Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.     

Short communication: bivariate genetic analysis of clinical mastitis and somatic cell count in Norwegian dairy cattle

Clinical mastitis (CM) and lactation mean somatic cell score (LSCS) were analyzed with a bivariate linear sire model. Nearly 1.4 million primiparous cows of Norwegian Dairy Cattle from 2043 sires were used. The heritability estimates were 0.03 for CM and 0.11 for LSCS. The estimates of genetic and residual correlations between the 2 traits were 0.53 and 0.10, respectively. It is postulated that the genetic correlation probably is highly population-specific.     

Genetic improvement in mastitis resistance: comparison of selection criteria from cross-sectional and random regression sire models for somatic cell score

Several selection criteria for reducing incidence of mastitis were developed from a random regression sire model for test-day somatic cell score (SCS). For comparison, sire transmitting abilities were also predicted based on a cross-sectional model for lactation mean SCS. Only first-crop daughters were used in genetic evaluation of SCS, and the different selection criteria were compared based on their correlation with incidence of clinical mastitis in second-crop daughters (measured as mean daughter deviations). Selection criteria were predicted based on both complete and reduced first-crop daughter groups (261 or 65 daughters per sire, respectively). For complete daughter groups, predicted transmitting abilities at around 30 d in milk showed the best predictive ability for incidence of clinical mastitis, closely followed by average predicted transmitting abilities over the entire lactation. Both of these criteria were derived from the random regression model. These selection criteria improved accuracy of selection by approximately 2% relative to a cross-sectional model. However, for reduced daughter groups, the cross-sectional model yielded increased predictive ability compared with the selection criteria based on the random regression model. This result may be explained by the cross-sectional model being more robust, i.e., less sensitive to precision of (co)variance components estimates and effects of data structure.     

Dairy management practices associated with incidence rate of clinical mastitis in low somatic cell score herds in France

An epidemiological prospective study was carried out in French dairy herds with Holstein, Montbéliarde, or Normande cows and with low herd somatic cell scores. The objective was to identify dairy management practices associated with herd incidence rate of clinical mastitis. The studied herds were selected on a national basis, clinical cases were recorded through a standardized system, and a stable dairy management system existed. In the surveyed herds, mean milk yield was 7420 kg/cow per yr and mean milk somatic cell score was 2.04 (132,000 cells/mL). Overdispersion Poisson models were performed to investigate risk factors for mastitis incidence rate. From the final model, the herds with the following characteristics had lower incidence rates of clinical mastitis: 1) culling of cows with more than 3 cases of clinical mastitis within a lactation; 2) more than 2 person-years assigned to dairy herd management; 3) balanced concentrate in the cow basal diet. Moreover, herds with the following characteristics had higher incidence rates of clinical mastitis: 1) milking cows loose-housed in a straw yard; 2) no mastitis therapy performed when a single clot was observed in the milk; 3) clusters rinsed using water or soapy water after milking a cow with high somatic cell count; 4) 305-d milk yield >7435 kg; 5) herd located in the South region; 6) herd located in the North region; 7) cows with at least 1 nonfunctional quarter; and 8) premilking holding area with a slippery surface. The underlying mechanisms of some highlighted risk factors, such as milk production level and dietary management practices, should be investigated more thoroughly through international collaboration.     

Genetic relationships of clinical mastitis,cystic ovaries,and lameness with milk yield and somatic cell score in first-lactation Canadian Holsteins

