Effects of season, milking routine and cow cleanliness on bacterial and somatic cell counts of bulk tank milk

The aim of the study was to investigate the effects of season, cow cleanliness and milking routine on bacterial and somatic cell counts of bulk tank milk. A total of 22 dairy farms in Lombardy (Italy) were visited three times in a year in different seasons. During each visit, samples of bulk tank milk were taken for bacterial and somatic cell counts; swabs from the teat surface of a group of cows were collected after teat cleaning and before milking. Cow cleanliness was assessed by scoring udder, flanks and legs of all milking cows using a 4-point scale system. Season affected cow cleanliness with a significantly higher percentage of non-clean (NC) cows during Cold compared with Mild season. Standard plate count (SPC), laboratory pasteurization count (LPC), coliform count (CC) and somatic cell count, expressed as linear score (LS), in milk significantly increased in Hot compared with Cold season. Coagulase-positive staphylococci on teat swabs showed higher counts in Cold season in comparison with the other ones. The effect of cow cleanliness was significant for SPC, psychrotrophic bacterial count (PBC), CC and Escherichia coli in bulk tank milk. Somatic cell count showed a relationship with udder hygiene score. Milking operation routine strongly affected bacterial counts and LS of bulk tank milk: farms that accomplished a comprehensive milking scheme including two or more operations among forestripping, pre-dipping and post-dipping had lower teat contamination and lower milk SPC, PBC, LPC, CC and LS than farms that did not carry out any operation.

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Bulk tank milk somatic cell count and sources of raw milk contamination with mastitis pathogens

Veterinární Medicína ◽

10.17221/1878-vetmed ◽

2008 ◽

Vol 52 (No. 6) ◽

pp. 223-230 ◽

Cited By ~ 12

Author(s):

D. Rysanek ◽

V. Babak ◽

M. Zouharova

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Bulk Tank Milk ◽

Somatic Cell Counts ◽

Milk Samples ◽

Cell Counts ◽

Milk Contamination ◽

A Cell ◽

Bulk Tank ◽

Mastitis Pathogens

The objective of this study was to probe the relationship between prevalence of selected principal mastitis pathogens and somatic cell counts in bulk tank milk samples. The sources of milk contamination were evaluated. The samples were collected from 298 dairy herds (with approximately 32 000 dairy cows). Only 48.3% of the bulk tank milk samples were free of contamination of pathogens of interest. Approximately 38.9% of the milk samples were contaminated with only one, 12.4% with two and 0.3% with three pathogens. The arithmetic mean of logarithmically transformed data of bulk tank milk somatic cell count rise in order: pathogen free, Pseudomonas aeruginosa, Streptococcus uberis, Escherichia coli and Staphylococcus aureus (5.381; 5.413; 5.495; 5.518; 5.563, respectively). The arithmetic mean differences between bulk tank milk somatic cell counts in pathogen-free and single-pathogen contaminated samples have revealed a significance for the Escherichia coli and Staphylococcus aureus groups (P < 0.01). Using binary logistic regression, a statistically highly significant relationship (P < 0.001) has been found between the number of contaminations of bulk tank milk samples with mastitis pathogens and bulk tank milk somatic cell counts. The relationship allows the determination of the probability of finding relevant mastitis pathogens in bulk tank milk samples with different levels of bulk tank milk SCC. A 63% probability can be defined at a cell count level of 400 000/ml and 20% at a cell count level of 100 000/ml. Analysis may reveal the potential sources of the bulk tank milk sample contamination, i.e. infected mammary glands or the environment. The presence of high levels of contamination along with a low bulk tank SCC may suggest an environmental source of contamination. The study clarified that a potential source of bulk tank milk contamination by relevant pathogens (the environment or the mammary gland) may be elucidated and the probability of the contamination of bulk tank milk samples with mastitis pathogens predicted by the analysis of relationship between the bulk tank milk somatic cell counts and the number of mastitis pathogen contaminations.

