Average Somatic Cell Count Research Articles

The Influence of Selected Environmental Factors on the Number of Somatic Cells in Cistern and Alveolar Milk of Polish Holstein-Friesian Cows.

The aim of the study was to evaluate the influence of the milking phase on somatic cell count (SCC) in milk obtained from the cisternal and alveolar parts of udders of selected Polish Holstein-Friesian cows. The study also assessed the impact of other genetic and environmental factors on SCC variability in cisternal and alveolar milk, including: the individual cow, lactation stage, age of cow, production level, milking speed, fat-to-protein ratio, and milking type. The research included 15 cows of Polish Holstein-Friesian breed at different ages, lactation stages, and with varying daily milk yield. A total of 210 milk observations were conducted, including 105 for 1 min milking and 105 for 8 min milking. The results obtained in the study indicated that milk obtained during two different milking phases exhibited similar SCC levels (F for LOGSCC = 0.79). The average actual SCC in milk produced by 15 cows in 105 observations for 1 min milking was 219,000 cells/mL, while for 8 min milking it was 229,000 cells/mL. The results were inconclusive, suggesting that SCC in cisternal and alveolar milk must be influenced by factors other than the milking phase. The analysis of variance conducted for this purpose provided the basis for stating a highly statistically significant effect of the individual cow (F for LOGSCC = 147.9), lactation stage (F for LOGSCC = 54.64), age of cow (F for LOGSCC = 12.39), daily production level (F for LOGSCC = 34.49), milking speed (F for LOGSCC = 17.56), and fat-to-protein ratio (F for LOGSCC = 22.99) on the variability of characteristics defining SCC in milk. In summary, SCC is characterized by high variability, influenced by a range of environmental and genetic factors such as the individual cow, lactation stage, age of cow, milking speed, and dietary fat-to-protein ratio. The influence of milking phase (1 min or 8 min) and milking type (morning or evening) should be considered inconclusive based on the entire population studied. For half of the cows, SCC in cisternal milk was higher than in alveolar milk, while for the other half, the situation was reversed. Further observations are required to confirm the hypothesis regarding the extent to which cows' immunological response to bacterial infections is concentrated in the cisternal or alveolar part of the udder under national environmental conditions.

Key udder health parameters on dairy farms with an automated milking system

Despite the increasing use of automated milking systems (AMS), udder health performance of farms has only been limitedly quantified on farms with a milking robot. The objective of this study was to quantify udder health parameters (UHP) at test-day and at herd level on robotic farms using routinely collected somatic cell counts (SCC) from test-day data, and to study the correlations between these UHP. Additionally, the associations between UHP and season, year and farm size as well as the association between the daily milk production and the herd milk SCC were investigated. To this end, we collected SCC test-day data from 48 Belgian and Dutch farms participating in the milk recording of a local dairy herd improvement program. The UHP were calculated based on individual animal records at each test day over three years (2017 until 2019). These UHP included herd milk SCC, average heifer SCC, average cow SCC, percentage of high SCC, percentage of new high SCC, percentage of chronic high SCC, percentage of high SCC cows after calving, and percentage of recovery during the lactation. By fitting a linear mixed model effect for each of the different UHP, significant associations between the UHP and season, year and farm size were observed at test-day level. A poorer udder health was observed during summer compared to other seasons and generally, larger farms performed worse than smaller farms. Using a linear regression model, a significant negative correlation between herd average SCC and average daily milk production was found: an increase of 6,085 cells/mL was associated with a decrease of one kg of milk production. Finally, the cow-level UHP were averaged over all test days of the entire study period per farm to investigate the farm-level udder health performance and correlations between them. At the farm level, UHP analysis revealed most farms had poor udder health performance (i.e. the herd milk SCC, average heifer SCC, average cow SCC, percentage of new high and chronic high SCC were all higher than their target values) as proposed by Barkema et al. (2013). Both at the farm and at test day level, strong correlations were found among the UHP. Similar to studies on farms with conventional milking systems, a strong correlation between herd milk SCC and the percentage of new and chronic high SCC cows was found. This study gives new insights into udder health performance on farms with an AMS and provides veterinarians and other dairy industry stakeholders with concrete benchmarks for udder health performance on farms.

