Fertility traits in spring-calving Aberdeen Angus cattle. 2. Model comparison

The aim of this study was to investigate the possible superiority of a threshold-linear (TL) approach for calving day (CD) and calving success (CS) analysis in beef cattle over 2 multiple-trait (MT), censored models, considering CD at the first 3 calving opportunities. The CD observations on animals that failed to calve in the latter models were defined as cows being assigned a penalty value of 21 d beyond the last observed CD record within contemporary group (PEN model) or censored CD values that were randomly obtained from a truncated normal distribution (CEN-model). In the TL model, CD records were treated as missing if a cow failed to calve, and parameters were estimated in a TL analysis including CS traits (TLMISS-model). The models included the effects of contemporary group (herd x year of calving x mating management), age at calving, physiological status at mating (lactating or nonlactating cow), animal additive genetic effects, and residual. Field data included 6,763 calving records obtained from first, second, and third parities of 3,442 spring-calving Uruguayan Aberdeen Angus cows. Models were contrasted using a data splitting technique, analyzing correlations between predicted breeding values (PBV) for each pair of subsamples, by rank correlations between PBV obtained with the different models, and by inspecting percentage of sires selected in common using the different approaches at 10 and 25% hypothetical percentages of animals selected. Breeding value correlations of CD between the subsamples for the TLMISS approach were greater (0.67 to 0.68) than correlations for the censored MT models (0.49 to 0.54). Average correlations between PBV of CD in 1 subsample obtained by CEN (PEN, TLMISS) and PBV of CS in the other subsample were -0.53 (-0.55, -0.60) in the first calving opportunity (CO), -0.54 (-0.58, -0.63) in the second CO, and -0.50 (-0.49, -0.58) in the third CO. Rank correlations between PBV for CD in PEN and CEN were high (0.93 to 0.97), but correlations of either method with PBV of CD in TLMISS ranged from 0.50 to 0.71. Common identification of bulls for the top 10% of sires (25% of sires), when selected with PEN/CEN models or the TLMISS model, varied between 50 (44%) and 60 (52%). The use of the TL animal model for genetic evaluation seems attractive for genetic evaluation of fertility traits in beef cattle.     

Estimation of genetic parameters for milk and fertility traits within and between low,medium and high dairy production systems in Kenya to account for genotype-by-environment interaction

Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305-day milk yield using the K-means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype-by-environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305-day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305-day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.     

Days to calving in artificially inseminated beef cows: Comparison of potential traits

Four fertility traits were compared for artificially inseminated (AI) beef cows: A) for cows that calved to the AI sire (from either the initial or follow-up inseminations that season), the number days from initial AI to calving; B) for cows calving either by AI or to a backup bull, the number days from initial AI to calving; C) As trait B for cows that calved, otherwise the maximum of trait B for the contemporary group plus a penalty of 21 days; D) Define the ‘start date’ for a contemporary group as the date the first cow in the group was AI'd. For cows that calved, trait D was the number of days from the ‘start date’ to calving, otherwise the maximum of trait D for cows in the group that calved plus a penalty of 21 days.The vast majority of cows received only one insemination in a season, so trait A resembled gestation length and had estimated heritability of 12%. Traits B, C and D had estimated heritabilities of 3.2%, 3.5% and 5.2% respectively; estimated genetic correlations of traits A–D with naturally mated days to calving were 0.48, 0.60, 0.80 and 0.74 respectively. Trait D is therefore the recommended female fertility trait for AI cows. It has a similar frequency distribution to days to calving from natural mating and should be included in a joint analysis with days to calving of naturally mated cows.     

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.     

Genetic analysis of days open in beef cattle

The aim of this work was to analyse the genetic parameters affecting days open (DO) in beef cattle to evaluate its potential as criterion of selection. The present study characterises DO as a trait with considerable genetic variability, relative to that usually found for reproduction traits, especially for heifers and second calving cows. The estimates of heritability for the trait ranged from 0.091 for cows with 10 or more calvings to 0.197 for second calving cows. The genetic correlations estimated for DO in different parities are situated between 0.9 and 1, showing that the genes affecting the trait are substantially the same across parities of the dam. A substantial permanent environment (around 9%) seems to affect DO performance. Permanent environmental factors seem to be especially important in younger cows. Genetic correlation between DO and calving interval was positive and very high (1.0), while those between DO and gestation length and calving date were negative from low to moderate (−0.089 and −0.308, respectively). DO can be used in improvement programs of beef cattle as an early indicator of reproductive performance of the cow.     

