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Genetic Analysis of Fertility Traits in Israeli Dairy Cattle
Abstract
First through third parity lactation records of 91,770 Israeli Holsteins inseminated between 1980 and 1986 were evaluated by univariate mixed model methodology for fertility and production traits. The analytical model included the effects of herd-year-season, group of sires, sire, cow, and residual. Sire, cow, and residual were random: all other effects were fixed. Sires were assumed to be unrelated. Variance components were computed separately for first and second parity by Henderson's method 3. First parity heritabilities were .035 for conception status [1/number of inseminations to conception], .048 for days from calving to first breeding, and .135 for milk production. Corresponding second parity heritabilities were .022, .031, and .125. First parity genetic correlations were -.02 between conception status and milk, .27 between days to first breeding and milk, and -.03 between the two fertility traits. All environmental correlations, and all second parity genetic correlations among these traits, were between -.2 and .2. Genetic trends, estimated as twice the regression of the evaluation of the cow's sire on calving date, were 1% for conception status, .1 for days to first breeding, and 154 kg milk/yr. Thus, there was no indication of an adverse genetic relationship between fertility and milk production in this population.
... to 1989, 1990and 1995.5: Conception rates across days in milk for low, medium and high milk production levels from 1985-1989, 1990and 1995.6: ...
... to 1989, 1990and 1995.5: Conception rates across days in milk for low, medium and high milk production levels from 1985-1989, 1990and 1995.6: Conception rates across service month for low, medium and high milk production levels from 1985-1989, 1990-1994 and 1995 to 2000..................60 INTRODUCTION Holsteins have been known as the most productive breed of dairy cattle. ...
... A decline in fertility in Holsteins has been reported by many studies . Lower fertility problem results in longer lactation lengths and economic losses due to increase in the number of inseminations, veterinary costs and involuntary culling (Hansen et al., 1983;Weller, 1989;Taylor et al., 1985;. ...
The objective of this study was to investigate environmental effects of conception rate and the trend over time in Holsteins using individual artificial insemination records. Data for cows born from 1988 to 2004 were obtained from Dairy Records Management Systems in Raleigh, NC. Records without calving or birth date, parity >1, days to service after calving <21 or >250, and without next calving date were eliminated. Conception rate was significantly affected by DIM, season, and milk production, and it varied by region. Conception rates increased with DIM, but there was a lag for high milk producing cows. Also, conception rates were negatively affected by heat stress in southeast USA. Conception rate can be improved by increasing the voluntary waiting period, especially for high producing cows. High producing cows in hot climates should be inseminated in spring. Conception rates decreased over the years while milk production increased.
... Traditionally, the most common criterion was nonreturn rate, the fraction of cows that were not reinseminated within a specific time interval. This criterion ignored cows that were culled after the first insemination (Weller, 1989). More recent measures have considered the time lapse from first insemination to pregnancy or some function of the number of times a cow is inseminated during the lactation (Fleming et al., 2019). ...
... Fertility data in Israel are unique in that cows that are not reinseminated within 60 d are checked for pregnancy by a veterinarian (Weller, 1989). Although abortions are recorded in Israel, very few first-trimester abortions are noted by either the herd manager or the attending veterinarian. ...
... Conception from the first insemination was determined as described previously (Weller, 1989). Briefly, conception was determined by veterinary pregnancy check approximately 60 d after conception. ...
One of the causes of observed low fertility is embryo loss after fertilization. Previous findings suggested that more than half of fertilizations result in embryo loss before pregnancy is detected. We proposed reinsemination between 49 and 100 d after the first insemination as an indicator trait for early abortion (EA) in dairy cattle based on the mean estrus interval of 21 d. This trait was compared with conception rate from first insemination and conception status, computed as the inverse of the number of inseminations to conception. Animal model variance components were estimated by REML, including parents and grandparents of cows with records. First-parity heritability for first insemination conception rate was 3%. In the multitrait analysis of parities 1 to 3 for putative EA, heritabilities ranged from 8.9% for first parity to 10.4% for second parity. All genetic correlations were >0.9, whereas all environmental correlations were <0.12. The variance component for the service sire effect for putative EA rate was less than half the variance component for conception rate. Thus, genetic control of the 2 traits is clearly different, and analysis of EA rate by a single-trait animal model is justified. Genetic evaluation for putative EA was computed using this model, including all first- through third-parity cows with freshening dates from January 1, 1985, through December 31, 2016, that either became pregnant on first insemination or were reinseminated between 49 and 100 d after the first insemination. All known parents and grandparents of cows with records were included in the analysis. The regression of the breeding value for non-abortion rate on the cows' birth year was 0.083%/yr. The genetic correlation between first-parity EA and conception status was 0.995. The genetic correlations between first-parity EA and milk, fat, and protein production were all negative, whereas the genetic correlation between EA and herd life was 0.33. Inclusion of putative EA in the selection index instead of conception status resulted in 10 to 20% greater genetic gain for both fertility traits. In a genome-wide association study based on 1,200 dairy bulls with reliabilities >50% for abortion rate genotyped for 41,000 markers, 6 markers were found with nominal probabilities of <10⁻¹² to reject the null hypothesis of no effect on EA rate. The markers with the lowest probabilities for EA rate were also included among the markers with the lowest probabilities for female fertility, but not vice versa. The marker explaining the most variance for abortion rate is located within the ABCA9 gene, which is found within an ATP-binding cassette (ABC) genes cluster. The ABC family is the major class of primary active transporters in the placenta.
... However, this selection for productive traits was detrimental for fertility in dairy cattle, since there is an antagonistic correlation between female fertility and milk production (VanRaden et al., 2004). At first, this idea was controversial, since some studies reported little or no relationship between traits of yield and reproduction (Weller, 1989), or even if the reported it, it was not significant (Shanks et al., 1978). Later, it became accepted that due to unfavorable genetic correlations selection for higher yields in dairy cattle has possibly led a decline in fertility, since the reproduction physiology of dairy cattle changed in response to genetic selection for milk production (Lucy, 2001). ...
... The relative importance of environmental differences is considerably higher for reproductive traits than for milk yield and composition (Raheja et al., 1989;Weller, 1989;Campos et al., 1994). This means that even with selection the changes in these traits would be expected to be nil (or small) and that efforts should therefore be devoted to improving management practices. ...
Estimates of the repeatability and heritability of 19 measures of performance in Jersey cows were obtained using an animal model with a relationship matrix and a derivative-free restricted maximum likelihood algorithm. The data consisted of 935 records for 374 cows by 69 sires over the period 1969-1987. The estimates were similar to those obtained by ordinary least squares methods reported for the same data set and in other studies, but had smaller error variances. A likelihood ratio test showed agreement between these heritability estimates and those in the literature. The heritability estimates of milk, fat, protein, lactose-mineral, solids-not-fat, and total solids yields were about 0.25; for the corresponding percentages, and for the protein to fat and solids-not-fat to fat ratios, the estimates were 0.50. Heritability estimates were 0.10 or less for the time from parturition to first breeding and for three measures of somatic cell counts. These estimates of heritability in a dairy cattle population in a subtropical environment were not different from those of populations in temperate climates.
