Genetic relationship between culling, milk production, fertility, and health traits in Norwegian red cows

First-lactation records on 836,452 daughters of 3,064 Norwegian Red sires were used to examine associations between culling in first lactation and 305-d protein yield, susceptibility to clinical mastitis, lactation mean somatic cell score (SCS), nonreturn rate within 56 d in heifers and primiparous cows, and interval from calving to first insemination. A Bayesian multivariate threshold-linear model was used for analysis. Posterior mean of heritability of liability to culling of primiparous cows was 0.04. The posterior means of the genetic correlations between culling and the other traits were −0.41 to 305-d protein yield, 0.20 to lactation mean SCS, 0.36 to clinical mastitis, 0.15 to interval from calving to first insemination, −0.11 to 56-d nonreturn as heifer, and −0.04 to 56-d nonreturn as primiparous cow. As much as 66% of the genetic variation in culling was explained by genetic variation in protein yield, clinical mastitis, interval of calving to first insemination, and 56-d nonreturn in heifers, whereas contribution from the SCS and 56-d nonreturn as primiparous cow was negligible, after taking the other traits into account. This implies that for breeds selected for a broad breeding goal, including functional traits such as health and fertility, most of the genetic variation in culling will probably be covered by other traits in the breeding goal. However, in populations where data on health and fertility is scarce or not available at all, selection against early culling may be useful in indirect selection for improved health and fertility. Regression of average sire posterior mean on birth-year of the sire indicate a genetic change equivalent to an annual decrease of the probability of culling in first-lactation Norwegian Red cattle by 0.2 percentage units. This genetic improvement is most likely a result of simultaneous selection for improved milk yield, health, and fertility over the last decades.     

Genotype x environment interactions in conventional versus pasture-based dairies in Canada

The objective of this study was to evaluate effects of genotype x environmental interaction (GxE) on dairy traits among herds in Canada that practice intensive rotational grazing versus conventional methods that rely on stored feeds. Based on responses to questionnaires, 22 herds were selected for the grazing group and the conventional group consisted of 34 large free-stall dairies. Production data consisted of 6,749 lactations of 2,817 cows in the grazing herds and 29,371 lactations of 12,774 cows in the control herds. Subsets of data for reproduction and conformation also were created. Per cow production was greater in the conventionally managed herds (9,947 kg of milk) than in the grazing herds (9,400 kg). Phenotypic data were regressed on sire predicted transmitting abilities (PTA) and genetic correlations for all traits were estimated between environments. A scaling effect was observed across environments for yield traits, as phenotypic differences among cows were greater than predicted by sire PTA in conventional herds and consistent with sire PTA in grazing herds. Heritabilities for yield also were greater in conventional herds. Other effects of GxE were minor, with genetic correlations of near 0.90 or greater for all traits. Among yield traits, genetic correlation was lowest for fat (0.88 with SE = 0.04). These results demonstrate that effects of GxE are small between the two types of management systems analyzed and that graziers can accurately select sires based on national rankings.     

Identification of factors that cause genotype by environment interaction between herds of Holstein cattle in seventeen countries

Currently, the International Bull Evaluation Service calculates international dairy sire evaluations using the multiple-trait across country evaluation procedure. This method depends implicitly on political boundaries between countries, because the input data are national evaluations from each participating country. Therefore, different countries are treated as different production environments. The goal of this study was to identify factors that describe the production system on each farm. Such factors could be used to group herds across countries for borderless genetic evaluations. First lactation milk records of Holstein cows calving between January 1, 1990 and December 31, 1997 in Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the USA were used in this study. Thirteen genetic, management, and climatic variables were considered as potential indicators of production environments: peak milk yield, persistency, herd size, age at first calving, seasonality of calving, standard deviation of milk yield, culling rate, days to peak yield, fat to protein ratio, sire PTA milk, percentage of North American Holstein genes, maximum monthly temperature, and annual rainfall. Herds were grouped into quintiles based on herd averages for each of these variables. Genetic correlations for lactation milk yield between quintiles were significantly less than one for maximum monthly temperature, sire PTA milk, percent North American Holstein genes, herd size, and peak milk yield. The variables can be used to group herds into similar production environments, regardless of country borders, for the purpose of accounting for genotype by environment interaction in international dairy sire evaluation.     

