Biomedical subjects

I Misztal

Publications and source records attributed to I Misztal.

At least 37 records · Page 2Linked to original sources

PubMed2004

Threshold-linear analysis of measures of fertility in artificial insemination data and days to calving in beef cattle.

Mating and calving records for 47,533 first-calf heifers in Australian Angus herds were used to examine the relationship between days to calving (DC) and two measures of fertility in AI data: 1) calving to first insemination (CFI) and 2) calving success (CS). Calving to first insemination and calving success were defined as binary traits. A threshold-linear Bayesian model was employed for both analyses: 1) DC and CFI and 2) DC and CS. Posterior means (SD) of additive covariance and corresponding genetic correlation between the DC and CFI were -0.62 d (0.19 d) and -0.66 (0.12), respectively. The corresponding point estimates between the DC and CS were -0.70 d (0.14 d) and -0.73 (0.06), respectively. These genetic correlations indicate a strong, negative relationship between DC and both measures of fertility in AI data. Selecting for animals with shorter DC intervals genetically will lead to correlated increases in both CS and CFI. Posterior means (SD) for additive and residual variance and heritability for DC for the DC-CFI analysis were 23.5 d2 (4.1 d2), 363.2 d2 (4.8 d2), and 0.06 (0.01), respectively. The corresponding parameter estimates for the DC-CS analysis were very similar. Posterior means (SD) for additive, herd-year and service sire variance and heritability for CFI were 0.04 (0.01), 0.06 (0.06), 0.14 (0.16), and 0.03 (0.01), respectively. Posterior means (SD) for additive, herd-year, and service sire variance and heritability for CS were 0.04 (0.01), 0.07 (0.07), 0.14 (0.16), and 0.03 (0.01), respectively. The similarity of the parameter estimates for CFI and CS suggest that either trait could be used as a measure of fertility in AI data. However, the definition of CFI allows the identification of animals that not only record a calving event, but calve to their first insemination, and the value of this trait would be even greater in a more complete dataset than that used in this study. The magnitude of the correlations between DC and CS-CFI suggest that it may be possible to use a multitrait approach in the evaluation of AI and natural service data, and to report one genetic value that could be used for selection purposes.

Animals↗

PubMed2004

Constructing covariance functions for random regression models for growth in Gelbvieh beef cattle.

Genetic parameters for a random regression model of growth in Gelbvieh beef cattle were constructed using existing estimates. Information for variances along ages was provided by parameters used for routine Gelbvieh multiple-trait evaluation, and information on correlations among different ages was provided by random regression model estimates from literature studies involving Nellore cattle. Both sources of information were combined into multiple-trait estimates; corrected for continuity, smoothness, and general agreement with literature estimates; and extrapolated to 730 d. Covariance functions using standardized Legendre polynomials were fit for the following effects: additive genetic (direct and maternal), and animal and maternal permanent environment. Residual variances at different ages were fitted using linear splines with three knots. Fit was by least squares. The order of polynomials was varied from third to sixth. Increasing the fit beyond cubic provided small improvements in R2 and increased the number of small eigenvalues of covariance matrices, especially for the additive effect. Parameters for a random regression model in beef cattle can be constructed with negligible artifacts from literature estimates. Formulas can easily be modified for other types of polynomials and splines.

Algorithms↗

PubMed2004

Genetic correlations among production, body size, udder, and productive life traits over time in Holsteins.

Genetic correlations among milk, fat, and protein yields; body size composite (BSC); udder composite (UDC); and productive life (PL) in Holsteins were investigated over time. The data set contained 25,280 records of cows born in Wisconsin between 1979 and 1993. The multiple trait random regression (MT-RR) animal model included registration status, herd-year, age group, and stage of lactation as fixed effects; additive genetic effects with random regressions (RR) on year of birth using the first-order Legendre polynomial; and residual effects. Heterogeneous residual variances were considered in the model. Estimates of variance components and genetic correlations among traits from MT-RR were compared with those estimated with a multiple trait interval (MT-I) model, which assumed that every 3-yr interval was a separate trait and included the same effects as in the MT-RR model except for the RR. Genetic correlations estimated with MT-RR and MT-I models over time among all traits were compared with correlations among breeding values predicted with the single trait (ST) model without RR. Correlations among breeding values predicted with MT-RR, ST, and MT models were also calculated. Additive genetic and residual variances for all traits except PL increased over time; those for PL were constant. As a result, heritability estimates had no significant changes during the 15 yr. Genetic correlations of PL with milk, fat, protein, and BSC declined to zero or negative; those with UDC remained positive. Correlations among breeding values predicted with ST, MT, and MT-RR models were relatively high for all traits except PL. Genetic correlations between PL and other traits varied over time, with some correlations changing sign. For accurate indirect prediction of PL from other traits, the genetic correlations among the traits need to be re-estimated periodically.

