(Co)Variance components and genetic parameter estimates for growth traits in Moghani sheep

Genetic parameters were estimated for birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (ADG1) and average daily gain from weaning to yearling (ADG2) in Moghani sheep. Maximum number of data was 4237 at birth, but only 1389 records at yearling were investigated. The data was collected from 1995 to 2007 at the Breeding Station of Moghani sheep in Jafarabad, Moghan, Iran. (Co)Variance components and genetic parameters were estimated with different models which including direct effects, with and without maternal additive genetic effects as well as maternal permanent environmental effects using restricted maximum likelihood (REML) method. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Maternal effects were important only for pre-weaning traits. Direct heritability estimates for BW, ADG1, WW, ADG2 and YW were 0.07, 0.08, 0.09, 0.09 and 0.17, respectively. Fractions of variance due to maternal permanent environmental effects on phenotypic variance were 0.08 for ADG1. Maternal heritability estimates for BW and WW were 0.18 and 0.06, respectively. Multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Direct genetic correlations among studied traits were positive and ranged from 0.37 for BW–ADG2 to 0.85 for ADG1–YW. Maternal genetic correlation estimate between BW and WW was 0.33. Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low direct heritability estimates imply that mass selection for these traits results in slow genetic gain.     

Estimation of genetic parameters for post-weaning traits of Kermani sheep

The objective of the present study was to estimate genetic parameters for post-weaning traits in Kermani sheep. Traits were included 6-month weight (6MW), 9-month weight (9MW), yearling weight (YW), greasy fleece weight at first shearing (GFW) and greasy fleece weights at various shearings (RFW). Data and pedigree information used in this research were collected at Breeding Station of Kermani sheep during 1993–2004. Genetic parameters were estimated with single- and multi-traits analysis using restricted maximum likelihood (REML) procedures, under animal models. Log likelihood ratio test indicated the most appropriate model for 6MW and 9MW should included direct additive genetic effects as well as maternal permanent environmental effects. However the most appropriate model for YW and GFW had only the direct additive genetic effects. The effects of sex, age of dam and year of birth were significant on body weight traits (P < 0.01). GFW was influenced significantly by sex and year of birth (P < 0.01) but was not affected by age of dam (P > 0.05). Type of birth was no significant effect on studied traits (P > 0.05). Also, the age of lamb at weighing time was a significant influence on 6MW, 9MW and YW. Direct heritability estimates for 6MW, 9MW, YW and GFW were 0.32, 0.03, 0.15 and 0.15, respectively. Maternal permanent environmental estimates of 0.09 were obtained for 6MW and 9MW. Genetic correlation estimates between mentioned traits ranged from 0.51 to 0.99. Phenotypic correlations were generally lower than those of genetic correlation and varied from 0.05 to 0.79 for various traits. The environmental correlations estimates between GFW with growth traits were low, but between other traits were positive and high, ranged from 0.54 to 0.72. The value of repeatability estimated for greasy fleece weight was 0.22.     

Estimates of phenotypic and genetic parameters for reproductive traits in Kermani sheep

Phenotypic and genetic parameter estimates for reproductive traits in Kermani sheep were estimated using reproductive records of 860 ewes. Data were collected during 1995–2007 at the experimental breeding station of Kermani sheep, south-east of Iran. Investigated traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB) and litter mean weight per lamb weaned (LMWLW) as basic traits, total litter weight at birth (TLWB) and total litter weight at weaning (TLWW) as composite traits. Quantitative genetic analyses were performed applying restricted maximum likelihood (REML) procedure under repeatability models. Ewe age had significant effect on LMWLB, LMWLW, TLWB and TLWW (P < 0.01). However, LSB and LSW were not affected by age of the ewe. All the studied traits were significantly affected by lambing year (P < 0.01). Direct heritability estimates for LSB, LSW, LMWLB, LMWLW, TLWB and TLWW were 0.01, 0.03, 0.13, 0.22, 0.06 and 0.18, respectively, while the corresponding repeatabilities were 0.08, 0.10, 0.17, 0.29, 0.09 and 0.23, respectively. Genetic correlation estimates between the investigated traits ranged from ?0.94 for LSB–LMWLB and LSW–LMWLW to 0.99 for LSB–TLWW. Phenotypic and environmental correlations were generally lower than those of genetic correlations. Phenotypic correlations ranged from ?0.34 for LSB–LMWLB to 0.58 for TLWB-TLWW. Environmental correlations ranged from ?0.33 for LSB–LMWLB and LSW–LMWLB to 0.33 for LMWLB–LMWLW. The results suggested that selection based on TLWW could be more effective than the other traits on improvement of reproductive performance in Kermani ewes.     