Genotype x environment interaction for grazing vs. confinement. II. Health and reproduction traits

Continual selection for increased milk yield for more than 40 yr, combined with the antagonistic relationship between increasing yield, somatic cell count, and fertility, have resulted in sires that may not be optimal for producing daughters for grazing systems where seasonal calving is very important. The objective of this study was to investigate the possible existence of a genotype x environment interaction (G x E) in grazing vs. confinement herds within the United States for lactation average somatic cell score (LSCS), days open (DO), days to first service (DFS), and number of services per conception (SPC). Grazing herds were defined as those that utilized grazing for at least 6 mo each year and were enrolled in Dairy Herd Improvement (DHI). Control herds were confinement DHI herds of similar size in the same states. For LSCS, the performance of daughters in grazing and control herds was examined using linear regression of LSCS on the November 2000 USDA-DHIA sire predicted transmitting abilities (PTA) for SCS. Genetic parameters for all traits were estimated using REML in a bivariate animal model that treated the same trait in different environments as different traits. Rank correlations were calculated between sires' estimated breeding values for LSCS, calculated separately for sires in both environments. The coefficient of regression of daughter LSCS on sire PTA was less in grazing herds than in control herds. The coefficient of regression for control herds was closer to expectation. Estimates of heritability were approximately 0.12 for LSCS, and less than 0.05 for the reproduction traits. Heritabilities for DO, DFS, and SPC were slightly higher for control herds. Estimates of genetic correlation for each reproductive trait between the 2 environments were high and not significantly different from unity. Generally, these traits appear to be under similar genetic control, but a lower coefficient of regression of LSCS on sire PTA for SCS in grazing herds suggests differences in daughter performance in grazing herds may be overstated based on current PTA for SCS.     

Genotype x environment interaction for grazing versus confinement. I. Production traits

The objective of this study was to investigate the possible existence of a genotype x environment interaction (GxE) for production traits of US Holsteins in grazing versus confinement herds. Grazing herds were defined as those that utilized grazing for at least 6 mo and were enrolled in dairy herd improvement (DHI). Control herds were confinement DHI herds of comparable size in similar regions. The performance of daughters in grazing herds and control herds was examined using linear regression of mature equivalent milk, fat, and protein yield on the November 2000 USDA-DHI predicted transmitting abilities (PTA) of their sires for those traits. Heritabilities and genetic correlations were estimated using restricted maximum likelihood in a bivariate animal model that considered the same trait in different environments as different traits. Product-moment and rank correlations were calculated between sires' estimated breeding values, estimated separately in both environments. For grazing herds, the coefficient of regression of milk, fat and protein on PTA were 0.78, 0.76, and 0.78, respectively. Corresponding coefficients in the control herds were 0.99, 0.96, and 0.98. Estimates of heritability for the traits ranged from 0.2 to 0.25, and differences between grazing and control environments were small. Estimates of the genetic correlations for the traits in both environments were 0.89, 0.88, and 0.91 for milk, fat, and protein, respectively. Within-quartile analyses revealed a lower correlation for milk and protein between the upper and lower grazing quartiles, while the same quartiles for the control herds did not differ from unity. Rank correlation coefficients between sire estimated breeding values from the 2 environments were 0.59, 0.63, and 0.66 for milk, fat, and protein, respectively. The mean rank change for the top 100 sires between the two environments was 27. The regression coefficients indicate that expected daughter differences may be overstated by current sire PTA in grazing herds. Genetic correlations less than unity suggests that there is, at least, some reranking among sires in both environments, while the rank correlations indicate the possibility of sire reranking when evaluations were performed within management system. However, differences are not so large as to justify separate genetic evaluations for each system.     

Short communication: use of culling information in genetic evaluation of fertility and mastitis in Norwegian red cows

Breeding values for clinical mastitis, interval from calving to first insemination, and 56-d nonreturn rate for heifers and primiparous cows, were predicted using multivariate linear-threshold sire models, with or without including information on culling during the first lactation. Breeding values for 3,064 sires were predicted using 3 data sets with an average of 273, 135, and 68 first-crop daughters per sire, respectively. For each data set, accuracies of selection for health and fertility traits were evaluated through the predictive ability of predicted sire breeding values with respect to phenotypic performance of second-crop daughters. The predictive ability of estimated breeding values for clinical mastitis and interval from calving to first insemination did not improve when including information on early culling, irrespective of the size of first-crop daughter groups. For 56-d nonreturn rates (heifer and primiparous cow), sire evaluations based on reduced size of daughter groups tended to predict performance of the future daughters slightly better when including data on early culling. Hence, for breeding programs with direct selection for health and fertility traits there is little to gain by including early culling as additional information.     