The objective of this study was to investigate the genetic relationships of the 3 most frequently reported dairy cattle diseases (clinical mastitis, cystic ovaries, and lameness) with test-day milk yield and somatic cell score (SCS) in first-lactation Canadian Holstein cows using random regression models. Health data recorded by producers were available from the National Dairy Cattle Health System in Canada. Disease traits were defined as binary traits (0 = healthy, 1 = affected) based on whether or not the cow had at least one disease case recorded within 305 d after calving. Mean frequencies of clinical mastitis, cystic ovaries, and lameness were 12.7, 8.2, and 9.1%, respectively. For genetic analyses, a Bayesian approach using Gibbs sampling was applied. Bivariate linear sire random regression model analyses were carried out between each of the 3 disease traits and test-day milk yield or SCS. Random regressions on second-degree Legendre polynomials were used to model the daily sire additive genetic and cow effects on test-day milk yield and SCS, whereas only the intercept term was fitted for disease traits. Estimated heritabilities were 0.03, 0.03, and 0.02 for clinical mastitis, cystic ovaries, and lameness, respectively. Average heritabilities for milk yield were between 0.41 and 0.49. Average heritabilities for SCS ranged from 0.10 to 0.12. The average genetic correlations between daily milk yield and clinical mastitis, cystic ovaries, and lameness were 0.40, 0.26, and 0.23, respectively; however, the last estimate was not statistically different from zero. Cows with a high genetic merit for milk yield during the lactation were more susceptible to clinical mastitis and cystic ovaries. Estimates of genetic correlations between daily milk yield and clinical mastitis were moderate throughout the lactation. The genetic correlations between daily milk yield and cystic ovaries were near zero at the beginning of lactation and were highest at mid and end lactation. The average genetic correlation between daily SCS and clinical mastitis was 0.59 and was consistent throughout the lactation. The average genetic correlation between daily SCS and cystic ovaries was near zero (−0.01), whereas a moderate, but nonsignificant, correlation of 0.27 was observed between SCS and lameness. Unfavorable genetic associations between milk yield and diseases imply that production and health traits should be considered simultaneously in genetic selection.     

Joint analysis of quantitative trait loci for clinical mastitis and somatic cell score on five chromosomes in three Nordic dairy cattle breeds

Five chromosomes were selected for joint quantitative trait loci (QTL) analyses for clinical mastitis (CM) and somatic cell score (SCS) in 3 breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB), and Danish Red (DR). In total, 19 grandsires and 672 sons in FA, 19 grandsires and 499 sons in SRB, and 8 grandsires and 258 sons in DR were used in the study. These individuals were genotyped with the 61 microsatellite markers used in any of the previous QTL scans on the selected chromosomes. Within-family QTL analyses based on linear regression models were carried out for CM and SCS to identify the segregating sires for each region. On the segregating families, joint single-trait and 2-trait analyses were performed using variance components models. The analyses confirmed that QTL affecting CM or SCS, or both, segregate on Bos taurus autosomes (BTA) 9, 11, 14, and 18, whereas a QTL on BTA29 could not be confirmed. Our results indicate that there may be at least 2 linked QTL on BTA9, one that primarily affects CM and a second that primarily affects SCS. On chromosomes BTA11, 14, and 18, the joint analyses were only significant for SCS.     

Genetic parameters for clinical mastitis, somatic cell score, and production in the first three lactations of Swedish holstein cows

Using a mixed linear animal model, genetic parameters were estimated for clinical mastitis (MAST), lactation average somatic cell score (LSCS), and milk production traits in the first 3 lactations of more than 200,000 Swedish Holstein cows with first calving from 1995 to 2000. Heritability estimates for MAST (0.01 to 0.03) were distinctly lower than those for LSCS (0.10 to 0.14) and production traits (0.23 to 0.36). The genetic correlation between MAST and LSCS was high for all lactations (mean 0.70), implying that selection for low LSCS will reduce the incidence of mastitis. Undesirable genetic relationships with production were found for both MAST and LSCS with genetic correlations ranging from 0.01 to 0.45. This emphasizes the need for including udder health traits in the breeding goal. Genetic correlations across lactations for the same trait were positive and high for both MAST (>0.7), LSCS (>0.8), and production traits (>0.9), with the strongest correlations between second and third parity for all traits (>0.9 for udder health traits and close to unity for production traits).     

Short communication: Genetic aspects of milk differential somatic cell count in Holstein cows: A preliminary analysis

The aim of the present study was to assess genetic variation and heritability of a novel indicator of udder health, milk differential somatic cell count (DSCC), which represents the percentage of neutrophils plus lymphocytes in the total somatic cell count (SCC). Furthermore, we estimated genetic and phenotypic correlations of DSCC with other milk traits routinely measured in Italian Holstein cows. Besides DSCC, test-day data included milk yield, composition traits (i.e., fat, protein, casein, and lactose percentages), pH, milk urea nitrogen, and SCC. After editing, the final data set included 10,709 test-day records of 5,142 cows in 299 herds. Mean of DSCC was 62.07%, which means that macrophages were approximately 38% of total SCC. Comparing our results with the literature offered compelling evidence of the importance of acquiring information about the proportion of the different cell types in milk to better define the udder health status. In addition, our analysis revealed, for the first time, that DSCC is a heritable trait, and heritability (0.08 ± 0.02) was higher than that of traditional somatic cell score (0.04 ± 0.02). Nevertheless, heritability of DSCC is still low compared with milk yield and quality traits. Single-trait analysis within parity showed that DSCC was less heritable in primiparous than in multiparous cows, whereas bivariate analysis confirmed that DSCC and somatic cell score were 2 different traits, as their genetic and phenotypic correlations differed from unity. From a genetic point of view, the DSCC was positively weakly associated with milk yield, lactose percentage, and milk urea nitrogen, and negatively associated with pH. Our findings contributed to the understanding of the genetic background of DSCC and are a precursor to the potential use of DSCC in breeding programs to enhance cow resistance to mastitis. However, further research is needed to determine the weight this novel trait should receive in a selection program aimed to reduce udder health problems.     