Genetic trends estimation for body weights of Kermani sheep at different ages using multivariate animal models

The objective of the present study was to estimate genetic trends for body weight traits at different ages in Kermani lambs. Data collected from 1993 to 2006 by the Kermani Breeding Station were analyzed. Genetic trends were estimated for birth weight (BW), weaning weight (WW), 6-month weight (6MW), 9-month weight (9MW) and yearling weight (YW). Maximum number of data was 2654 at birth, but only 1124 at yearling. Different appropriate models for investigation of each trait using multivariate analysis were applied. Variance component were estimated using Simplex procedure and breeding values of animals were predicted with Best Linear Unbiased Prediction (BLUP) methodology under multi-trait animal models. Genetic trends of studied traits were estimated by regressing mean of breeding values on birth year. Direct genetic trends were positive and significant for BW (p < 0.05) WW, 6MW, 9MW and YW (p < 0.01) and were 2, 125, 91, 81 and 156 g/year, respectively. Also, maternal trend for BW was positive and highly significant (p < 0.01) and was 3 g/year.     

Variance and covariance components for liability of piglet survival during different periods

Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual piglet level, the estimates of direct heritability in Landrace were 0.035, 0.057 and 0.027, and in Yorkshire the estimates were 0.012, 0.030 and 0.025 for liability of survival at farrowing (SVB), from birth to day 5 (SV5) and from day 6 to weaning (SVW), respectively. The estimates of maternal heritability for SVB, SV5 and SVW were, respectively, 0.057, 0.040 and 0.030 in Landrace, and 0.050, 0.038 and 0.019 in Yorkshire. Both direct and maternal genetic correlations between the three survival traits were low and not significantly different from zero, except for a moderate direct genetic correlation between SVB and SV5 and between SV5 and SVW in Landrace. Direct and maternal genetic correlations between piglet birth weight (BW) and SV5 were moderately high, but the correlations between BW and SVB and between BW and SVW were low and most of them were not significantly different from zero. These results suggest that effective genetic improvement in piglet survival before weaning by selection should be based on both direct and maternal additive genetic effects and treat survival in different periods as different traits.     

Genetic parameters estimation for preweaning traits and their relationship with reproductive,productive and morphological traits in alpaca

The aim of this study was to estimate the genetic parameters for preweaning traits and their relationship with reproductive, productive and morphological traits in alpacas. The data were collected from 2001 to 2015 in the Pacomarca experimental farm. The data set contained data from 4330 females and 3788 males corresponding to 6396 and 1722 animals for Huacaya and Suri variants, respectively. The number of records for Huacaya and Suri variants were 5494 and 1461 for birth weight (BW), 5429 and 1431 for birth withers height (BH), 3320 and 896 for both weaning weight (WW) and average daily gain (DG) from birth to weaning, 3317 and 896 for weaning withers height (WH), and 5514 and 1474 for survival to weaning. The reproductive traits analyzed were age at first calving and calving interval. The fiber traits were fiber diameter (FD), standard deviation of FD (SD), comfort factor and coefficient of variation of FD and the morphological traits studied were density, crimp in Huacaya and lock structure in Suri, head, coverage and balance. Regarding preweaning traits, model of analysis included additive, maternal and residual random effects for all traits, with sex, coat color, number of calving, month–year and contemporary group as systematic effects, and age at weaning as linear covariate for WW and WH. The most relevant direct heritabilities for Huacaya and Suri were 0.50 and 0.34 for WW, 0.36 and 0.66 for WH, 0.45 and 0.20 for DG, respectively. Maternal heritabilities were 0.25 and 0.38 for BW, 0.18 and 0.32 for BH, 0.29 and 0.39 for WW, 0.19 and 0.26 for WH, 0.27 and 0.36 for DG, respectively. Direct genetic correlations within preweaning traits were high and favorable and lower between direct and maternal genetic effects. The genetic correlations of preweaning traits with fiber traits were moderate and unfavorable. With morphological traits they were high and positive for Suri but not for Huacaya and favorable for direct genetic effect but unfavorable for maternal genetic effect with reproductive traits. If the selection objective was meat production, the selection would have to be based on the direct genetic effect for WW but not on the maternal genetic effect that has been shown to have less relevance. Other weaning traits such as WH or DG would be indirectly selected.     

Genotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-country multi-trait reaction norms test-day models

The progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G × E) within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm (RN) approach was used to investigate the presence of G × E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance for milk yield (MY) in Portugal was 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugal was 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR sire model were 0.78 (0.051) for MY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countries were higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G × E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G × E between Brazilian herd environments, the low genetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions.     

Bayesian inference of genetic parameters for ultrasound scanning traits of Kivircik lambs

Ultrasound scanning traits have been adapted in selection programs in many countries to improve carcass traits for lean meat production. As the genetic parameters of the traits interested are important for breeding programs, the estimation of these parameters was aimed at the present investigation. The estimated parameters were direct and maternal heritability as well as genetic correlations between the studied traits. The traits were backfat thickness (BFT), skin+backfat thickness (SBFT), eye muscle depth (MD) and live weights at the day of scanning (LW). The breed investigated was Kivircik, which has a high quality of meat. Six different multi-trait animal models were fitted to determine the most suitable model for the data using Bayesian approach. Based on deviance information criterion, a model that includes direct additive genetic effects, maternal additive genetic effects, direct maternal genetic covariance and maternal permanent environmental effects revealed to be the most appropriate for the data, and therefore, inferences were built on the results of that model. The direct heritability estimates for BFT, SBFT, MD and LW were 0.26, 0.26, 0.23 and 0.09, whereas the maternal heritability estimates were 0.27, 0.27, 0.24 and 0.20, respectively. Negative genetic correlations were obtained between direct and maternal effects for BFT, SBFT and MD. Both direct and maternal genetic correlations between traits were favorable, whereas BFT–MD and SBFT–MD had negligible direct genetic correlation. The highest direct and maternal genetic correlations were between BFT and SBFT (0.39) and between MD and LW (0.48), respectively. Our results, in general, indicated that maternal effects should be accounted for in estimation of genetic parameters of ultrasound scanning traits in Kivircik lambs, and SBFT can be used as a selection criterion to improve BFT.     

Genetic and phenotypic parameters for lactation traits in a flock of Saanen goats in Mexico

Heritability, repeatability and genetic and phenotypic correlations of total milk production (TM), cumulated milk production to 120 days (M120) and lactation length (LL), were estimated from the analysis of 1413 records (566 does) obtained from a Saanen goat flock in Querétaro, Mexico, during 1991–1997. Variance components were estimated using a restricted maximum likelihood procedure and applying an animal model. The model included the fixed effects of year–season of kidding, litter size and age of doe, and random effects of animal, permanent environment and residual. For TM, M120 and LL estimates of heritability were 0.22 ± 0.07, 0.12 ± 0.05 and 0.04 ± 0.03, and of repeatability were 0.40, 0.27 and 0.11, respectively. Genetic correlations between TM and M120, TM and LL, and M120 and LL, were 0.98, 0.58 and 0.53, respectively. Phenotypic correlations ranged from 0.30 to 0.83. The correlated selection response for TM from indirect selection on M120 was 71.5% of that expected from direct selection. Efficient selection for TM is possible and M120 could be used as an early indicator of TM, due to the high indirect selection response calculated.     

Genetic parameters for carcase measurements and age at slaughter in commercial cattle

Genetic parameters were estimated for cold carcase weight (CCW), carcase conformation (CON), carcase fat class (FAT), age at slaughter (AGE) and average daily carcase gain (ADCG) in 14 common UK breeds of cattle. These included crossbred animals but purebred datasets were also analysed for the most populous sire-breeds. Heritability estimates for beef breeds that were significant ranged from 0.24 to 0.44, 0.12 to 0.35, 0.12 to 0.36, 0.15 to 0.38 and 0.26 to 0.43 for CCW, CON, FAT, AGE and ADCG, respectively. For Holstein-Friesian, a dairy breed, heritability estimates were consistently lower than most beef breeds with estimates of 0.12, 0.13, 0.13, 0.06 and 0.15 for CCW, CON, FAT, AGE and ADCG, respectively. In all breed groups, genetic correlations were positive between CCW, CON and ADCG. In general, genetic correlations were moderate between CCW and CON (0.13 to 0.77), moderate to strong between CCW and ADCG (0.57 to 0.98) and weak or moderate between CON and ADCG (0.12 to 0.82). Genetic correlations for FAT with CCW (−  0.20 to −  0.42) and CON (−  0.16 to −  0.52) tended to be negative in the beef breed but were positive in the dairy breed, although not significant between CCW and FAT. For most beef breeds genetic correlations between AGE and carcase traits were not significant with the exceptions of AGE and CCW for Simmental (−  0.15) and Salers (−  0.24), AGE and CON for Limousin (0.15) and Simmental (0.14) and AGE and FAT from three sire-breeds (−  0.17 to −  0.35). However, the correlation between AGE and ADCG was negative and moderate to strong in magnitude (−  0.23 to −  0.67) in all beef breeds as expected since faster-growing animals reach slaughter age earlier. For Holstein-Friesian, all genetic correlations with AGE were negative and moderate to strong. Genetic correlations indicate that selection for increased carcase weight should simultaneously increase growth rate and improve conformation in all breeds and reduce carcase fatness in the majority of beef breeds. The results indicate that there is genetic variation in all five traits suitable for undertaking genetic improvement of carcase traits and age at slaughter; however, there are apparent breed differences. The use of abattoir-derived phenotypes for undertaking genetic improvement is an example where the supply chain can work together to share information to enable the cattle industry to move forward.     

