Body condition scores and dairy form evaluations as indicators of days open in US Holsteins

The objectives of this study were to estimate genetic correlations among body condition score (BCS), dairy form, milk yield, and days open in US Holsteins and investigate the potential of using BCS or dairy form evaluations as early indicators of days open. Dairy form and BCS obtained from the Holstein Association USA, Inc., were merged with mature equivalents (ME) for milk yields and days open data from AIPL-USDA. Cows were required to be classified between 24 and 60 mo of age, before 335 d in milk (DIM) and have ME milk of at least 4537 kg. A minimum of 20 daughters per sire and 10 cows per herd-classification visit (HV) or herd-year-season of calving (HYS) were required. The final data set included 159,700 records. Heritabilities and correlations among dairy form, BCS, milk yield, and days open were estimated with multiple trait sire models. Fixed effects included age at classification for dairy form and BCS, age at calving for milk yield, HV for dairy form and BCS, HYS for milk yield and days open, DIM within lactation group for dairy form and BCS and lactation group for milk yield and days open. Correlations among dairy form, BCS, and days open were generated with and without a ME milk covariable. Correlations between ME milk and days open were generated with and without covariables for dairy form or BCS. Random effects included sire and error. The genetic correlation estimates of days open with dairy form, BCS, and ME milk were 0.48, -0.30, and 0.38, respectively. The genetic correlation estimate between days open and dairy form was 0.38 after adjustment for ME milk, whereas the genetic correlation between days open and BCS was -0.24 after adjustment for ME milk. Combining dairy form evaluations with days open evaluations for 19 recently proven bulls resulted in an average increase of 0.06 for reliability of days open evaluations. The addition of BCS evaluations did not increase reliability when dairy form observations were available.     

Genetic correlations among protein yield, productive life, and type traits from the United States and diseases other than mastitis from Denmark and Sweden.

Sire genetic evaluations for protein yield, productive life, and selected type traits from the US were correlated with sire evaluations for disease from Denmark and Sweden and were then adjusted to approximate genetic correlations. Disease categories from Denmark included reproductive diseases, foot and leg diseases, metabolic and digestive diseases, and all diseases other than mastitis. Genetic evaluations for Denmark were from separate analyses for each disease category using a multiple-trait sire model with first, second, and third lactations handled as multiple traits. Evaluations from Sweden for all diseases other than mastitis were from a single-trait sire model using only first lactations. In addition, Danish and Swedish genetic evaluations were regressed on US type evaluations to test for quadratic relationships. Relationships were based on 104 bulls with US and Danish evaluations (88 with US type) and 84 bulls with US and Swedish evaluations (83 with US type). Genetic correlations between US protein yield and diseases were unfavorable, but correlations were favorable between productive life and disease. Genetic correlations among US type and diseases were around zero, except for correlations with US dairy form (range -0.34 to -0.73). Genetic correlations calculated from residual correlations (adjusted for predicted transmitting abilities for milk) between productive life and diseases were favorable (range 0.29 to 0.51). Genetic correlations calculated from residual correlations (adjusted for predicted transmitting abilities for milk) between dairy form and diseases ranged from -0.10 to -0.53. Selection for increased productive life may reduce disease occurrences, but selection for higher dairy form scores will increase disease occurrences.     

Genetic parameters and association of national evaluations with breeding values for health traits in US organic Holstein cows