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The microbiome of bulk tank milk: Characterization and associations with somatic cell count and bacterial count

Journal of Dairy Science ◽

10.3168/jds.2016-11540 ◽

2017 ◽

Vol 100 (4) ◽

pp. 2536-2552 ◽

Cited By ~ 21

Author(s):

M.X. Rodrigues ◽

S.F. Lima ◽

S.G. Canniatti-Brazaca ◽

R.C. Bicalho

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Bacterial Count ◽

Bulk Tank Milk ◽

Bulk Tank

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Relationships of Bulk Tank Somatic Cell Counts to Prevalence of Intramammary Infection and to Indices of Herd Production1

Journal of Food Protection ◽

10.4315/0362-028x-45.12.1125 ◽

1982 ◽

Vol 45 (12) ◽

pp. 1125-1128 ◽

Cited By ~ 45

Author(s):

R. J. EBERHART ◽

L. J. HUTCHINSON ◽

S. B. SPENCER

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Coefficient Of Determination ◽

Somatic Cell Counts ◽

Cell Counts ◽

Bulk Tank ◽

B Test ◽

Linear Regressions ◽

Daily Milk

Linear regressions and correlations between bulk tank somatic cell counts and (a) prevalence of intrammary infection (n = 80), (b) test day average daily milk and fat production per cow (n = 85), and (c) rolling herd average milk and fat production per cow (n = 83) were determined. The correlation coefficient between bulk tank somatic cell count and prevalence of infection was + . 77 and the coefficient of determination was .59; prevalence of infection was thus the major determinant of bulk tank somatic cell count. Highly significant negative correlations were found between bulk tank somatic cell counts and indices of herd production.

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Description of the Characteristics of Five Bedding Materials and Association With Bulk Tank Milk Quality on Five New York Dairy Herds

Frontiers in Veterinary Science ◽

10.3389/fvets.2021.636833 ◽

2021 ◽

Vol 8 ◽

Author(s):

Valeria M. Alanis ◽

Michael Zurakowski ◽

Deb Pawloski ◽

Tiago Tomazi ◽

Daryl V. Nydam ◽

...

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Milk Quality ◽

Dairy Herds ◽

Bulk Tank Milk ◽

Bacterial Counts ◽

Cell Counts ◽

Bulk Tank ◽

Bacterial Groups

Environmental mastitis represents a major challenge on dairy farms where contagious pathogens are controlled by improved milking procedures. Therefore, research focused on the environment is important to improve udder health programs. The objectives of this prospective and descriptive study were to (1) describe bedding bacterial counts, pH, and dry matter (DM) of five different bedding types (organic: manure solids, straw, paper fiber; inorganic: sand, recycled sand) and (2) explore the association between bedding bacterial counts with bulk tank milk quality. This study took place within five conveniently selected commercial dairy herds, each with a predominant bedding material in lactating pens. Bedding samples (used n = 237; fresh n = 53) were collected monthly from July 2018 to July 2019 following a standard operating procedure (SOP) to minimize sampling variability. Additionally, a bulk tank (BT) milk sample (n = 40) was collected on the same day unless milk had been picked up prior to arrival. Both BT and bedding samples were submitted to the laboratory for culture and bacterial identification and quantification of Streptococcus spp, coliforms, and non-coliforms as well as detection of several pathogens of mastitis importance. Somatic cell count was evaluated in BT samples. Within bedding type, the correlation between bedding characteristics and bacterial counts in bedding was evaluated using Pearson correlation. Within bedding type, the correlation between bacterial counts in bedding samples and bacterial counts in BT were determined. The Kruskal–Wallis test was used to evaluate the bacterial count by bedding type and to evaluate BT somatic cell count differences based on bedding type. In fresh bedding, bacterial counts were generally higher for manure solids for all bacterial groups compared with other materials. In used samples, organic materials had the highest levels of all bacterial groups. The proportion of samples with detectable organisms of mastitis importance varied within and among herds in both bedding and BT samples throughout the study period. In bedding samples, a higher DM content had the lowest levels of bacterial growth compared with those with lower DM content. Most bedding samples were on the alkaline side within a pH range of 8–11. No relationship between bacterial counts and pH was observed. No associations between BT bacteria counts and bedding bacterial counts were observed. No association between bulk tank somatic cell counts based on bedding type were observed. Despite using an SOP for bedding sampling in an effort to consistently collect samples, we still observed a large amount of variability both within and among bedding samples. This variability may have obscured any potential association between BT milk quality and bedding type.

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Extensive Countrywide Field Investigation of Somatic Cell Counts and Total Bacterial Counts in Bulk-Tank Raw Milk in Sheep Flocks in Greece

Foods ◽

10.3390/foods10020268 ◽

2021 ◽

Vol 10 (2) ◽

pp. 268

Author(s):

Daphne T. Lianou ◽

Charalambia K. Michael ◽

Natalia G. C. Vasileiou ◽

Efthymia Petinaki ◽

Peter J. Cripps ◽

...