Phenotypic and genetic relationships between udder morphology and udder health in dairy ewes

The aim of this paper was studying the phenotypic and genetic relationships between udder morphology traits and udder health in dairy sheep. From 2000 to 2008 udder traits, somatic cell count (SCC) and clinical mastitis cases were recorded in an experimental flock consisting each year of around 900 ewes. A logistic regression was performed to evaluate the risk for a ewe of showing either a mastitis or at least 2 daily SCC records greater than 1 × 10⁶ cells/ml in one of its lactations as function of udder traits scored in 1st lactation. 1587 individual udder scores and 39,950 SCC daily records were used for the analysis. Secondly, genetic correlation between lactation mean of somatic cell score and udder traits were estimated by a REML method applied to four bi-trait animal models, using data from 2251 primiparous ewes. Logistic regression results indicated that the risk of mastitis or high SCC values during the productive life increased as the cistern height increased and the degree of udder suspension and udder depth decreased. This suggests that the appraisal of the udder is a useful tool for culling decision aimed at increasing the sanitary status of the flock. The genetic correlation between lactation SCS and udder traits were favourable for udder depth (−0.50 ± 0.12), teat placement (0.39 ± 0.011) and degree of udder suspension (−0.42 ± 0.011) and closed to zero for the degree of separation of the two halves. Thus selection for udder morphology, already implemented in some dairy sheep breeds with the aim of improving machine milkability, will lead to a favourable correlated genetic response on SCC.     

The maternal environment determines the timing of germination in Pinus pinaster

Optimizing the germination timing is crucial for the establishment of new generations. We hypothesized that environmental maternal effects may be relevant in the fine tuning of this trait in a long-lived Mediterranean model tree. We analyzed the influence of maternal genotype, maternal environment and their interaction on the germination success and germination phenology of 8725 Pinus pinaster seeds collected from genotypes clonally replicated in two contrasting environments. Besides maternal genetic effects, the maternal environment significantly affected both the percentage and the timing of germination. Seeds from the more favourable environment germinated 7.5 days earlier and showed higher germination rate (0.93 ± 0.01 vs 0.85 ± 0.03). Seed weight significantly influenced germination time, but seed weight differences between maternal environments were not enough to explain this form of transgenerational plasticity. The effect of the maternal environment varied depending on the genotype, indicating that genetic variation in the sensitivity to the maternal environment in this pine species does exist.     

Heritability estimates and genetic correlations for body weight and scrotal circumference adjusted to 12 and 18 months of age for male Nellore cattle

Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12, BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 ± 0.11, 0.21 ± 0.13, 0.21 ± 0.11, -0.08 ± 0.15, 0.16 ± 0.12 and 0.89 ± 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12, suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other. The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other. Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter, it is suggested that the practice of individual selection for these traits is possible.     

The relationship between fetal and maternal selenium concentrations in sheep and goats

