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The aim of this study was to determine risk factors for bovine intramammary infection (IMI) associated with the most common bacterial species in Finland. Large databases of the Finnish milk-recording system and results of microbiological analyses of mastitic milk samples from Valio Ltd. (Helsinki, Finland) were analyzed. The study group comprised 29,969 cows with IMI from 4,173 dairy herds. A cow with a quarter milk sample in which DNA of target species was detected in the PathoProof Mastitis PCR Assay (Thermo Fisher Scientific, Waltham, MA) was determined to have IMI. Only cows with IMI caused by the 6 most common pathogens or groups of pathogens, coagulase-negative staphylococci (CNS), Staphylococcus aureus, Streptococcus uberis, Streptococcus dysgalactiae, Corynebacterium bovis, and Escherichia coli, were included. The control group comprised 160,176 IMI-free cows from the same herds as the study group. A multilevel logistic regression model was used to study herd- and cow-specific risk factors for incidence of IMI. Pathogen-specific results confirmed those of earlier studies, specifically that increasing parity increases prevalence of IMI regardless of causative pathogen. Holsteins were more susceptible to IMI than Nordic Reds except when the causative pathogen was CNS. Occurrence of IMI caused by C. bovis was not related to milk yield, in contrast to IMI caused by all other pathogens investigated. Organic milk production was associated with IMI only when the causative pathogen of IMI was Staph. aureus; Staph. aureus IMI was more likely to occur in conventional than in organic production. Cows in older freestall barns with parlor milking had an increased probability of contracting an IMI compared with cows in tiestall barns or in new freestall barns with automatic milking. This was the case for all IMI, except those caused by CNS, the prevalence of which was not associated with the milking system, and IMI caused by Staph. aureus, which was most common in cows housed in tiestall barns. A better breeding index for milk somatic cell count was associated with decreased occurrence of IMI, indicating that breeding for improved udder health has been successful in reducing the incidence of IMI caused by the most common pathogens in Finland. In the Finnish dairy sector, the importance of other measures to control IMI will increase as the Holstein breed progressively takes the place of the Nordic Red breed. Attention should be paid to hygiene and cleanliness, especially in old freestall barns. Based on our results, the increasing prevalence of automatic milking is not a reason for special concern.

The objectives of the present case-control study were to assess (1) daily activity patterns (lying time, number of steps, number of lying bouts, and lying bout duration), and (2) circulating concentrations of biomarkers of pain (substance P), inflammation (haptoglobin), and stress (cortisol) in lactating dairy cows diagnosed with clinical metritis. Lactating dairy cows (n = 200) from 2 commercial dairy herds were enrolled in the present study. Cows diagnosed with clinical metritis (n = 100) at 7 +/- 3 d in milk were matched according to lactation and days in milk to cows without clinical metritis (NO-CM; n = 100). On study d 1, clinical metritis was diagnosed (using a Metricheck device, Simcro Tech Ltd., Hamilton, New Zealand) by the presence of watery, reddish, or brownish foul-smelling vaginal discharge, and blood samples were collected for assessment of circulating concentration of substance P, haptoglobin, cortisol, total calcium, beta-hydroxybutyrate, and blood cells. In addition, on study d 1 body condition of cows was visually assessed, and activity monitors were placed on the hind leg of a subset of cows (CM, n = 56; CON, n = 56) and were kept until study d 7. Cows showing any other signs of other diseases were not included in the study. Cows with clinical metritis tended to spend more time lying (CM = 628.92 min/d; NO-CM = 591.23 min/d) compared with NO-CM cows. Activity analysis by parity revealed that primiparous cows with clinical metritis spent more time lying compared with primiparous cows without clinical metritis. However, no differences in daily lying time were observed between multiparous cows with and without clinical metritis. Furthermore, cows in the CM group had a higher circulating concentration of substance P (CM = 47.15 pg/mL; NO-CM = 37.73 pg/mL) arid haptoglobin (CM = 233.00 mu g/mL; NO-CM = 99.98 mu g/mL) when compared with NO-CM cows. Cows with clinical metritis had lower body condition score, and a greater proportion of cows in this group had hypocalcemia when compared with cows without clinical metritis. The circulating concentration of leukocytes and erythrocytes were decreased in cows with clinical metritis compared with cows without clinical metritis. Results from this study showed that concentrations of markers of inflammation, stress, pain, and activity were affected in cows diagnosed with clinical metritis; thus, strategies aimed to minimize the negative effects associated with clinical metritis may be required to improve the welfare of dairy cows.

