities, management, and animal factors associated with heifer culls in New York State dairy farms

Validation of a mycoplasma molecular diagnostic test and distribution of mycoplasma species in bovine milk among New York State dairy farms

Mycoplasma mastitis is a contagious and costly disease of dairy cattle that significantly affects animal health and milk productivity. Mycoplasma bovis is the most prevalent and invasive agent of mycoplasma mastitis in dairy cattle, and early detection is critical. Other mycoplasma have been isolated from milk; however, the role and prevalence of these species as mastitis pathogens are poorly understood. Routine screening of milk for mycoplasma by bacteriological culture is an important component of a farm control strategy to minimize a herd mycoplasma outbreak, but phenotypic methods have limited ability to speciate mycoplasma, affecting how farms and practitioners can understand the role and effect of species other than M. bovis in herd health. Fastidious mycoplasma culture can be lengthy and inconclusive, resulting in delayed or false negative reports. We developed and validated a multitarget PCR assay that can in the same day confirm or reject a presumptive positive mycoplasma culture found upon bacteriological testing of clinical specimens, further discriminate between Acholeplasma and Mycoplasma, and identify M. bovis. Coupled with sequence analysis isolates can be further identified as bovine mycoplasma Mycoplasma arginini, Mycoplasma alkalescens, Mycoplasma canadense, Mycoplasma bovirhinis, Mycoplasma bovigenitalium, Mycoplasma californicum, Acholeplasma laidlawii, and Acholeplasma oculi. Assay validation included analysis of 845 mycoplasma representing these species and 30 additional bacterial species obtained from routine milk submissions to the Quality Milk Production Services from New York State farms and veterinary clinics between January 2012 and December 2015. Among 95 herds, we found 8 different Mycoplasma species and 3 different Acholeplasma species, with an overall prevalence of M. bovirhinis of 1%, A. oculi of 2%, M. arginini of 2%, M. californicum of 3%, M. canadense of 10%, M. bovigenitalium of 10%, A. laidlawii of 11%, M. alkalescens of 17%, and M. bovis of 78%. More than one mycoplasma was found in 14% of the herds tested, and both M. bovis and Acholeplasma were found in 6% of the farms. Incorporation of the validated molecular diagnostic assay into routine bacteriological screening as a supportive confirmation and identification tool will lead to an improved assessment of Mycoplasma and Acholeplasma prevalence data, which will facilitate increased knowledge about the role of these mycoplasma in mastitis.

Microbiological profile of milk produced on dairy farms in the State of São Paulo according to the standards of Normative Instruction 62 of the Brazilian Ministry of Agriculture, Livestock and Food Supply

Objetivou-se avaliar o atendimento a Instrucao Normativa 62 em propriedades leiteiras no estado de Sao Paulo, estudar a ocorrencia de mastite subclinica de quartos mamarios por meio do California Mastitis Test (CMT) e da contagem de celulas somaticas (CCS), estabelecer a etiologia da mastite, analisar o comprometimento da CCS das diferentes propriedades de acordo com os micro-organismos isolados e verificar a influencia das condicoes climaticas na ocorrencia de mastite. Os percentuais de mastite subclinica analisados pelo CMT em relacao ao numero de animais e quartos mamarios foram de 48,3% (232/480) e 26,2% (496/1892) respectivamente. Considerando o limite atual de CCS da IN 62, 88,8% das propriedades atendem a IN 62. No entanto, analisando o objetivo final da IN 62 que e atingir 400.000 cels/mL algumas propriedades ja ultrapassam e outras estao muito proximas desse limite. As frequencias dos micro-organismos por propriedade foram diferentes. As propriedades E e D tiveram os resultados mais criticos. Entre as 388 amostras positivas ao exame microbiologico, Staphylococcus aureus foi o micro-organismo mais prevalente, com 34,02% dos isolados. O Streptococcus spp. foi o agente mais associado as elevadas CCS, com coeficiente de correlacao de 0,20286. O trabalho mostrou que os patogenos da mastite consistem em um fator de variacao da resposta celular. Os micro-organismos isolados representam uma reducao na producao e qualidade do leite, alem de oferecerem varios riscos a saude humana. A associacao entre clima e mastite esta subordinada ao tipo de manejo adotado, profilaxia e tambem a estrutura e limpeza das instalacoes da propriedade.

Efficiency and regulation: a comparison of dairy farms in Ontario and New York State

We study the cost efficiency of dairy farms operating under two different regulatory regimes. While neo-classical economic theory suggests that farms should maximize their efficiency regardless of their regulatory system, we find that farms operating in a more regulated environment have, on average, a lower cost efficiency. Differences in cost efficiency are primarily explained by allocative decisions—farms in the more regulated environment are overcapitalized and overly reliant on homegrown feed. Efficiency is estimated using bootstrapped data envelopment analysis and a stochastic distance function. We discuss the implications of these results for welfare and policy.

