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Academic literature on the topic 'Somatic cell count'

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Published: 4 June 2021
Last updated: 10 March 2023

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Journal articles on the topic "Somatic cell count"

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Harding, B. "Somatic cell count campaign." Veterinary Record 136, no. 3 (January 21, 1995): 78. http://dx.doi.org/10.1136/vr.136.3.78-a.

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Wojdak-Maksymiec, K., M. Kmiec, and J. Ziemak. "Associations between bovine lactoferrin gene polymorphism and somatic cell count in milk." Veterinární Medicína 51, No. 1 (March 19, 2012): 14–20. http://dx.doi.org/10.17221/5512-vetmed.

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The study included 124 Polish Black-and-White dairy cows of various share of the Holstein-Friesian (HF) breed. Lactoferrin (LTF) gene polymorphism was obtained with PCR-RFLP method using EcoRI enzyme. Two alleles of LTF, A and B, were found in the studied population. Their frequencies were 67.74% and 32.56%, respectively. The alleles controlled the occurrence of three genotypes: AA, BB and AB, of frequencies equal to 37.90%, 2.42% and 59.68%, respectively. It was established that statistically significant associations exist between the somatic cell count (SCC) and LTF genotype, lactation month and parity as well as the HF gene share. No significant association was found between somatic cell count and season. The highest somatic cell count (transformed to a logarithmic scale) was found in milk of the AB genotype, whereas the lowest one was found in cows of the AA genotype.
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LINTNER, T. J., A. L. LANGE, C. W. HEALD, and R. J. EBERHART. "Preparation and Use of Somatic Cell Count Samples (SCCS) for Comparison of Milk Somatic Cell Counting Methods." Journal of Food Protection 50, no. 2 (February 1, 1987): 132–35. http://dx.doi.org/10.4315/0362-028x-50.2.132.

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Somatic cell count samples (SCCS) for use in comparison of milk somatic cell counting methods were prepared from the cell sediment deposited in a creamery milk separator. Bovine milk somatic cells were resuspended from the sediment, and serial cell dilutions were prepared in bronopol-preserved milk diluent. Over a 1-year period, sets of SCCS were prepared each month and sent to milk-testing laboratories in the U.S.A., Canada and Europe, and counted by the methods in use at those Laboratories: (a) direct microscopic somatic cell count (DMSCC), (b) Fossomatic counter and (c) Coulter counter. Cell counts were normalized to eliminate the effect of month to month variation in the cell content of the SCCS. Counts obtained by the three methods were similar, although Coulter counter results tended to be lower, and significantly lower (P< 0.05) in SCCS with cell counts greater than 700,000 cells/ml than those counts by the other two methods. The effect of shipping on SCCS stability was assessed for SCCS samples sent to and returned from other laboratories, and counted by the Fossomatic method on their return. Counts were similar before and after shipping, except that results for SCCS with cell counts greater than 1,000,000 cells/ml were significantly higher (P<0.05) after their return.
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Dunham, James R. "Using the somatic cell count report." Kansas Agricultural Experiment Station Research Reports, no. 2 (January 1, 1996): 13–16. http://dx.doi.org/10.4148/2378-5977.3250.

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Albenzio, M., L. Figliola, M. Caroprese, R. Marino, A. Sevi, and A. Santillo. "Somatic cell count in sheep milk." Small Ruminant Research 176 (July 2019): 24–30. http://dx.doi.org/10.1016/j.smallrumres.2019.05.013.

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Deluyker, H. A., J. M. Gay, and L. D. Weaver. "Interrelationships of Somatic Cell Count, Mastitis, and Milk Yield in a Low Somatic Cell Count Herd." Journal of Dairy Science 76, no. 11 (November 1993): 3445–52. http://dx.doi.org/10.3168/jds.s0022-0302(93)77683-3.

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Schukken, Ynte H., K. E. Leslie, A. J. Weersink, and S. W. Martin. "Ontario Bulk Milk Somatic Cell Count Reduction Program. 2. Dynamics of Bulk Milk Somatic Cell Counts." Journal of Dairy Science 75, no. 12 (December 1992): 3359–66. http://dx.doi.org/10.3168/jds.s0022-0302(92)78112-0.

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Ducková, Viera, Margita Čanigová, Peter Zajác, Zuzana Remeňová, Miroslav Kročko, and Ľudmila Nagyová. "Effect of somatic cell counts occurred in milk on quality of Slovak traditional cheese – Parenica." Potravinarstvo Slovak Journal of Food Sciences 13, no. 1 (August 28, 2019): 675–80. http://dx.doi.org/10.5219/1099.