Keyword(s):

Somatic Cell ◽

Geometric Mean ◽

Cell Counting ◽

Lactation Period ◽

Mechanical Ventilators ◽

Bulk Tank Milk ◽

Bacterial Counts ◽

Somatic Cell Counts ◽

Cell Counts ◽

Bulk Tank

Objectives were to investigate somatic cell counts (SCC) and total bacterial counts (TBC) in the raw bulk-tank milk of sheep flocks in Greece, to study factors potentially influencing increased SCC and TBC in the bulk-tank milk of sheep and to evaluate possible associations of SCC and TBC with milk content. Throughout Greece, 325 dairy sheep flocks were visited for collection of milk sampling for somatic cell counting, microbiological examination and composition measurement. Geometric mean SCC were 0.488 × 106 cells mL−1; geometric mean TBC were 398 × 103 cfu mL−1; 228 staphylococcal isolates were recovered form 206 flocks (63.4%). Multivariable analyses revealed annual incidence risk of clinical mastitis, age of the farmer and month into lactation period (among 53 variables) to be significant for SCC > 1.0 × 106 cells mL−1 and month into lactation period at sampling and availability of mechanical ventilators (among 58 variables) to be significant for TBC > 1500 × 103 cfu mL−1. Negative correlation of SCC with fat, total protein and lactose and positive correlation of SCC with added water were found. With SCC > 1.0 × 106 cells mL−1, significant reduction of protein content (2%) was observed, whilst in flocks with SCC > 1.5 × 106 cells mL−1, significantly lower annual milk production per ewe (42.9%) was recorded.

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Rapid Detection of Mycoplasma bovis, Staphylococcus aureus and Streptococcus agalactiae in Cattle Bulk Tank Milk in Cyprus and Relations with Somatic Cell Counts

Pathogens ◽

10.3390/pathogens10070841 ◽

2021 ◽

Vol 10 (7) ◽

pp. 841

Author(s):

Maria Liapi ◽

George Botsaris ◽

Costas Arsenoglou ◽

Nikolas Markantonis ◽

Christodoulos Michael ◽

...

Keyword(s):

Staphylococcus Aureus ◽

Somatic Cell ◽

Real Time ◽

Streptococcus Agalactiae ◽

Mycoplasma Bovis ◽

Bulk Tank Milk ◽

Somatic Cell Counts ◽

Milk Samples ◽

Cell Counts ◽

Bulk Tank

One hundred and seventy-seven (177) bulk tank milk samples were analyzed with a commercially available real-time polymerase chain reaction kit and 11 (6.21%), 41 (23.16%), and 58 (32.77%) tested positive for Mycoplasma bovis, Staphylococcus aureus, and Streptococcus agalactiae, respectively. Statistical analysis revealed a significant relationship between the presence of S. aureus and S. agalactiae. Enumeration of somatic cells was performed in the same samples by flow cytometry. The somatic cell counts were found higher in S. aureus and S. agalactiae positive samples. No association was found between M. bovis presence and somatic cells counts. Low internal assay control Ct values were found to be related with high somatic cell counts. Noticeably, this is the first report for the presence of M. bovis in Cyprus. Therefore, its presence was confirmed by bulk tank milk culture, conventional PCR, and next generation sequencing. Furthermore, M. bovis was typed with multilocus sequencing typing and was allocated to sequence type 29 (ST 29). Real-time PCR in bulk tank milk samples is a useful tool to detect mammary infections, especially for neglected pathogens such as M. bovis.

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Prediction of total quarter milk somatic cell counts based on foremilk sampling

Journal of Dairy Research ◽

10.1017/s0022029909004166 ◽

2009 ◽

Vol 76 (3) ◽

pp. 326-330 ◽

Cited By ~ 5

Author(s):