Animals↗

PubMed2004

Undesired phenotypic and genetic trend for stillbirth in Danish Holsteins.

The primary aim of this study was to evaluate the phenotypic and genetic trends for stillbirth in Danish Holsteins. Trends of calving difficulty and calf size were also evaluated. The second aim was to compare predicted transmitting abilities (PTA) of sires for stillbirth using a linear and a threshold model. Direct and maternal genetic effects were modeled by fitting correlated additive genetic effects of the sire and the maternal grandsire (MGS). For both the calf and the dam, covariates of breed proportions of Holstein-Friesian (HF) and the heterozygosity between HF and the original Danish Black and White (ODBW) were included. Records from 1.8 million first-calving Danish Holstein cows calving from 1985 to 2002 were used. In this period, the overall frequency of stillbirth increased from 0.071 to 0.090. An unfavorable genetic trend of stillbirth was found for both the direct and maternal effect. The background for the genetic trends was an intense use of HF sires as sires of sons, which increased the proportion of HF genes to 94% in the Danish Holstein calves born in 2002. The effect of the imported HF genes was higher direct effects of calf size, calving difficulty, and stillbirth compared with the ODBW genes. The maternal effect of stillbirth was poorer for HF than for ODBW even though HF had a better maternal calving performance than ODBW. The threshold and the linear models showed almost similar predictions of transmitting abilities of sires.

Animals↗

PubMed2004

Genetic components of days open under heat stress.

A reaction norm approach was used to estimate the genetic parameters of days open (DO) with a model that accounted for heat stress. Data included DO records for Georgia, Tennessee, and North Carolina in the Southeastern United States. A fixed effect model included herd-year, month of calving (MOC), age of cow, and a regression on 305-d milk yield. The reaction norm model additionally included the effect of animal with random regression on a heat stress index (HI), calculated as the standardized solutions to MOC derived from the fixed effect model; the residual variance was assumed to be a function of the HI. The shape of the distribution of the HI was close to a sinusoidal function with the highest value in March/April and the lowest value in September. Genetic and residual variances and heritabilities were highest for spring calvings and lowest for fall calvings. The variance associated with the random regression of the highest level of HI was 33% of the genetic variance of the regular animal genetic effect. Genetic correlation between these effects was 0.67. As a validation, DO data were grouped into 4 seasons of calving and treated as different traits. A 4-trait mixed linear model that included the fixed effects listed above except MOC, was used to analyze the grouped data. In general, the estimates of genetic and residual variances of the multiple trait analyses followed those of the reaction norm model. Genetic correlations of spring with summer, and fall with winter were both 0.90. Genetic correlations between spring/summer and fall/winter were around 0.80. The reaction norm model for DO allows inexpensive genetic evaluation of fertility under heat stress. Results of such an evaluation may strongly depend on editing criteria and model specifications.

Analysis of Variance↗

PubMed2004

Genetic parameters for days open and pregnancy rates in US Holsteins using different editing criteria.