peer-reviewed Feed represents a large proportion of the variable costs in dairy production systems. The omission of feed intake measures explicitly from national dairy cow breeding objectives is predominantly due to a lack of information from which to make selection decisions. However, individual cow feed intake data are available in different countries, mostly from research or nucleus herds. None of these data sets are sufficiently large enough on their own to generate accurate genetic evaluations. In the current study, we collate data from 10 populations in 9 countries and estimate genetic parameters for dry matter intake (DMI). A total of 224,174 test-day records from 10,068 parity 1 to 5 records of 6,957 cows were available, as well as records from 1,784 growing heifers. Random regression models were fit to the lactating cow test-day records and predicted feed intake at 70 d postcalving was extracted from these fitted profiles. The random regression model included a fixed polynomial regression for each lactation separately, as well as herd-year-season of calving and experimental treatment as fixed effects; random effects fit in the model included individual animal deviation from the fixed regression for each parity as well as mean herd-specific deviations from the fixed regression. Predicted DMI at 70 d postcalving was used as the phenotype for the subsequent genetic analyses undertaken using an animal repeatability model. Heritability estimates of predicted cow feed intake 70 d postcalving was 0.34 across the entire data set and varied, within population, from 0.08 to 0.52. Repeatability of feed intake across lactations was 0.66. Heritability of feed intake in the growing heifers was 0.20 to 0.34 in the 2 populations with heifer data. The genetic correlation between feed intake in lactating cows and growing heifers was 0.67. A combined pedigree and genomic relationship matrix was used to improve linkages between populations for the estimation of genetic correlations of DMI in lactating cows; genotype information was available on 5,429 of the animals. Populations were categorized as North America, grazing, other low input, and high input European Union. Albeit associated with large standard errors, genetic correlation estimates for DMI between populations varied from 0.14 to 0.84 but were stronger (0.76 to 0.84) between the populations representative of high-input production systems. Genetic correlations with the grazing populations were weak to moderate, varying from 0.14 to 0.57. Genetic evaluations for DMI can be undertaken using data collated from international populations; however, genotype-by-environment interactions with grazing production systems need to be considered.

With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in dairy cattle, data from Australia (AU), the United Kingdom (UK), and the Netherlands (NL) were combined using both single-trait and multi-trait models. In total, DMI records were available on 1,801 animals, including 843 AU growing heifers with records on DMI measured over 60 to 70 d at approximately 200 d of age, and 359 UK and 599 NL lactating heifers with records on DMI during the first 100 d in milk. The genotypes used in this study were obtained from the Illumina Bovine 50K chip (Illumina Inc., San Diego, CA). The AU, UK, and NL genomic data were matched using the single nucleotide polymorphism (SNP) name. Quality controls were applied by carefully comparing the genotypes of 40 bulls that were available in each data set. This resulted in 30,949 SNP being used in the analyses. Genomic predictions were estimated with genomic REML, using ASReml software. The accuracy of genomic prediction was evaluated in 11 validation sets; that is, at least 3 validation sets per country were defined. The reference set (in which animals had both DMI phenotypes and genotypes) was either AU or Europe (UK and NL) or a multi-country reference set consisting of all data except the validation set. When DMI for each country was treated as the same trait, use of a multi-country reference set increased the accuracy of genomic prediction for DMI in UK, but not in AU and NL. Extending the model to a bivariate (AU-EU) or trivariate (AU-UK-NL) model increased the accuracy of genomic prediction for DMI in all countries. The highest accuracies were estimated for all countries when data were analyzed with a trivariate model, with increases of up to 5.5% compared with univariate models within countries.