Olga Wellnitz ◽

Marcus G Doherr ◽

Marta Woloszyn ◽

Rupert M Bruckmaier

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Practical Reasons ◽

Udder Health ◽

Somatic Cell Counts ◽

Cell Numbers ◽

Cell Counts

Determination of somatic cell count (SCC) is used worldwide in dairy practice to describe the hygienic status of the milk and the udder health of cows. When SCC is tested on a quarter level to detect single quarters with high SCC levels of cows for practical reasons, mostly foremilk samples after prestimulation (i.e. cleaning of the udder) are used. However, SCC is usually different in different milk fractions. Therefore, the goal of this study was the investigation of the use of foremilk samples for the estimation of total quarter SCC. A total of 378 milkings in 19 dairy cows were performed with a special milking device to drain quarter milk separately. Foremilk samples were taken after udder stimulation and before cluster attachment. SCC was measured in foremilk samples and in total quarter milk. Total quarter milk SCC could not be predicted precisely from foremilk SCC measurements. At relatively high foremilk SCC levels (>300×103 cells/ml) foremilk SCC were higher than total quarter milk. At around (50–300)×103 cells/ml foremilk and total quarter SCC did not differ considerably. Most interestingly, if foremilk SCC was lower than 50×103 cells/ml the total quarter SCC was higher than foremilk SCC. In addition, individual cows showed dramatic variations in foremilk SCC that were not very well related to total quarter milk SCC. In conclusion, foremilk samples are useful to detect high quarter milk SCC to recognize possibly infected quarters, only if precise cell counts are not required. However, foremilk samples can be deceptive if very low cell numbers are to be detected.

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Haptoglobin and serum amyloid A in relation to the somatic cell count in quarter, cow composite and bulk tank milk samples

Journal of Dairy Research ◽

10.1017/s0022029906002305 ◽

2007 ◽

Vol 74 (2) ◽

pp. 198-203 ◽

Cited By ~ 25

Author(s):

Maria Åkerstedt ◽

Karin Persson Waller ◽

Åse Sternesjö

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Serum Amyloid A ◽

Dairy Farms ◽

Serum Amyloid ◽

Bulk Tank Milk ◽

Amyloid A ◽

Milk Samples ◽

Bulk Tank

Milk somatic cell count (SCC) is the gold standard in diagnosis of subclinical mastitis, and is also an important parameter in quality programmes of dairy cooperatives. As routine SCC analysis is usually restricted to central laboratories, much effort has been invested in the search for alternative biomarkers of mastitis and milk quality, including the presence in the milk of the acute phase proteins (APP), haptoglobin (Hp) and serum amyloid A (SAA). The aim of this study was to investigate relationships between Hp, SAA and SCC in quarter, cow composite, and bulk tank milk samples. Cows (n=165), without any clinical signs of disease or abnormalities in the milk or udder, from three different dairy farms, were used. Cow composite milk samples from all cows delivering milk at the sampling occasion were taken once in each herd. In one of the farms, representative quarter milk samples (n=103) from 26 cows were also collected. In addition, bulk tank milk samples from 96 dairy farms were included in the study. Samples were analysed for Hp, SAA and SCC, and relationships between the parameters were evaluated at quarter, cow and tank milk levels using Chi-square analysis. Milk samples were categorized according to their SCC, and the presence, or no presence, of SAA and Hp, based on the detection limits of the screening methods (0·3 mg/l and 1·0 mg/l for SAA and Hp, respectively). Hp and SAA were found in milk at quarter, cow composite and bulk tank levels. A large proportion (53%) of the animals had detectable milk concentrations of APP, and SAA was detected more frequently, and at higher concentrations than Hp, regardless of sample type. SAA was detected in as many as 82% of the bulk tank milk samples. Significant relationships were found between Hp, SAA and SCC at quarter and cow composite milk levels, but only between SAA and SCC at bulk tank milk level. Detectable levels of APP were more common at high SCC.

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Electronic Somatic Cell Count—Chemical Method, DMSCC, and WMT Tests for Raw Milk

Journal of Milk and Food Technology ◽

10.4315/0022-2747-39.12.854 ◽

1976 ◽

Vol 39 (12) ◽

pp. 854-858 ◽

Cited By ~ 2

Author(s):

D. R. THOMPSON ◽

V. S. PACKARD ◽

R. E. GINN

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Confidence Intervals ◽

Somatic Cell Count ◽

Raw Milk ◽

Field Method ◽

Regression Equations ◽

Somatic Cell Counts ◽

Cell Counts ◽

Coefficients Of Variation

The Direct Miscroscopic Somatic Cell Count — field method (DMSCC), Wisconsin Mastitis Test (WMT), and Electronic Somatic Cell Count (ESCC) were studied to determine variability and relationship to each other. The coefficients of variation computed at a DMSCC count near one million were 15.6% (DMSCC), 6.3% (WMT), and 4.2% (ESCC). Linear regression equations were determined for predicting DMSCC results by WMT and ESCC. The approximate width of the 95% confidence intervals for ESCC predicting DMSCC were ± 275,000 and for WMT predicting DMSCC were ± 600,000. The prediction of square root and log transformations of DMSCC by WMT exhibited narrower confidence intervals for low somatic cell counts, but wider intervals for high counts (greater than 1,000,000).

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