Estimation of genetic and phenotypic relationships between age at first calving and productive performance in Iranian Holsteins

Calving records from the Animal Breeding Center of Iran collected from January 1990 to December 2007 and comprising 207,106 first calving events of Holsteins from 2,506 herds were analysed using univariate and bivariate linear sire models to estimate heritabilities and genetic correlations between age at first calving (AFC) and productive performance. Average AFC was 26.48 months in this study. The peak in the frequency distribution of AFC clearly exists coinciding with cows calving for the first time at approximately 25 months of age. Heritability estimate for AFC was 0.34 which was greater than the corresponding values for productive traits. The heritability estimates were low to medium for productive traits which ranged from 0.17 to 0.26 for cows in their first calvings. Except for fat and protein percentages of milk, phenotypic and genetic correlations between AFC and productive performance traits were low to moderately negative. Range of genetic correlations between productive traits was −0.53 to 0.99. Reduction of age at first calving appeared to have a negative effect on first lactation protein and fat percentages; however, it had positive effects on milk yield, fat yield, protein yield and their mature equivalents. It seems that reducing age at first calving to 24–25 months is probably more profitable than reducing age at first calving to an earlier time in Iranian conditions.     

Udder health and female fertility traits are favourably correlated and support each other in multi-trait evaluations

Genetic parameters were estimated for protein yield (PY), clinical mastitis (CM), somatic cell score, number of inseminations (NI) and days from calving to first insemination (CFI) in first‐parity Swedish Red cows by series of tri‐variate linear animal models. The heritability of PY was moderate (0.34 ± 0.004), and the heritabilities of the functional traits were all low (0.014 ± 0.001–0.14 ± 0.004). The genetic correlation between CM and CFI (0.38 ± 0.05) was stronger than the correlation between CM and NI (0.05 ± 0.06), perhaps because CM and CFI usually are observed in early lactation when the cow is likely to be in negative energy balance, whereas NI generally is recorded when the cow is not in negative energy balance any more. The genetic correlation between NI and CFI was very close to zero (?0.002 ± 0.05), indicating that these two fertility traits have different genetic backgrounds. All genetic correlations between PY and the functional traits were moderate and unfavourable, ranging from 0.22 ± 0.02 to 0.47 ± 0.03. In addition, the effect of including genetic and phenotypic correlations between the trait groups milk production, udder health and female fertility on the accuracy of the selection index was quantified for a heifer, a cow and a proven bull. The difference between the accuracy obtained by multi‐trait and single‐trait evaluations was largest for the cow (0.012) and small for the heifer and the bull (0.006 and 0.004) because the phenotype of the cow for one trait could assist in predicting the Mendelian sampling term for a correlated trait.     

Genetic associations of teat cup attachment failures,incomplete milkings,and handling time in automatic milking systems with milkability,temperament, and udder conformation

Automatic milking systems (AMS) allow recording of alternative milkability measures. Our objectives were to estimate genetic parameters for teat cup attachment failures (AtF), incomplete milkings (IM), and handling time (HT), and their genetic correlations with box time (BT), udder traits and temperament. Teat coordinates were to measure udder conformation and teat placement. Genetic correlations were estimated between these traits and linear classification traits. Data on Swedish Holstein and Swedish Red cows in 19 AMS herds and 74 herds with conventional milking parlors were analyzed. HT and IM had low heritabilities, but that of AtF was 0.21–0.31. Genetic correlations between AtF and temperament were 0.44–0.71 (calm cows having low AtF). Short BT was weakly genetically associated with shallow udders with short and thin teats. High genetic correlations (0.91–0.98) were found between teat coordinate traits and linear classification traits. Thus, AMS records can be effectively used to select for improved milkability and temperament.     