Estimates of genetic parameters for Canadian Holstein female reproduction traits

Age at first insemination, days from calving to first insemination, number of services, first-service nonreturn rate to 56 d, days from first service to conception, calving ease, stillbirth, gestation length, and calf size of Canadian Holstein cows were jointly analyzed in a linear multiple-trait model. Traits covered a wide spectrum of aspects related to reproductive performance of dairy cows. Other frequently used fertility characteristics, like days open or calving intervals, could easily be derived from the analyzed traits. Data included 94,250 records in parities 1 to 6 on 53,158 cows from Ontario and Quebec, born in the years 1997 to 2002. Reproductive characteristics of heifers and cows were treated as different but genetically correlated traits that gave 16 total traits in the analysis. Repeated records for later parities were modeled with permanent environmental effects. Direct and maternal genetic effects were included in linear models for traits related to calving performance. Bayesian methods with Gibbs sampling were used to estimate covariance components of the model and respective genetic parameters. Estimates of heritabilities for fertility traits were low, from 3% for nonreturn rate in heifers to 13% for age at first service. Interval traits had higher heritabilities than binary or categorical traits. Service sire, sire of calf, and artificial insemination technician were important (relative to additive genetic) sources of variation for nonreturn rate and traits related to calving performance. Fertility traits in heifers and older cows were not the same genetically (genetic correlations in general were smaller than 0.9). Genetic correlations (both direct and maternal) among traits indicated that different traits measured different aspects of reproductive performance of a dairy cow. These traits could be used jointly in a fertility index to allow for selection for better fertility of dairy cattle.     

Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model

Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations.     

Evaluation of bull fertility in Italian Brown Swiss dairy cattle using cow field data

Dairy bull fertility is traditionally evaluated using semen production and quality traits; however, these attributes explain only part of the differences observed in fertility among bulls. Alternatively, bull fertility can be directly evaluated using cow field data. The main objective of this study was to investigate bull fertility in the Italian Brown Swiss dairy cattle population using confirmed pregnancy records. The data set included a total of 397,926 breeding records from 1,228 bulls and 129,858 lactating cows between first and fifth lactation from 2000 to 2019. We first evaluated cow pregnancy success, including factors related to the bull under evaluation, such as bull age, bull inbreeding, and AI organization, and factors associated with the cow that receives the dose of semen, including herd-year-season, cow age, parity, and milk yield. We then estimated sire conception rate using only factors related to the bull. Model predictive ability was evaluated using 10-fold cross-validation with 10 replicates. Interestingly, our analyses revealed that there is a substantial variation in conception rate among Brown Swiss bulls, with more than 20% conception rate difference between high-fertility and low-fertility bulls. We also showed that the prediction of bull fertility is feasible as our cross-validation analyses achieved predictive correlations equal to 0.30 for sire conception rate. Improving reproduction performance is one of the major challenges of the dairy industry worldwide, and for this, it is essential to have accurate predictions of service sire fertility. This study represents the foundation for the development of novel tools that will allow dairy producers, breeders, and artificial insemination companies to make enhanced management and selection decisions on Brown Swiss male fertility.     

Genetic analysis of dairy cattle production traits in a management intensive rotational grazing environment

Management intensive rotational grazing is a low input form of dairy herd management that is practiced by an increasing number of US dairy producers. However, concerns exist regarding the predictability of progeny performance in a grazing environment because most US dairy sires are progeny tested under conventional conditions of herd management. Lactation data from 27 Wisconsin dairy herds that have practiced management intensive rotational grazing for at least 4 yr were analyzed, as were data from three randomly chosen groups of control herds. Coefficients of regression of progeny milk, fat, and protein yields on USDA sire PTA values were 0.99, 0.76, and 0.96, respectively, from the grazing herds. In the control herds, regression coefficients for milk, fat, and protein yields averaged 0.95, 0.98, and 0.88, respectively. Therefore, progeny performance of grazing herds was predicted adequately by national sire PTA values that were derived primarily from conventionally managed herds. Heritability estimates for milk, fat, and protein yields were 0.23, 0.17, and 0.26, respectively, in the grazing herds and 0.24, 0.27, and 0.27, respectively, in a pooled data set containing all control herds. Estimated genetic correlations between production traits in the grazing environment and in the control environment were 0.92, 0.88, and 0.99 for milk, fat, and protein yields, respectively. These correlations, as well as the regression coefficients, indicate that interaction of genotype by environment is not important for these management systems, and nearly optimal genetic progress can be achieved by selecting AI sires progeny tested under traditional management conditions.     