... In those studies, higher-yielding animals were associated with more days nonpregnant and hence longer calving intervals. Some studies have reported no correlation between yield and fertility (Raheja et al., 1989; Weller, 1989). Increasing the calving interval is undesirable, particularly in a production system in which there is a high demand for pregnant or lactating heifers, as in Kenya. ...
Purebred Holstein-Friesian cows are the main exotic breed used for milk production on large, medium, and small farms in Kenya. A study was undertaken on seven large-scale farms to investigate the genetic trends for milk production and fertility traits between 1986 and 1997 and the genetic relationships between the traits. This involved 3,185 records from 1,614 cows, the daughters of 253 sires. There was a positive trend in breeding value for 305-d milk yield of 12.9 kg/ yr and a drop in calving interval of 0.9 d/yr over the 11-yr period. Bulls from the United States (U.S.) had an average total milk yield breeding value 230 kg higher than the mean of all bulls used; Canada (+121 kg), Holland (+15 kg), the United Kingdom (U.K., 0 kg), and Kenya (-71 kg) were the other major suppliers of bulls. Average breeding values of bulls for calving interval by country of origin were -1.31 (Canada), -1.27 (Holland), -0.83 (U.S.), -0.63 (Kenya), and 0.68 d (U.K.). The genetic parameters for 305-d milk yield were 0.29 (heritability), 0.05 (permanent environment effect as proportion of phenotypic variance) resulting in an estimated repeatability of 0.34. Using complete lactation data rather than 305-d milk yield resulted in similar estimates of the genetic parameters. However, when lactation length was used as a covariate heritability was reduced to 0.25 and the permanent environment effect proportion increased to 0.09. There was little genetic control of either lactation length (heritability, 0.09) or calving interval (heritability, 0.05); however, there were strong genetic correlations between first lactation milk yield, calving interval, and age at first calving.
... Genetic trend of sires of first-crop Holstein DHIA cows was 176 kg of milk per year from 1979 to 1987 (Meinert et al, 1992). Lee et al (1980) found an annual genetic trend of .75% of the phenotypic mean for milk yield, while Weller (1989) observed a genetic trend of 154 kg of milk yield per year in Israeli Holsteins. ...
A total of 248,230 first parity Northeast USDA DHIA records of Holstein cows calving from 1987 to 1994, daughters from 588 sires in 3,042 herds were used to evaluate genotype by environment interactions of mature equivalent milk yield (MEM), conception rate at first service (CRFS) and lactation mean somatic cell score (LMSCS), using a multiple trait linear model approach. Herds were classified into low and high level of management using three different criteria. High level herds had higher MEM and body weight at first calving means than low level herds, while the low level herds had higher CRFS, LMSCS, and age at first calving means than high level herds. Genetic parameters were estimated using multiple trait linear mixed models and multiple trait derivative free software (MTDFREML). For the complete data set heritabilities for MEM, LMSCS, and CRFS were estimated in .276, .103, and .015, respectively. Heritabilities and genetic and phenotypic correlations were consistent regardless of the classification criteria. For low level, heritabilities for MEM, LMSCS, and CRFS averaged .232, .101, and .020, while for high level they averaged .283, .097, and .009. For low level, genetic (and phenotypic) correlations between MEM and LMSCS, MEM and CRFS, LMSCS and CRFS averaged .247, -.407, and -.228, (-.055, -.174, and -.037), while for high level they averaged .178, -.304, and -.139, (-.089, -.171, and -.034). The genetic correlation between low and high management levels for MEM, LMSCS, and CRFS averaged .972, .972, and .949. The genetic correlation between pairs of traits were consistently lower in high than in low management groups, indicating a genotype by environment interaction. These changes are all in a positive direction, suggesting that differences of management between two levels reduces the genetic negative association between the traits considered. Given the magnitude of differences in the expected correlated responses in LMSCS and CRFS in the two levels of management, in order to achieve, in breeding programs, the same genetic goal of increasing milk yield, at the same time that reducing the rate of deterioration of CRFS, and reducing the increase of LMSCS, the relative weight of CRFS and LMSCS in selection indexes, would be smaller in well managed herds than in poor managed herds.
... However, since sires of sires are often selected among high-repeatability proven sires, selection for twinning may be practised in the sire-to-sire path. Weller (1989) found that selection based on an index including milk production and fertility could increase conception rate by 5% in 10 y, but would result in an 8% reduction in the genetic gain for economically fat-corrected milk. Using the same method, and assuming the same reduction in genetic gain for production traits, selection for twinning rate in the male pathways would result in a genetic increase of 1.2% over this time period. ...
... The heritability estimate of service per conception was very low (0.073 ± 0.068), and it was within the range of the estimates of Singh et al. (1997) in Indian Holstein population (0.06 ± 0.11), Menendez and Dempfle (1998) in Cuban Frisian crosses (0.03), Hayes et al. (1993) in Canadian Frisian crossbred population and Weller (1989) in Israelis Friesian population (0.03). However, some researchers reported higher estimates (0.18 ± 0.001 in Frisian crosses by Al-Salman, 1985 and 0.18 ± 0.05 in Shahiwal crosses by Khan et al., 1992) than that was found in the present study. ...
Heritability and genetic correlation of economic traits of Bangladesh Livestock Research Institute (BLRI) Cattle Breed-1 (BCB-1) were estimated with Residual Maximum Likelihood (REML) principle. The BCB-1 is a native cattle breed developed by BLRI through selective breeding among indigenous cattle of Bangladesh. Data asserted from performance record sheets of 500 animals maintained during 1992 to 2005 were analyzed for estimation of genetic parameters. The heritabilities were estimated with single trait animal model for age at service and age at first calving and those of single trait repeatability model for other traits. However, two traits animal models were used for estimation of genetic correlations among different traits. The model includes sex, season and year of birth, parity, generation and additive genetic merit of each individual. The estimated heritabilities were higher for lactation milk yield (LMY, 0.404) and age at first calving (AFC, 0.404) followed by moderate estimates of daily milk yield (DMY, 0.257), lactation length (LL, 0.333), peak milk yield (PMY, 0.335), milk yield per day of calving interval (MYCI, 0.227), age at first service (AFS, 0.316), calving interval (CI, 0.273), and post partum heat period (PPHP, 0.276). The genetic correlations of lactation milk yield were high with DMY (+0.797), LL (+0.797) and MYCI (+0.876), moderate with CI (+0.399), PPHP (+0.205) and DP (-0.404) and low with AFS (-0.048) and AFC (-0.025). The moderate to high heritabilities for along with high genetic correlations among most of the milk yield traits emphasized continuation of selective breeding program for maximization of genetic improvement of this breed. The information generated in the present study may also be used in planning breeding program for other indigenous cattle germplasm of the country.