Investigation of genotype by country interactions for growth traits for Charolais populations in Australia,Canada, New Zealand and USA

Evidence of heterogeneity of parameters and genotype by country interactions was investigated for birth weight (BWT), weaning weight (WWT) and postweaning gain (PWG) between Australian (AUS), Canadian (CAN), New Zealand (NZ) and USA populations of Charolais cattle. An animal model was fit to data sets for each individual country to compare the within-country parameter estimates for homogeneity. The direct heritability estimates of BWT in AUS (0.34) and NZ (0.31) were less than CAN (0.55) and USA (0.47). Maternal BWT heritabilities (0.13–0.18), direct WWT heritabilities (0.22–0.27), and maternal WWT heritabilities (0.12–0.18) were similar across all four countries. Direct PWG heritability for AUS (0.14) was smaller than the same estimate in the other three countries (0.24–0.31). The phenotypic variances for all three traits were similar across AUS, CAN and USA; however, NZ was higher for BWT and WWT and lower for PWG. A multiple trait animal model that considered each trait as a different trait in each country was also fit to the data for pairs of countries. Direct (maternal) estimated genetic correlations for BWT for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.88 (0.86), 0.85 (0.82), 0.88 (0.82), 0.85 (0.83), and 0.84 (0.80), respectively. Direct (maternal) estimated genetic correlations for WWT for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.96 (0.91), 0.95 (0.90), 0.95 (0.91), 0.95 (0.92), and 0.95 (0.92), respectively. Direct estimated genetic correlations for PWG for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.89, 0.91, 0.94, 0.90, and 0.91, respectively. The magnitude of the across-country genetic correlations indicates that genotype by country interactions were biologically unimportant. However, strong evidence exists for heterogeneity of parameters across the countries for some traits and effects. Therefore, combining these countries into one single analysis to produce a common set of genetic values will depend on the development of methods to adjust for heterogeneous parameters for models containing both direct and maternal effects, and for circumstances where constant variance ratios or heritabilities are not present across populations.     

Simulation of genetic control of reproduction in beef cows. IV. Within-herd breeding value estimation with pasture mating

Procedures for breeding value estimation for reproductive traits under pasture mating conditions were developed and tested using a computer simulation model of genetic control of bovine reproduction. The model generated annual calving rates (BCR) (0 or 1) and calving dates (CD) for each cow as a function of underlying genetic variation in two independent traits: single-service conception rate, which was indicative of the ability to conceive when estrus occurs, and postpartum interval (PPI) from calving to first estrus. Observed values for BCR and CD were shown to be complex, nonlinear functions of breeding values for ability to conceive (CRG) and for postpartum interval (PPIG) and of the previous CD. Effects of CRG on BCR and CD were small at high values of CRG, but these effects increased as CRG declined. Effects of PPIG on BCR and CD were small for cows that previously calved within the first 21 d of the calving season, but these effects increased for cows that calved after d 21. Previous CD had substantial nongenetic carryover effects on both BCR and CD. Unbiased estimates of CRG and PPIG could not be derived in the absence of breeding information. However, CD were reasonably highly correlated with breeding values for ability to conceive, provided information on open cows was included in the evaluation. Calving dates were only weakly associated with breeding values for PPI, in part because of the relatively short mean PPI (70 d) that was simulated.     

Genetic parameters and genetic trends for age at first calving and calving interval in an Angus-Blanco Orejinegro-Zebu multibreed cattle population in Colombia

Genetic parameters and genetic trends for age at first calving (AFC), interval between first and second calving (CI1), and interval between second and third calving (CI2) were estimated in a Colombian beef cattle population composed of Angus, Blanco Orejinegro, and Zebu straightbred and crossbred animals. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 3-trait model included the fixed effects of contemporary group (year-season of calving-sex of calf; sex of calf for CI1 and CI2 only), age at calving (CI1 and CI2 only), breed genetic effects (as a function of breed fractions of cows), and individual heterosis (as a function of cow heterozygosity). Random effects for AFC, CI1, and CI2 were cow and residual. Program AIREMLF90 was used to perform computations. Estimates of heritabilities for additive genetic effects were 0.15 ± 0.13 for AFC, 0.11 ± 0.06 for CI1, and 0.18 ± 0.11 for CI2. Low heritabilities suggested that nutrition and reproductive management should be improved to allow fuller expressions of these traits. The correlations between additive genetic effects for AFC and CI1 (0.33 ± 0.41) and for AFC and CI2 (0.40 ± 0.36) were moderate and favorable, suggesting that selection of heifers for AFC would also improve calving interval. Trends were negative for predicted cow yearly means for AFC, CI1, and CI2 from 1989 to 2004. The steepest negative trend was for cow AFC means likely due to the introduction of Angus and Blanco Orejinegro cattle into this population.     