Calving interval and survival breeding values as measure of cow fertility in a pasture-based production system with seasonal calving

In a grass-based production system with seasonal calving, fertility is of major economic importance. A delay in conception due to poor fertility prolongs intercalving interval and causes a shift in calving pattern, which can lead to culling. Calving interval (CIV) information is readily available from milk records; analyzing it, however, presents a problem, as it is only available for cows that conceive and calve again. Calving interval should therefore be treated as a censored trait. In this study, survival to the next lactation (SUV) was analyzed jointly with CIV in a multivariate linear model to account for the selection in CIV data. Genetic parameters for first lactation calving interval were estimated with a sire model for Holstein Friesian cows in Ireland. SUV was preadjusted for production within herd-year-season (HYS), while milk yield was included as a third trait in the analysis to account for the large effect it has on both traits. The residual covariance between CIV and SUV was fixed as 3 times the sire covariance within the model, as it was inestimable because of the structure of the data. Breeding values were estimated with various models to test the effect of culling and milk yield. Heritability was 0.04 +/- 0.006 for CIV and 0.01 +/- 0.003 for SUV, while the genetic correlation between them was -0.28 (+/-0.11). The genetic standard deviation was around 4% for SUV and 7 d for CIV. Sire predicted transmitting abilities for progeny tested bulls ranged between -5 and 3% for survival rate and between -4 and 8 d for calving interval. Differences between the best and worst bull varied with model. Including SUV and milk yield as traits in the model reduced the mean and variance of sire predicted transmitting abilities but increased the coefficient of variation by 30% compared with the univariate model. The current model is expected to account for most of the genetic variation in fertility that is possible from calving dates and future extensions, such as the use of linear type trait or additional lactations for predicting survival, appear straightforward. These traits now form part of the national index for selecting dairy bulls in Ireland.     

Genetic analysis of fertility-related diseases and disorders in Norwegian Red cows

Heritability of and genetic correlations among silent heat (SH), cystic ovaries (CO), metritis (MET), and retained placenta (RP) were inferred. These traits were chosen because they are the 4 most frequent fertility-related diseases and disorders among first-lactation cows in Norway. Records of 503,683 first-lactation daughters of 1,058 Norwegian Red sires with first calving from 2000 through 2006 were analyzed with a 4-variate threshold sire model. Presence or absence of each of the 4 diseases was scored as 1 or 0 based on whether or not the cow had at least 1 veterinary treatment for the disease. The mean frequency was 3.1% for SH, 0.9% for MET, 0.5% for CO, and 1.5% for RP. The model for liability had effects of age at calving and of month-year of calving, herd, sire of the cow, and a residual. Posterior mean (SD) of heritability of liability was 0.06 (0.01) for SH, 0.03 (0.01) for MET, 0.07 (0.01) for CO, and 0.06 (0.01) for RP. The genetic correlation between MET and RP was strong, with posterior mean (SD) 0.64 (0.10). A negative genetic correlation (−0.26) was found between RP and CO. The posterior distributions of the other genetic correlations included zero with high density, and could not be considered different from zero. The frequency of fertility-related diseases and disorders is very low in the Norwegian Red population at present, so there is limited scope for genetic improvement. However, this study indicates that reasonably precise genetic evaluation of sires is feasible for these traits given information from large daughter groups.     

Genetic parameters for conformation traits in herds that differ in mean final score and completeness of pedigree and performance data

The objectives of this study were to assess differences in the heritability of type (conformation) traits between herds that differ in mean final score and completeness of pedigree and performance data and to estimate genetic correlations among these environments. Measurement of subjective characteristics, such as conformation traits, may be more difficult in herds with poor management conditions, and genetic evaluation of sires using data from such herds could lead to inaccurate selection decisions. Furthermore, missing pedigree data is a significant problem in many herds, and a lack of phenotypic data from maternal relatives may reduce the effectiveness of animal model evaluation systems. These hypotheses were examined using type classification scores of 1,728,836 first-parity Holstein cows (from 54,223 sires) that calved from 1993 to 2002 in 24,207 US dairy herds. These data included 480,927 records from progeny test daughters, but only 254,891 (47%) were from dams that had valid sire identification, and only 132,953 (28%) were from dams that had also been classified. Herds were grouped into quartiles by mean classification score, percentage of known maternal grandsires, and percentage of classified dams. Estimated heritability of final score was 0.20 in herds with mean score <74.5, 0.17 in herds with <25% known maternal grandsires, and 0.19 in herds with <18% classified dams. Conversely, estimates were 0.39 in herds with mean score >78.7, 0.35 in herds with 100% known maternal grandsires, and 0.37 in herds with >71% classified dams. Estimated genetic correlations between quartiles ranged from 0.86 to 0.95. Based on this study, it appears that improvements in animal identification and data collection in progeny test herds would lead to greater accuracy and stability of genetic evaluations for conformation traits in US Holstein cattle.     