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The aim of this work was to compare somatic cell count in milk used for making steamed cheese Parenica in Slovak industrial dairies and small farm dairies and to find out whether somatic cell counts in milk affect the dry matter content of Parenica cheese. The samples of raw milk were taken from 3 industrial dairies (A, B, C) and from 3 farm dairies (E, F, G), produced traditional Slovak cheese Parenica in period from January untill December 2018. The somatic cell count in milk was determined by FossomaticTM 5000 (Foss, Denmark) and dry matter of cheese by oven drying method to constant weight. There were no statistically significant differences (p >0.05) for somatic cell counts in milk processed in industrial and farm dairies. Lower somatic cell counts were determined in milk amples from industrial dairies (mean value 326.55 thousand in 1 mL) in comparison to milk samples from farm dairies (mean value 507.67 thousand in 1 mL). Statistically lower dry matter content (p <0.01) in the samples of Parenica cheese was found out in farm dairy E in comparison to other dairies. The relationship between somatic cell count in milk and dry matter in cheese was confirmed by the relatively low correlation coefficients in dairies, A = 0.22; C = 0.15 and F = -0.12 and higher correlation coefficients in dairies, B = -0.32; D = 0.45 and E = -0.48. Obtaining a more accurate effect of somatic cell count on cheese quality requires the continuation of the research on a larger number of samples and consideration of other factors.
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Rysanek, D., V. Babak, and M. Zouharova. "Bulk tank milk somatic cell count and sources of raw milk contamination with mastitis pathogens." Veterinární Medicína 52, No. 6 (January 7, 2008): 223–30. http://dx.doi.org/10.17221/1878-vetmed.

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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, <i>Pseudomonas aeruginosa</i>, <i>Streptococcus uberis</i>, <i>Escherichia coli</i> and <i>Staphylococcus aureus</i> (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 <i>Escherichia coli</i> and <i>Staphylococcus aureus</i> groups (<i>P</i> &lt; 0.01). Using binary logistic regression, a statistically highly significant relationship (<i>P</i> &lt; 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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Fauteux, V., E. Bouchard, D. Haine, D. T. Scholl, and J. P. Roy. "Prediction of bulk tank somatic cell count violations based on monthly individual cow somatic cell count data." Journal of Dairy Science 98, no. 4 (April 2015): 2312–21. http://dx.doi.org/10.3168/jds.2014-7965.

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Dissertations / Theses on the topic "Somatic cell count"

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Larson, Ann Michelle. "Selection for milk somatic cell count in laboratory mice." Thesis, Virginia Tech, 1988. http://hdl.handle.net/10919/44079.

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A bidirectional selection experiment for high and low somatic cell count (SCC) was conducted over 14 generations with two selected lines (high line = HSCC, low line = LSCC) of mice. Seven secondary traits (milk yield, total white blood cell count, percentage of phagocytic cells in blood, endotoxin challenge response, percentage of females littering, number of young born alive, and percentage of young surviving to weaning) were measured to examine correlated responses to selection for SCC.

Average response per generation for log2 SCC was small in both selected lines (HSCC = .0678 ±.0341, LSCC = .0384 ± .0390, P > .05). There was little per generation divergence between the selected lines (.0294 ± .0178, P > .05). Genetic and phenotypic selection differentials indicated that selection procedures did select the more extreme individuals for SCC, even though response to selection was poor.

Phenotypic correlations among SCC and the seven secondary traits were generally small, and near zero. Correlation coefficients ranged from -.17 to .17. Milk yield was negatively correlated with SCC (-.07, P < .05). The correlation between endotoxin challenge response and SCC was also negative (-.17, P < .05).

Components of genetic variance for SCC were estimated to explain the lack of selection response. Covariances between daughter and dam, and among full sibs were negative (-.1180 and -.0362, respectively). Analysis for offspring and maternal components for SCC yielded a negative estimate for the covariance between additive effects for the offspring and maternal components (-.1781). No biological explanation can be offered for its existence. Heritability from this same analysis was .05.


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Broaddus, Brent A. "IMPACT OF SEASON AND HEAT STRESS ON SOMATIC CELL COUNTS." UKnowledge, 2001. http://uknowledge.uky.edu/gradschool_theses/180.

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Infection data were obtained monthly from June, 1999 to September, 2000 at the University ofKentucky dairy. Quarter foremilk samples were collected for bacteriological determination andsomatic cell counts (SCC). The Livestock Stress Index (LSI) estimated heat stress and is calculatedby combination of temperature and humidity. For uninfected quarters the geometric mean SCC was29,000 cells/ml. For infected quarters the geometric mean SCC was 213,000 cells/ml. Coagulasenegativestaphylococci (CNS) infections comprised 61 percent of the total infected quarters with ageometric mean SCC of 155,000 cells/ml. Staphylococcus aureus infected quarters had a geometricmean SCC of 680,000 cells/ml. There were no significant correlations between log SCC and LSIwhen looking at the total sample period. However, evaluating October, 1999 through September,2000, significant correlations were found for LSI and log SCC of uninfected quarters (P andlt; 0.05) and`infected quarters (P andlt; 0.0001). All correlation coefficients were less than 0.12. The results suggest nomarked changes in SCC were observed in uninfected quarters during hot summer weather. Hotsummer weather may have a minor impact on SCC in infected quarters, but the effect is variable.Thus, infection status of the mammary gland, not heat stress, is the major factor determining SCC.
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Rogers, Sheryle Ann. "The influence of somatic cell count on milk composition and milk product quality." Thesis, Queensland University of Technology, 1986. https://eprints.qut.edu.au/35983/1/35983_Rogers_1986.pdf.