Genetic parameters for claw health and feet and leg conformation traits in Finnish Ayrshire cows

Genetic parameters for different claw disorders, overall claw health and feet and leg conformation traits were estimated for Finnish Ayrshire cows. The merged data set with records of claw health and feet and leg conformation traits consisted of 105 000 observations from 52 598 Finnish Ayrshire cows between 2000 and 2010. The binary claw health data and the linearly scored conformation data were analysed using an animal model and restricted maximum likelihood method by applying the statistical package ASReml. Binomial logistic models with mixed effects were used to estimate genetic parameters for sole haemorrhages, chronic laminitis, white‐line separation, sole ulcer, interdigital dermatitis, heel horn erosion, digital dermatitis, corkscrew claw and overall claw health. Estimated heritabilities for different claw disorders using a binomial logistic model ranged from 0.01 to 0.20. Estimated heritability for overall claw health using a binomial logistic model was 0.08. Estimated heritabilities for feet and leg conformation traits ranged from 0.07 to 0.39. The genetic correlations between claw health and feet and leg conformation traits ranged from ?0.40 to 0.42. All phenotypic correlations were close to zero. The moderate genetic correlation, together with higher heritability of feet and leg conformation traits, showed that RLSV (rear leg side view) is a useful indicator trait to be used together with claw trimming information to increase the accuracy of breeding values for claw health in genetic evaluation.     

Genetic relationships among female fertility disorders,female fertility traits and productivity of Holstein dairy cows in the early lactation period

Fertility health disorders from the early lactation period including retained placenta (REPLA), metritis (MET), corpus luteum persistence (CLP), anoestria/acyclia (AOEAC) and ovarial cysts (OC), as well as overall disease categories (disorders during the postpartal period (DPP), ovary infertility (OINF), overall trait definition “fertility disorders” (FD)), were used to estimate genetic (co)variance components with female fertility and test‐day traits. The disease data set comprised 25,142 Holstein cows from parities 1, 2 and 3 resulting in 43,584 lactations. For disease traits, we used the binary trait definition (sick or healthy) and disease count data reflecting the sum of treatments for the same disease within lactation or within lactation periods. Statistical modelling included single and multiple trait repeatability animal models for all trait combinations within a Bayesian framework. Heritabilities for binary disease traits ranged from 0.04 (OC) to 0.10 (REPLA) and were slightly lower for the corresponding sum trait definitions. Correlations between both trait definitions were almost one, for genetic as well as for permanent environmental effects. Moderate to high genetic correlations were found among puerperal disorders DPP, REPLA and MET (0.45–0.98) and among the ovarian disorders OINF, AOEAC, CLP and OC (0.59–0.99). Genetic correlations between puerperal and ovarian disorders were close to zero, apart from the REPLA–OC association (0.55). With regard to fertility disorders and productivity in early lactation, a pronounced genetic antagonistic relationship was only identified between OC and protein yield. Genetic correlations between fertility disorders and test‐day SCS were close to zero. OINF and all diseases contributing to OINF were strongly correlated with the female fertility traits “interval from calving to first service,” “interval from service to pregnancy” and “interval from calving to pregnancy.” The strong correlations imply that fertility disorders could be included in genetic evaluations of economic fertility traits as correlated predictors. Vice versa, a breeding focus on female fertility traits will reduce genetic susceptibility to OC, CLP and AOEAC.     

