scholarly journals Prevalence of High Somatic Cell Counts in Bulk Tank Goat Milk

1993 ◽  
Vol 76 (4) ◽  
pp. 1035-1039 ◽  
Author(s):  
E.A. Droke ◽  
M.J. Paape ◽  
A.L. Di Carlo
Keyword(s):  
Somatic Cell ◽  
Goat Milk ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Bulk Tank

Presence of Mycoplasma species and somatic cell counts in bulk-tank goat milk

2008 ◽  
Vol 75 (2-3) ◽  
pp. 247-251 ◽  
Author(s):  
A. Contreras ◽  
R.E. Miranda ◽  
A. Sánchez ◽  
C. de la Fe ◽  
D. Sierra ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Goat Milk ◽  
Mycoplasma Species ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Bulk Tank

Extensive countrywide field investigation of somatic cell counts and total bacterial counts in bulk tank raw milk in goat herds in Greece

2021 ◽  
pp. 1-7
Author(s):  
Daphne T. Lianou ◽  
Charalambia K. Michael ◽  
Natalia G.C. Vasileiou ◽  
Efthimia Petinaki ◽  
Peter J. Cripps ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Total Protein ◽  
Goat Milk ◽  
Dairy Goat ◽  
Bulk Tank Milk ◽  
Bacterial Counts ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Total Milk ◽  
Bulk Tank

Abstract Dairy goat farming is an important sector of the agricultural industry in Greece, with an annual total milk production exceeding 450 000 l and accounting for over 25% of all goat milk produced in the European Union; this milk is used mainly for cheese production. Despite the importance of goat milk for the agricultural sector in Greece, no systematic countrywide investigations in the bulk-tank milk of goats in Greece have been reported. Objectives were to investigate somatic cell counts (SCC) and total bacterial counts (TBC) in raw bulk-tank milk of goat herds in Greece, study factors influencing SCC and TBC therein and evaluate their possible associations with milk content. Throughout Greece, 119 dairy goat herds were visited for milk sampling for somatic cell counting, microbiological examination and composition measurement. Geometric mean SCC and TBC were 0.838 × 106 cells ml−1 and 581 × 103 cfu ml−1, respectively. Multivariable analyses revealed annual frequency of check-ups of milking system and total milk quantity per goat (among 53 variables) to be significant for increased SCC; no factor emerged (among 58 variables) to be significant for increased TBC. Negative correlation of SCC with total protein was found; mean total protein content in the bulk-tank milk in herds with SCC >0.75 × 106 cells ml−1 was 5.1% lower and in herds with SCC >1.5 × 106 cells ml−1, it was 7.8% lower.

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

Foods ◽  
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.

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

Pathogens ◽  
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.

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

2011 ◽  
Vol 78 (4) ◽  
pp. 436-441 ◽  
Author(s):  
Maddalena Zucali ◽  
Luciana Bava ◽  
Alberto Tamburini ◽  
Milena Brasca ◽  
Laura Vanoni ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Bacterial Count ◽  
Cold Season ◽  
Plate Count ◽  
Bulk Tank Milk ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Bulk Tank

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.

THE EFFECT OF MIXING ON DISTRIBUTION OF SOMATIC CELLS IN BULK TANK MILK1

1971 ◽  
Vol 34 (10) ◽  
pp. 470-470 ◽  
Author(s):  
Gilbert E. Ward ◽  
David T. Berman
Keyword(s):  
Somatic Cell ◽  
Somatic Cells ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Bulk Tank ◽  
Representative Samples

Agitation of milk in bulk tanks for at least 1 min is necessary so that representative samples for somatic cell counts can be obtained.

Bulk tank milk somatic cell counts in dairy herds with different bovine viral diarrhoea virus status in Poland

2014 ◽  
Vol 116 (1-2) ◽  
pp. 183-187
Author(s):  
Jolanta G. Rola ◽  
Magdalena Larska ◽  
Monika Grzeszuk ◽  
Lukasz Bocian ◽  
Aleksandra Kuta ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Bovine Viral Diarrhoea Virus ◽  
Dairy Herds ◽  
Bovine Viral Diarrhoea ◽  
Bulk Tank Milk ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Diarrhoea Virus ◽  
Bulk Tank

scholarly journals Relationship among specific bacterial counts and total bacterial and somatic cell counts and factors influencing their variation in ovine bulk tank milk

2013 ◽  
Vol 96 (2) ◽  
pp. 1021-1029 ◽  
Author(s):  
M.L. de Garnica ◽  
B. Linage ◽  
J.A. Carriedo ◽  
L.F. De La Fuente ◽  
M.C. García-Jimeno ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Bulk Tank Milk ◽  
Bacterial Counts ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
Factors Influencing ◽  
Bulk Tank

scholarly journals Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Animals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1693 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Francisco Javier Navas González ◽  
Vincenzo Landi ◽  
Jose Manuel León Jurado ◽  
Juan Vicente Delgado Bermejo ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Dry Matter ◽  
Model Comparison ◽  
Minimum Mean Square Error ◽  
Goat Milk ◽  
Individual Performance ◽  
Information Criteria ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
The Individual

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry.

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