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Mastitis is the most common and economically the most important disease of dairy cattle throughout the world. However in Australia, there is an absence of scientifically based data using herd bulk milk supplies. Animals from each of two farms were divided into three groups based on milk sec and NAGase contents. Milk collected from these animals over a two year period was used to study the influence of sec (as a measure of mastitic infection) on milk composition and milk product quality. Milk compositional studies indicated that log sec was positively correlated to the NCN, BSA, chloride, sodium, NAGase (P<0.005), K-casein, {-casein (P<0.01) and IgG (P<0.05) contents, the pH level (P<0.005) and the NCN:total nitrogen, chloride:lactose and sodium:potassium ratios (P<0.005). Log sec was negatively correlated to the SNF, lactose (P<0.005), ft-casein, ~-lactalbumin, ~-lactoglobulin, soluble calcium (P<0.01), total solids, casein and total calcium (P<0.005) contents and the casein:total protein ratio (P<0.005). When milk samples were grouped into sec categories, results indicated that samples with an sec of greater than 500 000 cells/ml were compositionally inferior to samples with an sec of less than 500 000 cells/ml. Pasteurised milk studies indicated that the organoleptic quality of samples with an sec of less than 1 000 000 cells/ml was generally superior to the organoleptic quality of samples with an sec greater than 1 000 000 cells/ml. Skim milk yoghurt studies indicated that the organoleptic quality of both unsweetened and sweetened yoghurts manufactured from milk with an sec of less than 250 000 cells/ml were superior when compared to yoghurtsmanufactured from milk with an sec of greater than 250 000 cells/ml. The rennet coagulating time of milk was significantly longer when the sec became greater than 500 000 cells/ml. Cheddar cheese manufactured from milk with an sec of greater than 500 000 cells/ml had higher moisture and MFFS and lower fat, FDM and pH. Increased losses of fines (P<0.05) into the whey resulted in lower cheese yields (P<0.10). Log sec was negatively correlated to both cheese flavour and body and texture grades (P<0.10) at six months of age. Cheeses became softer, less springy (P<0.10) and cohesive, more adhesive (P<0.05), and less stringy (P<0.05) as the sec of the milk increased. Skim milk powder studies indicated that the effects of elevated sec on skim milk powder properties and organoleptic quality were minimal. From the results obtained in this study it is suggested that sec threshold values of 1 000 000 and 500 000 cells/ml should be used for market milk and manufacture milk supplies respectively.
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Archer, Simon C. "Influence of somatic cell count in heifers on lifetime milk yield and disease management." Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/13747/.

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The aim was to assess the impact of milk somatic cell count (SCC) during the first lactation on the lifetime milk production of cows, and therefore estimate potential savings through heifer mastitis control. Cow level SCC over the first lactation was summarised as SCC between 5 and 30 days in milk (SCC1), and the geometric mean and variance of first lactation SCC. The impact of SCC1 on cumulative milk yield over different time periods was assessed for cows in Irish, English, and Welsh dairy herds. The impact of SCC1 and the geometric mean and variance of first lactation SCC on lifetime milk yield, and the association between SCC1 and disposal risk were assessed for cows in Irish dairy herds. Increase in SCC throughout the first lactation was associated with large reductions in the milk yield of cows, and increased disposal risk. Bayesian micro-simulation was used to demonstrate the impact in different herd scenarios. This was extended to synthesise evidence on potential savings using previous research, to estimate the economic impact of specific interventions to reduce the prevalence of cows with high SCC1. There was considerable variation between herds in the apparent impact of SCC1 on SCC throughout the first lactation, indicating the importance of a herd specific approach to control. ‘Cost effectiveness’ of interventions to reduce the prevalence of cows with high SCC1, was found to be highly dependent on the willingness of decision makers to pay for control measures. Increase in herd size was associated with increase in cow SCC, highlighting a need for improved management of mastitis when expansion is planned. An important component of this should be through monitoring and control of mastitis in heifers, especially those in spring-calving Irish dairy herds.
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Green, Martin Jeremy. "Clinical mastitis in dairy cows : studies of bacterial ecology and somatic cell count patterns." Thesis, University of Warwick, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404860.

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Roveglia, Chiara. "Genetic and phenotypic aspects of production, conformation and somatic cell count traits in Italian Jersey cattle." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3426342.