Total bacterial count and somatic cell count in bulk and individual goat milk around kidding: Two longitudinal observational studies

Total bacterial count (TBC) and somatic cell count (SCC) are important quality parameters in goat milk. Exceeding the bulk milk TBC (BMTBC) thresholds leads to price penalties for Dutch dairy goat farmers. Controlling these milk quality parameters can be challenging, especially around kidding. First, we describe the variation and the peaks around kidding of TBC and SCC in census data on Dutch bulk milk over the last 22 years. Second, to explore causes of these elevations, we studied the variation of TBC and SCC in individual goat milk from 3 weeks before to 5 weeks after kidding and their association with systemic response markers interferon-γ (IFN-γ), calprotectin, β-hydroxybutyrate (BHB), body condition score (BCS) and fecal consistency. We visited 4 Dutch dairy goat farms weekly for 10 to 16 weeks around kidding. Some of the goats had been dried off, other goats were milked continuously throughout pregnancy. A total of 1,886 milk samples from 141 goats were collected for automated flowcytometric quantification of TBC and SCC measurement. IFN-γ, calprotectin and BHB were determined twice in blood of the same goats, most samples were collected after kidding. The BCS and fecal consistency were scored visually before and after kidding. We found a strong correlation between TBC and SCC (Spearman's rho = 0.87) around kidding. Furthermore, in the third week before kidding, the average TBC (5.67 log10 cfu/mL) and SCC (6.70 log10 cells/mL) were significantly higher compared with the fifth week after kidding, where the average TBC decreased to 4.20 log10 cfu/mL and the average SCC decreased to 5.92 log10 cells/mL. In multivariable linear regression models, farm and stage of lactation were significantly associated with TBC and SCC, but none of the systemic response markers correlated with TBC or SCC. In conclusion, TBC and SCC in dairy goats were high in late lactation and decreased shortly after parturition. For SCC, the dilution effect might have caused the decrease, but this was not plausible for TBC. Moreover, the excretion of bacteria and cells in goat milk was not associated with the selected systemic response markers that were chosen as a read out for general immunity status, intestinal health and metabolic diseases. Therefore, we assume that the TBC increase before kidding and the decrease after parturition is caused by other systemic, possibly hormonal, processes. To reduce BMTBC and BMSCC, it would be advisable to keep milk of goats with highest numbers of bacteria and cells in their milk out of the bulk milk during end lactation. Further studies are needed to investigate the effects of withholding this end lactation milk from the bulk tank.

Animal welfare on Argentinean dairy farms based on the Welfare Quality® protocol framework

Animal welfare is a multidimensional concept that comprises animal health, mental state and natural living conditions and plays an essential role in dairy production. On dairy farms, animal welfare can be assessed with different available protocols. The goal of this study was to describe the animal welfare strengths and hazards of dairy farms in Argentina using the Welfare Quality® protocol as a framework. We conducted a literature search using the Scopus database to find articles related to the measures included in the protocol for Argentinean farms. Furthermore, we included data from national statistics. The data available were grouped according to the four principles of the protocol: good feeding, good housing, good health, and appropriate behavior. The results suggest that cows are well nourished; however, water provision is limited because grazing cows need to walk long distances, between 244 m and 460 m, to access a water point. Heat stress is a notable constraint affecting the welfare of cows, as the temperature-humidity index is greater than 72 for at least 100 days during the year. The prevalence of lameness and downer cows was estimated to be 2.2% and 0.7%, respectively, which are below the thresholds for ensuring good welfare. The annual average somatic cell count was 385,000/ml, close to the cutoff recommended for good health. The mortality rate of the cows was higher than recommended. The main strength of Argentinean dairy farms in relation to animal welfare is access to pasture throughout the year for 90% of the farms.

Quality assessment and comparative study of somatic cell fluctuation at different lactation stages of buffalo's milk