... As a consequence, FSC is relatively high, leading to deceasing NSPC, especially in mid-to late lactation. However, some studies have reported no and low correlations between milk yield and fertility (Raheja et al. 1989;Weller 1989). ...
The test-day milk fat-to-protein ratio (TD-FPR) could serve as a measure of energy balance status and might be used as a criterion to improve metabolic stability and fertility through genetic selection. Therefore, genetic parameters for fertility traits, test-day milk yield (TD-MY) and TD-FPR, as well as, their relationships during different stages of lactation, were estimated on data collected from 25 968 primiparous Thai dairy crossbred cows. Gibbs sampling algorithms were implemented to obtain (co)variance components using both univariate linear and threshold animal models and bivariate linear-linear and linear-threshold animal models with random regression. Average TD-MY and TD-FPR were 12.60 and 1.15. Heritability estimates for TD-MY, TD-FPR and selected fertility traits ranged from 0.31 to 0.58, 0.17 to 0.19 and 0.02 to 0.05, respectively. Genetic correlations among TD-FPR and TD-MY, TD-FPR and fertility traits, and TD-MY and fertility traits ranged from 0.05 to -0.44, from -0.98 to 0.98 and -0.22 to 0.79, respectively. Selection for lower TD-FPR would decrease numbers of inseminations per conception and increase conception at first service and pregnancy within 90 days. In addition, cow selection based only on high milk production has strong effects to prolong days to first service, days open and calving interval.
© 2015 Japanese Society of Animal Science.
... This agrees with several studies that have found a mild but antagonistic relationship between fertility and milk yield (Abdallah and McDaniel, 2000;Campos et al., 1994), whereas some other studies have found correlations around 0 (Raheja et al., 1989). Other studies have found a slight but positive relationship between conception rate and NR with milk production (Weller, 1989;Roth et al., 1999). Genetic correlation between heat tolerance for milk yield and heat tolerance for NR90 was −0.04, indicating that the metabolic and physiological processes that areresponsible for heat tolerance for milk and for reproduction are different. ...
The genetic component in heat tolerance for nonreturn rate in Holsteins was estimated using an animal linear model augmented by a random regression on a temperature-humidity index (THI). Data consisted of 18,059 nonreturn rates at 45,60, and 90 d after insemination and 81,674 first-parity test-day milk yields from 78 herds in Florida. The THI on the day of insemination or test day was added to each record. Only first-insemination records were used. The model for nonreturn rate included the effects of herd-year-season, age, days in milk, milk yield, THI as a covariable, regular additive effect, and random regression on THI for heat-tolerance additive effect. With a single-trait model, heritability estimates for NR45, NR60, and NR90 at THI = 70 for first-lactation cows were 0.006, 0.014, and 0.053, respectively. Genetic correlation between regular NR90 and heat tolerance was -0.95. A bivariate analysis for NR90 and test-day milk production yielded a correlation between regular merit and heat tolerance for NR90 of -0.35, substantially lower than by the univariate model, indicating a bias in the univariate estimates caused by ignored selection. The regular genetic correlation between NR90 and milk yield was -0.41. Genetic correlation between heat tolerance for NR90 and heat tolerance for milk yield was -0.04, indicating the need to separate selection.
... Genetic parameters for female reproductive traits have been a subject of numerous publications in recent years (e.g., Jansen, 1986;Jansen et al., 1987;Weller, 1989;Raheja et al., 1989;Hayes et al., 1992;Weigel and Rekaya, 2000;Kadarmideen et al., 2003;Ranberg et al., 2003;Muir et al., 2004). Estimates obtained in the current study were in a good agreement with results from other projects. ...
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.
... However, since sires of sires are often selected among high-repeatability proven sires, selection for twinning may be practised in the sire-to-sire path. Weller (1989) found that selection based on an index including milk production and fertility could increase conception rate by 5% in 10 y, but would result in an 8% reduction in the genetic gain for economically fat-corrected milk. Using the same method, and assuming the same reduction in genetic gain for production traits, selection for twinning rate in the male pathways would result in a genetic increase of 1.2% over this time period. ...
Summary - Second and third parity twinning rate of Israeli Holsteins was analyzed by linear (LM) and threshold models (TM). Data were 124 553 calving records of daughters of 179 sires. Twinning rates were 4.8 and 6.9% for second and third parity, respectively. Heritabilities, as estimated by REML for the LM analysis, and the counterpart of REML for the TM analysis, were 2.2 and 10.1%. The correlation betwen LM and TM evaluations was 0.98. Both distributions of sire evaluations were positively skewed, but only the LM distribution differed significantly from normality. Heritability as estimated from the maternal grandsire effect on twinning rate, correlations between sire and maternal grandsire evaluations, intraclass correlations among half-brothers, and son-sire regressions were all consistent with the hypothesis of polygenic additive inheritance. Sire evaluations for twinning rate were economically favorably correlated with evaluations for dystocia. Breeding for twinning rate may be feasible by selection of sires with high repeatability evaluations, and will not result in significant undesirable correlated responses. cattle / twinning / threshold model / selection / additive inheritance
... It has been suggested that fertility interval traits are more influenced by management policy and that traits such as number of matings better reflect the reproductive function ( Nebel & McGilliard, 1993). For cows that did not conceive, the interpretation of a low NINS could potentially be more problematic as described by Weller (1989). However, the editing rules applied to the data in the current study ensured that low NINS was not caused by early culling. ...
The aim of this study was to estimate and compare genetic trends in Swedish Red cattle using a full multiple-trait (MT) model and trait-group-wise models for female fertility, udder health and protein yield. Field data for maiden heifers from 1989 and cows with a first and second lactation between 1990 and 2007 were included. (Co)variance components were estimated prior to prediction of breeding values. The estimated genetic trends were clearly favourable for protein yield and udder conformation, and in most cases neutral to favourable for clinical mastitis and calving to first insemination. In maiden heifers, the trends were neutral for number of inseminations per service period. Unfavourable genetic trends were estimated for number of inseminations in the first two lactations, but the trends seemed less unfavourable from evaluations within trait groups compared with when using the full MT model. Excluding maiden heifer data affected genetic trends less than using trait-group-wise analyses instead of a full MT model. Unfavourable genetic trends in functional traits may be missed unless the traits are evaluated in a MT model including traits under strong selection.