Genetic association of clinical mastitis with test-day somatic cell score and milk yield during first lactation of Finnish Ayrshire cows

In this study the genetic association during lactation of 2 clinical mastitis (CM) traits: CM1 (7 d before to 30 d after calving) and CM2 (31 to 300 d after calving) with test-day somatic cell score (SCS) and milk yield (MY) was assessed using multitrait random regression sire models. The data analyzed were from 27,557 first-lactation Finnish Ayrshire cows. Random regressions on second- and third-order Legendre polynomials were used to model the daily genetic and permanent environmental variances of test-day SCS and MY, respectively, while only the intercept term was fitted for CM. Results showed that genetic correlations between CM and the test-day traits varied during lactation. Genetic correlations between CM1 and CM2 and test-day SCS during lactation varied from 0.41 to 0.77 and from 0.34 to 0.71, respectively. Genetic correlations of test-day MY with CM1 and CM2 ranged from 0.13 to 0.51 and from 0.49 to 0.66, respectively. Correlations between CM1 and SCS were strongest during early lactation, whereas correlations between CM2 and SCS were strongest in late lactation. Genetic correlations lower than unity indicate that CM and SCS measure different aspects of the trait mastitis. Milk yield in early lactation was more strongly correlated with both CM1 and CM2 than milk yield in later lactation. This suggests that selection for higher lactation MY through selection on increased milk yield in early lactation will have a more deleterious effect on genetic resistance to mastitis than selection for higher yield in late lactation. The approach used in this study for the estimation of the genetic associations between test-day and CM traits could be used to combine information from traits with different data structures, such as test-day SCS and CM traits in a multitrait random regression model for the genetic evaluation of udder health.     

Genetic and phenotypic relationships among milk yield and somatic cell count before and after clinical mastitis

This paper studies whether cows with originally lower somatic cell count (SCC) are more susceptible to clinical mastitis (CM) than cows with higher somatic cell count, and evaluates the correlations between CM, SCC, and milk yield. Data were extracted from the Finnish national milk-recording database and from the health recording system. First and second lactation records of 87,861 Ayrshire cows calving between January 1998 and December 2000 were included. Traits studied were incidence of CM, test-day SCC, and test-day milk yield before and following CM. Genetic parameters were estimated using multitrait REML with a sire model. Results did not indicate that cows with genetically low SCC would be more susceptible to CM. The genetic correlation between CM in the first and second lactation was reasonably high (0.73), suggesting that susceptibility to mastitis remains similar across lactations. The genetic correlation between CM and milk yield traits was positive (from 0.38 to 0.56), confirming the genetic antagonism between production and udder health traits. The genetic correlation between SCC and milk was positive in the first lactation, but negative, or near zero in the second lactation. This indicates that breeding for lower SCC might not affect milk production in later lactations. The results of this study support the use of SCC as an indicator of mastitis and a tool for selection for mastitis resistance.     

Association between somatic cell count and serial locomotion score assessments in UK dairy cows

This research investigated the effect of lameness, measured by locomotion score (LS) on the somatic cell count (SCC) of UK dairy cows. The data set consisted of 11,141 records of SCC and LS collected monthly on 12 occasions from 1,397 cows kept on 7 farms. The data were analyzed to account for the correlation of repeated measures of SCC within cow. Results were controlled for farm of origin, stage of lactation, parity, season, and test-day milk yield. Compared with the geometric mean SCC for cows with LS 1 on each farm, cows on farm 3 with LS 2 produced milk with 28,000 fewer somatic cells/mL, and cows with LS 2 on farm 6 produced milk with 30,000 fewer somatic cells/mL at a test day within 10 d. Cows that would have LS 3 six months later produced milk with 16,000 fewer somatic cells/mL compared with the geometric mean SCC for cows that would have LS 1 in 6 mo time. These results illustrate differences in disease dynamics between farms, highlight potential conflict between lameness and mastitis control measures, and emphasize the importance of developing farm-specific estimates of disease costs, and hence, health management plans in clinical practice.     