The aim of current study is to check the health status and the quality of milk by counting somatic cells. Total 50 samples of fresh raw buffalo milk were gathered and divided into five groups on the basis of lactation stages i.e early, mid, late, buffalo at parturition and post parturition (colostrum). Fresh samples were collected and assessed with quality assessment test i.e. pH analysis, lactometer reading test, clots on boiling (COB), alcohol precipitate test (APT) and acidity % age test and the somatic cell count (SCC) through Neubauer chamber under light microscope. Data were evaluated by the stage of lactation with the SPSS programme. The total mean values of pH, Lr and acidity % at each lactation stages were (±6.96, ±31 and ±0.19). Significant effect of SCC on different stages were observed (P<0.05). The average SCC was determined to be 10.1000±5.8121 cells/ml. The effects lactation stages on the SCC value between group were statistically significant (P<0.05). The mean SCC values for early, mid, late, parturition and post parturition stages were (±6.4750, ±5.7500, ±10.8750, ±16.2750 and ±11.1250). The significant differences recognized between the groups indicates that there is a fluctuation of somatic cells at different lactation stages. The number of somatic cells increase from early stage, then decrease gradually in mid stage and starts increasing till the end of lactation and have no significant difference (P<0.05), whereas the mean comparison is highly significant in parturition and colostrum stage.

Bacterial count and somatic cell count in milk from community tanks in Alagoas

Milk is a highly nutritious liquid produced by the mammary glands of cows, serving as a crucial food source for a significant portion of the population. Therefore, ensuring its quality and safety is essential. The purpose of this study is to evaluate the Plate Count and Somatic Cell Count of raw milk from community expansion tanks in the state of Alagoas. For the research, 160 milk samples were collected from mammary quarters in the months of January, February, May, and August 2013, across 23 municipalities covering the three mesoregions of the state of Alagoas. The samples were sent in appropriate containers to the Milk Quality Network Laboratory for Somatic Cell Count (SCC) and Plate Count (PC) analysis. After analysis, it was found that 79.4% (127/160) of the samples met the criteria established by legislation for SCC, while 20.6% (33/160) did not. For PC, 100% (160/160) of the samples were non-compliant with the limits set by legislation. The study highlighted a higher percentage of samples outside the SCC standard in August and the PC with the highest percentage of non-compliance occurring in May. The average SCC and PC for the studied regions showed a significant difference in SCC mean (748,235.3 cells/mL) in the East region, with no significant difference in PC, having the lowest mean (1,853,029.4 CFU/mL) compared to other regions. It was noted that 12.5% of the samples had a fat measurement outside the allowed range, total proteins ranged from 2.4 to 3.86 (g/100g), and the amount of lactose ranged from 3.42 to 5.42 (g/100g). Thus, it can be concluded that all samples were non-compliant with legislation for PC, particularly in the eastern region of the state, indicating issues with the milk extraction, preservation, or cooling process. Implementation of corrective and educational measures is suggested to improve the quality of the product.

Status of subclinical mastitis in lactating cows of selected dairy farms in Bangladesh and farmers’ understanding of mastitis

Background: Subclinical mastitis, a disease that is economically important to dairy cows, affects milk production. Management of udder health is an essential element in the process of safe milk production. Consumption of milk with a high somatic cell count (SCC) may also pose a health risk to humans. Objectives. We aimed to evaluate the SCC method for the detection of SCM in dairy cows and to assess farmers’ knowledge, attitudes, and practices towards mastitis detection and control. Methods. A cross-sectional study was conducted to evaluate the current status of subclinical mastitis (SCM) in lactating dairy cows. The research work was also designed to assess farmers’ knowledge, attitudes, and practices about bovine mastitis. A total of 320 milk samples from 80 lactating cows were collected for physical examination and tested for subclinical mastitis using SCC. Results. Out of 80 lactating cows examined, 53 (66%, 95% CI: 55-76%) cows were diagnosed with subclinical mastitis. The average cow level SCC per ml of milk was 503101. According to the farmers’ self-report, 100% of farms practiced hand milking and 100% of milkmen washed their hands before milking. The majority of farms (90%) had brick floors. Most of the farmers (70%) knew about screening for subclinical mastitis. However, they never performed screening to detect subclinical mastitis. Conclusion. The high prevalence of SCM in dairy raised significant concerns about farm management, personal hygiene and biosecurity practices. Further study is needed to identify the etiologies of SCM and its associated risk factors.

Mastitis in a flock of milking sheep.