Among other regulations, organic cows in the United States cannot receive antibiotics and preserve their organic status, emphasizing the importance of prevention of illness and benefit of high genetic merit for disease resistance. At the same time, data underlying national genetic evaluations primarily come from conventional cows, drawing concern to the possibility of a genotype by environment interaction whereby the value of a genotype varies depending on the environment, and potentially limits the relevance of these evaluations to organic cows. The objectives of this study were to characterize the genetics of and determine the presence of genotype by environment interaction for health traits in US organic dairy cows. Individual cow health data were obtained from 16 US Department of Agriculture certified organic dairy farms from across the United States that used artificial insemination and maintained detailed records. Data were obtained for the following traits: died, lameness, mastitis, metabolic diseases (displaced abomasum, ketosis, and milk fever), reproductive diseases (abortion, metritis, and retained placenta), transition health events (any health event occurring 21 d before or after parturition), and all health events. Binary phenotypes (1 = diseased, 0 = otherwise) for 38,949 lactations on 19,139 Holstein cows were used. Genotypes from 2,347 cows with 87.5% or greater Holstein breed-based representation were incorporated into single-step multitrait threshold animal models that included stayability (1 = completed lactation, 0 = otherwise). Gibbs sampling was used. Genomic predicted transmitting abilities (gPTA) from national genetic evaluations were obtained for sires for production, fitness, health, and conformation traits. We approximated genetic correlations for sires using these gPTA and our estimated breeding values. We also regressed health phenotypes on cow estimated breeding values and sire gPTA. Heritabilities (± standard error) ranged from 0.03 ± 0.01 (reproductive diseases) to 0.11 ± 0.03 (metabolic diseases). Most genetic correlations among health traits were positive, though the genetic correlation between metabolic disease and mastitis was ?0.42 ± 0.17. Approximate genetic correlations between disease resistance for our health trait categories and disease resistance for the nationally-evaluated health traits generally carried the expected sign with the strongest correlation for mastitis (0.72 ± 0.084). Regression coefficients carried the expected sign and were mostly different from zero, indicating that evaluations from primarily conventional herd data predicted health on organic farms. In conclusion, use of national evaluations for health traits should afford genetic improvement for health in US organic herds.     

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.     

Heritability and correlations for body condition score and dairy form within and across lactation and age

The objectives of the current study were to investigate the relationship between body condition score (BCS) and dairy form and changes in genetic parameters for BCS and dairy form within and across lactations and age. Body condition score and dairy form were obtained from the Holstein Association USA, Inc. Records were edited to include those cows classified between 24 and 60 mo of age and between 0 and 335 d in milk (DIM). A minimum of 20 daughters per sire and 15 cows per herd-classification visit were required. The dataset consisted of 135,178 records from 119,215 cows. Repeatability, multiple trait, and random regression models were used to analyze the data. All models included fixed effects for herd-classification visit, age within lactations 1, 2, and 3 or higher, and 5th-order polynomials for DIM. Random effects included sire and permanent environment for all models. Random regression models included age at classification nested within sire or DIM and lactation number nested within sire. Genetic variance for both BCS and dairy form was lowest in early lactation and highest in midlactation. Genetic correlations within and across lactations were high. The genetic correlation between DIM 0 in lactation 1 and DIM 305 in lactation 3 was estimated to be 0.77 for BCS and 0.60 for dairy form. The genetic correlation estimate between 30 mo of age at classification and 50 mo of age at classification was 0.94 for both dairy form and BCS. The repeatability models appeared to generate accurate evaluations for BCS or dairy form at all ages and stages of lactation.     

Heritabilities and correlations among body condition score,dairy form and selected linear type traits

The objectives of this study were to estimate the heritability of body condition score (BCS) with data that could be used to generate genetic evaluations for BCS in the US, and to estimate the relationship among BCS, dairy form and selected type traits. Body condition score and linear type trait records were obtained from Holstein Association USA Inc. Because BCS was a new trait for classifiers, scoring distribution and accuracy was not normal. Records from 11 of 29 classifiers were eliminated to generate a data set that should represent BCS data recorded in the future. Edited data included 128,478 records for analysis of first lactation cows and 207,149 records for analysis of all cows. Heritabilities and correlations were estimated with ASREML using sire models. Models included age at calving nested within lactation, 5th order polynomials of DIM, fixed herd-classification visit effects and random sire and error. Genetic correlation estimates were generated between first lactation data that had records from 11 classifiers removed and data with no classifiers removed. Genetic correlation estimates were 0.995 and above between data with and without classifiers removed for scoring distributions, but heritability estimates were higher with the classifiers edited from the data. Heritability estimates for type traits and final score were similar to previously reported estimates. The heritability estimate for BCS was 0.19 for first lactation cows and 0.22 for all cows. The genetic correlation estimate for first lactation cows between BCS and dairy form was -0.73, whereas the genetic correlation estimate between BCS and strength was 0.72. Genetic correlation estimates were nearly identical when cows from all lactations were included in the analyses. Body condition score had a genetic correlation with final score closer to zero (0.08) than correlations of final score with dairy form, stature or strength.     