Genetic correlations between pathogen-specific mastitis and somatic cell count in Danish Holsteins

The aim of this study was to estimate genetic correlations (r_a) between 2 lactation average somatic cell count (LASCC) traits and 6 different mastitis traits in 226,482 first-parity Danish Holstein cows that calved between 1998 and 2008. The LASCC traits were defined from 5 to either 170 d (LASCC_170) or 300 d (LASCC_300) after calving, and the mastitis traits were unspecific mastitis (all mastitis treatments, both clinical and subclinical, regardless of the causative pathogen) and mastitis caused by either Streptococcus dysgalactiae, Escherichia coli, coagulase-negative staphylococci (CNS), Staphylococcus aureus, or Streptococcus uberis. Variance components were estimated using bivariate threshold-Gaussian models via Gibbs sampling. The posterior means of r_a between LASCC_170 and the mastitis traits were greatest for unspecific mastitis (r_a = 0.71), followed by CNS, Strep. dysgalactiae, Strep. uberis, and E. coli (r_a = 0.54 to 0.69) and were lowest for Staph. aureus mastitis (r_a = 0.44). The genetic correlation between LASCC_300 and the mastitis traits were generally smaller (r_a = 0.47 to 0.69). Caution should be taken when interpreting the results, however, because some posterior density intervals for r_a were large (between 0.14 and 0.47 units). Phenotypically, Staph. aureus is known to be associated with high SCC and especially with subclinical mastitis through chronic infections, so the low r_a between Staph. aureus mastitis and LASCC, compared with r_a for the other pathogens, was not expected. Subclinical cases are usually submitted to dry cow therapy (not included in the present study), not treated at all, or wrongly recorded as clinical cases. Thus, the incidence of Staph. aureus mastitis is likely too low, and the genetic correlation between Staph. aureus mastitis and LASCC may therefore be underestimated in the present study. The results for the remaining pathogens were as expected, smallest for E. coli and larger but similar for Strep. dysgalactiae, Strep. uberis, and CNS. Selection for lower LASCC is expected to decrease the incidence of pathogen-specific mastitis, especially for Strep. uberis, Strep. dysgalactiae, and CNS and, to a lesser extent, for Staph. aureus and E. coli. Data recording should preferably be improved, and economic weights for the pathogen-specific mastitis traits should be estimated before implementing an udder health index that includes pathogen-specific mastitis traits.     

Alternative somatic cell count traits exploitable in genetic selection for mastitis resistance in Italian Holsteins

The aim of the present study was to characterize alternative somatic cell count (SCC) traits that could be exploited in genetic selection for mastitis resistance. Data were from 66,407 first-parity Holsteins in 404 herds. Novel SCC traits included average somatic cell score (SCS, log-transformation of SCC) in early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), the presence of at least one test-day (TD) SCC >400,000 cells/mL in the lactation, and the ratio of number of TD SCC >400,000 cells/mL to total number of TD in the lactation. Novel traits and lactation-mean SCS (SCS_LM) were analyzed using linear mixed or logistic regression models, including month of calving, year of calving, number of TD, and milk yield as fixed effects, and herd and residual as random terms. A multitrait linear animal model was applied to a random subset of 152 herds (n = 22,695 cows) to assess heritability of and genetic correlations between SCC traits. Alternative SCC traits were affected by the environmental factors included in the model; in particular, results suggested a seasonal effect and a tendency toward an improvement of the udder health status in the last years. Association was also found between novel SCC traits and milk production. Alternative SCC traits exhibited coefficients of additive genetic variation that were similar to or larger than that of traditional SCS_LM. Heritability of novel SCC traits was smaller than heritability of SCS_LM (0.126 ± 0.014), ranging from 0.044 ± 0.008 (SCS_SD) to 0.087 ± 0.010 (SCS_150). Genetic correlations between SCC traits ranged from 0.217 ± 0.096 (SCS_150 and SCS_SD) to 0.969 ± 0.010 (SCS_LM and SCS_150). Alternative SCC traits exhibited additive genetic variation that is potentially exploitable in breeding programs of Italian Holstein population to improve resistance to mastitis.     