Determination of somatic cell counts (SCC) becomes more and more important also for ewe's milk. SCC can be a useful indicator of milk quality for milk processors while it can be a mastitis indicator for sheep keepers and an important selection criterion for breeders. The objective of our study was to acquire basic information about factors influencing SCC variability in lambing ewes of the Tsigai (T) and Improved Valachian (IV) breeds. Somatic cell counts (SCC) were determined in 866 milk samples in 2017 and 2018, during lamb sucking and during milking period. An instrument Fossomatic 90 (Foss Electric, Hillerød, Denmark) was used for analysis. Average SCC varied from 270 to 1897 × 103 cells/ml during lamb sucking and from 268 to 2139 × 103 cells/ml during milking period. Differences between the sampling periods were statistically significant in 2017. An increase in SCC was observed at the end of both sucking and milking periods. An overall evaluation of lactation brought about the average SCC at 364 × 103 cells/ml in 2017 (log(10) SCC - 2,25) and at 1,091 × 103 cells/ml in 2018 (log(10) SCC - 2,68). The indicator log(10) was significantly influenced by breed in 2017 (T - 2,61; IV - 2,75). The effect of lactation number and number of sucking lambs did not have any significant influence on SCC.

The effect of a herbal anthelmintic (garlic and neem) on the production performance of Karan Fries cows

The present study was conducted to evaluate the effect of a herbal anthelmintic (Garlic and Neem combination) on the production parameters of Karan Fries cows. For this study, a total of 28 freshly calved cows (1-3 parity), were divided into four groups with 7 cows in each group (T1, T2, T3, T4). The cows in T1 were kept as the control. In T2, a commercial dewormer was used, whereas in T3, a single dose of garlic and neem in the ratio of 1:5 @ 4g/kg BW was used 7 days post calving, and in T4, in addition to the first dose, a second dose was also supplemented on day 60 after calving. The milk samples were collected at 0, 1, 2, 3, 4, 5, 6, 7, 8 fortnights after the deworming treatment and analyzed for milk composition and SCC. From the 5th fortnight onwards, a significantly higher (P≤0.05) daily milk yield (kg) was observed in T1, T2, T3 groups compared to T1. The overall average Somatic Cell Count (SCC) was found to be significantly lower in T4 followed by T3, compared to T2, which was further significantly lower than T1. From the 3rd to the 8th fortnight, protein (%) was observed to be significantly (p≤0.05) higher in the anthelmintic treated groups (significantly higher in T4 followed by T2, T3) compared to T1. From the 4th to the 8th fortnight, fat (%) was significantly (P≤0.05) higher in T4 compared to T1. The overall SNF (%) in T2, T3 and T4 differed significantly (P≤0.05) from the control group (T1). The overall value of lactose (%) was found to be significantly higher in the T4 group compared to the other groups. During the 7th and 8th fortnight significantly higher (P≤0.05) lactose (%) was observed in the T4 group compared to the other groups. This study concluded that besides providing better anthelmintic effects in comparison to chemical anthelmintics, the garlic and neem combination might improve the production performance of dairy cows.

Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows

Use of selective dry cow antimicrobial therapy requires to precisely differentiate cows with an intramammary infection (IMI) from uninfected cows close to drying-off to enable treatment allocation. Milk somatic cell count (SCC) is an indicator of an inflammatory response in the mammary gland and is usually associated with IMI. However, SCC can also be influenced by cow-level variables such as milk yield, lactation number and stage of lactation. In recent years, predictive algorithms have been developed to differentiate cows with IMI from cows without IMI based on SCC data. The objective of this observational study was to explore the association between SCC and subclinical IMI, taking cognizance of cow-level predictors on Irish seasonal spring calving, pasture-based systems. Additionally, the optimal test-day SCC cut-point (maximized sensitivity and specificity) for IMI diagnosis was determined. A total of 2,074 cows, across 21 spring calving dairy herds with an average monthly milk weighted bulk tank SCC of ≤200,000 cells/mL were enrolled in the study. Quarter-level milk sampling was carried out on all cows in late lactation (interquartile range = 240-261 d in milk) for bacteriological culturing. Bacteriological results were used to define cows with IMI, when ≥1 quarter sample resulted in bacterial growth. Cow-level test-day SCC records were provided by the herd owners. The ability of the average, maximum and last test-day SCC to predict infection were compared using receiver operator curves. Predictive logistic regression models tested included parity (primiparous or multiparous), yield at last test-day and a standardized count of high SCC test-days. In total, 18.7% of cows were classified as having an IMI, with first parity cows having a higher proportion of IMI (29.3%) compared with multiparous cows (16.1%). Staphylococcus aureus accounted for the majority of these infections. The last test-day SCC was the best predictor of infection with the highest area under the curve. The inclusions of parity, yield at last test-day, and a standardized count of high SCC test-days as predictors did not significantly improve the ability of last test-day SCC to predict IMI. The cut-point for last test-day SCC which maximized sensitivity and specificity was 64,975 cells/mL. This study indicates that in Irish seasonal pasture-based dairy herds,with low bulk tank SCC control programs, the last test-day SCC (interquartile range days in milk = 221-240) is the best predictor of IMI in late lactation.