Genomic selection for producer-recorded health event data in US dairy cattle

Emphasizing increased profit through increased dairy cow production has revealed a negative relationship of production with fitness and health traits. Decreased cow health can affect herd profitability through increased rates of involuntary culling and decreased or lost milk sales. The development of genomic selection methodologies, with accompanying substantial gains in reliability for low-heritability traits, may dramatically improve the feasibility of genetic improvement of dairy cow health. Producer-recorded health information may provide a wealth of information for improvement of dairy cow health, thus improving profitability. The principal objective of this study was to use health data collected from on-farm computer systems in the United States to estimate variance components and heritability for health traits commonly experienced by dairy cows. A single-step analysis was conducted to estimate genomic variance components and heritabilities for health events, including cystic ovaries, displaced abomasum, ketosis, lameness, mastitis, metritis, and retained placenta. A blended H matrix was constructed for a threshold model with fixed effects of parity and year-season and random effects of herd-year and sire. The single-step genomic analysis produced heritability estimates that ranged from 0.02 (standard deviation = 0.005) for lameness to 0.36 (standard deviation = 0.08) for retained placenta. Significant genetic correlations were found between lameness and cystic ovaries, displaced abomasum and ketosis, displaced abomasum and metritis, and retained placenta and metritis. Sire reliabilities increased, on average, approximately 30% with the incorporation of genomic data. From the results of these analyses, it was concluded that genetic selection for health traits using producer-recorded data are feasible in the United States, and that the inclusion of genomic data substantially improves reliabilities for these traits.     

Genetic parameters of dairy character, protein yield, clinical mastitis, and other diseases in the Danish Holstein cattle

The primary aim of this study was to estimate genetic correlations between dairy character, protein yield, clinical mastitis, and other diseases. Data consisted of first lactation records of Danish Holstein cows calving from 1990 to 1999. After editing, the data included records on 934,639 cows, of which 101,853 were assessed for dairy character, 472,421 for diseases, and 834,993 for protein yield. The disease traits were defined as binary traits in the period from 10 d before to 50 d after calving for clinical mastitis, and from 10 d before to 100 d after calving for diseases other than mastitis. Data were analyzed with a linear sire model using the method of AI-REML. Heritabilities were estimated to be 0.265 for protein yield, 0.261 for dairy character, 0.035 for clinical mastitis, and 0.020 for diseases other than mastitis. Estimates of genetic correlations between protein yield and dairy character, protein yield and clinical mastitis, and protein yield and diseases other than mastitis were 0.38, 0.33, and 0.14. Between the two disease traits, the genetic correlation was 0.24. The genetic correlation between dairy character and clinical mastitis was 0.24. Between dairy character and diseases other than mastitis the genetic correlation was 0.41. Thus, cows with high score for dairy character were more prone to diseases. The genetic correlation between dairy character and the disease traits, when both traits were adjusted for protein yield, was 0.13 for clinical mastitis and 0.39 for diseases other than mastitis. These findings suggest that, dairy character should be given a negative rather than a positive weight in the breeding goal.     

Liability to diseases and their relation to dry matter intake and energy balance in German Holstein and Fleckvieh dairy cows

Dairy cow efficiency is increasingly important for future breeding decisions. The efficiency is determined mostly by dry matter intake (DMI). Reducing DMI seems to increase efficiency if milk yield remains the same, but resulting negative energy balance (EB) may cause health problems, especially in early lactation. Objectives of this study were to examine relationships between DMI and liability to diseases. Therefore, cow effects for DMI and EB were correlated with cow effects for 4 disease categories throughout lactation. Disease categories were mastitis, claw and leg diseases, metabolic diseases, and all diseases. In addition, this study presents relative percentages of diseased cows per days in milk (DIM), repeatability, and cow effect correlations for disease categories across DIM. A total of 1,370 German Holstein (GH) and 287 Fleckvieh (FV) primiparous and multiparous dairy cows from 12 dairy research farms in Germany were observed over a period of 2 yr. Farm staff and veterinarians recorded health data. We modeled health and production data with threshold random regression models and linear random regression models. From DIM 2 to 305 average daily DMI was 22.1 kg/d in GH and 20.2 kg/d in FV. Average weekly EB was 2.8 MJ of NE_L/d in GH and 0.6 MJ of NE_L/d in FV. Most diseases occurred in the first 20 DIM. Multiparous cows were more susceptible to diseases than primiparous cows. Relative percentages of diseased cows were highest for claw and leg diseases, followed by metabolic diseases and mastitis. Repeatability of disease categories and production traits was moderate to high. Cow effect correlations for disease categories were higher for adjacent lactation stages than for more distant lactation stages. Pearson correlation coefficients between cow effects for DMI, as well as EB, and disease categories were estimated from DIM 2 to 305. Almost all correlations were negative in GH, especially in early lactation. In FV, the course of correlations was similar to GH, but correlations were mostly more negative in early lactation. For the first 20 DIM, correlations ranged from ?0.31 to 0.00 in GH and from ?0.42 to ?0.01 in FV. The results illustrate that future breeding for dairy cow efficiency should focus on DMI and EB in early lactation to avoid health problems.     