... An antagonistic correlation between female fertility and milk production has been reported in several studies over the years (Everett et al., 1966;Miller et al., 1967;Berger et al., 1981;Oltenacu et al., 1991;Dematawewa and Berger, 1998;VanRaden et al., 2004). However, the effect of selection for milk on reproduction was controversial in the beginning because some studies reported little or no relationship between yield and reproduction (Weller, 1989). Even if an antagonistic relationship between female fertility and milk yield existed, the correlated response on fertility due to selection on lactation production would not be significant (Everett et al., 1966;Miller et al., 1967;Shanks et al., 1978). ...
Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving , health, and workability have now been integrated into selection indices. Current research focuses on fitness , health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques , and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.
A longitudinal Bayesian threshold analysis of insemination events during the first 250 d after calving of first-parity Holsteins was carried out. The outcome of an insemination event was treated as a binary response of either a success (1) or a failure (0). Thus, all breeding information for a cow, including all service sires, was included, thereby allowing for a joint evaluation of male and female fertility. An edited data set of 297,823 insemination records from 151,758 first lactation cows was used. On the liability scale, the model included the systematic effects of herd-year of insemination, technician, month of insemination, and regressions on age of service sire, 3 test days in the first 100 d of lactation (early milk yield), and days in milk at insemination. The random effects in the model were the additive breeding value, the permanent effect of the cow, and the service sire effect. Posterior mean (standard deviation) of the dispersion parameters in the model were 0.034 (0.006), 0.009 (0.001), and 0.171 (0.013) for the additive, service sire, and permanent environmental variances, respectively. The residual variance was fixed at 1, as a result of the nonidentifiability of the threshold model. The posterior mean (standard deviation) of heritability was 0.028 (0.005). This point estimate of heritability is well within the range of available estimates for the trait. Thus, these estimates suggest that some genetic variation exists that can potentially be used to improve reproductive performance or at least avoid its further deterioration. The estimate of the regression coefficient on age of service sire was 0.001, indicating better fertility among older bulls. However, this result has to be interpreted with caution given the preferential use of proven bulls on well-managed cows (as opposed to problem breeders). The estimate of the regression coefficient was negative (-0.005) for early milk yield, as expected, and positive (0.003) for days in milk at insemination. This suggests that high-producing cows are less likely to conceive at the beginning of lactation.
Correlations were obtained between 18 response variables of a Jersey herd (Florida Agricultural Experiment Station, Gainesville) for 374 first lactations. Estimates were from the use of multivariate, derivative-free, restricted maximum likelihood procedures with the simplex method of partial maximization. Estimates agreed closely with those obtained previously by other methods in this and other dairy populations. All correlations between yields were high and positive; those between yields and days from parturition to first service were negative and near zero. Correlations between yields and somatic cell scores were moderate and negative; those between yields and constituent percentages in general were negative, except for the yield and percentage of the same constituent. Genetic correlations between chloride content and somatic cells and between measures of somatic cells were 1.0. Results suggest that single-trait selection for milk yield should result in correlated increases in constituent yields with slight decreases in percentage composition of constituents and somatic cell counts.
A data file containing 122,715 lactation records of Holstein cows distributed across 11,374 herd-year-season groups was analyzed to obtain (co)variance estimates for yield, fertility and cow survival. Milk, fat, and protein yields were adjusted to 305 d. Days open was truncated to 305 d, and the number of services was truncated to 9. Survival of a cow during a full lactation (305 d) was recorded as 0 (died) or 1 (alive). Variance components for the six traits were estimated using a multiple-trait animal model and the REML procedure. The model included herd-year-season, parity (three groups), age (three groups nested within parity), sex of calf (1 = male, 2 = female), and dystocia score (1 = no problem,..., 5 = extreme difficulty) as fixed effects and animal and permanent environment as random effects. Heritabilities for milk, fat, and protein yields, days open, number of services and cow survival were 0.2, 0.18, 0.18, 0.04, 0.03, and 0.002, respectively. The corresponding repeatabilities were 0.42, 0.41, 0.41, 0.12, 0.08, and 0.009, respectively. Genetic and phenotypic correlations between yield traits were high and positive, and correlations between yields and reproduction traits were high and antagonistic. Phenotypic correlations between survival and yields were about 0.1, and their genetic counterparts were slightly negative. Thus, management practices seem to keep mortality rates of high producing cows lower even though those cows have lower genetic potential for survival than do the low producers. Fertility traits showed a slightly undesirable (e.g., 0.1 to 0.3) genetic relationship with survival, but phenotypic correlations were essentially 0. For heifers, yields increased significantly with age. For cows in other parities, the significant changes with age were reduced fertility and reduced survival.
The individual animal model was used to analyze the conception index, defined as the inverse of the number of inseminations to conception, and mean lactation somatic cell scores (SCS) of Israeli Holsteins. In addition, multitrait variance components were estimated for these traits and for milk production traits. The animal model analyses included 440,558 lactation records for conception index and 224,869 SCS records collected over 10 yr. First parity heritabilities were 0.035 for conception index and 0.158 for SCS. Genetic correlations were negative between conception index and milk production traits and positive between SCS and milk production traits. Genetic correlations between first and second lactations were 0.9 for conception index and 0.7 for SCS. Phenotypic correlations were 0.08 and 0.3, respectively. Despite the low heritability for conception index, the standard deviation of the sire evaluations was 2%, and the range of evaluations was 10%. Predicted genetic trends for conception index and SCS were computed based on the current selection index of Israel. The realized genetic trend for the conception index was slightly positive, despite the predicted negative trend, and the realized genetic trend for SCS, although positive as predicted, was fourfold the predicted value. The reasons for these discrepancies are not known.
Conception rates of Israeli Holstein cows and heifers were analyzed separately by linear and threshold models. Fixed effects for both data files were insemination number, AI institute, geographical region, and calendar month. Analysis of cows also included the fixed effects of parity, calving status, and DIM at insemination. Random effects included in the models were herd-year-season, insemination technician, sire of cow, and service sire. Fixed effect solutions for heifers and cows were not similar. For cows, insemination month had the greatest effect on conception rate. Heritability of conception rate ranged from 2 to 3.5% for heifers and from 1 to 2% for cows. Correlations between corresponding threshold and linear model random effect solutions were all greater than or equal to .99. Correlations between heifer and cow analyses for sire and service sire solutions were less than .4. Analysis with an incorrect herd-year-season variance component affected only the technician solutions.