荷斯坦牛皮肤褶皱厚度及体况评分性状遗传分析

本研究通过对荷斯坦牛颈侧部、肋部和后乳房基部皮肤褶皱厚度（分别简称为颈部、肋部和乳房皮褶厚）及体况评分（body condition score,BCS）进行大群测定,旨在探究荷斯坦牛不同部位皮肤褶皱厚度和BCS的群体特征,并建模估计荷斯坦牛不同部位皮肤褶皱厚度及BCS的遗传参数。本研究于2015—2020年夏季测定了北京地区12个规模化牧场10 915头泌乳荷斯坦牛的皮肤褶皱厚度,同时对测定牛群进行了体况评分,使用单性状和四性状动物模型分别对颈部皮褶厚、肋部皮褶厚、乳房皮褶厚和BCS进行遗传分析并估计遗传参数,并计算了上述4个性状与奶牛寿命和繁殖等重要功能性状之间的近似遗传相关。结果显示,荷斯坦牛乳房皮褶厚、颈部皮褶厚、肋部皮褶厚和体况评分分别为（7.49±1.45） mm、（7.27±1.34） mm、（11.74±1.90） mm和（2.94±0.79）;乳房皮褶厚和颈部皮褶厚为中等遗传力性状,遗传力分别为0.11和0.15;肋部皮褶厚和体况评分为中高遗传力性状,遗传力分别为0.28和0.22;不同部位的皮褶厚之间存在中高遗传相关,颈部和肋部皮褶厚之间的遗传相关最高（0.69）,颈部和乳房皮褶厚之间的遗传相关最低（0.21）;BCS与不同部位皮褶厚之间遗传相关的差异较大,BCS与颈部、肋部皮褶厚之间为正遗传相关（0.28、0.13）,BCS与乳房皮褶厚之间为负遗传相关（-0.25）;体况评分和皮褶厚性状与部分重要功能性状之间存在中等遗传相关。本研究对奶牛3个部位的皮肤褶皱厚度和BCS性状进行了遗传分析,研究获得的遗传参数有助于通过皮肤褶皱厚度和BCS理解奶牛体脂沉积的遗传基础,助力我国奶牛的平衡育种。     

Genetic parameters for direct and maternal calving ability over parities in Piedmontese cattle

Estimates of heritabilities and genetic correlations for calving ease over parities were obtained for the Italian Piedmontese population using animal models. Field data were calving records of 50,721 first- and 44,148 second-parity females and 142,869 records of 38,213 cows of second or later parity. Calving ability was scored in five categories and analyzed using either a univariate or a bivariate linear model, treating performance over parities as different traits. The bivariate model was used to investigate the genetic relationship between first- and second- or between first- and third-parity calving ability. All models included direct and maternal genetic effects, which were assumed to be mutually correlated. (Co)variance components were estimated using restricted maximum likelihood procedures. In the univariate analyses, the heritability for direct effects was .19 +/- .01, .10 +/- .01, and .08 +/- .004 for first, second, and second and later parities, respectively. The heritability for maternal effects was .09 +/- .01, .11 +/- .01, and .05 +/- .01, respectively. All genetic correlations between direct and maternal effects were negative, ranging from -.55 to -.43. Approximated standard errors of genetic correlations between direct and maternal effects ranged from .041 to .062. For multiparous cows, the fraction of total variance due to the permanent environment was greater than the maternal heritability. With bivariate models, direct heritability for first parity was smaller than the corresponding univariate estimate, ranging from .18 to .14. Maternal heritabilities were slightly higher than the corresponding univariate estimates. Genetic correlation between first and second parity was .998 +/- .00 for direct effects and .913 +/- .01 for maternal effects. When the bivariate model analyzed first- and third-parity calving ability, genetic correlation was .907 +/- .02 for direct effects and .979 +/- .01 for maternal effects. Residual correlations were low in all bivariate analyses, ranging from .13 for analysis of first and second parity to .07 for analysis of first and third parity. In conclusion, estimates of genetic correlations for calving ease in different parities obtained in this study were very high, but variance components and heritabilities were clearly heterogeneous over parities.     