Genetic correlations between milk production and health and fertility depending on herd environment

High milk production in dairy cattle can have negative side effects on health and fertility traits. This paper explores the genetic relationship of milk yield with health and fertility depending on herd environment. A total of 71,720 lactations from heifers calving in 1997 to 1999 in the Netherlands were analyzed. Herd environment was described by 4 principal components: intensity, average fertility, farm size, and relative performance indicating whether herds had good (poor) health and fertility despite a high (low) production. Fertility was evaluated by days to first service and number of inseminations (NINS); somatic cell score was used as a measure of udder health. Data were analyzed with a multitrait reaction norm model. Genetic correlation within traits across environments ranged from 0.84 to unity. Genetic correlations of the 3 traits with milk yield were antagonistic but varied over environments. Genetic correlation of milk yield with days to first service varied from 0.30 in small herds to 0.48 in herds with low average fertility. Correlations with NINS varied from 0.18 in large herds to 0.64 in high fertility herds, and with somatic cell score from 0.25 in herds with a high fertility relative to production to 0.47 in herds with a relative low fertility. Selection in environments of average value resulted in different predicted responses over environments. For example, selection for a decrease of NINS of 0.1 in an average production environment decreased milk yield by 35 kg in low production herds, but by 178 kg in high production herds.     

Prediction of longevity breeding values for US Holstein sires using survival analysis methodology

Breeding values of Holstein sires for daughter longevity in each of 9 geographical regions of the United States were predicted using a Weibull proportional hazards model. Longevity (also commonly referred to as herd life or length of productive life) was defined as the number of days from first calving until culling or censoring. Records from 2,322,389 Holstein cows with first calving from 1990 to 2000 were used. In addition to the sire's additive genetic merit, our failure time model included time-dependent effects of herd-year-season of calving, parity-stage of lactation, and within-herd-year quintiles for mature equivalent fat plus protein yield, as well as the time-independent effect of age at first calving. Sire variances and parameters of the Weibull distribution were estimated separately for each region. The relative risk of culling for daughters of each individual sire was expressed relative to that of daughters of an average sire (within a specific region). Predicted breeding values for functional longevity, expressed as relative risk ratios, ranged from 0.7 to 1.3. Sizable differences were observed between geographical regions in sire rankings, as well as estimated sire variances and gamma parameters (of the distribution of herd-year-season effects), suggesting that a single national ranking may not be appropriate for every region. Two random samples of herds were selected from the full national data set; these contained 375,086 records and 256,751 records, respectively. Predicted transmitting abilities (PTA) of sires for daughter longevity were calculated using the Weibull proportional hazards (sire) model described previously but without the correction for milk production. These were compared with predictions from a linear (animal) model, as currently used for routine genetic evaluation of length of productive life in the United States. Logistic regression of daughters' stayability to 36, 48, 60, 72, or 84 mo of life (among animals that had opportunity to stay that long) on sires' PTA indicated that the proportional hazards model yielded more accurate predictions of daughter longevity than the linear animal model, even though the latter relied on denser pedigree information.     

Genetic analysis of reproductive disorders and their relationship to fertility and milk yield in Austrian Fleckvieh dual-purpose cows