Long-term trends of nitrogen and phosphorus mass balances on New York State dairy farms

The whole-farm nutrient mass balance (NMB) is an adaptive management tool that can be used to identify areas for improvement in nutrient management and to monitor progress over time. The objectives of this study were to (1) evaluate the trends of nitrogen and phosphorus mass balances of 27 New York State dairy farms over 6 to 10 yr, (2) identify specific management changes made by 4 case study farms that improved NMB over time by shifting NMB up or down depending on the initial NMB, and (3) evaluate the potential of key indicators to identify opportunities for improvement in NMB. During the study period, milk price fluctuated whereas costs associated with feed and fertilizer increased substantially. Of the 27 farms, 67 to 74% (depending on the nutrient) decreased NMB per hectare over time, whereas 63 to 67% decreased NMB per megagram of milk over time. In general, changes in NMB were directionally correct, with 43 to 56% of farms operating in the optimum operational zone (with both NMB per hectare and per megagram of milk below the feasible levels suggested for New York) toward the end of the study versus 22 to 26% in the first 2 yr of the assessments. The 4 case study farms improved their NMB, whole-farm nutrient use efficiencies, and feed nutrient use efficiencies while maintaining or increasing milk production per cow. The case study farmers made the largest changes in precision feed management, reducing protein and P in purchased feed by replacing concentrates with blends with lower nutrient concentrations. Total nutrient imports, feed imports, the percentage of homegrown feed and nutrients, the concentration of nutrients in the purchased feed, fertilizer imports, and overall crop yields were useful in identifying potential areas for improvement in NMB.

Changes in nutrient mass balances over time and related drivers for 54 New York State dairy farms

Whole-farm nutrient mass balances (NMB) can assist producers in evaluation and monitoring the nutrient status of dairy farms over time. Most of the previous studies that report NMB for dairy farms were conducted over 1 to 3 yr. In this study, annual N, P, and K mass balances were assessed on 54 dairy farms in New York State for 4 to 6 yr between 2005 and 2010 with the objectives to (1) document changes in NMB over time and drivers for change, and (2) identify nutrient use efficiency parameters that predicted the potential for improvement in NMB. The study farms varied in size (42 small, 12 medium and large) and management practices. Phosphorus, K, and 2 N balances (N1 without N2 fixation, and N2 including N2 fixation) were calculated. In general, farms with high initial NMB levels reduced them over time whereas farms with negative NMB tended to increase their NMB, demonstrating a tendency across all farms to move toward more optimal NMB levels over time. Sixty-three to 76% of farms (depending on the nutrient) reduced their NMB per hectare over the 4 to 6 yr, and 55 to 61% of these farms were able to do so while increasing milk production per cow. Across all farms, the overall reduction in NMB per hectare averaged −22kg of N/ha for N1 (29% reduction), −16kg of N/ha for N2 (15% reduction), −4kg of P/ha (36% reduction), and −10kg of K/ha (29% reduction). Change in feed imports was the most important driver for change in N and P balances across farms, whereas adjustments in both feed and fertilizer imports affected the K balances. Key predictors of potential areas for improvement in NMB over time include total nutrient imports, feed imports, animal density, percentage of farm-produced feed and nutrients, and feed nutrient use efficiency. Overall, this study highlights the opportunities of an adaptive management approach that includes NMB assessments to evaluate and monitor changes in nutrient use efficiency and cost-efficiency over time.

Recent Emergence of Escherichia coli with Cephalosporin Resistance Conferred by blaCTX-M on Washington State Dairy Farms.

Enterobacteriaceae-associated blaCTX-M genes have become globally widespread within the past 30 years. Among isolates from Washington State cattle, Escherichia coli strains carrying blaCTX-M (CTX-M E. coli strains) were absent from a set of 2008 isolates but present in a set of isolates from 2011. On 30 Washington State dairy farms sampled in 2012, CTX-M E. coli prevalence was significantly higher on eastern than on northwestern Washington farms, on farms with more than 3,000 adult cows, and on farms that recently received new animals. The addition of fresh bedding to calf hutches at least weekly and use of residual fly sprays were associated with lower prevalence of CTX-M E. coli. In Washington State, the occurrence of human pathogens carrying blaCTX-M genes preceded the emergence of blaCTX-M-associated E. coli in cattle, indicating that these resistance determinants and/or their bacterial hosts may have emerged in human populations prior to their dissemination to cattle populations.

English

English

Comparative antibiogram of coagulase-negative Staphylococci (CNS) associated with subclinical and clinical mastitis in dairy cows.

Aim:The present study was planned to determine the in vitro antibiotic susceptibility of coagulase-negative Staphylococci (CNS) strains isolated from clinical and subclinical cases of mastitis in dairy cows. Antibiotic sensitivity profile will be helpful to recommend early therapy at the field level prior to availability of CST results.Materials and Methods:The milk samples from cases of clinical mastitis received in Mastitis Laboratory, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana and those of subclinical mastitis collected during routine screening of state dairy farms, were subjected to microbial culture. Identification of CNS organisms was done by standard biochemical tests. Antibiotic sensitivity testing, based on 30 antibiotics belonging to 12 groups, was done on 58 randomly selected CNS isolates (clinical isolates: 41, subclinical isolates: 17).Results:Isolates were highly susceptible to chloramphenicol (98.3%), gentamicin (93.1%), streptomycin (91.4%), linezolid (91.4%), ceftixozime (87.9%), cloxacillin (86.2%), clotrimazole (86.2%), bacitracin (86.2%), enrofloxacin (84.5%) and ceftrioxone + tazobactum (70.7%), while resistance was observed against amoxicillin (77.6%), penicillin (75.9%), ampicillin (74.1%) and cefoperazone (51.7%). Overall, isolates from clinical cases of mastitis had a higher resistance than subclinical isolates.Conclusion:CNS isolates were susceptible to chloramphenicol, gentamicin and streptomycin, while higher resistance was recorded against routinely used penicillin group.