International genetic evaluations of Holstein sires for milk somatic cell and clinical mastitis

International genetic evaluations for milk somatic cell and clinical mastitis have been implemented on a routine basis by Interbull. This paper examines possible genetic consequences of such evaluations. Holstein data from 12 countries were used for this purpose. Trait definitions and national genetic evaluation procedures were first summarized and showed that differences between countries existed. Estimated genetic correlations among milk somatic cell in these countries ranged from 0.47 to 0.97, with a median of 0.88. Estimated genetic correlations among clinical mastitis in three Nordic countries ranged from 0.59 to 0.83, and estimated genetic correlations between clinical mastitis in the three Nordic countries and milk somatic cell in the non-Nordic countries ranged from 0.37 to 0.78 with a median of 0.55. Bulls without daughter information in the Nordic countries had low reliabilities on the Nordic clinical mastitis scales. International genetic evaluations for milk somatic cell and clinical mastitis enable a broader selection among foreign bulls, and higher selection differentials were found when using international evaluations compared with national evaluations.     

Associations between pathogen-specific cases of clinical mastitis and somatic cell count patterns

Associations were estimated between pathogen-specific cases of clinical mastitis (CM) and somatic cell count (SCC) patterns based on deviations from the typical curve for SCC during lactation and compared with associations between pathogen-specific CM and lactation average SCC. Data from 274 Dutch herds recording CM over an 18-mo period were used. Pathogens found were Staphylococcus aureus, coagulase-negative staphylococci, Escherichia coli, Streptococcus dysgalactiae, Streptococcus uberis, streptococci other than Strep. dysgalactiae and Strep. uberis, and culture-negative samples. The dataset contained 245,595 test-day records on SCC, recorded in 24,012 lactations of 19,733 cows of different parities. Pattern definitions were based on three or five consecutive test-day records. The patterns differentiated between a short or longer period of increased SCC and also between lactations with and without recovery. Logistic regression was applied to identify associations between presence of patterns and occurrence of pathogens. Occurrence of overall CM in a lactation is equally or even more accurately predicted by the presence of SCC in that lactation, than by a lactation average SCC of more than 200,000 cells/mL. Patterns can also distinguish between chances of risk for specific mastitis-causing pathogens. Clinical E. coli mastitis was significantly associated with the presence of a short peak in SCC, whereas Staph. aureus was associated with long increased SCC. Streptococcus dysgalactiae was not strongly associated with any of the defined patterns of peaks in SCC, and no single unambiguous pattern was found for Strep. uberis.     

Genetic analysis of somatic cell score in Norwegian cattle using random regression test-day models

The dataset used in this analysis contained a total of 341,736 test-day observations of somatic cell scores from 77,110 primiparous daughters of 1965 Norwegian Cattle sires. Initial analyses, using simple random regression models without genetic effects, indicated that use of homogeneous residual variance was appropriate. Further analyses were carried out by use of a repeatability model and 12 random regression sire models. Legendre polynomials of varying order were used to model both permanent environmental and sire effects, as did the Wilmink function, the Lidauer-M?ntysaari function, and the Ali-Schaeffer function. For all these models, heritability estimates were lowest at the beginning (0.05 to 0.07) and higher at the end (0.09 to 0.12) of lactation. Genetic correlations between somatic cell scores early and late in lactation were moderate to high (0.38 to 0.71), whereas genetic correlations for adjacent DIM were near unity. Models were compared based on likelihood ratio tests, Bayesian information criterion, Akaike information criterion, residual variance, and predictive ability. Based on prediction of randomly excluded observations, models with 4 coefficients for permanent environmental effect were preferred over simpler models. More highly parameterized models did not substantially increase predictive ability. Evaluation of the different model selection criteria indicated that a reduced order of fit for sire effects was desireable. Models with zeroth- or first-order of fit for sire effects and higher order of fit for permanent environmental effects probably underestimated sire variance. The chosen model had Legendre polynomials with 3 coefficients for sire, and 4 coefficients for permanent environmental effects. For this model, trajectories of sire variance and heritability were similar assuming either homogeneous or heterogeneous residual variance structure.     