Analysis of The Effect of Region, Province and Breed on Somatic Cell Count in Dairy Cattle in Turkey By Regression Tree Method

This study aimed to determine the effect of various environmental factors on the somatic cell count (SCC) in cow’s milk. The material of the study consisted of an SCC analysis result obtained from 207.614 raw milk samples collected from 65.288 head cattle had different breeds, ages, lactation number, and lactation length between May and December in 2019. They were raised on 6,305 dairy farms that are members of the Cattle Breeders Association (CBAT). In order to determine the effect of region, city, and cattle breed on SCC in raw milk of cattle, a regression tree was created using the Chi-square Automatic Interaction Detection (CHAID) algorithm, a Data Mining (DM) method. Accordingly, the mean SCC value of all enterprises was determined as 201.253 cells/mL. In this study, it was found that the region, city and breed groups with the highest average somatic cell counts were CAR, MSR, MR and SAR region group (285.430 cells/mL); C09, C45, C20, C64, C48, C43 city group (266.744 cells/mL); and HF, MC, and BS breed group (295.705 cells/mL). As a result of this study, the variables affecting SCC were determined as region, city, and breed respectively, in order of importance. Keywords: CHAID; Dairy cattle; Somatic cell count

Association of herd hyperketolactia prevalence with transition management practices and herd productivity on Canadian dairy farms—A retrospective cross-sectional study

The objective of this observational study was to assess the relationship between herd-level prevalence of hyperketolactia (HPH) with management practices of the transition period and herd milk production. Dairy herds (n = 71) were selected based on their inclusion in a herd management risk assessment study (August 2014-March 2018) using a Vital 90 (Elanco) Risk Assessment tool (one assessment per farm). Data from multiple milk recording test-days (Dairy Herd Improvement, DHI; Lactanet) were included in the analysis. Tests performed within ±6 mo relative to each farm's risk assessment date were included (10 ± 2 SD tests per farm). The majority of the farms were located in Ontario (83%). For each farm DHI test, the data set included herd average milk yield (kg/cow per day), average milk fat and protein (%), average somatic cell count (cells/mL), average days in milk (DIM), number of cows tested for ketosis, number of ketosis-positive tests (milk β-hydroxybutyrate ≥0.15 mmol/L), and proportion of cows by parity groups. Overall HPH (5-21 DIM) was calculated based on data available per farm (sum of all positive tests within 5-21 DIM/sum of all cows tested within 5-21 DIM). Each farm average was obtained by considering all test-days. A logit-transformation was applied to hyperketolactia prevalence. Linear regression models (PROC GLM and MIXED of SAS, Version 9.4) were used to predict herd HPH (milk β-hydroxybutyrate ≥0.15 mmol/L within 5 to 21 DIM; the outcome of interest). Four initial models (far-off, close-up, and fresh periods, and DHI) were separately built to assess associations between their variables and HPH; a final model considered variables selected in the initial models. Univariable (liberal P < 0.25) followed by multivariable models were used to build specific models for each period of the risk assessment. Herd prevalence of hyperketolactia was 27 ± 14%, with an average herd size of 141 ± 110 cows. The final HPH model (R2 = 24.8%) included weighted milk yield, the proportion of primiparous cows, water access in the close-up period, and access to rest areas or stall access in the fresh period. Herd prevalence of hyperketolactia was negatively associated with milk yield [odds ratio, OR = 0.96 (95% confidence interval 0.92-0.99)] and proportion of primiparous cows [OR = 0.98 (0.96-0.99)]. The odds of hyperketolactia were greater with poor water access and quality (<5 cm of linear access per cow; dirty water; only 1 water location in pen) than with ≥10.2 cm of linear access per cow; clean water; >2 water locations in pen [1.23 (1.11-2.39)] in the close-up period. The odds of hyperketolactia were greater in farms providing limited access to rest areas in the fresh period than in farms providing constant access to rest areas, without dead-ends [1.64 (1.03-2.80)]. In Canadian dairy herds, HPH in early lactation was associated with certain transition-period management practices and was negatively associated with herd productivity.