Estimation of genetic parameters for 13 female fertility indices in Holstein dairy cows

This study was aimed to assess genetic parameters for 13 traits in heifers and first-parity Holstein dairy cows. Data consisted of calving and insemination dates of 14,707 Holstein dairy cows in Isfahan province of Iran. Reproductive traits included age at first service (AFS), first service to conception (FSTC), gestation length (GL), age at first calving (AFC), calving to first service (CTFS), days open (DO), calving interval (CI), number of services per conception (NS), and non-return rate at 56 days (NRR). Model equations were optimized using GLM procedure in SAS package following genetic analysis using animal models in ASREML software. Minimum and maximum departure from normal distribution for phenotypic records belonged to AFS, NRR, GL, DO, CI and AFC, NS, FSTC, CTFS, respectively. Estimated heritability varied from 0.002 (NRR) to 0.184 (GL) in heifers and from 0.003 (NRR) to 0.153 (GL) in first-parity cows. AFS, CTFS, and GL were noticeably heritable compared to other assessed traits. Estimated absolute additive genetic correlations were in the range of 0.01 (NRR and AFS) and 0.99 (NRR and NS) in heifers and 0.07 (GL and CI) to 1 (FSTC and CI) in cows. Additive genetic correlations were antagonistic between AFS and other traits, except AFC. Interestingly, NRR which has been included in sire catalogs had the highest average absolute genetic associations with other traits.     

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.     

Genetic relationships between calving and carcass traits for Charolais and Hereford cattle in Sweden

The objective of this study was to estimate genetic correlations between calving difficulty score and carcass traits in Charolais and Hereford cattle, treating first and later parity calvings as different traits. Genetic correlations between birth weight and carcass traits were also estimated. Field data on 59,182 Charolais and 27,051 Hereford calvings, and carcass traits of 5,260 Charolais and 1,232 Hereford bulls, were used in bivariate linear animal model analyses. Estimated heritabilities were moderate to high (0.22 to 0.50) for direct effects on birth weight, carcass weight, and (S)EUROP (European Community scale for carcass classification) grades for carcass fleshiness and fatness. Heritabilities of 0.07 to 0.18 were estimated for maternal effect on birth weight, and for direct and maternal effects on calving difficulty score at first parity. Lower heritabilities (0.01 to 0.05) were estimated for calving difficulty score at later parities. Carcass weight was positively genetically correlated (0.11 to 0.53) with both direct and maternal effects on birth weight and with direct effects on calving difficulty score. Carcass weight was, however, weakly or negatively (-0.70 to 0.07) correlated with maternal calving difficulty score. Higher carcass fatness grade was genetically associated with lower birth weight, and in most cases, also with less difficult calving. Genetic correlations with carcass fleshiness grade were highly variable. Moderately unfavorable correlations between carcass fleshiness grade and maternal calving difficulty score at first parity were estimated for both Charolais (0.42) and Hereford (0.54). This study found certain antagonistic genetic relationships between calving performance and carcass traits for both Charolais and Hereford cattle. Both direct and maternal calving performance, as well as carcass traits, should be included in the breeding goal and selected for in beef breeds.     

Genetic relationships between calving performance and beef production traits in Piemontese cattle

The aim of the study was to obtain estimates of genetic correlations between direct and maternal calving performance of heifers and cows and beef production traits in Piemontese cattle. Beef production traits were daily gain, live fleshiness, and bone thinness measured on 1,602 young bulls tested at a central station. Live fleshiness (six traits) and bone thinness were subjectively scored by classifiers using a nine-point linear grid. Data on calving performance were calving difficulty scores (five classes from unassisted to embryotomy) routinely recorded in the farms. Calving performance of heifers and cows were considered different traits. A total of 30,763 and 80,474 calving scores in first and later parities, respectively, were used to estimate covariance components with beef traits. Data were analyzed using bivariate linear animal models, including direct genetic effects for calving performance and beef traits and maternal genetic effects only for calving performance. Due to the nature of the data structure, which involved traits measured in different environments and on different animals, covariances were estimated mostly through pedigree information. Genetic correlations of daily gain were positive with direct calving performance (0.43 in heifers and 0.50 in cows) and negative with maternal calving performance (-0.23 and -0.28 for heifers and cows, respectively). Live fleshiness traits were moderately correlated with maternal calving performance in both parities, ranging from 0.06 to 0.33. Correlations between live fleshiness traits and direct calving performance were low to moderate and positive in the first parity, but trivial in later parities. Bone thinness was negatively correlated with direct calving performance (-0.17 and -0.38 in heifers and cows, respectively), but it was positively correlated to maternal calving performance (0.31 and 0.40). Estimated residual correlations were close to zero. Results indicate that, due to the existence of antagonistic relationships between the investigated traits, specific selection strategies need to be studied.