A total of 226 651 fertility records of dairy cows obtained from 1980 to 1988 was studied in order to determine the environmental and genetic factors affecting the reproductive performance of Holstein cows under Cuban conditions. Only 43.9% of the inseminated females were pregnant at first service however, for heifers this value was 63.1%. The seasonal variability was higher for heifers and for primiparous than for older lactating cows. The best performance was found from February to April, whereas during the hot and humid summer (July to September) poorer results were obtained. Age at calving or number of calvings was another important environmental source of variation: the earlier the calving the poorer is the next reproductive performance. The genetic analyses were made within calving number with the REML procedure. For heifers (226 sires, 45 575 records) the heritability and the genetic coefficient of variation were: 2.26 and 10.94%, 3.24 and 11.24%, and 3.04 and 6.19% for conception rate (CR), numbers of services per conception (SG) and conception status (CS = 1/SG); respectively. For first calving females (280 sires, 43 647 records) the results were: 1.94 and 15.93%, 3.25 and 12.80%, and 3.47 and 9.47% for CR, SG and CS, respectively. For the second and third calving, the results were poorer. For the calving interval and days open, the heritabilities were between 1.86 and 4.64%. The results of SG were selected as the best and more useful traits showing high genetic correlations (> 0.60) for the same traits in different calving number.
Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h2) was 0.012 to 0.028 and of permanent environmental variance (c2) was 0.016 to 0.032. Genetic correlations (rg) among fertility traits were generally high (>0.70). Genetic correlations of fertility with milk production traits were unfavourable (range −0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h2 and c2 were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69–0.83 for all animals in the pedigree and 0.89–0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended.
The objective of this study was to estimate genetic parameters for milk production and selected fertility traits in Irish dairy cattle. Data were derived from 74 seasonal spring-calving dairy herds with a potential cow population of 6,783 in the 1999 calving season. The average 305-day yields (kg) of milk, fat, and protein, the concentrations (g/kg) of fat and protein were 6572, 245, 222, 37.6 and 33.9, respectively. Calving to first service interval (CFS), calving to conception interval (DO) and first service to conception interval (FSCO) averaged 72, 90, and 17 days, respectively, while pregnancy rate to first service (PRFS) and number of services/cow were 0.48 and 1.78, respectively. The proportion of cows conceiving within the first 21, 42, and 63 days after start of breeding (PR21, PR42, and PR63) were 0.36, 0.57 and 0.72, respectively. (Co)variance components were estimated for the complete data set as well as a separate analysis for pedigree and non-pedigree herds within the data set. Heritability estimates, using the complete data set, for milk production traits ranged from 0.22 (±0.042) for milk yield to 0.70 (±0.049) for milk fat concentration while heritability estimates for fertility traits ranged from zero for PR21 to 0.03 (±0.017) for CFS and SBFS (start of breeding to first service interval). Heritability estimates were numerically greater than zero for all fertility traits in the pedigree herd data set with the exception of PR21. Only two fertility traits had heritability estimates for the non-pedigree herds, namely, CFS (0.03 ± 0.030), SBFS (0.03 ± 0.030); analyses for the other fertility traits failed to converge. Genetic correlations between production and fertility traits were mostly antagonistic, for example, correlations between milk yield and number of services (0.98 ± 0.35) and PRFS (-0.51 ± 0.61). Results indicate that selection for yield alone may lead to a deterioration in fertility and that future selection programmes should include some measures of reproductive performance.
Genetic and environmental effects on female fertility were analysed using the 90-day non return (NR) rate and the interval from first to last insemination (IFL). First insemination records from 706 040 cows and 345 775 heifers of the Swiss Simmental breed gathered over a 6-year period were used. Variance components for sire of females were estimated using a restricted maximum likelihood (REML) procedure. Estimated heritabilities ranged from 1.1% (90-day NR rate, heifer) to 3.8% (IFL, cow) and genetic coefficients of variation from 6.5% (90-day NR rate,heifer) to 30.2% (lFL, cow). An approximate approach was applied to derive estimates of genetic correlations among traits using estimated breeding values. The following results were found: (1) 90-day NR rate and IFL are genetically highly correlated (r(g) approximate to -0.9); (2) the genetic correlation among male and female fertility is close to zero; (3) the genetic correlation between cow and virgin heifer fertility is 0.4; and (4) female fertility and milk yield have antagonistic genetic correlations ( r(g) approximate to 0.6). Based on genetic variability of fertility traits and their high economic importance, it is concluded that fertility should be considered in the selection scheme for Swiss Simmental cattle.
Effects of composite β–κ-casein genotypes and β-lactoglobulin genotypes on age at first insemination and length of service period of 17,059 Finnish Ayrshire heifers, and on days from calving to first insemination and length of service period of 17,869 first lactation cows were estimated. A mixed linear model under an animal model was assumed. The effect of the β–κ-casein genotypes on days from calving to first insemination (DFI) was statistically significant. The difference in DFI between the rare extreme β–κ-casein genotypes A1A2BB and A1A2EE was about 19 days (0.75 phenotypic standard deviation), but the standard errors of the effects of these genotypes were large. Between the most frequent β–κ-casein genotypes the differences in DFI were negligible. The other reproduction traits studied were not affected by composite β–κ-casein genotypes or β-lactoglobulin genotypes. Based on the results presented in this study, selection based on β–κ-casein and β-lactoglobulin polymorphism should thus have no substantial impact on fertility of Finnish Ayrshire heifers and cows.
The data on 23 196 Ayrshire cows were extracted from the Finnish health register for dairy cattle to study the relationships of veterinary diagnoses of ovulatory disorder and metritis within 150 d postpartum across the first three lactations. A subset of 11 173 disease recordings was merged with information on 305 d milk yield and operational days open to study the genetic correlations between reproduction disorders, daughter fertility, and milk production. (Co)variance components were estimated using linear multitrait REML and the expectation-maximization algorithm with a sire model. The estimates of genetic correlations between different lactations were positive and from moderate to high for operational days open (0.77 to 0.93) and ovulatory disorder (0.60 to 0.94). The high genetic correlation between ovulatory disorder and operational days open (0.80) indicates that the both traits are expressions of the same trait complex. A moderately high unfavourable genetic association was found between milk yield and both reproductive disorder and operational days open. Based on the results, a genetic improvement of 500 kg in milk yield would, as a correlated response, result in an increase of 1.7 %-units, 0.9 %-units and 4.2 d in the frequency of ovulatory disorder and of metritis, and in operational days open, respectively.