Mitigation of enteric methane (CH₄) emission in ruminants has become an important area of research because accumulation of CH₄ is linked to global warming. Nutritional and microbial opportunities to reduce CH₄ emissions have been extensively researched, but little is known about using natural variation to breed animals with lower CH₄ yield. Measuring CH₄ emission rates directly from animals is difficult and hinders direct selection on reduced CH₄ emission. However, improvements can be made through selection on associated traits (e.g., residual feed intake, RFI) or through selection on CH₄ predicted from feed intake and diet composition. The objective was to establish phenotypic and genetic variation in predicted CH₄ output, and to determine the potential of genetics to reduce methane emissions in dairy cattle. Experimental data were used and records on daily feed intake, weekly body weights, and weekly milk production were available from 548 heifers. Residual feed intake (MJ/d) is the difference between net energy intake and calculated net energy requirements for maintenance as a function of body weight and for fat- and protein-corrected milk production. Predicted methane emission (PME; g/d) is 6% of gross energy intake (Intergovernmental Panel on Climate Change methodology) corrected for energy content of methane (55.65 kJ/g). The estimated heritabilities for PME and RFI were 0.35 and 0.40, respectively. The positive genetic correlation between RFI and PME indicated that cows with lower RFI have lower PME (estimates ranging from 0.18 to 0.84). Hence, it is possible to decrease the methane production of a cow by selecting more-efficient cows, and the genetic variation suggests that reductions in the order of 11 to 26% in 10 yr are theoretically possible, and could be even higher in a genomic selection program. However, several uncertainties are discussed; for example, the lack of true methane measurements (and the key assumption that methane produced per unit feed is not affected by RFI level), as well as the limitations of predicting the biological consequences of selection. To overcome these limitations, an international effort is required to bring together data on feed intake and methane emissions of dairy cows.

The voluntary waiting period (VWP) is defined as the time between parturition and the time at which the cow is first eligible for insemination. Determining the optimal VWP from field data is difficult and unlikely to happen. Therefore, a Monte-Carlo dynamic-stochastic simulation model was created to calculate the economic effects of different VWP. The model is dynamic and uses time steps of 1 wk to simulate the reproductive cycle (ovulation, estrous detection, and conception), the occurrence of postpartum disorders, and the lactation curve. Inputs of the model were chosen to reflect the situation of Dutch dairy cows. In the model, we initially created a cow of a randomly selected breed, parity, month of calving, calf status of last calving, and expected 305-d milk yield. The randomly varied variables were based upon relevant distributions and adjusted for cow statuses. The lactation curve was modeled by Wood's function. The economic input values in the analysis included: cost of milk production (€0.07 to €0.20 per kg), calf price (€35 to €150 per calf), AI cost (€7 to €24 per AI), calving management cost (€137 to €167 per calving), and culling cost, expressed as the retention pay-off (€118 to €1,117). A partial budget approach was used to calculate the economic effect of varying the VWP from 7 to 15 wk postpartum, using a VWP of 6 wk as reference. Per iteration, the VWP with either the lowest economic loss or the maximum profit was determined as the optimal VWP. The optimal VWP of most cows (90%) was less than 10 wk. On average, every VWP longer than 6 wk gave economic losses. Longer VWP were in particular optimal for the first parity of breeds other than Holstein-Friesian, cows calving in winter with low milk production, high milk persistency, delayed peak milk yield time, a delayed time of first ovulation, or occurrence of a postpartum disorder, and while costs of milk production are low and costs for AI are high

Foot disorders are an important health problem in dairy cattle, in terms of economics and animal welfare. The incidence, severity, and duration of foot disorders account for their importance. Prevalence of both subclinical and clinical foot disorders is high. More insight into the economic consequences could increase awareness among dairy farmers and could be an incentive for them to take action on this problem of animal welfare. The objective of this research was to estimate the economic consequences of different types of foot disorders, both clinical and subclinical. A dynamic stochastic Monte Carlo simulation model was used, taking into account the different types of foot disorders. The economic consequences of the foot disorders modeled were costs due to milk production losses, culling, prolonged calving interval, labor of the dairy farmer and the foot trimmer, visits of a veterinarian, treatment, and discarded milk. Under the milk quota system in the Netherlands, costs due to foot disorders for a default farm with 65 cows averaged $4,899 per year (ranging from $3,217 to $7,001), an annual loss of $75 per cow. This calculation implies that the costs due to foot disorders are more substantial than farmers might think. The costs of subclinical foot disorders account for 32% of all costs due to foot disorders. The costs due to foot disorders that are present without treatment or detection by the farmer are considerable. This finding implies that farmers might underestimate the benefits of taking action earlier and more thoroughly. A clinical foot disorder costs, on average, $95, and a subclinical foot disorder $18. The highest costs classified by foot disorder were those due to digital dermatitis, which has a high incidence and relatively high clinical prevalence. The highest costs classified by cost factor were those due to milk production losses and culling. Sensitivity analysis showed that variables regarding milk production were important for economic costs due to foot disorders. Furthermore, the probability of getting a foot disorder and probability of cure were important for estimating the costs due to foot disorders. Farmer awareness concerning dairy cow foot health and taking action more thoroughly, therefore, could reduce the economic consequences and improve welfare simultaneously.