The genetic relationship of body weight and early-lactation health disorders in two experimental herds

The objectives of this study were to estimate genetic parameters for body weight (BW) and BW change (BWC) and genetic correlations of BW and BWC with diseases and genomic predicted transmitting abilities (PTA) of productive and conformation traits of Holsteins during the first 120 DIM. Daily BW data were from the Afiweigh cow body weighing system (SAE Afikim, Kibbutz Afikim, Israel), which records BW as a cow exits the milking parlor. Disease categories included metabolic diseases, ketosis, infectious diseases, mastitis, reproductive diseases, and other diseases. Edited data included 68,914 and 11,615 daily BW observations from 441 Pennsylvania State University and 72 Virginia Tech Holstein cows, respectively. Two-trait random regression models were used to estimate relationships between BW, BWC, and diseases at 25, 38, and 58 mo of age at calving. Fixed effects for BW were age at calving nested within lactation group, week of lactation, and herd date; random effects for BW included animal, permanent environment, and error. Fixed effects for disease were herd-year-season of calving and age at calving nested within lactation group; random effects for disease were animal, permanent environment (for mastitis only), and error. Correlations of PTA for BW and BWC with genomic PTA for productive and type traits were also estimated with data from 117 cows. Heritability estimates for daily BW ranged from 0.34 to 0.63. Greater BW and less BWC were favorably correlated with ketosis, metabolic diseases, infectious diseases, and other diseases. The genetic correlation estimate between BW and ketosis was strongest at 60 DIM (−0.51), and genetic correlation estimates at 60 DIM with metabolic diseases (−0.52), infectious diseases (−0.81), and other diseases (−0.48) followed the same trend as ketosis. The genetic correlation estimate between BWC and ketosis was strongest for the change from 5 to 20 DIM (0.70) and was similar for metabolic diseases (0.37), infectious diseases (0.74), and other diseases (0.49). Correlations of BW and BWC with reproductive diseases tended to be in the reverse direction of those reported for ketosis. A larger PTA for BW was significantly correlated with smaller genomic PTA for milk yield, dairy form, rear udder height, and udder cleft. Predicted transmitting ability for BWC was negatively correlated with genomic PTA for protein percentage, strength, and hip width (ranging from −0.26 to −0.13 across lactation) and was positively correlated with dairy form, rear udder height, and udder cleft (ranging from 0.20 to 0.37 across lactation). Selection for reduced BW loss can be implemented with automated body weighing systems and may be successful in decreasing disease incidence in the early stages of lactation.     

Genetic relationship between body condition score, dairy character, mastitis, and diseases other than mastitis in first-parity Danish Holstein cows

The aim of this study was to explore the possibilities of using body condition score (BCS) or dairy character (DC) as indicators of mastitis and diseases other than mastitis in first-parity Danish Holsteins. The dataset included 28,948 observations on conformation scores and 365,136 disease observations. The analysis was performed using a multitrait linear sire model. Heritability estimates for BCS and DC were moderate (0.25 and 0.22), and heritability estimates for mastitis and diseases other than mastitis were low (0.038 and 0.022). Between BCS and diseases other than mastitis, the genetic correlation was -0.22, whereas the genetic correlation was -0.16 between BCS and mastitis. The genetic correlation between DC and diseases other than mastitis was 0.43, and between DC and mastitis it was 0.27. The genetic correlation between BCS and DC was -0.61. Residual correlations were close to 0, except between BCS and DC (-0.37). Including DC as an indicator of diseases other than mastitis will increase the accuracy of the predicted breeding value for diseases, especially when the progeny group is small. Using BCS as an additional indicator of diseases did not increase the accuracy. Breeding for less DC will increase resistance to diseases.     

Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle

Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between daily genetic evaluations on d 10 or 30 and subsequent daily evaluations were used to assess BCS change at different stages of lactation. Genetic evaluations for BCS level or change were used to estimate genetic correlations between BCS measures and fertility traits in order to assess the capacity of BCS to predict fertility. Genetic correlation estimates with calving interval and non-return rate were consistently higher for daily BCS than single measure BCS evaluations, but results were not always statistically different. Genetic correlations between BCS change and fertility traits were not significantly different from zero. The product of the accuracy of BCS evaluations with their genetic correlation with the UK fertility index, comprising calving interval and non-return rate, was consistently higher for daily than for single BCS evaluations, by 28 to 53%. This product is associated with the conceptual correlated response in fertility from BCS selection and was highest for early (d 10 to 75) evaluations.     

Genetic evaluation of Holstein sires and maternal grandsires in the United States for perinatal survival

Stillbirth, defined as a calf that dies just prior to, during, or within 48 h of parturition, represents a reoccurring concern among breeders of dairy cattle in the United States. About 11% of parturitions of primiparous Holstein cows result in the death of a calf; 5.7% in multiparous cows. Genetic evaluations can be reported as perinatal survival to 48 h to emphasize the positive information about the trait. The purpose of this research was to: 1) estimate genetic parameters by restricted maximum likelihood for perinatal survival rates; 2) characterize the genetic evaluation of sires for the perinatal survival of their progeny and maternal grandsires for the perinatal survival of their daughters progeny; and 3) estimate genetic trends from 1984 to 1994. Data (n = 666,339) were from the National Association of Animal Breeders calving ease database. Over 600 new young sires were available each year. The binomial response variable, 1 = alive, 0 = stillborn within 48 h of parturition was analyzed by using a sire-maternal grandsire linear mixed model. The model included fixed effects for sex of calf, dystocia, and season of birth, and gestation length as a covariate; correlated random effects of sire and maternal grandsire; and uncorrelated random effects of herd-years. Parturitions of primiparous and multiparous cows were analyzed separately. In primiparous cows, heritability estimates were 1.1 and 2.2% for sire of the calf and maternal grandsire, respectively. The genetic correlation between sire and maternal grandsire predicted transmitting ability (PTA) for perinatal survival, was 0.31; simple product moment correlations among sire-MGS PTA were 0.43 and 0.46 for primiparous and multiparous cows, respectively. The PTA for sire of the calf ranged from -2.9 (lower survival) to 2.8% (higher survival). Mean PTA from 1984 to 1994 was quite variable from year to year. Evidence showed a slightly negative, but nonsignificant, genetic trend in perinatal survival (-0.04% per year for sires and -0.02% per year for maternal grandsires). Estimates of genetic parameters and genetic trends for data from multiparous cows are also reported. Correlations among PTA for perinatal survival, milk yield, and calving ease are given.     

Short communication: Genetic parameters for mastitis and its predictors in Canadian Holsteins

The objective of this study was to estimate genetic parameters for mastitis and its predictors [mean somatic cell score (SCS) in early lactation, standard deviation of SCS, excessive test-day somatic cell count (SCC), udder depth (UD), fore udder attachment (FUA), and body condition score (BCS)]. Mastitis data recorded by producers were available from the national dairy cattle health system in Canada. Mastitis was defined as a binary variable based on whether or not the cow had at least 1 mastitis case in the period from calving to 305 d after calving. A Bayesian analysis using Gibbs sampling was applied. Threshold liability models were applied for binary traits (mastitis and excessive test-day SCC), and linear models were used for other normally distributed traits. For mastitis, a heritability of 0.07 was obtained. Heritability estimates for mean SCS in early lactation, standard deviation of SCS, excessive test-day SCC, UD, FUA, and BCS were 0.10, 0.04, 0.06, 0.41, 0.21, and 0.18, respectively. Mastitis was highly correlated with mean SCS in early lactation (0.63), standard deviation of SCS (0.74), and excessive test-day SCC (0.76). Moderate genetic correlations of −0.36, −0.24, and −0.28 were found between mastitis and UD, FUA, and BCS, respectively. As much as 72% of the genetic variation in mastitis resistance was explained by all the indirect predictor traits, whereas the most commonly used indirect measures of mastitis resistance (SCS in early lactation, UD, and FUA) explained together only 46% of the genetic variation in mastitis resistance. A combination of mean and standard deviation of SCS seem to be more successful in improving udder health than the traditional indirect measures. The results of the present study highlight that although routine cow SCC is the best measurement to monitor udder health, it cannot explain all the genetic variation in mastitis resistance and, therefore, direct information on mastitis resistance can be expected to yield to a more accurate genetic evaluation for this trait.     