Genetic correlation patterns between somatic cell score and protein yield in the Italian Holstein-Friesian population

Genetic parameters for somatic cell score (SCS) in the Italian Holstein-Friesian population were estimated addressing the pattern of genetic correlation with protein yield in different parities (first, second, and third) and on different days in milk within each parity. Three approaches for parameter estimation were applied using random samples of herds from the national database of the Italian Holstein Association. Genetic correlations for lactation measures (305-d protein yield and lactation SCS) were positive in the first parity (0.31) and close to zero in the second (0.01) and third (0.09) parities. These results indicated that larger values of SCS were genetically associated with increased production. The second and third sets of estimates were based on random regression test-day models, modeling the shape of lactation curve with the Wilmink function and fourth-order Legendre polynomials, respectively. Genetic correlations from both random regression models showed a specific pattern associated with days in milk within and across parities. Estimates varied from positive to negative in the first and second parity, and from null to negative in the third parity. Patterns were similar for both random regression models. The average overall correlation between SCS and protein yield was zero or slightly positive in the first lactation and ranged from zero to negative in later lactations. Correlation estimates differed by parity and stage of lactation. They also demonstrated the dubiousness of applying a single genetic correlation measure between SCS and protein in setting selection strategies. Differences in magnitude and the sign of genetic correlations between SCS and yields across and within parities should be accounted for in selection schemes.     

Short communication: correlated selection responses in somatic cell count from selection against clinical mastitis

Correlated selection responses in lactation mean somatic cell score (LSCS) were estimated for groups of cows selected for high protein yield and low mastitis frequency, respectively. Selection for increased milk production resulted in an unfavorable correlated response for LSCS, whereas direct selection against clinical mastitis resulted in a favorable correlated selection response. After 6 cow generations, the genetic difference between the high protein yield group and the low mastitis group was 0.3 units LSCS, equivalent to a difference in somatic cell count of approximately 15,000, assuming deviations from a population mean LSCS of 4.1.     

Alternative somatic cell count traits as mastitis indicators for genetic selection

The aim of this study was to define alternative traits of somatic cell count (SCC) that can be used to decrease genetic susceptibility to clinical and subclinical mastitis (CM and SCM, respectively). Three kinds of SCC traits were evaluated: 1) lactation-averages of SCC, 2) traits derived from the proportion of test-day SCC above 150,000 cells/mL, and 3) patterns of peaks in SCC. Genetic parameters for these SCC traits and their genetic correlation with CM and SCM were estimated; CM and SCM were scored as binary traits. Two data sets (A and B) depending on CM recording were available. After editing, subset A contained 28,688 lactations from 21,673 cows in 394 herds. Subset B contained 56,726 lactations of 30,145 cows in 272 herds. Variance components for sire and permanent animal effects were estimated. Estimated heritabilities for all mastitis traits were around 0.03. Heritabilities for SCC traits ranged from 0.01 for patterns of peaks in SCC to 0.13 for lactation-average SCC. Genetic correlations between SCC traits and CM or SCM ranged from 0.55 to 0.93 for CM and from 0.55 to 0.98 for SCM. High genetic correlations were estimated between CM and SCC averaged over 250 d in milk (0.87), and between SCM and presence of test-day SCC >150,000 cells/mL (0.98) in subset A. In subset B, a high genetic correlation was estimated between CM and an SCC peak with a quick recovery (0.93) and between SCM and SCC averaged between 151 and 400 d (0.95). Partial genetic correlations were calculated to investigate the additional information of the alternative SCC traits, compared with lactation-average SCC. They showed that some traits remain informative for CM and others for SCM. Therefore, use of information from a combination of different SCC traits may be more successful in improving overall udder health than the traditional single SCC measure.     

Invited review: Low milk somatic cell count and susceptibility to mastitis

An enduring controversy exists about low milk cell counts and susceptibility to mastitis. The concentration of milk leukocytes, or somatic cell count (SCC), is a well-established direct indicator of mammary gland inflammation that is highly correlated with the presence of a mammary infection. The SCC is also used as a trait for the selection of dairy ruminants less prone to mastitis. As selection programs favor animals with less SCC, and as milk cells contribute to the defense of the mammary gland, the idea that susceptibility to mastitis could possibly be increased in the long term has been put forward and is still widely debated. Epidemiological and experimental studies aimed at relating SCC to susceptibility to mastitis have yielded results that seem contradictory at first sight. Nevertheless, by taking into account the immunobiology of milk and mammary tissue cells and their role in the defense against infection, along with recent studies on SCC-based divergent selection of animals, the issue can be settled. Apparent SCC-linked susceptibility to mastitis is a phenotypic trait that may be linked to immunomodulation but not to selection.