The influence of various editing criteria for days open (DO) records on genetic parameter estimates of DO and pregnancy rates (PR) in US Holsteins was investigated. Data included first parity 305-d milk yield and DO records from 8 states: Georgia (GA), Florida (FL), North Carolina (NC), Texas (TX), Arizona (AZ), California (CA), New York (NY), and Wisconsin (WI). The pregnancy rate was computed as 1/[(DO - VWP)/HI + 1)], where VWP was the approximate voluntary waiting period and HI was the heat interval set as 21 d. The upper limit for PR was set to 1.0. A bivariate animal model for DO (or PR) and 305-d milk yield was fit separately for each state. The model included fixed effects of herd-year, month of calving, and age of cow, as well as random animal and residual effects. In separate analyses, maximum DO records were limited to 150, 200, 250, 300, and 365 d. Analyses for PR used values of 50, 80, and 120 d for the VWP. Genetic and residual variances for DO were strongly dependent on the upper limit; both variances were 8 times larger as the upper bound increased from 150 to 365 d. Estimates of heritability for DO varied between 0.03 and 0.06. There was a 30% increase in the heritability estimate as the upper limit increased from 150 to 250 d for FL and NC, and small or no increases for the other states. The increase of the upper limit from 250 to 365 d resulted in little change. The genetic correlation between milk and DO was the highest for FL (0.6) and the lowest for GA (0.12 to 0.23). For PR with VWP=50, the heritability was higher than the corresponding estimate for DO in GA, equal to that in AZ, and lower in the remaining states. Heritabilities of PR also varied by the length of VWP; highest heritabilities were obtained at VWP=50 d for GA and AZ; at VWP=80 d for NY and WI; at VWP=120 d for FL, NC, and CA. Increase of genetic variation for records of DO < 250 d was small. Days open and PR are strongly influenced by differences in management protocols among states.

Animal Husbandry↗

PubMed2003

Analyses of growth curves of nellore cattle by multiple-trait and random regression models.

The purpose of this study was to compare estimates of genetic parameters for sequential growth of beef cattle using two models and two data sets. Growth curves of Nellore cattle were analyzed using body weights measured at ages 1 (birth weight) to 733 d. Two data samples were created, one with 71,867 records sampled from all herds (MISS), and the other with 74,601 records sampled from herds with no missing traits (NMISS). Records preadjusted to a fixed age were analyzed by a multiple-trait model (MTM), which included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Analyses were by REML, with five traits at a time. The random regression model (RRM) included the effects of age of animal, contemporary group, age of dam class, additive direct, additive maternal, permanent environment, and maternal permanent environment. All effects were modeled as cubic Legendre polynomials. These analyses were also by REML. Shapes of estimates of variances by MTM were mostly similar for both data sets for all except late ages, where estimates for MISS were less regular, and for birth weight with MISS. Genetic correlations among ages for the direct and maternal effects were less smooth with MISS. Genetic correlations between direct and maternal effects were more negative for NMISS, where few sires were maternal grandsires. Parameter estimates with RRM were similar to MTM cept that estimates of variances showed more artifacts for MISS; the estimates of additive direct-maternal correlations were more negative with both data sets and approached -1.0 for some ages with NMISS. When parameters of a growth model obtained by used for genetic evaluation, these parameters should be examined for consistency with parameters from MTM and prior information, and adjustments may be required to eliminate artifacts.

Age Factors↗

PubMed2003

Genetic evaluation of growth in nellore cattle by multiple-trait and random regression models.

The objective of this study was to identify issues in genetic evaluation of beef cattle for growth by a random regression model (RRM). Genetic evaluation data included 2,946,847 records of up to nine sequential weights of 812,393 Nellore cattle measured at ages ranging from birth to 733 d. Models considered were a five-trait multiple-trait model (MTM) and a cubic RRM. The MTM included the effects of contemporary group, age of dam class, additive direct, additive maternal, and maternal permanent environment. Both additive effects were assumed correlated. The RRM included the same effects as MTM, with the addition of permanent and random error effects. The purpose of the random error effect, which was in addition to a residual effect with constant variance, was to model heterogeneous residual variances. All effects in RRM were modeled as cubic Legendre polynomials. Expected progeny differences (EPD) were obtained iteratively using a preconditioned conjugate gradient algorithm. Numerically accurate solutions with RRM were not obtained until the random regressions were orthogonalized. Computing requirements of RRM were reduced by more than 50%, without affecting the accuracy by removing regressions corresponding to very low eigen-values and by replacing the random error effects with weights. Afterward, the correlations between EPD from RRM and from MTM for EPD on selected weights were between 0.84 and 0.89. For sires with at least 50 progeny, these correlations increased to 0.92 to 0.97. Low correlations were caused by differences in parameters. The RRM applied to growth i s prone to numerical problems. Estimates of EPD with RRM may be more accurate than those with MTM only if accurate parameters are applied.

Age Factors↗

PubMed2003

Calving ease (Co)variance components for a sire-maternal grandsire threshold model.