Nongenetic effects and genetic parameters for length of productive life of Holstein cows in Hokkaido, Japan

Records of Holstein dairy cows in Hokkaido, Japan, were used to study the effects of environmental factors on length of productive life and to estimate genetic parameters for length of productive life. Each record was assigned to 1 of 3 data sets depending on the percentage of type-scored cows in the herd. This percentage was considered to partly reflect the management policy in each herd, in particular regarding culling. The A, B, and C data sets consisted of herds with none, less than 60%, and more than 60% of type-scored cows, respectively, and included 158,719, 787,598, and 131,499 records, respectively. Analyses of length of productive life were separately carried out on each data set using the Survival Kit software (Version 5.0). Nonparametric hazards estimates and the shape parameters of the baseline Weibull distribution differed between the 3 data sets. A cow having a sire originating from the United States or Canada had a relatively lower risk of being culled than a cow having Japanese sire in data set C. However, in data set A, a cow having a Canadian sire had a higher relative risk than a cow having a Japanese sire. The herd-year variance for data set A was about twice as large as for data set C. In contrast, the sire variance for data set A was about 40% of the one for data set C. As a result, heritability varied across data sets from 0.046 to 0.134. The results of this study suggest that it is important to consider factors related to herd management policy, such as the percentage of type-scored cows, in genetic analyses on length of productive life of Holstein cows in Hokkaido, Japan.     

Impact of paternity errors in cow identification on genetic evaluations and international comparisons.

The impact of paternity identification errors on US genetic evaluations and international comparisons of Holstein dairy bulls for milk, fat, and protein yields was investigated. Sire identification was replaced for 11% of Holstein cows that were sired by AI bulls and had records in the US database for national genetic evaluations; US evaluations were computed based on those modified pedigrees and compared with official national evaluations. Estimated breeding values from the data with introduced paternity errors were biased, especially for later generations. Estimated genetic trends decreased by 11 to 15%. Estimates of standard deviations of sire transmitting ability also decreased by 8 to 9%. International multitrait across-country comparisons of bulls were computed based on national evaluations from the United States, Canada, New Zealand, and The Netherlands. Estimates of genetic correlations between the United States and other countries decreased by 0.04 to 0.06 when US evaluations were based on modified pedigree. The resulting bias toward selection of domestic bulls and the inability to identify truly superior animals that are available internationally could decrease potential selection differentials by 0.07 to 0.09 standard deviation units on the US scale, which corresponds to sire breeding values of approximately 50 kg for milk, 3 kg for fat, and 1.7 kg for protein. Losses for the other countries were lower and ranged from 0.02 to 0.05 standard deviation units, because a correlation of less than unity with the United States decreased the impact of US cow paternity errors on the scales of other countries. Although paternity verification is desirable and technically feasible, commercial implementation would require low testing costs.     

Genetic and phenotypic parameters for type and production in Guernsey dairy cows.

Heritabilities; genetic and phenotypic correlations for milk, fat, and protein production; and linear type traits were estimated from a sire model including sire relationships using multiple-trait REML. For the milk production traits, 68,109 first parity records were analyzed. Heritabilities ranged from .31 to .37, genetic correlations between the milk production traits ranged from .80 to .92, and phenotypic correlations ranged from .86 to .94. Linear type traits from 12,996 cows on 15 traits were used to estimate heritabilities and genetic and phenotypic correlations between linear type traits. The heritabilities ranged from .53 for stature to .09 for foot angle. Rear udder height and rear udder width had the highest positive genetic correlation (.85), whereas dairy form and udder depth had the highest negative genetic correlation (-.41). When the first parity production records were merged with type records for cows, 9867 records on 18 traits were obtained. Dairy form, rear udder height, and rear udder width had strong to moderate positive genetic correlations with the three production traits. Fore udder attachment and udder depth had moderate negative genetic correlations with the three milk production traits. These results suggest that selection for improvement of milk production will lead to correlated increases in dairy form, rear udder height, rear udder width, and udder depth and to correlated decreases in the strength of fore udder attachment.     

