Case Study: Animal bedding cost and somatic cell count across New England dairy farms: Relationship with bedding material, housing type, herd size, and management system

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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Profile of somatic cell count on dairy farms in the municipalities of Patos de Minas and Lagoa Grande in the state of Minas Gerais

Revista Brasileira de Higiene e Sanidade Animal ◽

10.5935/1981-2965.20140042 ◽

2014 ◽

Vol 8 (5) ◽

Author(s):

Diogo Olímpio Chaves de Sousa ◽

Leoni Ferreira Martins ◽

Luis Oliveira Lopes ◽

Anna Monteiro Correia Lima

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Dairy Farms ◽

Minas Gerais ◽

The State

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Effect of coagulase-negative staphylococci on somatic cell count in Dutch dairy herds

Journal of Dairy Research ◽

10.1017/s0022029910000191 ◽

2010 ◽

Vol 77 (3) ◽

pp. 318-324 ◽

Cited By ~ 14

Author(s):

Otlis Sampimon ◽

Bart HP van den Borne ◽

Inge Santman-Berends ◽

Herman W Barkema ◽

Theo Lam

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Health Management ◽

Dairy Farms ◽

Subclinical Mastitis ◽

Dairy Herds ◽

Coagulase Negative Staphylococci ◽

Intramammary Infections ◽

Milk Samples

The effect was quantified of coagulase-negative staphylococci (CNS) intramammary infections on quarter- and cow-level somatic cell count (SCC) and on bulk milk somatic cell count (BMSCC) in different BMSCC cohorts in Dutch dairy herds. Two datasets were used for this purpose. In the first dataset, on 49 randomly selected dairy farms a total of 4220 quarter milk samples of 1072 cows were collected of all cows and heifers with a test-day SCC ⩾250 000 and ⩾150 000 cells/ml, respectively, and of 25% of cows and heifers below these thresholds. In the second dataset, on 39 selected dairy farms a total of 8329 quarter milk samples of 2115 cows were collected of all cows with a test-day SCC ⩾250 000 cells/ml following two consecutive SCC <250 000 cells/ml, and of heifers using the same SCC criteria but with a threshold of 150 000 cells/ml. These cows and heifers were defined as new high SCC. In both datasets, CNS was the most frequently isolated pathogen, 11% in the first dataset and 12% in the second dataset. In both datasets, quarters with CNS IMI had a lower SCC than quarters infected with major pathogens, and a higher SCC than culture-negative quarters. The same was found for SCC at cow level. Coagulase-negative staphylococci were more often found in quarters with SCC ⩾200 000 cells/ml in dairy farms with a BMSCC <150 000 cells/ml compared with dairy farms with a higher BMSCC. Prevalence of CNS in cows and heifers with a high SCC was higher in dairy farms with a BMSCC <150 000 cells/ml compared with dairy farms with a medium or high BMSCC: 30, 19 and 18%, respectively. This indicates that CNS IMI as a cause of subclinical mastitis is relatively more important in dairy farms with a low BMSCC and may become a point of attention in udder health management on that type of farm.

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Management and sanitary practices in ewe dairy farms and bulk milk somatic cell count

Spanish Journal of Agricultural Research ◽

10.5424/sjar/2010082-1213 ◽

2010 ◽

Vol 8 (2) ◽

pp. 334 ◽

Cited By ~ 2

Author(s):

A. Molina ◽

M. Yamaki ◽

M. Berruga ◽

R. L. Althaus ◽

M. P. Molina

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Dairy Farms ◽

Bulk Milk

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Milking Machines on Chilean Dairy Farms and their Effects on Somatic Cell Count and Milk Yield: A Fied Study

Agricultura Técnica ◽

10.4067/s0365-28072006000100004 ◽

2006 ◽

Vol 66 (1) ◽

Cited By ~ 1

Author(s):

R Garcés A ◽

J López F ◽

R. M Bruckmaier

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Milk Yield ◽

Somatic Cell Count ◽

Dairy Farms

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Association of season and herd size with somatic cell count for cows in Irish, English, and Welsh dairy herds

The Veterinary Journal ◽

10.1016/j.tvjl.2012.12.004 ◽

2013 ◽

Vol 196 (3) ◽

pp. 515-521 ◽

Cited By ~ 19

Author(s):

Simon C. Archer ◽

Finola Mc Coy ◽

Wendela Wapenaar ◽

Martin J. Green

Keyword(s):

Somatic Cell ◽

Cell Count ◽

Somatic Cell Count ◽

Herd Size ◽

Dairy Herds

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Genetic and environmental factors influencing milk, protein and fat yields of pasture-based dairy cows in Tasmania

Animal Production Science ◽

10.1071/an09084 ◽

2010 ◽

Vol 50 (4) ◽

pp. 265 ◽

Cited By ~ 1

Author(s):

S. A. Adediran ◽

P. Nish ◽

D. J. Donaghy ◽

D. A. Ratkowsky ◽

A. E. O. Malau-Aduli

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Milk Fat ◽

Somatic Cell Count ◽

Milk Protein ◽

Herd Size ◽

Production Traits ◽

Phenotypic Correlations ◽

Genetic And Phenotypic Correlations

The objective of this study was to provide an update on milk production performance, heritability, genetic and phenotypic correlations among production traits that are valuable for management, breeding and selection decisions in pasture-based dairy systems. The study utilised a total of 106 990 lactation records of Holstein–Friesian (FF), Jersey (JJ) and their crossbreds (HF) from 428 Tasmanian dairy herds collected between 2000 and 2005. The data were analysed using the least-squares approach with a general linear model and restricted maximum likelihood approach with a linear animal model. Results indicated highly significant (P < 0.01) effects of breed, herd size, cow’s parity, season and year of calving on milk, protein and fat yields. Average milk and protein yields per cow per lactation were highest in the FF breed (5212 L and 171 kg, respectively) and lowest in the JJ breed (3713 L and 143 kg, respectively). FF cows also produced 13.5 kg more milk fat than JJ and HF cows. Furthermore, milk, fat and protein yields were highest for cows calving during spring and lowest for autumn-calving cows. It was also evident that cows in very large herds (>1110 cows/herd) out-produced those in smaller herds. Heritability was highest for milk yield and lowest for somatic cell count ranging from 0.28 to 0.41. Genetic and phenotypic correlations between milk, fat and protein yields ranged from 0.41 to 0.85, and 0.66 to 0.92, respectively. However, genetic and phenotypic correlations between the log of somatic cell count and the production traits ranged from 0.03 to 0.09 and –0.03 to –0.05. We conclude that breed, herd size, parity, season and year of calving were among the main factors correlated with the productivity of dairy cows in Tasmania and adjustments for these factors would be mandatory for any unbiased comparison of lactation performance within and between pasture-based dairy production systems. The practical application of this information would be valuable to dairy farmers for decisions related to breeding, selection and management of their herds.

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