Variance components for a sire-maternal grandsire (MGS) threshold model were estimated from subsets of the US calving ease (CE) database, which includes over 10 million calving records with CE scored 1 (no problem) to 5 (extreme difficulty). Selected records included sire and MGS among the 2601 most frequently appearing bulls. The data were further restricted by requiring at least 20 records in each herd year. Five mutually exclusive sample datasets of approximately 200,000 records each were created based on herd code. The model included random herd-year, sire, MGS, and residual effects and fixed year-season, parity-sex, and birth year of sire and MGS effects. Fewer than 50 iterations were required to reach convergence. The (co)variance component estimates from the five replicates were quite similar. The set of estimates (0.438, herd-year; 0.022, sire; 0.016, MGS; 0.009, sire-MGS) that yielded among the highest heritabilities (0.086, direct; 0.048, maternal) and a correlation of direct and maternal effects near the mean (-0.12) was selected for use in the implementation of a sire-MGS model for CE.

Analysis of Variance↗

PubMed2003

Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States.

The objective of this study was to add a maternal grandsire (MGS) effect to the existing sire model for national calving ease genetic evaluations. The Animal Improvement Programs Laboratory (AIPL) of USDA assumed responsibility for conducting the national genetic evaluation for calving ease and maintaining the associated database in 1999. Existing evaluations used a sire threshold model. Adding an MGS effect to the model was expected to improve accuracy by partially accounting for merit of mates and differences in maternal ability of the dams. Dystocia data were migrated to a relational database integrated with the AIPL production database. This database design allowed more rigorous data edits by comparison with the production data and improved MGS identification (ID) rate by utilizing pedigrees from the production records. Integration of dystocia data with production data increased MGS ID rate from 58 to 73%. In addition, nearly 200,000 duplicate records were identified using the new edit system. Sire and sire-MGS models were compared using over 10 million observations available for the August 2002 national genetic evaluation. The sire model included herd-year, season, sex of calf, parity of dam, birth year group of sire, and sire. For the sire-MGS model, MGS and birth year group of MGS were added, year-seasons rather than seasons were used, and sex of calf and parity of dam were combined into a single interaction effect. Herd-year, sire, and MGS were random effects. Variance components used for the sire model were those previously used in the national evaluation and for the sire-MGS model were estimated in a separate study. Correlations between predicted genetic merits for service sire calving ease from the two models was 85%, indicating general agreement, but with some significant differences in evaluations. A sire-MGS model was implemented in August 2002 for the national calving ease genetic evaluation system.

Animals↗

PubMed2003

Seasonality of days open in US Holsteins.

The objectives of this study were to establish a pattern for the seasonality of days open (DO) by state and region within the United States and to present statistics on regional trends for DO. Data included 8,676,915 records on DO for Holsteins from 1997 to 2002 covering all regions of the United States. Fixed effects in the model included herd, parity, milk-class, state x month of calving (MOC), year of calving x MOC, and parity x MOC. Least squares means of DO were highest for calvings in March and lowest for calvings in September. The highest mean DO of 155 d was recorded in the Southeast, while the mean DO for the Midwest, Northeast, Northwest, and Southwest were 142, 141, 140, and 137 d, respectively. Variation in monthly averages of DO was highest in Southeast with a range of 51 d, and less than 25 d in all the other regions. Seasonality of calving was defined as the ratio of the fewest to the most calvings in months. The SOC was > or = 60% in Southeast and < or = 23% in the other regions. Selected states: Texas, Oklahoma, and Arizona in the Southwest and Missouri, Kansas, and Kentucky in the Midwest showed patterns of variation in monthly averages and seasonality of calving similar to those of Southeast. Distributions of DO were bimodal for some months of calving due to postponed breeding during the hot season or depressed fertility as a result of thermal stress; the second mode at > 200 d was highest in the Southeast but also could be observed in Texas, Wisconsin, and California. High level of heat stress for DO exists in the Southeast and in selected states of the Midwest and the Southwest; these regions contribute less than 10% of national records. A methodology for analyzing DO especially under heat stress needs to consider effects of intentionally delayed breeding--by using a model that accounts for bimodality, for example.

Animals↗

PubMed2002

Joint evaluation of purebreds and crossbreds in swine.