Reproductive performance is an important determinant of dairy production efficiency, which has not been extensively studied in pasture-based seasonal production systems. The objectives of this study were to investigate the suitability of various fertility traits for describing the reproductive performance of dairy cows under the seasonal production conditions in New Zealand and to estimate genetic parameters for selected fertility traits. Data were derived from the first and second lactation of 66294 animals born between 1984 and 1990. Since the primary breeding objective in a seasonal production system is to have each cow in a herd conceive as soon as possible after the date selected for the start of breeding (SB), many of the parameters must be derived using SB as a reference point. Based on SB, the average intervals to first service (SBFS) were 17.5 and 17.0 days and intervals to successful service (SBCO) were 31.7 and 30.8 days for the first and second lactation, respectively, resulting in the respective intervals from first service to successful service (FSCO) of 14.2 and 13.8 days. The percentages of cows conceiving within the first 21 or 42 days (PR21 and PR42) after SB were 48.5% and 74.7% for first lactation and 50.0% and 76.5% for second lactation. Breeds differed in reproductive performance with Jersey cows being superior to Friesian cows mainly due to a shorter SBFS interval for Jersey cows. Heritability estimates obtained using data for the first or second lactation ranged from 0.01 to 0.06 except for age at calving (AC) at 0.13 and 0.12, respectively. The genetic coefficients of variation were higher for SBFS, SBCO, FSCO, PR21 and PR42 than for other traits studied. Genetic correlations between calving interval and SBFS or SBCO were high (0.92 and 0.96), and between SBCO and PR21 or PR42 were both — 1.00. Antagonistic genetic correlations existed between milk production and most fertility traits. Phenotypic correlations between milk production and fertility traits were all close to zero except for AC. It is concluded that fertility traits based on SB are appropriate for measuring reproductive performance of dairy cows under seasonal production systems. Fertility traits should be incorporated into selection programmes for dairy cows to counteract the antagonistic relationships between milk production and fertility. PR21 is a suitable selection criterion for improving reproductive performance of cows in New Zealand dairy herds.
Genetic parameters for conception rate in Holstein cattle were estimated from insemination data collected in western France in 1987–88. Data included 513020 inseminations of 250215 lactating cows. Sire, service bull, herd and cow variance components were estimated with the “tilde-hat” method. Both linear and threshold models were used and provided very similar results for the fixed effects. Conception rate was lowest in latest parities, before 60 days postpartum, in winter and on Mondays. With the linear model, the estimated heritability and repeatability of conception rate were 2 and 3.2%, respectively, and the service bull and herd components contributed 0.8 and 1.1% of the total variance, respectively. All variance components were 60% greater from the threshold model. The correlation between male and female fertility was small and slightly negative (−0.11). In spite of a low heritability, the genetic variability of female fertility was large, with a genetic coefficient of variation of 14%. The genetic correlations between conception rate at first insemination and 100-day yield traits were estimated by REML on 83 606 first lactation data. They were found to be antagonistic, with −0.60, −0.42 and −0.36 for milk, fat and protein yields, respectively, whereas the phenotypic correlations were only slightly negative (−0.02 to −0.04).
Records collected between December 1979 and June 1986 provided measures of age and weight at calving, days open, 305-d measures of milk, fat, and protein yield, milk value, feed cost, and total energy intake for 8156 Ayrshire and 80,604 Holstein cows in first lactation. Phenotypic and genetic variances and covariances were estimated from separate analyses per breed using a multiple trait mixed model that included traits of body weight at calving, energy intake, 3.5% FCM, and days open with (five-trait model) and without (four-trait model) age at calving, which was treated as a fixed effect in the four-trait model. Sixty-five Ayrshire and 410 Holstein sires were treated as random in the analyses. The resulting parameters were used to develop four-and five-trait selection indexes, which were then paired with a number of traits in a series of two-trait analyses. Heritability estimates were higher in Holsteins than in Ayrshires for all traits, especially for 3.5% FCM. Also, with the exception of days open, which had a very low heritability (.01 and .03), heritability estimates were higher when traits were adjusted for age at calving as a fixed effect. Phenotypic correlations between traits were almost identical for the two breeds, whereas genetic correlations were similar. Selection index weights were smaller in Ayrshires than corresponding weights in Holsteins, and the relative weighting of the traits was not the same. Nevertheless, in both breeds, genetic correlations between the indexes and milk production, fat percentages, and protein percentages and milk value were all very high, exceeding .936. Total energy intake, feed cost, and days open were also very positively correlated with the indexes. Weight at calving was negatively genetically correlated with FCM. The relationship between body weight and the selection indexes was even more negative.
The effect of days open and days to first breeding on cumulative calf and milk production in the current and following lactation was studied based on annualized yield in 121.627 Israeli-Holstein lactations. Optimum days open for first parity ranged from 110 for low calf value (500 kg milk) to 91 for high calf value (4000 kg milk). Optimum days open for second parity ranged from 91 for low calf value to 40 for high calf value. Expected production as a function of days to first breeding was computed as a function of probability of conception, which was varied from .4 to .6, and estrus detection, which was varied from .5 to .7. Optimum days to first breeding as a function of calf value and reproductive management ranged from 95 to 65 d for first parity and from 77 to less than 40 d for second parity. Optimum days to first breeding was higher with lower calf value and better reproductive management. Expected losses from early first breeding (40 d in milk), as compared with the optimum, ranged up to 780 kg of FCM for first parity cows, while expected losses from late first breeding (120 d in milk) ranged up to 790 kg for second parity cows.
This study was carried out to estimate the heritabilities and the genetic and phenotypic correlations between some milk production traits in Holstein cows in Ceylanpinar State Farm. A mixed-model equation was used in the study. The heritabilities and the genetic correlations were estimated by the Restricted Maximum Likelihood method (REML) for all the variables. Phenotypic correlations were estimated from measurements of the traits. Paternal half-sib correlations were used for the estimation of the heritability values. The heritabilities for the 2x305ME milk yield, the lactation length, the length of the dry period, and the calving interval were estimated to be 0.169±0.0287, 0.013±0.0205, 0.017±0.0270, 0.007±0.0240 and 0.138±0.0556, respectively. The phenotypic correlations between the lactation period and milk yield, the calving interval and the length of the dry period were 0.128, 0.006, and -0.005, respectively. The correlations between the milk yield and the calving interval and the length of the dry period were estimated to be 0.092 and 0.051, while the correlations between the length of the dry period and the calving interval was 0.621. The genetic correlations between the milk yield and the lactation length and the calving interval were 0.411 and 0.097, respectively. The genetic and phenotypic correlations for the milk yield and the age at first calving were 0.802 and 0.019, respectively. The correlations between the lactation length and the milk yield at first lactation and the age at first calving were 0.113 and -0.030, respectively. It was concluded that the use of selection methods would result in genetic improvements in the Holstein herd at Ceylanpinar State Farm.