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Breeders appreciated Italian Jersey dairy cattle (IJ) for the efficiency and high quality of milk yield in the national dairy scenario. The overall object of this PhD thesis is to investigate the phenotypic and genetic aspects of milk production, conformation and somatic cell score traits of IJ in order to lay the groundwork for an updating of selection index in IJ population (Jersey Quality Index). The first chapter aimed to highlight the phenotypic peculiarities of IJ milk and confirmed that high content of fat (5.18%), protein (4.08%) and casein (3.16%) made IJ milk suitable for cheese manufacture. Moreover, somatic cell score (SCS), one of the best indicator of both clinical and subclinical mastitis, was investigated in IJ. The SCS average of 3.35 units should be lowered through specific managerial actions in order to reduce the IJ susceptibility to one of the most prominent and economically significant disease impacting on the dairy industry. Also milk urea nitrogen (MUN) content was assessed in order to verify if could be a valid indicator of feed efficiency; this was confirmed by the phenotypic variance of this trait, mainly due to the herd management. In the second chapter, heritability estimates of 0.14, 0.21, 0.26, 0.24, 0.20 and 0.10 for milk yield, content of fat, protein, casein, lactose and SCS, respectively, were assessed in 1902 Italian Jersey. Genetic correlations investigated between SCS and milk yield components were negative (ranging from -0.13 to -0.27), the most unfavourable was with lactose percentage (-0.30). The third chapter updated estimates of genetic parameters of 20 type traits in first-lactation IJ, including novel traits of functional and economic relevance, as locomotion score. Despite IJ type traits heritabilities estimated were generally low or moderate (from 0.04 to 0.32), additive genetic variation suggested the possibility to further enhanced functionality in IJ. The strongest correlations were estimated between locomotion and other feet and legs traits, but also between locomotion and front teat placement (0.97) and rear teat placement (0.88), suggesting that improved udder conformation was also associated with better mobility. Four alternative somatic cell count (SCC) traits, derived from routine test-day (TD) recording system, were defined in the fourth chapter as: 1) TD SCS averaged over early lactation (SCS_150); 2) standard deviation of SCS of the entire lactation (SCS_SD); 3) a binary trait indicating absence (0) or presence (1) of at least one TD SCC >400 000 cells/mL in the lactation (Infection); and 4) the ratio of the number of TD SCC >400 000 cells/mL to total number of TD in the lactation (Severity). Genetic and phenotypic parameters between alternative SCS traits and milk yield, composition and udder type traits in IJ were estimated. Results showed exploitable genetic variation and heritability, suggesting that alternative SCS traits might be suitable candidates to update Jersey Quality Index and improve mastitis resistance in IJ. Finally, to ensure maximal benefit for IJ farmers, not only genetic parameters, but also economic values (EV) of milk production and quality traits are required. Economic values of SCS based on its relationship to price payment system in IJ were assessed in the final chapter, comparing two different methods in two different Italian dairy plants which produced Grana Padano cheese. The second method (method 2), that defined SCS costs as the sum of frequency of each level of SCS multiplied by its penalty, was more penalizing than method 1, which was based on a non-linear function of the penalty applied in the milk price respect to the average of SCS. Penalties for high SCS are intended to include SCS in IJ breeding goal with the final purpose of reducing mastitis susceptibility in the next generations of IJ cows.
La razza Jersey Italiana (IJ) è apprezzata per la sua efficienza e l’alta qualità del suo latte all’interno del contesto lattiero-caseario nazionale. L'obiettivo generale della presente tesi è la caratterizzazione fenotipica e genetica della produzione di latte, della morfologia e della conta di cellule somatiche della JI al fine di fornire alcuni strumenti utili per migliorare l’attuale indice di selezione della popolazione (Indice Qualità Jersey, IQJ). Nel primo capitolo si confermano le peculiarità fenotipiche del latte di JI, ovvero un alto contenuto di grasso (5.18%), proteina (4.08%) e caseina (3.16%), che lo rendono adatto alla trasformazione casearia. Il valore medio di punteggio di cellule somatiche (SCS) è risultato piuttosto alto (3.35), il che suggerisce l’importanza di indirizzare gli sforzi verso una riduzione di questo valore attraverso il miglioramento del management aziendale e la selezione, diminuendo indirettamente la suscettibilità della JI alla mastite. In questo studio è stato investigato anche il contenuto di urea del latte di JI quale indicatore di efficienza alimentare. Nel secondo capitolo sono state stimate ereditabilità pari a 0.14, 0.21, 0.26, 0.24, 0.20 e 0.10 rispettivamente per la produzione di latte, il contenuto di grasso, proteina, caseina, lattosio e SCS nel latte di bovine IJ. Le correlazioni genetiche tra SCS e i costituenti del latte sono risultate negative, e la più forte è stata stimata tra SCS e la percentuale di lattosio (-0.30). Il terzo capitolo ha stimato i parametri genetici di 20 caratteri morfologici in primipare di JI, includendo nuovi caratteri di rilievo funzionale ed economico, come la locomozione. Anche se le ereditabilità stimate per i caratteri morfologici sono risultate generalmente basse o moderate (da 0.04 a 0.32), la variabilità genetico-additiva ha suggerito la possibilità di intervenire con la selezione per migliorare geneticamente alcuni aspetti funzionali della razza. Le correlazioni più forti sono state stimate tra il punteggio di locomozione e i caratteri legati ad arti e piedi, ma anche tra punteggio di locomozione e la posizione dei capezzoli anteriori (0.97) e posteriori (0.88), suggerendo che un miglioramento della conformazione della mammella è associato a un potenziale perfezionamento della locomozione. Nel quarto capitolo sono stati definiti quattro caratteri alternativi derivati dalla conta di cellule somatiche (SCC) nel latte di JI rilevata nel corso dei controlli funzionali routinari (test-day, TD): 1) la media di TD SCS nei primi 150 giorni di lattazione; 2) la deviazione standard delle SCS nell’intera lattazione; 3) un carattere binario che indica l’assenza (0) o la presenza (1) di almeno un valore di TD SCC >400.000 cellule/mL nell’intera lattazione (Infezione); e 4) il rapporto tra il numero di TD SCC >400.000 cellule/mL e il numero totale di TD nell’intera lattazione (Severità). Sono stai stimati i parametri genetici di questi 4 caratteri alternativi delle SCC e le correlazioni genetiche gli aspetti produttivi e la morfologia della mammella. I risultati hanno mostrato la presenza di varianze genetiche ed ereditabilità dei caratteri alternativi delle SCC potenzialmente sfruttabili per migliorare la resistenza alla mastite. Infine, nel quinto capitolo sono stati stimati i valori economici (VE) delle SCS con due metodi differenti e in base al sistema pagamento latte-qualità di due caseifici italiani che producono Grana Padano. Tra i due metodi, quello basato sulla somma delle frequenze di ogni livello di SCS moltiplicato per la rispettiva penalità si è rivelato più penalizzante. Il sistema pagamento latte–qualità del caseificio 1 è risultato più rigido rispetto al caseificio 2. L’aumento delle penalità per livelli alti di SCS nel latte incentiva maggiormente ad includere SCS nell’indice di selezione della JI.
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Testa, F. "INFLUENCE OF ATMOSPHERIC TEMPERATURE AND RELATIVE HUMIDITY ON BULK MILK SOMATIC CELL COUNT IN DAIRY HERDS." Doctoral thesis, Università degli Studi di Milano, 2012. http://hdl.handle.net/2434/168080.