Evidence that elevation of maternal somatic cell count could lead to production of offspring with inferior reproductive and productive performance in dairy cows during the first lactation period

Although the effect of mastitis on reproduction and production of lactating dairy cows has been vastly studied, little information is available about the association of maternal udder health status with offspring reproduction and production. Therefore, the present research was conducted to study the association between maternal average monthly somatic cell count (SCC) with reproduction, anti-Müllerian hormone (AMH) concentration, udder health status and milk production in the offspring. Based on maternal average monthly SCC (MSCC), offspring were classified into five categories including MSCC1 (SCC <200,000; n = 3005), MSCC2 (200,000 ≤ SCC <400,000; n = 252), MSCC3 (400,000 ≤ SCC <600,000; n = 103), MSCC4 (600,000 ≤ SCC <800,000; n = 40) and MSCC5 (SCC ≥800,000; n = 61). Data associated with reproduction, production and udder health status of offspring were retrieved from the herd database. In addition, blood samples were collected from a subset of offspring (n = 136) for measurement of serum AMH, as a reliable marker of ovarian reserves. Offspring in MSCC5 category had more services per conception and longer calving to conception interval than offspring in MSCC1 and MSCC2 categories (P < 0.05). The average number of SCC and risk of clinical mastitis in the offspring were not associated with MSCC (P > 0.05). But offspring in MSCC5 category produced less milk, fat and protein than offspring in MSCC1 category (P < 0.05). In addition, AMH concentration was lower in MSCC5 than MSCC1 category (P < 0.05). In conclusion, the present study showed that elevated maternal average monthly SCC could culminate in birth of offspring with inferior reproductive performance, smaller size of ovarian reserves and lower level of milk production during the first lactation period.

A Practical Application of Genomic Predictions for Mastitis Resistance in Italian Holstein Heifers.

Simple SummarySelecting the best animals for farms has always been a fundamental aspect of animal breeding. To assist in the traditional selection performed on phenotypes and to further improve genetic selection as performed in recent years, genomic tools could be applied to select animals early in their productive careers. The aim of this study was to evaluate the application of a commercial genomic tool on animals selected from farms grouped by their average somatic cell count. The obtained results showed that farms with good animal management practices also rear animals with better genomic indexes, probably due to selection on other well-established indexes (e.g., productive traits). Selecting heifers based on their wellness genomic indexes would further improve both their economic value and their disease resistance and resilience.Heifers are a fundamental resource on farms, and their importance is reflected in both farm management and economy. Therefore, the selection of heifers to be reared on a farm should be carefully performed to select only the best animals. Genomic selection is available nowadays to evaluate animals in a fast and economic way. However, it is mainly used on the sire line and on performance traits. Ten farms were selected based on their 5-year records of average somatic cell count and evenly classified into high (>300,000 cells/mL) and low somatic cell count (<150,000 cells/mL). Genomic indexes (regarding both wellness and productive traits) were evaluated in 157 Italian Holstein heifers reared in the selected ten farms (90 from high-cells farms and 67 from low-cells ones). Linear mixed models were fitted to analyze the effects of the abovementioned genomic indexes on related phenotypes. Results have shown that farms classified into low somatic cell count had an overall better animal genomic pool compared to high somatic cell count ones. Additionally, the results shown in this study highlighted a difference in wellness genomic indexes in animals from farms with either a high or a low average somatic cell count. Applying genomic tools directly to heifer selection could improve economic aspects related to herd turnover.