The objective of this study was to investigate the effect of vitamin E supplementation on oxidative status in blood, liver, milk, and ovarian follicular fluid in periparturient heifers. Vitamin E supplementation started 8 wk before calving and continued until 8 wk postpartum. Grass silage was the main forage fed during the experiment. In addition, supplemented heifers (n = 9) received 3,000 IU of vitamin E daily on a carrier food; control heifers (n = 9) consumed only the carrier food. Blood samples and liver biopsies were taken frequently throughout the study and ovarian follicular fluid was sampled at 8 wk postpartum. Body condition score was scored weekly and milk yield was measured daily. A marker of oxidative damage, determinable reactive oxygen metabolites (d-ROM), and a set of antioxidants were measured in blood, liver, milk, and ovarian follicular fluid. Control heifers had a low vitamin E status, and selenium status was marginal in control and supplemented heifers. Vitamin E supplementation increased vitamin E concentrations in blood, liver, and ovarian follicular fluid and increased triacylglycerol in liver. Serum d-ROM were not reduced by vitamin E supplementation. Superoxide dismutase and glutathione peroxidase activity in red blood cells and liver and glutathione peroxidase activity in ovarian follicular fluid were not affected by vitamin E supplementation and they were not increased around calving. Protein thiol groups and ratio of reduced glutathione to oxidized glutathione were also not increased around calving. These results suggest that heifers around calving experience a low level of oxidative processes. This might be caused by lower than expected milk production attributed to a low forage intake. Serum d-ROM were negatively correlated with protein thiol groups and positively correlated with the activity of glutathione peroxidase in red blood cells, oxidized glutathione, and the ratio of reduced glutathione and oxidized glutathione in serum. The lack of treatment effects allowed estimation of the effects of body condition 4 wk before calving and the loss of body condition on markers of lipid peroxidation and antioxidants. A trend that a body condition of =3 might result in more oxidative damage measured by serum d-ROM was observed, but fatter heifers had a significantly higher ratio of reduced glutathione to oxidized glutathione

A reaction norm approach was used to estimate trends for days open (DO) with a model that indirectly accounted for heat stress. Data included 3.4 million first-parity records of DO of US Holsteins. A fixed effect model included herd-year, month of calving within region (MOC), age class, and regression on 305-d milk yield. An index calculated from the standardized solutions to MOC derived from the fixed effect model was treated as a proxy for an index on heat stress (SI). The lowest index for any region was set to zero. The highest index was 1.00 for the Southeast, 0.56 for the Northeast, 0.54 for the Midwest, 0.33 for the Northwest, and 0.42 for the Southwest. In all regions except the Northwest, the highest DO and the corresponding highest indices were in March-April. Compared with the fixed model, the reaction norm model also included the effect of an animal and a random regression on the SI; the 2 animal solutions are subsequently referred to as an intercept and a slope. Genetic trends were calculated for cows and sires separately. For cows, the trend for the intercept was - 0.1 d/yr, whereas the trend for the slope was 1 d/yr. For sires, the same trends were - 0.3 and 1.5, respectively. Official proofs were used to characterize the 100 top and 100 bottom bulls with at least 50 daughters for the intercept and the slope. Compared with the top bulls, the bottom bulls for the intercept gave 56 kg more milk and their type performance index was higher by 212 points. For the slope, the same numbers were - 435 kg and - 242 points, respectively. Trends for seasonal changes of days open are unfavorable.