Data from two purebred swine lines A (n = 6,022) and B (n = 24,170), and their reciprocal, cross C (n = 6,135), were used to examine gains in reliability of combined purebred and crossbred evaluation over conventional within-line evaluations using crossbred and pureline models. Random effects in the pureline model included additive, parental dominance, and litter. In the crossbred model, effects were as in the pureline model except traits of each line were treated as separate traits and two additive effects were present. The approximate model was the same as the pureline except it was used for all lines disregarding breed differences. The traits in the evaluation were lifetime daily gain (LDG) and backfat. When separate line evaluations were replaced by evaluations with crossbreds, mean reliabilities of predicted breeding values increased by 2 to 9% for purebreds and by 21 to 72% for crossbreds. Rank correlations between these breeding values were > 0.99 for purebreds but 0.85 to 0.87 for crossbreds. Rank correlations between predicted breeding values obtained from crossbred and approximate models were 0.98 to 0.99 for purebreds and 0.96 to 0.98 for crossbreds. When the number of crossbreds was small in comparison to purebreds, the increase in reliability by using the crossbred data and the crossbred model as opposed to purebred models was small for purebreds but large for crossbreds. The approximate model provided very similar rankings to the crossbred model for purebreds but rankings were less consistent for crossbreds.

Animals↗

PubMed2002

Analysis of age-specific predicted transmitting abilities for final scores in Holsteins with a random regression model.

Conformation final scores obtained by the Holstein Association were used in this study. Five subsets were sampled from the original complete data, which contained about 7 million records, and (co)variance components for additive genetic, permanent environmental, and residual effects were estimated with a multiple-trait (MT) model at different ages of cows and with a random regression model. Transmitting abilities were predicted with the random-regression (RR) model and with the repeatability model for the national evaluation, using the entire data set. The RR model included fixed and random regressions on age at classification for additive genetic and permanent environmental effects. Additive genetic and residual variances estimated with the MT model increased with aging. Genetic correlations between age groups decreased with their distance. Heritability and repeatability estimates with the RR model were 0.27 and 0.88 on average, increasing with cow's age. Correlations between transmitting abilities predicted with the RR model at various ages and with the repeatability model were in the range of 0.89 to 0.99. In the 1980s, predicted transmitting abilities (PTA) of sires increased with their daughters' age, but in 1991 and 1995, the PTA decreased. In general, sires whose daughters were evaluated at mature ages tended to have higher PTA. For sires and cows, genetic trends estimated from the repeatability model and from the RR model were similar. The low genetic trend of cows at 60 mo for recent years was due to many grade cows that had only single records and little pedigree information.

Aging↗

PubMed2002

Studies on genetics of heat tolerance in dairy cattle with reduced weather information via cluster analysis.

The objective of this study was to explore the possibility of reducing the number of weather stations for studies on genetics of heat tolerance in dairy cattle. The similarity of information from 21 Georgia weather stations was analyzed by cluster analysis. Two major clusters have been found, separating Georgia along the NE and SW line. One weather station was selected for each of the clusters based on the minimal distance to all the remaining weather stations and on completeness of the weather information. The production dataset consisted of 114,751 first-parity test-day records for milk on 14,297 Holsteins from 120 herds in Georgia. Analyses using a model for daily milk yield with temperature-humidity index classes and several other fixed effects showed no increase in error sum of squares when using only two weather stations. The threshold of heat stress was different for each of the two regions but the rate of decline after the threshold was similar. After accounting for different thresholds, the genetic component of heat tolerance for milk was higher with the two-station model. Genetic studies on or evaluation for heat tolerance based on information from a few carefully selected weather stations can be as accurate as those based on information from numerous such stations.

Animals↗

PubMed2002

Effect of heat stress on nonreturn rate in Holstein cows: genetic analyses.

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.

Animals↗

PubMed2002

Effect of heat stress on nonreturn rate in Holsteins: fixed-model analyses.