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The production loss and health issues due to the presence of high bulk milk tank somatic cell count in dairy herds makes it essential to implement a consistent effort to maintain this indicator at levels below those required by law. For veterinary practitioners, providing evidence-based advice to clients in order to reduce risk factors of increasing somatic cell count is a difficult task. Statistical Process Control tools allow to verify with statistical certainty when process performance is improving, staying the same, or getting worse and they can be used in dairy farms. The main purpose of the project was to improve understanding in bulk milk somatic cell count variation related to daily temperature and relative humidity, and to build a model which could be predictive of future performance of somatic cell count. Daily bulk milk samples of thirteen commercial dairy farms included in the study were collected and data on daily mean temperature and relative humidity were used. Statistical analysis was performed using Generalized Additive Mixed Models to assess the impact of climatic variables on somatic cell count. We could describe a regression model which shows that the effect of temperature on response appears approximately linear while the one of humidity varies in a more complex way. The model fits well for all herds except one, and explanations are provided. The model constitutes a solid basis for further study of the relationship between daily temperature and humidity, and daily bulk milk somatic cell count. It will allow to set up a quality control on dairy farm using atmospheric temperature and humidity data. Hence it will be possible to provide evidence-based advice to dairy farmers with the use of control charts created on the basis of our statistical model.
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Martinkus, Nerijus. "Karvių melžimo operacijų įtaka somatinių ląstelių skaičiui piene." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080318_142138-89478.