The objective of this study was to estimate heritability (h(2)), a useful criterion, in the improvement studies which would De conducted to improve milk productivity in the Karacabey State Farm. A total of 760 cows, of which milk yield records were used in the study in different lactation period, consisted of 111 American Browns, 142 American Holsteins, 87 German Browns, 130 Swiss Browns, 83 Holland Holsteins and 207 Karacabey Browns. Milk yields were corrected according to the 2x305ME standardisation procedure, Furthermore, coefficients of relationship were calculated separately for Brown and Holstein cows using the pedigree cards of the animals whose milk yield records were utilised in the study. The heritability coefficients for milk yield according to the origin of the animals were estimated by using the Half Sib-Correlation Method. Heritability coefficients: Utilising 305ME corrected milk yields of all daughters of each sire secured, Considering 305ME corrected milk yields of at least 5 daughters of each sire, Using actual milk yields of at least 5 daughters of each sire, were estimated for three different situations. Again, heritability coefficients were calculated one by one considering the coefficients of relationship obtained from the study and those from the method itself. The animals were grouped according to origin and the heritability coefficient for each origin was estimated one by one, but the results were not found to be satisfactory. The most suitable result was reached when the breed rather than the origin was considered and in the cases where new relativity degrees obtained were used for sires having at least five daughters. Accordingly, estimated Heritability coefficient for milk yield were as follows: for Brown Swiss :0.3050 +/- 0.1182 for Holstein :0.2926 +/- 0.2562.
In this study, data relating to the milk yield of a Holstein herd on Bala State Farm was analysed for the period 1985-92. The aim of this study was to estimate the heritability of the milk yield using two-factor experiments with repeated measures on one factor. The heritability of the milk yield was estimated to be 0.36.
The heritability of common reproductive disorders was asessed in Israeli Holstein cows. Data were collected from 76,000 calvings on 102 collective farms (kibbuts) over a 36-mo period. The disorders considered were those of retained placenta, abnormal lochia, endometritis, anestrus, ovarian cysts with anestrus and ovarian cysts with nymphomania. The statistical model included fixed effects of herd-year, month of calving, duration of previous pregnancy, interaction between calving difficulty and sex of offspring, and the random effect of the sire. Herd-year effects consituted 0.68 of the explained variance of the incidence of retained placenta and approximately 0.89 of all the other disorders. Sire and calving-month effects were significant (P<0.05) for all the disorders. Heritability estimates of the disorders were 0.01 for retained placenta, abnormal lochia, and endometritis; 0.02 for anestrus; and 0.03 for all disorders. Correlations between any two disorders did not exceed 0.20. High genetic correlations were found between retained placenta and either abnormal lochia (0.90) or endometritis (0.70), while moderate genetic correlations were found among each of these and anestrus (0.30). Reproductive disorders occur as part of a complex which may be efficiently controlled by management measures. Nevertheless, breeding for resistance to reproductive disorders may also be feasible by using appropriate sires evaluated on a large number of daughters.
The present contribution is a review of earlier studies on genetic aspects of bull fertility as measured by non-return rate when used for AI. The conclusions may be summarised as follows. 1. (1) Conception rate and calving interval are determined by the fertility of the bull and the fertility of the cow jointly. One unit of genetic improvement in male fertility is therefore of equal importance to one unit of improvement in female fertility. 2. (2) The heritability of bull fertility, as measured by the non-return rates from a few hundred inseminations, is large enough to provide a basis for efficient selection. The genetic standard deviation is, however, considerably less for male than for female fertility. 3. (3) The genetic correlation between male and female fertility is slight, and the same holds true for the genetic correlation between male fertility and milk production. 4. (4) In the final selection of progeny-tested bulls, due attention should be given to the estimated breeding value of the bull with respect to male fertility as well as to female fertility.
Genetic correlations among Predicted Differences for milk yield corrected for economic value of fat content, annualized yield, yield persistency, conception rate, and culling rate were estimated. Correlations were .43 between yield persistency and annualized yield, .42 between yield persistency and conception rate, and .1 between annualized yield and conception rate. For Predicted Differences for these traits computed separately for each of first three parities, correlations between pairs were highest for annualized yield and lowest for culling rate. Regression coefficients for conception rate from cow insemination records on daily yield preceding insemination and on absolute change of yield during month of insemination were significantly negative for the first three parities. A positive pleiotropic effect for yield, yield persistency, and conception rate was suggested; therefore, progeny testing for yield persistency may improve yield and conception rate. High yields and large changes of yield during month of insemination adversely affected conception rate of cows within herds.
Milk recording, artificial insemination and computers have given the dairy cattle industry and effective combination of tools for genetic improvement. Selection theory (Robertson and Rendel, 1950) indicates that annual gains of 1.5 to 2.0% of the mean should be possible.
The dairy industry is also fortunate that one trait, milk production (used as a general term for yield of milk, fat and protein), is of primary importance. Another advantage is that no intermediate optimum for milk production is obvious--more and more seems to be profitable--in contrast to the situation for most traits of most livestock.
With these advantages for making genetic gain, evaluation of dairy cattle breeding programs would seem simple; compare gain that has occurred with theoretical gain. Most estimates of genetic gain have been for mild production records. The theme of the following pages will be to review a few recent estimates of genetic gain and to review three factors that may contribute to the failure of actual gain to equal theoretical gain. These factors are generation interval, emphasis on traits other than milk production, and weaknesses in genetic evaluations of bulls and cows.
Variance and covariance components for sire of cow and sire of insemination of fertility traits were estimated by parity using REML procedures. Subsequently direct genetic and maternal components were calculated. Heritabilities for 56-day non-return rate, conception rate (heifers, parity one to three) and days open (parity one to three) varied between 0.007 and 0.049. The heritability for age at conception in heifers was 0.192. The maternal component for days open was greater than the direct genetic component. The genetic correlations between sire of insemination and sire of cow for non-return rate changed from -0.29 in heifers to 0.59 in parity three, that for conception rate from -0.74 to 0.48. The relation between maternal and direct genetic components changed from -0.94 to 0.26 and -0.97 to 0.12 for non-return and conception rates, respectively. Changes in correlations for days open from parity one to three were smaller. The results indicated that the genetic correlation between the sire of cow components for non-return and conception rate in heifers, first parity and older cows may differ from unity.
The problem area of female fertility in dairy cattle has been discussed, especially as regards its genetic variation and correlation with production, in the light of recently published results. Furthermore, the implications for selection of the parameters found have been illuminated. It is concluded that the magnitude of the additive genetic variance in several fertility traits is considerable, despite the generally low heritability values of individual insemination results. The genetic effect of cow culling within herds for poor fertility is almost negligible, while progeny testing of bulls for daughter fertility offers valuable information for selection purposes. Several recent investigations appear to indicate antagonistic relationships between production and fertility. However, the findings are somewhat ambiguous. When unfavourable, even though not very strong, correlations do exist, detrimental effects on fertility will occur as a consequence of intense long-term selection for yield if the fertility of daughters is not considered simultaneously with production in selection programmes.
The genetic relationship between milk yield and reproductive performance was investigated in 72,187 records with breeding information from 201 California dairy herds. Traits characterizing repro- ductive performance were days to first and last breeding, days open, and number of services; their heritabilities in prima- parous cows were 4, 4, 2, and 1. Genetic correlations between reproductive per- formance and 60-day, 180-day, and 305-day fat-corrected-milk-yields were positive, indicating that higher pro- ducing cows were bred later, took longer to conceive, and required more services per conception. Genetic correlations were highest between measures of reproducitve performance and 305-day yield but were less for the 180-day and 60-day yields which were unaffected by pregnancy.