In this study, biological samples (slaughterhouse material) were collected from 30 sheep and 36 goats and classified according to gestational stage into either early or late gestation. Samples consisted of allantoic fluid, amniotic fluid, fetal liver, fetal kidney, fetal thyroid gland, maternal plasma and liver to determine selenium (Se) concentrations throughout gestation. The Se concentrations in the allantoic fluid, fetal liver and kidney increased significantly (p < 0.01) during late gestation. Concurrently, the Se concentrations in amniotic fluid, maternal plasma and liver decreased significantly (p < 0.01) over time. Significant (p < 0.01) positive relationships were recorded between the age of the fetus and Se concentrations in the allantoic fluid (r = 0.57–0.75), fetal liver (r = 0.43–0.59) and kidney (r = 0.80–0.81) in both sheep and goats. A significant (p < 0.05) positive relationships were also recorded between the Se concentrations in the allantoic fluid and fetal liver (r = 0.35–0.37), the maternal plasma and liver Se concentrations (r = 0.37–0.57) between sheep and goats. A significant (p < 0.05) negative correlation was recorded between the Se concentrations in the allantoic fluid with maternal plasma of sheep (r = −0.41) as well as between the fetal liver and maternal liver Se (r = −0.22 to 0.50) and a negative correlation (r = −0.42 to 0.43) (p < 0.01) between Se concentrations in the fetal liver and amniotic fluid in both sheep and goats, respectively. Se concentration in the fetal liver was significantly (p < 0.01) higher than that of the kidney and thyroid. In the thyroid gland no morphological differences were noted. Strong fetal–maternal relationships in Se concentration were evident throughout the gestational period and dams seem to sacrifice Se levels in order to maintain that in the fetus. Se concentrations in the amniotic and allantoic fluids could be used as a possible indicator of the Se status of the fetus throughout gestation.     

Performance of Toggenburg dairy goats in smallholder production systems of the eastern highlands of Kenya

The use of exotic dairy goats in breeding programmes for smallholder production systems is popular in Eastern Africa. However, information on the performance of exotic breeds within these systems is scarce. This paper presents information on performance of Toggenburg dairy goats under smallholder production systems in a medium to high agricultural potential environment in Kenya under a community-based set-up as part of the characterization of its adaptive and productive attributes. Environmental factors affecting growth of 646 goats born in the environment, and fertility and milk production of 160 does from 1997 to 2005 were evaluated. Genetic parameters were also estimated for early growth traits. The average birth weight (BW) for 607 kids was 3.27 kg. Corrected weaning weights (CW), and average daily gain to weaning (ADG) for 646 kids were 19.12 kg and 136 g/day, respectively. The results indicated that the smallholder farmers were able to maintain comparably high levels of milk production in the first three parities (LMY), with yields of 475 ± 9 l in 201 days for 160 does in the first parity, 507 ± 9 l in 264 days from 130 does in the second parity and 513 ± 13 l in 296 days for 82 does in the third parity. Kidding intervals though initially long decreased with time to reasonable levels (302 ± 117 days). The heritability estimates obtained were low (0.23 ± 0.13 for BW, 0.18 ± 0.11 for CW and 0.14 ± 0.11 for ADG). Genetic correlations between the traits were also low. Genetic and phenotypic trends indicated little change in BW, CW and LMY over the years. The phenotypic trend in the kidding interval showed a reducing interval over time. The results demonstrated that the Toggenburg goats were able to perform and thrive reasonably well under the low-input farming conditions.     

Genetic analysis of sexual dimorphism of body weight in broilers

Variation in sexual dimorphism (SD) is particularly marked in meat-type chickens. This paper investigates the genetic basis of SD in an important economic trait, i.e. body weight (BW) at 35 days of age, in broilers by applying quantitative genetic analysis. A large dataset comprising 203,323 BW records of a commercial line of broiler chicken was used. First, a bivariate approach was employed treating BW as a sex-specific trait. During this approach, seven bivariate models were applied and variances due to direct additive genetic, maternal genetic and maternal environmental effects were estimated via the restricted maximum likelihood method. The best-fitting model included direct additive genetic, maternal genetic and maternal environmental effects with a direct–maternal genetic covariance. Differences between male and female direct heritabilities were non-significant (0.28 vs. 0.29 for males and females, respectively), implying no need for sex-specific selection strategies. The direct–maternal genetic correlation was more strongly negative in males than in females (?0.72 vs. ?0.56), implying a more profound antagonism between direct additive and maternal genetic effects in this particular gender. The direct genetic correlation of BW between the two sexes was as high as 0.91, i.e. only slightly lower than unity. Second, variance components and genetic parameters of two measures of SD, i.e. the weight difference (Δ) and the weight ratio (R), between the genders were estimated. Direct heritabilities for both measures were significantly different to 0 but of low magnitude (0.04). Apart from the additive–maternal covariance, no other random effects were found to be of importance for Δ and R. The results of the present study suggest that only minimal selection responses due to the selection of Δ and/or R and a small capacity for amplifying or reducing the BW differences between the sexes are to be expected in this specific population. Furthermore, selection pressure on BW is expected to amplify SD.     