The objective of this study was to estimate genetic parameters for various reproductive disorders based on veterinary diagnoses for Austrian Fleckvieh (Simmental) dual-purpose cattle. The health traits analyzed included retained placenta, puerperal diseases, metritis, silent heat and anestrus, and cystic ovaries. Three composite traits were also evaluated: early reproductive disorders, late reproductive disorders, and all reproductive disorders. Heritabilities were estimated with logit threshold sire, linear sire, and linear animal models. The threshold model estimates for heritability ranged from 0.01 to 0.14, whereas the linear model estimates were lower, ranging from 0.005 to 0.04. Rank correlations among random effects of sires from linear and threshold sire models were high (>0.99), whereas correlations between any sire model (linear, threshold) and the linear animal model were lower (0.88-0.92). Genetic correlations among reproductive disorders, fertility traits, and milk yield were estimated with bivariate linear animal models. Fertility traits included interval from calving to first insemination, nonreturn rate at 56 d, and interval between first and last insemination. Milk yield was calculated as the mean from test-day 1 and test-day 2 after calving. Estimated genetic correlations were 1 among metritis, retained placenta, and puerperal diseases and 0.85 between silent heat-anestrus and cystic ovaries. Low to moderate correlations (−0.01 to 0.68) were obtained among the other disorders. Genetic correlations between reproductive disorders and fertility traits were favorable, whereas antagonistic relationships were observed between milk yield in early lactation and reproductive disorders. Pearson correlations between estimated breeding values for reproductive disorders and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to longevity, calving ease maternal, and stillbirth maternal. The results showed that data from the Austrian health monitoring project can be used for genetic selection against reproductive disorders in Fleckvieh cattle.     

Heritabilities and genetic and phenotypic correlations for milk production and fertility traits of spring-calved once-daily or twice-daily milking cows in New Zealand

The objectives of this study were to estimate the genetic and phenotypic correlations and heritabilities for milk production and fertility traits in spring-calved once-daily (OAD) milking cows for the whole season in New Zealand and compare those estimates with twice-daily (TAD) milking cows. Data used in the study consisted of 69,252 first parity cows from the calving seasons 2015–2016 to 2017–2018 in 113 OAD and 531 TAD milking herds. Heritability estimates for production and fertility traits were obtained through single-trait animal models, and estimates of genetic and phenotypic correlations were obtained through bivariate animal models. Heritability estimates of production traits varied from 0.26 to 0.61 in OAD and from 0.13 to 0.63 in TAD. Heritability estimates for fertility traits were low in both OAD and TAD milking cow populations, and estimates were consistent (OAD: 0.01 to 0.10 and TAD: 0.01 to 0.08) across milking regimens. Estimates of phenotypic and genetic correlations among production traits were consistent across populations. In both populations, phenotypic correlations between milk production and fertility traits were close to zero, and most of the genetic correlations were antagonistic. In OAD milking cows, genetic correlations of milk and lactose yields with the start of mating to conception, 6-wk in-calf, not-in-calf, and 6-wk calving rate were close to zero. Interval from first service to conception was negatively genetically correlated with milk and lactose yields in OAD milking cows. Protein percentage was positively genetically correlated with 3-wk and 6-wk submission, 3-wk in-calf, 6-wk in-calf, first service to conception, 3-wk calving, and 6-wk calving rate in the TAD milking cow population, but these correlations were low in the OAD milking cow population. Further studies are needed to understand the relationship of protein percentage and fertility traits in the OAD milking system. The phenotypic correlations between fertility traits were similar in OAD and TAD milking populations. Genetic correlations between fertility traits were strong (≥0.70) in cows milked TAD, but genetic correlations varied from weak to strong in cows milked OAD. Further research is required to evaluate the interaction between genotype by milking regimen for fertility traits in terms of sire selection in the OAD milking cow population.     

Heifer fertility and its relationship with cow fertility and production traits in Holstein dairy cattle

Breeding receipts from three AI units were merged with Ontario Dairy Herd Improvement Corporation and Record of Performance production records. Data comprised 53,705 heifer, 41,253 lactation 1, 14,688 lactation 2, and 3054 lactation 3 records by daughters of 2150 sires represented in 15,877 herd-year-seasons of birth. Three measures of heifer fertility, three measures of cow fertility, and three measures of production were investigated. Measures of heifer fertility were ages at first and last breeding and number of inseminations per conception. Cow fertility traits were days from calving to first breeding, days open, and number of inseminations per conception. Production traits were breed class average milk, breed class average fat, and fat percentage. Relationships among these nine traits for the first three lactations were estimated using a maximum likelihood multiple-trait procedure. The linear mixed model for each trait included fixed effects of herd-year-season of birth and genetic groups of sire and the random effect of sire. Transformations of the data for nonnormality had no influence on the estimates of genetic and phenotypic parameters. The heritability of .12 for age at first insemination, which was higher than other heifer fertility traits, indicated that selection would result in genetic response. Genetic and phenotypic correlations between heifer fertility and cow fertility and production traits in all three lactations were not different from zero. There was no genetic antagonism between fertility and subsequent production traits.