A well-known formula for expressing a covariance in terms of variances is shown to hold true for estimating components of covariance.
Nulliparous Israeli Holstein heifers were inseminated in 111 high-producing dairy herds with 9411 doses of semen from 26 proven sires of five national strains: Canada (CA), New Zealand (NZ), Sweden (SW), Israel (IS) and United States (US); 4914 calves were born and 1483 F1 daughters were milk recorded. Significant differences among strains were found for all traits analyzed. Mates of NZ sires and daughters of IS sires were most favorable for calving traits and mates of SW sires and daughters of CA sires were least favorable. NZ daughters were smallest, and CA daughters were largest and most favorable for udder conformation traits. SW daughters were least favorable for conformation traits, but had the highest conception rate. US daughters had the lowest conception rate. The ranges of strain effects for milk, fat and fat percentage were 1551 kg, 27 kg and 0.28%, respectively. IS daughters were highest for dairy character and milk and fat production, but lowest in fat percentage. NZ daughters were lowest in milk and fat production, but highest in fat percentage. The correlations between predicted differences for kg fat and kg milk and fat percentage were 0.96 and -0.85, respectively. Within-strain correlations between sire evaluations for milk in each of the countries of origin and IS were 0.84, 0.80, 0.51 and 0.01, for US, SW, CA and NZ, respectively. The results provide a basis for comparison of sire evaluations among US, CA, SW and IS.
Genetic relationships between fertility measurements for heifers and cows in Parities 1, 2 and 3 were studied. A multivariate linear model was used for analyses and genetic parameters were obtained via a REML procedure, thus accounting for selection. The measurements studied were age at first insemination and age at conception for heifers, 56-day non-return rate after first insemination, calving to first service interval and days open. Components of variance increased by parity, especially for 56-day non-return rate. Genetic correlation between age at first insemination for heifers and interval to first service for first-parity cows was 0.67, that for age at conception and days open was 0.66. Genetic correlations between interval to first service in Parities 1, 2 and 3 varied from 0.78 to 0.89, whereas relationships between days open varied from 0.68 to 1.06. Genetic correlations between non-return rates were all above unity. Culling had little effect on the parameter estimates for fertility.
Extension factors for annualized lactation yields [365 (total lactation yield)/-days between calvings] were computed by generating 747,904 partial lactations from complete lactation records of 105,379 Israeli-Holstein cows with one to three lactations. Factors included in the model were last test yield, days pregnant, days in milk, farm type, calving season, and days remaining in the lactation. Both linear and quadratic effects were assumed for the first three factors. Primiparous and multiparous cows were analyzed separately for milk, fat, and economically fat-corrected milk [.67 (milk) + 10 (fat)] yields. Adjusted coefficients of determination computed for this model were .04 higher for fat and .01 higher for milk and economically fat-corrected milk than for an alternate model in which remaining yield was predicted as a linear function of last test yield and remaining days in milk. Correlations between actual and predicted lactations for partial lactations of less than 4 mo in milk computed by the first model were .03 higher for fat but were nearly identical to those computed by the second model for milk. Although last test yields was the most important factor in predicting annualized yields, inclusion of other factors increased accuracy of annualized fat yield prediction.
Length of open period affected annualized yield [(total lactation yield/calving interval) 365]. Yield was maximum with more days open for low, as opposed to high, peak production and for primiparous, as opposed to multiparous, cows. Interactions with days open were not found for mean herd production or cow production relative to the herd mean. Number of days open for maximum yield was similar for milk, fat, and economically fat-corrected milk [.67 kg milk + 10 kg fat]. Correction factors were derived by smoothed least square means of days open classes. Additive adjustment factors were more appropriate than multiplicative adjustment factors. Records adjusted for days open were not able to predict the following lactation yield significantly better than unadjusted records. Cumulative yield of current and following annualized lactations, including the contribution of the calf expressed in units of milk production, was greatest at 117 and 98 days open for primiparous and multiparous cows. For cows with high peak production maximum yield was with 12 to 14 fewer days open than for cows with moderate peak. Conception prior to 2 mo postpartum had an adverse effect on cumulative yield.
Genetic correlations of heifer fertility and first-parity yield usually were negative and opposite in sign from genetic correlations of first-parity fertility and yield. Most estimates of genetic correlation between heifer and first-parity fertility were not significantly different from zero. Increasing yield may improve genetic potential for fertility, but stress of increased yield may overcome genetic potential for improved fertility. Days open and 305-day yield for first parity were considered with index selection; sires were evaluated on daughter performance. Days open had a small influence on the selection index; genetic gains in days open for first parity were largely offset by correlated losses in service period for heifers. Restricted index selection, holding days open constant, required considerable economic importance of days open.
Measures of yield and fertility were obtained from breeding receipts of artificial insemination and records of test-day yield. Estimates of heritability were by Henderson Method 3, maximum likelihood, and restricted maximum likelihood. Heritabilities for measures of yield varied, but most were within the range of earlier estimates. Measures of fertility had heritabilities from 0 to .03. Alternative upper bounds were placed on days open, number of services, and service period, and always the measure with the lesser bound had higher heritability for first parity. Measures of yield for early stages of lactation had slight positive phenotypic correlations with fertility whereas those for measures of cumulative yield later in lactation increased in relation to effect of gestation. Genetic correlations of first-parity yield and most measures of fertility were positive and less influenced by stage of lactation than phenotypic correlations. Antagonism moderated for second parity. Most genetic correlations were not significantly different from zero for third parity. Considerable genetic antagonism of yield and fertility may be of limited consequence because estimates of genetic variance of fertility were near zero.
First lactations from a total of 5802 cows in the North Carolina Institutional Breeding project from 1950 to 1980 were used. Heritabilities from paternal half-sisters were .05 for days open, .05 for age at first calving, .27 for lactation milk yield, and .29 for fat yield. Corresponding estimates from regressions of cow on dam were .13 for days open, .06 for age at first calving, .35 for milk yield, and .33 for fat yield. Genetic correlations between yields and days open from various methods of estimation and editings of the data were all antagonistic and ranged from .35 to .60. Genetic correlations of yield and age at first calving were favorable, ranging from -.10 to -.36. Heritabilities for days open and genetic antagonism between days open and yield were greater for cows calving prior to the hot summer months than for cows calving in the fall. Heritabilities and variance of sires increased for days open and yield traits from the 1950's to 1980. For records from 1970 to 1980, heritability from paternal half-sisters of days open was .12. Genetic increase of 1000 kg milk would result in 5 to 10 additional days open.