Genetic determination of mortality rate in Danish dairy cows: A multivariate competing risk analysis based on the number of survived lactations

Dairy cow mortality has been steadily increasing during the last 2 decades in Denmark. This study aims to verify whether genetic mechanisms might be contributing to this increase. To do so, the records of 880,480 Holstein, 142,306 Jersey, and 85,206 Red Danish dairy cows calving from 1990 to 2006 were retrieved from the Danish Cattle register. Two causes of culling of cows were considered: death and slaughtering. Bivariate competing risk genetic models with a sire model structure were used to describe the death and the slaughtering rates simultaneously. The models included 2 random components: a sire random component with pedigree representing the sire genetic effects and a herd-year-season component. Moreover, the level of heterozygosity and the sire breed proportions were included in the models as covariates to account for potential nonadditive genetic effects due to the massive introduction of genetic material from other populations. The correlations between the sire components for death rate and slaughter rate were negative and small for the 3 populations, suggesting the existence of specific genetic mechanisms for each culling reason and common concurrent genetic mechanisms. In the Holstein population, the effects of the changes in the level of heterozygosity, breed composition, and the increasing genetic trend acted in the same direction, increasing the death rate in recent years. In the Jersey population, the effects of the level of heterozygosity and the breed proportion were small, and only the increasing genetic trend can be pointed as a genetic cause to the observed increase in the mortality rate. In the Red Danish population, neither the time-development pattern of the genetic trend nor the changes in the level of heterozygosity and breed composition could be causing the observed increase in the mortality; thus, nongenetic factors must be causing this negative development.     

Genetic parameters for female fertility in Nordic Holstein and Red Cattle dairy breeds

Genetic evaluation of female fertility in Danish, Finnish, and Swedish dairy cows was updated in 2015 to multiple-trait animal model evaluation, where heifer and cow fertility up to third parity are considered as separate traits. A model for conception rate was also developed, which required variance component estimation for Nordic Holstein and Nordic Red Dairy Cattle. We used a multiple-trait multiple-lactation sire model to determine variance components for interval from calving to first insemination, length of service period, and conception rate. Monte Carlo Expectation Maximization REML allowed estimation of all 11 traits simultaneously. Study data were sampled from Swedish Holstein (n = 140,040) and Red Dairy Cattle (n = 101,315) heifers and cows. Conception rate observations are binomial observations with various numbers of failures preceding an observation of success. Using a simulation study, we confirmed that including a service number effect into the conception rate model allowed us to model the change in expectation of successful AI with increasing number of services. Heifers outperformed cows in all fertility traits according to the phenotypic means in the records. Heritabilities for the traits varied from 3 to 7% for interval from calving to first insemination, from 1 to 5% for length of service period, and from 1 to 3% for conception rate. Genetic correlations within traits (i.e., between parities) were favorable, ranging from moderate to high; genetic correlations between heifer and cow traits were lower than between cow traits in different parities. Lowest genetic correlations between traits were for interval from calving to first insemination and conception rate, intermediate for interval from calving to first insemination and length of service period, and highest for length of service period and conception rate. The variance components estimated in this study have been used in Nordic fertility breeding value evaluations since 2016.     

Heritabilities of and genetic correlations among six health problems in Holstein cows

Information from 7712 lactations of Holstein dairy cows was collected from 33 commercial herds around Ithaca, NY in the 3 yr from 1981 to 1983. The data were divided into subsets corresponding to lactation 1, lactation 2, and lactation 3 or greater. To estimate heritabilities of dystocia, retained placenta, metritis, ovarian cysts, milk fever, and mastitis, a mixed linear model (herd-year fixed and sire random effects) with 0 or 1 as the observed response was used. Variance components were estimated using Henderson's Method 3. The results show moderate heritabilities (.15 to .40) for dystocia, metritis, milk fever, and mastitis and low heritability (less than .12) for retained placenta and cystic ovaries. Genetic correlations between dystocia, retained placenta, metritis, and mastitis were moderate in size and positive, whereas cystic ovaries were correlated negatively with dystocia and retained placenta. A general reproductive health trait (dystocia, retained placenta, metritis, cystic ovaries, and milk fever combined in one trait) also was analyzed. The estimated heritability of this trait was .21, .11, and .00 for first calf heifers, second lactation cows, and older cows, respectively.