Udder health, veterinary costs, and antibiotic usage in free stall compared with tie stall dairy housing systems: An optimized matching approach in Switzerland

Observational studies are important in livestock science. As treatment is not assigned randomly in such studies, selection bias can be a problem. This is often addressed by matching methods. However, if treatment and control groups differ considerably in their characteristics, it might be necessary to additionally prune observations that lack overlap in the opposite group. “Matching Frontier” method was developed because pruning observations manually often results in suboptimal solutions. The feasibility of the approach for animal health and welfare issues was tested in an observational study evaluating the effect of free stall housing and increased lying comfort on udder health, veterinary costs, and antibiotic usage in Swiss dairy farming.Data were collected in a survey with 1835 Swiss dairy farmers (response rate 28.3%). The treatment group (n = 179) comprised farmers participating in a voluntary animal welfare program that, in addition to free stall housing, required increased lying comfort. Farmers in the control group (n = 229) kept their cows in tie stalls.Using the Matching Frontier method, treated units were matched to control units based on five confounders. Subsequently, observations were pruned to achieve sufficient balance and overlap between the two groups. The effect of the program on the eight outcome variables was finally estimated using linear regression.Farmers in the treatment group had a lower incidence of clinical mastitis (−3.66 per 100 cow-years, −25%, p < 0.05), a lower incidence of culled cows due to udder health problems (−1.61 per 100 cow-years, −30%, p < 0.05), fewer veterinary costs (−42.44 per cow-year, −22%, p < 0.05), a lower incidence of total intramammary antibiotic treatments (−15.88 per 100 cow-years, −23%, p < 0.01), a lower incidence of intramammary antibiotic treatments for mastitis therapy (−7.83 per 100 cow-years, −32%, p < 0.01), and a lower incidence of intramammary antibiotic treatments for dry-cow therapy (−8.80 per 100 cow-years, −21%, p < 0.05). No differences were found for the average somatic cell count and the number of cows with a cell count above 150.000.The results suggest that free stall housing, in combination with increased lying comfort, can have a positive effect on udder health, animal welfare, and the economic situation of the farm. Additionally, fewer antibiotic treatments can be beneficial to public health.The Matching Frontier method has proven to be a helpful tool that may also have added value for future observational studies in livestock science.

Application of international committee for animal recording (ICAR) methodology in dairy herd management in south of Russia

This experiment was conducted to determine the advantages of introducing modern innovative approaches to dairy herd management based on the study and implementation of the methodological of International Committee for Animal Recording (ICAR). This research shows the main directions for introduction to new breeding and the technological model of interaction with breeding farms for breeding dairy cattle. This interaction occurs through the services provision for breeding farms, the control-assistant and expert-boniter services, as well as laboratories for selection control of milk quality and genetic control. The tasks of the control-assistant service included participation in the control milking of cows and individual milk samples picking from each cow and its delivery to the laboratory in a chilled form. Using as the example dairy herd of the black and white breed by studying the dynamics of somatic cells has been showing the effectiveness of different methods for assessing the quality of milk. Implementation of the milk quality regular monitoring during 1-2 months allows bringing the main parameters of milk quality in line with the requirements of national and international ICAR standards. The cow's conformation assessment by animals' linear assessment allows revealing the bull’s prepotent abilities and choosing the right strategy for improving the cow's conformation in the herd. Genetic well-being assessment of cows makes it possible to exclude unwanted individuals with genetic abnormalities and use only healthy animals in breeding. The research purpose was studying the possibility of applying the ICAR method in Russian breeding livestock to improve the dairy herd management system. The research results showed that Implementation of individual veterinary measures for two months allowed reducing the average somatic cell count by 1.85 times and reaching the level recommended by ICAR. The spread of individual indicators also significantly decreased. Therefore, Using the individual monitoring of dairy raw materials quality assessment makes it possible to study the influence of para-typical (climatic) factors on the content of dairy components, as well as to stabilize the quality parameters in terms of the level of somatic cells not higher than 200 thousand cells/cm3. Keywords: Breeding, Dairy cattle breeding, Dairy herd, Genetic resources, Milk quality.

Effect of supplementation of probiotics and rumen buffer on performance of lactating buffaloes

The study involved 12 Murrah buffaloes which were divided into two groups of six each viz. Control (T0) and Treatment group (T1). The buffaloes from Group T0 received standard concentrate mixture and roughages as per the routine practice of the farm. Whereas Group T1 received same ration as that of Group T0 along with supplement containing probiotics like yeast (Saccharomyces cerevisiae), bacteria (Bacillus subtilis, Bacillus pumilus and Bacillus amyloliquifaciens) and rumen buffer 10 g/day/animal. The experiment lasted for 91 days. The average daily milk yield and FCM yield, DMI, TDN and DCP intake of buffaloes from Treatment group (T1) was significantly (P˂0.01) higher than Control group. The efficiency of feed utilization in terms of dry matter required per kg of FCM yield produced was significantly (P˂0.01) better in Group T1 than Control group. The average milk fat, protein, total solids, SNF and lactose percentage of Group T1 was significantly (P˂0.01) higher than Control group. The average somatic cell count of milk of buffaloes form Group T1 was significantly (P˂0.05) lower than Control group. The economics of the study showed an extra profit of ₹ 25.20 in Supplemented group over Control group.