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Modernios pienininkystės fermos sėkmė priklauso nuo to, ar joje gaminamas pienas yra aukštos kokybės. Pagrindiniai veiksniai, turintys įtakos somatinių ląstelių skaičiui piene, yra gera melžimo organizacija, melžimo įrangos taisyklingas veikimas, klinikinių mastitų gydymas antibiotikais ir kt. Mokslininkai įrodė, kad melžti karves kas dvylika valandų yra optimaliausia, kai jos melžiamos du kartus per parą. SLS piene daug priklauso nuo taisyklingos melžimo darbotvarkės, kuri apima skirtingas melžimo operacijas (tešmens ir spenių paruošimas melžimui, spenių dirginimas, pirmųjų pieno čiurkšlių numelžimas, melžiklių užmovimas ant spenių, melžiklių numovimas pamelžus ir efektyvi spenių antiseptika po melžimo) ir nuo šių operacijų trukmės. Teisingai atliekamos melžimo procedūros yra svarbios mastito prevencijai ir užtikrina visišką pieno išmelžimą iš tešmens. Tyrėjai įrodė, kad daugiau kaip 50 % melžimo proceso laiko užtrunka pats melžimas. Dabartiniu metu melžimo operacijos vis labiau mechanizuojamos. Netaisyklingas melžimas gali pailginti pieno atleidimo laiką, didėja rizika susirgti tešmens uždegimais. Pablogėja pieno kokybė, todėl gaunami ekonominiai nuostoliai. Padidėjęs somatinių ląstelių skaičius piene ¬ svarbus mastito požymis. Perdirbamajai pramonei karvių mastitas buvo ir liks vienu iš svarbiausių trukdžių gaminant aukštos kokybės pieno produktus. Klinikine forma serga 2 – 5 % laktuojančių ir užtrūkintų karvių, o slaptuoju uždegimu – iki 50 % karvių. Viena dažniausiai... [toliau žr. visą tekstą]
Data were collected from two dairy farms. On the farm A cows were milked using full automatised milking equipment „Milkmaster“. On the farm B cows were milked with „Interpuls“ milking equipment. The DeLaval milking system was supplied with automatic cluster remover. On dairy farms A and B cows were milked twice daily. The goal of our studies was to analyse consumption of main milking operations (cow udder preparation before milking, milking and over-milking) and their influence on milk somatic cell count. Were selected 20 cows in each farm. The duration of main milking procedures were recorded. Data on milk, fat and protein yields and somatic cell count were collected.The mean duration of pre-milking udder preparation was 42 s (farm A) and 46,03 s (farm B). Some cows were prepared only for 25,50 Afarm A) s, whereas the udder preparation comprised merely inadequate cleaning of teats. The maximum duration of over-milking was 41,10 (farm B).
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9

Mazal, Guillaume. "Efeito da contagem de celulas somaticas do leite na fabricação do queijo prato." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/255198.

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Orientadores: Mirna Lucia Gigante, Marcos Veiga dos Santos
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos
Made available in DSpace on 2018-08-05T00:26:38Z (GMT). No. of bitstreams: 1 Mazal_Guillaume_M.pdf: 1093019 bytes, checksum: a2931e0c265f17d65f21671d7680bb5a (MD5) Previous issue date: 2005
Mestrado
Mestre em Tecnologia de Alimentos
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Ekman, Torkel. "A study of dairy herds with constantly low or constantly high bulk milk somatic cell count, with special emphasis on management /." Uppsala : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 1998. http://epsilon.slu.se/avh/1998/91-576-5434-4.gif.

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Books on the topic "Somatic cell count"

1

Ryan-Purcell, Walter. A quick guide: Achieving and maintaining a low somatic cell count. Buttevant, Co. Cork: Dairy Hygiene Services, 1995.

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Ekman, Torkel. A study of dairy herds with constantly low or constantly high bulk milk somatic cell count, with special emphasis on management. Uppsala: Sveriges Lantbruksuniversitet, 1998.

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United States. Animal and Plant Health Inspection Service. Veterinary Services. and National Animal Health Monitoring Service (U.S.), eds. Bulk tank milk somatic cell counts and your milk quality assurance program. Fort Collins, Colo: U.S. Dept. of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, 1994.

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How to control somatic cell counts: A practical and easy to use guide to mastitis - no 1. Leicestershire, England: Context Products Ltd., 2014.

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East, Chantelle. The effectiveness of the California Mastitis Test as a means of estimating somatic cell counts at farm level. Dublin: University College Dublin, 1996.

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Hutton, Catherine Trawatha. Investigation of management factors which influence the somatic cell count status of the herd. 1988.

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Book chapters on the topic "Somatic cell count"

1

Sivasangari, A., D. Deepa, R. M. Gomathi, P. Ajitha, and S. Poonguzhali. "New IoT-Based Portable Microscopic Somatic Cell Count Analysis." In Data Intelligence and Cognitive Informatics, 113–19. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6004-8_10.

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Raboisson, D., E. Cahuzac, P. Sans, and G. Allaire. "Factors influencing average herd somatic cell count in France in 2005 and 2006." In Udder Health and Communication, 344. Wageningen: Wageningen Academic Publishers, 2011. http://dx.doi.org/10.3920/978-90-8686-742-4_62.

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Tsenkova, Roumiana, and Jelena Muncan. "Near-Infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count." In Aquaphotomics for Bio-diagnostics in Dairy, 99–112. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_9.

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Mijić, P., V. Gantner, T. Bobić, and K. Kuterovac. "Variation of somatic cell count (SCC) of dairy cattle in conditions of Mediterranean region in Croatia." In Animal farming and environmental interactions in the Mediterranean region, 249–54. Wageningen: Wageningen Academic Publishers, 2012. http://dx.doi.org/10.3920/978-90-8686-741-7_31.