The aim of this paper was to explore general characteristics of multistage breeding schemes and to evaluate multistage dairy cattle breeding schemes that use information on quantitative trait loci (QTL). Evaluation was either for additional genetic response or for reduction in number of progeny-tested bulls while maintaining the same response. The reduction in response in multistage breeding schemes relative to comparable single-stage breeding schemes (i.e., with the same overall selection intensity and the same amount of information in the final stage of selection) depended on the overall selection intensity, the selection intensity in the various stages of the breeding scheme, and the ratio of the accuracies of selection in the various stages of the breeding scheme. When overall selection intensity was constant, reduction in response increased with increasing selection intensity in the first stage. The decrease in response was highest in schemes with lower overall selection intensity. Reduction in response was limited in schemes with low to average emphasis on first-stage selection, especially if the accuracy of selection in the first stage was relatively high compared with the accuracy in the final stage. Closed nucleus breeding schemes in dairy cattle that use information on QTL were evaluated by deterministic simulation. In the base scheme, the selection index consisted of pedigree information and own performance (dams), or pedigree information and performance of 100 daughters (sires). In alternative breeding schemes, information on a QTL was accounted for by simulating an additional index trait. The fraction of the variance explained by the QTL determined the correlation between the additional index trait and the breeding goal trait. Response in progeny test schemes relative to a base breeding scheme without QTL information ranged from +4.5% (QTL explaining 5% of the additive genetic variance) to +21.2% (QTL explaining 50% of the additive genetic variance). A QTL explaining 5% of the additive genetic variance allowed a 35% reduction in the number of progeny tested bulls, while maintaining genetic response at the level of the base scheme. Genetic progress was up to 31.3% higher for schemes with increased embryo production and selection of embryos based on QTL information. The challenge for breeding organizations is to find the optimum breeding program with regard to additional genetic progress and additional (or reduced) cost.

Objectives of this study are to describe the biological basis for multiphasic milk production and to propose a new empirical model for the lactation curve. To illustrate this model, we used data on 3573 first-lactation Holsteins having lactations of various lengths (285, 345, 405, 465, and 525 d) and with various days open (45, 105, 165, 225, and 285 d). The model describes an increasing first phase of milk yield and a series of decreasing phases of yield. The increasing phase, described by an increasing logistic function of time, is associated with increase in number of active mammary gland cells and increase in yield per cell. The decreasing phases, described by three decreasing logistic functions of time, are associated with decreases in cell number due to apoptosis and in yield per cell due to pregnancy. The new model is [GRAPHICS] where Y-DIM is milk yield at each day in milk (DIM), a, is upper level for the increasing first phase, and p(2), p(3), and p(4) = (1 - p(2) - p(3)) are proportions of a(1) for the decreasing second, third, and fourth phases; b's are proportional to duration of each phase; and c's are time of maximum increase or decrease. Nonlinear regression was used to fit average milk yield for each of nine datasets, four with 180 d carried calf and five with 240 d carried calf. Average results indicated that for the first phase, upper level of milk yield was about 22 kg. Duration was about 120 d, centered on time of maximum increase, which was about 11 d before calving. For the second phase (first phase of apoptosis), decrease in yield was relatively large (about 20%) and duration was relatively long (about 375 d). Time of maximum decrease was about 107 d after calving. For the third phase (pregnancy), decrease in yield was relatively small (about 6%) and duration was relatively short (about 200 d). Time of maximum decrease was about 300 d after calving. For each additional day open, time of maximum decrease increased about 1 d. For the fourth phase (second phase of apoptosis), decrease in yield was relatively large (about 74%) and duration was relatively long (about 765 d). Duration for the lactation length of 525 d was exceptionally long. Time of maximum decrease was about 382 d after calving. For each additional day of lactation, duration increased about 5.4 d and day of maximum decrease increased about 0.82 d. We believe that it is possible to model empirically standard and extended lactation curves of dairy cows, based on biological theory and predicated on the multiphasic approach. Further research to understand better the biology of extended lactations, using the proposed multiphasic model, should use planned extended lactations that are at least 525 d in milk and have at least 240 d carried calf.

To examine the development of teat end callosity thickness and roughness in early lactation and to quantify cow factors of interest, a system to classify teat end condition was developed. A distinction was made between rough and smooth rings around the teat orifice. In addition, a classification of the degree of callosity was developed. Kappa coefficients for the repeatability of scoring by this classification system by different workers were 0.71 for teat end callosity thickness and 0.86 for teat end callosity roughness. The teat end callosity classification system was used for a longitudinal study with 40 cows during the first 14 wk of lactation. Models were built to predict teat end callosity thickness and roughness, machine-on time, and milk yield. For the response variables, teat end callosity thickness, machine-on time, and milk yield, the consecutive measurements appeared to follow a lactation curve model with a subject-specific general slope and intercept. Teat end callosity increased rapidly the first 8 wk. Cow factors such as days in milk, parity, machine-on time, and teat end shape were associated with the degree of teat end callosity, and the probability of the callosity ring to become rough. Teat end callosity thickness did not decrease within the 14-wk trial period for most teats. Pointed or round teat ends showed more callus than inverted teat ends. Longer machine-on time resulted in a higher probability of the callosity ring to become rough. Rear teats showed less callosity than front teats in this study.