Estimation of genetic parameters for subclinical mastitis using a threshold model in first parity dairy cows under pasture-based systems of Los Ríos Region in Chile

Somatic cell count (SCC) is an indirect measurement to estimate mammary gland health status. This trait provides information regarding the severity of the mammary tissue inflammation in each quarter. Milk samples coming from the farm milk storage vat containing 100,000 to 200,000 cell/mL are considered suspicious, while SCC over 200,000 cell/mL is an indication of subclinical mastitis. Chilean dairy processors penalise farmers monetarily when their bulk tank samples reach levels of 300,000 cell/ mL SCC. The objective of this study was to quantify the additive genetic component of the liability of cows to reach the 300,000 cell/mL threshold. A data set containing the highest SCC test-day record of 10,528 first lactation cows from 15 commercial dairy farms of Los Ríos Region in southern Chile was analysed. The unknown continuous underlying susceptibility of each cow to reach the 300,000 SCC threshold was modelled as a function of a contemporary group formed by the herd, year, and calving season, the regression coefficient of the unknown underlying susceptibility value of a cow on her daily milk yield (MY) and the additive animal genetic effect. Bayesian inference and Gibbs sampling were used to estimate additive and residual variances. The average daily MY and SCC were 17.84±5.25 kg and 125,327±236,297 cell/mL, respectively. The estimated heritability varied from 0.03 to 0.22 and the average was 0.10±0.03. It is concluded that the genetic variability for the susceptibility to reach the 300,000 SCC threshold could be exploited to improve resistance to subclinical mastitis.

Farm-level factors associated with lameness prevalence, productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.

Detecting intramammary infection at the end of lactation in dairy cows

To reduce antimicrobial use, infusion of antimicrobials into only infected cows at the end of lactation (selective dry cow therapy) is preferable to infusion of every cow with antimicrobials. Use of selective dry cow antimicrobial therapy requires differentiation of probably infected from uninfected cows to enable treatment allocation. Milk somatic cell count (SCC) has been used to distinguish between cows with and without intramammary infection (IMI). However, SCC may be influenced by milk yield, stage of lactation, breed, and herd-level variables such as prevalence of infection. Cut points for SCC, to distinguish between cows with and without an IMI, may need to differ between cow age groups and breeds, or among herds. This study evaluated associations between SCC and major pathogen IMI in one or more quarters of 2,606 cows from 36 herds in 4 regions of New Zealand. In the last week of lactation, cows selected at random had milk samples collected from each quarter, and the teat-end condition and hygiene of the udder were scored. Herd- and cow-level data including age, breed, milk volume, and SCC at each production were recorded, and bulk tank milk SCC and volume of milk shipped were collated. At cow level, the association between average, maximum, and last cow-composite SCC, and presence of a major pathogen IMI in one or more quarters of cows, was examined using receiver operator curves. Predictive logistic regression models were then developed that included potential effect modifiers such as age, milk yield, and bulk tank milk SCC. The population average prevalence of major pathogen IMI was 7.2% of cows (95% confidence interval = 5.9-8.6), and this varied significantly between herds. The average, maximum, and last cow-composite SCC of lactation were all predictive of presence of a major pathogen IMI and did not differ in their ability to discriminate infected from uninfected cows. However, the optimal cut points for the last SCC, the maximum SCC, and average SCC were 108, 152, and 105 × 1,000 cells/mL, respectively. Inclusion of age, bulk tank SCC, and history of clinical mastitis improved overall model fit. However, inclusion of these variables did not improve the discriminatory power of maximum cow-composite SCC used alone. We conclude that cow-composite SCC on its own resulted in sensitivities and specificities of between 0.76 and 0.86, and 0.71 to 0.80, respectively, for determination of presence of major pattern IMI, and the predictive value was not improved by addition of other predictor variables.