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Albrechtsen, M., A. T. Duse, T. W. Bennedsgaard, and I. C. Klaas. "Use of in-line measurements of somatic cell count to evaluate treatment efficacy of subclinical bovine Staphylococcus aureus mastitis." In Udder Health and Communication, 309–15. Wageningen: Wageningen Academic Publishers, 2011. http://dx.doi.org/10.3920/978-90-8686-742-4_55.

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Tsenkova, Roumiana, and Jelena Muncan. "Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region Using PLS Regression and Referenced Data." In Aquaphotomics for Bio-diagnostics in Dairy, 127–36. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_11.

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Tsenkova, Roumiana, and Jelena Muncan. "Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400–1,100 nm Short Wavelength Region." In Aquaphotomics for Bio-diagnostics in Dairy, 113–26. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_10.

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Tsenkova, Roumiana, and Jelena Muncan. "Two-Dimensional Near-Infrared Correlation Spectroscopy of an Individual Cow’s Milk for Functional Study of Somatic Cell Count Changes in Milk." In Aquaphotomics for Bio-diagnostics in Dairy, 277–88. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_24.

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Tsenkova, Roumiana, and Jelena Muncan. "Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region: Comparison of At-Line and On-Line Measurement Modes." In Aquaphotomics for Bio-diagnostics in Dairy, 137–47. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_12.

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Tsenkova, Roumiana, and Jelena Muncan. "Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis." In Aquaphotomics for Bio-diagnostics in Dairy, 223–34. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7114-2_20.

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Conference papers on the topic "Somatic cell count"

1

Lusis, Ivars, Armins Laurs, and Vita Antane. "Viscosity method in robotic milking system for detection of somatic cell count in milk." In 18th International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, 2019. http://dx.doi.org/10.22616/erdev2019.18.n095.

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Mrode, R., M. W. Winters, and M. Coffey. "292. Within and across breed single step genomic prediction for somatic cell count including foreign information." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_292.

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Khoo, Geoffrey, Rainer Kuennemeyer, and Rod W. Claycomb. "Fluorescence photon migration techniques for the on-farm measurement of somatic cell count in fresh cow's milk." In SPIE Proceedings, edited by Jose F. Lopez, Chenggen Quan, Fook Siong Chau, Francisco V. Fernandez, Jose Maria Lopez-Villegas, Anand Asundi, Brian Stephen Wong, Jose M. de la Rosa, and Chwee Teck Lim. SPIE, 2005. http://dx.doi.org/10.1117/12.621771.

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Gómez, M. M., R. Cimmino, Y. Gombia, G. Zullo, and S. Biffani. "810. Somatic cell count and its relationship with udder type traits in Italian Mediterranean Buffaloes (Bubalus bubalis)." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_810.

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Egil Simensen, Camilla Kielland, Knut Egil Bøe, Lars Erik Ruud, and Geir Næss. "Milk Production, Reproductive Performance, Milk Somatic Cell Count and Disease Incidences in Alternative Housing Systems for Dairy Cows." In Sixth International Dairy Housing Conference Proceeding, 16-18 June 2007, (Minneapolis, Minnesota) (Electronic Only). St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2007. http://dx.doi.org/10.13031/2013.22814.

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Bobbo, T., R. Matera, G. Pedota, J. Ramirez-Diaz, A. Manunza, A. Stella, A. Cotticelli, G. Neglia, and S. Biffani. "137. Machine learning to predict somatic cell count at the subsequent test-day record in the Italian Mediterranean Buffaloes." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_137.

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Ismiraj, Muhammad Rifqi, and Novi Mayasari. "Effects of Different Milk Somatic Cell Count Level on Plasma Total Protein, Albumin, and Globulin in Transition Dairy Cows." In 6th International Seminar of Animal Nutrition and Feed Science (ISANFS 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/absr.k.220401.019.

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SILVA, SERGIO E. LEMOS DA, THALITA VIEIRA VINHAL, GUSTAVO PAULA DE OLIVEIRA, GABRIELA FRATARI FREITAS, LUANNA DE SOUZA FERNANDES, and HEMONIELLE GOMES DE MELO SILVEIRA. "PREVALENCE AND INCIDENCE OF CLINICAL AND SUBCLINICAL BOVINE MASTITIS IN A DAIRY HERD IN THE SOUTHEAST OF GOIÁS, BRAZIL." In II South Florida Congress of Development. brazco, 2022. http://dx.doi.org/10.47172/iisfcdv2022.0023.