The objectives of this study were to characterize the changes of body condition score (BCS), energy content (EC), cumulative effective energy balance (CEEB), and blood serum concentrations of glucose, beta-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFA) across the first lactation of Holstein cows, and to estimate variance components for these traits. Four hundred ninety-seven cows kept on a commercial farm in Greece that had calved during 2005 and 2006 were used. Body condition score, estimated live weight, and blood metabolic traits were recorded weekly for the first 3 mo of lactation and monthly thereafter until the end of lactation. Body condition score and estimated live weight records were used to calculate EC and CEEB throughout the first lactation. Estimates of fixed curves and genetic parameters for each trait, by week of lactation, were obtained with the use of random regression models. The estimated fixed curves were indicative of changes in the metabolic process and energy balance of the cows. Significant genetic variance existed in all studied traits, and was particularly high during the first weeks of lactation (except for the genetic variance of CEEB, which was not significant at the beginning of lactation). Significant heritability estimates for BCS ranged from 0.34 to 0.79, for EC from 0.19 to 0.87, for CEEB from 0.58 to 0.93, for serum glucose from 0.12 to 0.39, for BHBA from 0.08 to 0.40, and for NEFA from 0.08 to 0.35. Genetic correlations between different weeks of lactation were near unity for adjacent weeks and decreased for weeks further apart, becoming practically zero for measurements taken more than 3 to 4 mo apart, especially with regard to blood metabolic traits. Significant heritability estimates were also obtained for BCS recorded before first calving. Results suggest that genetic evaluation and selection of dairy cows for early-lactation body energy and blood metabolic traits is possible.

Selection indexes have been extensively applied in the estimation of breeding value of dairy cattle for single traits as well as for combinations of traits for selection purposes. Milestones in methodology, such as multiple-trait evaluation procedures by BLUP, (co)variance component estimation, nonlinear models, discounted gene flow, dynamic programming, and international sire evaluations, together with increased computing power and the development of integrated AI and recording schemes, have contributed to efficient implementation of selection indexes and are reviewed in this article. Results of an international survey on evaluation practices and breeding programs are presented, demonstrating wide adoption of index selection for total merit and the need for further applications. Results from a simulation study on the efficiency of index selection for total merit are also presented; when the breeding goal includes, in addition to production traits, functional nonproduction traits such as mastitis resistance and fertility, failure to consider these traits in the selection index decreases efficiency 15 to 25%. Future applications are also discussed in view of advances in the areas of genome mapping, marker detection, and international comparisons. Further research should focus on functional nonproduction traits.

Test day SCC records were obtained from the Ontario DHI and converted to somatic cell score using a logarithmic transformation. Adjustment factors for stage of lactation and calendar month were obtained for first and later lactations. Effects of stage of lactation were significant and followed a systematic pattern. Seasonal effects were small. Sire estimated breeding values for lactation mean adjusted test day somatic cell scores were obtained from an animal model based on first, later, and all lactations, assuming a heritability of .11 and repeatability of .27. Mean accuracy of estimated breeding values for sires with at least 30 daughters was .64 for first lactation, .76 for second to fifth, and .86 for all lactations. Genetic trends for somatic cell score were not significant. The correlation of breeding values estimated from first lactations with estimates based on later lactations was .62 for sires with at least 50 daughters, which resulted in an approximate genetic correlation of .72. Correlations of sire estimated breeding values for somatic cell score from first lactation with estimated breeding values for milk, fat, protein, fat percentage, protein percentage, and milking speed were .12, .05, .11, -.09, -.02, and .20. Coffelations between sire estimated breeding values for somatic cell score and type traits were generally small, but favorable with mammary system, -.13, and fore udder, -.16, and unfavorable with dairy character, .24. Somatic cell score should be considered as an auxiliary trait in dairy cattle breeding programs.