The objective of this study was to examine the relationship between reproductive traits and heat stress. Nonreturn rate at 45 d (NR45) was analyzed in a fixed-effect model that included the temperature-humidity index (THI) from a nearby weather station as a measurement of heat stress. Data consisted of 150,200 first inseminations at first and later parities of 110,860 Holstein cows from 550 herds in Georgia, Tennessee, and Florida with weather information from 16 weather stations. THI on the day of the insemination, 2 d prior, 5 d prior, 5, 10, 20, and 30 d after insemination were studied as independent variables. The THI on the day of insemination showed the highest effect on NR45, followed by 2 d prior, 5 d prior, and 5 d after insemination, but no relationship was found with THI at 10, 20, and 30 d after insemination. NR45 showed a decrease of 0.005 per unit increase in THI on the day of insemination for THI >68. First and later parities presented similar thresholds but responded differently to an increase in THI, with NR45 being significantly lower and more susceptible to increases of THI in cows in their first parity than in later parities (0.008 vs. 0.005 decrease). Threshold for sensitivity to heat stress changed with the states, with Florida, Georgia, and Tennessee having thresholds of 70, 70, and 66, respectively. The decrease in NR45 per unit increase of THI was 0.007, 0.005, and 0.006 for Florida, Georgia, and Tennessee, respectively. With respect to only the Florida data, the final fixed-effect model used was NR45 = herd(year) + month(year) + month(year) + age(parity) + days in milk + 100d milk + THI + error. Animals with more than 150 d in milk (DIM) had a 0.16 lower NR45 than animals with less than 60 DIM at insemination. Lower milk-producing animals showed 0.08 higher NR45 than higher-producing animals. A difference of 0.10 in NR45 was observed between THI lower than 70 and THI 84. This variation in NR45 caused by THI changes is sufficient to merit further studies to examine genetic components of heat tolerance for this trait.

Animals↗

PubMed2001

The empirical bias of estimates by restricted maximum likelihood, Bayesian method, and method R under selection for additive, maternal, and dominance models.

Bayesian analysis via Gibbs sampling, restricted maximum likelihood (REML), and Method R were used to estimate variance components for several models of simulated data. Four simulated data sets that included direct genetic effects and different combinations of maternal, permanent environmental, and dominance effects were used. Parents were selected randomly, on phenotype across or within contemporary groups, or on BLUP of genetic value. Estimates by Bayesian analysis and REML were always empirically unbiased in large data sets. Estimates by Method R were biased only with phenotypic selection across contemporary groups; estimates of the additive variance were biased upward, and all the other estimates were biased downward. No empirical bias was observed for Method R under selection within contemporary groups or in data without contemporary group effects. The bias of Method R estimates in small data sets was evaluated using a simple direct additive model. Method R gave biased estimates in small data sets in all types of selection except BLUP. In populations where the selection is based on BLUP of genetic value or where phenotypic selection is practiced mostly within contemporary groups, estimates by Method R are likely to be unbiased. In this case, Method R is an alternative to single-trait REML and Bayesian analysis for analyses of large data sets when the other methods are too expensive to apply.

Animals↗

PubMed2001

Estimation of additive and nonadditive genetic variances in Hereford, Gelbvieh, and Charolais by Method R.

Parameters for direct and maternal dominance were estimated in models that included non-additive genetic effects. The analyses used weaning weight records adjusted for age of dam from populations of Canadian Hereford (n = 467,814), American Gelbvieh (n = 501,552), and American Charolais (n = 314,552). Method R estimates of direct additive genetic, maternal additive genetic, permanent maternal environment, direct dominance, and maternal dominance variances as a proportion of the total variance were 23, 12, 13, 19, and 14% in Hereford; 27, 7, 10, 18, and 2% in Gelbvieh; and 34, 15, 15, 23, and 2% in Charolais. The correlations between direct and maternal additive genetic effects were -0.30, -0.23, and -0.47 in Hereford, Gelbvieh, and Charolais, respectively. The correlations between direct and maternal dominance were -0.38, -0.02, and -0.04 in Hereford, Gelbvieh, and Charolais, respectively. Estimates of inbreeding depression were -0.20, -0.18, and -0.13 kg per 1% of inbreeding for Hereford, Gelbvieh, and Charolais, respectively. Estimates of the maternal inbreeding depression were -0.01, -0.02, and -0.02 kg, respectively. The high ratio of direct dominance to additive genetic variances provided some evidence that direct dominance effects should be considered in beef cattle evaluation. However, maternal dominance effects seemed to be important only for Hereford cattle.

Animals↗