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Bovine mastitis is a disease of extreme importance to the dairy production chain, since it causes economic losses in production. Mastitis is an inflammatory disease that affects the mammary glands. There are two forms of presentation of the disease, the clinical and subclinical, requiring diagnostic tests to differentiate them. This article aimed to verify the prevalence and incidence of mastitis in a dairy farm located in the southeast of the state of Goiás. To carry out this research, the Somatic Cell Count (SCC) test was used. The results showed 54% mastitis prevalence, a lower value if compared to other studies. The incidence of clinical mastitis was also low, and it was possible to observe periods of more than 30 days without any identification of new cases, due to the care taken on the property, such as the correct management of the herd and milking, hygiene and the use of qualified labor. According to the SCC findings, it can be inferred that the low values of the epidemiological indicators analyzed may be associated with good management and hygiene practices practiced on the property, reducing the prevalence and incidence of mastitis.
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Reports on the topic "Somatic cell count"

1

Schultz, Lorilee, and Leo L. Timms. Case Study of Prevention and Therapy Strategies for a High Somatic Cell Count Herd. Ames (Iowa): Iowa State University, January 2006. http://dx.doi.org/10.31274/ans_air-180814-144.

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Timms, Leo L. Evaluation of recommended and extended pirlimycin therapy strategies in four high somatic cell count. Ames (Iowa): Iowa State University, January 2004. http://dx.doi.org/10.31274/ans_air-180814-37.

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Timms, Leo L. Prevention and Pirlimycin Therapy Strategies for a High Somatic Cell Count Herd: A Case Study. Ames (Iowa): Iowa State University, January 2004. http://dx.doi.org/10.31274/ans_air-180814-100.

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Leitner, Gabriel, and Naomi Balaban. Novel Immunotherapeutic Agent for the Treatment and Prevention of Staphylococcal Mastitis in Dairy Cows. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7709880.bard.

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Staphylococci are the most common and costly mammary disease of dairy cattle worldwide. TRAP, a membrane associated 167AA protein, is highly conserved among staphylococci. The aims of this study were to test the safety and efficacy of recombinant TRAP (rTRAP) vaccine in dairy animals. The vaccine was safe as 2-3 subcutaneous injections of rTRAP (54–100μg) with adjuvant ISA 206 to cows and goats did not lead to any abnormal symptoms of sensitivity to the vaccine. The rTRAP vaccine was immunogenic and caused the induction of a humoral immune response that remained high for at least 160 days post second immunization. rTRAP vaccine also elicited a cell-mediated immune response (memory CD4+ and CD8+ T cells), as determined by lymphocyte proliferation assays. The rTRAP vaccine was efficacious as at parturition, only 13.5% heifers in the immunized group were infected with Staphylococcus chromogenes as compared to 42.9% in the non immunized group. Additionally, when cows were immunized in mid-lactation, the difference between somatic cell count (SCC) in immunized and control animals was profound (45±7 vs. 470±194, respectively). At the same time, the difference in milk yield was also evident (48.3±1.4 vs. 44.3±0.9 l/day, respectively). Put together, these studies indicate the value of the rTRAP vaccine in preventing new udder infections by staphylococci, which significantly lead to lowered SCC and some increase in milk yield. TRAP is conserved among all strains and species and is constitutively expressed in any strain of S. aureus or CNS tested so far, including those isolated from cows. TRAP may thus serve as a universal anti-staphylococcus vaccine.
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Leitner, Gabriel, and Naomi Balaban. Novel Immunotherapeutic Agent for the Treatment and Prevention of Staphylococcal Mastitis in Dairy Cows. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7695866.bard.

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Staphylococci are the most common and costly mammary disease of dairy cattle worldwide. TRAP, a membrane associated 167AA protein, is highly conserved among staphylococci. The aims of this study were to test the safety and efficacy of recombinant TRAP (rTRAP) vaccine in dairy animals. The vaccine was safe as 2-3 subcutaneous injections of rTRAP (54–100μg) with adjuvant ISA 206 to cows and goats did not lead to any abnormal symptoms of sensitivity to the vaccine. The rTRAP vaccine was immunogenic and caused the induction of a humoral immune response that remained high for at least 160 days post second immunization. rTRAP vaccine also elicited a cell-mediated immune response (memory CD4+ and CD8+ T cells), as determined by lymphocyte proliferation assays. The rTRAP vaccine was efficacious as at parturition, only 13.5% heifers in the immunized group were infected with Staphylococcus chromogenes as compared to 42.9% in the non immunized group. Additionally, when cows were immunized in mid-lactation, the difference between somatic cell count (SCC) in immunized and control animals was profound (45±7 vs. 470±194, respectively). At the same time, the difference in milk yield was also evident (48.3±1.4 vs. 44.3±0.9 l/day, respectively). Put together, these studies indicate the value of the rTRAP vaccine in preventing new udder infections by staphylococci, which significantly lead to lowered SCC and some increase in milk yield. TRAP is conserved among all strains and species and is constitutively expressed in any strain of S. aureus or CNS tested so far, including those isolated from cows. TRAP may thus serve as a universal anti-staphylococcus vaccine.
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