Genetic parameter estimates for pre-weaning performance and reproduction traits in Markhoz goats

Genetic parameters for growth, mortality and reproductive performances of Markhoz goats were estimated from data collected during 1993–2010 at Markhoz goat Performance Testing Station in Sanandaj, Iran. For kid performance traits 3763 records were available for birth weight (BW), 2931 for weaning weight (WW), average daily gain (ADG) and Kleiber ratio (KR) (approximated as ADW/WW^0.75) and 3032 for pre-weaning mortality (PWM). For doe reproductive performance traits there were 2920 records available for litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB) and litter mean weight per kid born (LMWKB), and 2182 for total litter weight at weaned (TLWW) and litter mean weight per kid weaned (LMWKW). Genetic parameters were estimated with univariate and bivariate models using restricted maximum likelihood (REML) procedures. Random effects were explored by fitting additive direct genetic effects, maternal additive genetic effects, maternal permanent environmental effects, the covariance between direct and maternal genetic effects, and common litter effects in different models for pre-weaning traits of kids. Also, in addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of PWM. Models for LSB, LSW, TLWB, TLWW, LMWKB, and LMWKW included direct additive genetic effects, permanent environmental effects due to the animal as well as service sire effects. Estimated direct heritabilities were moderate for pre-weaning traits (0.22 for BW, 0.16 for WW, 0.21 for ADG, and 0.27 for KR and 0.29 for PWM), and low for reproduction traits (0.01 for LSB, 0.01 for LSW, 0.02 for TLWB, 0.03 for TLWW, 0.07 for LMWKB, and 0.06 for LMWKW). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BW (0.07) and KR (0.04). The estimate for the maternal permanent environmental variance ratios (c²) varied from 0.01 for KR to 0.07 for WW and ADG. The magnitude of common litter variance ratios (l²) was more substantial for BW (0.46) than the PWM (0.19) and KR (0.16). The estimate for the permanent environmental variance due to the animal (c²) ranged from 0.03 for LMWKB to 0.07 for TLWB and LMWKW, whereas service sire effects (s²) ranged from 0.02 to 0.04. The correlation between direct and maternal genetic effects were negative and high for BW (?0.51) and KR (?0.62). The genetic correlations between pre-weaning growth traits were positive and moderate to strong, as were genetic correlations between reproductive traits. Between BW and PWM the correlation was ?0.35. Phenotypic and environmental correlations for all traits were generally lower than genetic correlations.     

(Co)variance components, genetic parameters and annual trends for calf weights in a Brahman herd kept on floodable savanna

(Co)variance components and genetic parameters were estimated for body weights of an elite Brahman herd under a designed, supervised management and genetic program, including strategic artificial insemination (AI). Restricted maximum likelihood methods were used with a univariate animal model for birth weight (BW) and a bivariate model for weaning weight (205-day weight, 205W) and 18-month weight (548-day weight, 548W). Models included random animal direct and maternal genetic effects, maternal permanent environmental effect (c2), and sex-year-month of birth-age of dam and genetic group (identified and unidentified paternity), as fixed effects. Analysis A1 included all calves and analysis A2 included only those with identified sires. Of the 8,066 calves born, 36% were progeny of AI, 11% from single sire and 53% from multi-sire herds. They were born from 1985 to 1998, from 2559 dams and 146 sires (78 identified). Estimates of direct, maternal and total heritabilities from A1 for BW, 205W and 548W were: 0.23, 0.07 and 0.30; 0.08, 0.14 and 0.16; 0.16, 0.04 and 0.28, respectively. Corresponding estimates of direct maternal genetic correlations were 0.22, 0.07 and 0.86, and c2 estimates were 0.04, 0.14 and 0.04, respectively. Estimates of direct and maternal genetic, and permanent environmental correlations between 205W and 548W were: 0.66, 0.70 and 1.00. Variances and genetic parameters from A1 and A2 were, in general, very similar. Estimates of phenotypic, and direct and maternal genetic trends per year from A1 were: 0.393, 0.004 and 0.003 kg (BW), 3.367, 0.142 and 0.115 kg (205W), 1.813, 0.263 and 0.095 kg (548W). Estimates of direct and maternal genetic trends from A2 were: 0.033 and -0.002 kg (BW); 0.186 and 0.276 kg (205W); 0.471 and 0.136 kg (548W). The modern selection methods that have been used recently should be continued, with emphasis on the improvement of cow efficiency for sustainable beef production on floodable savanna combined with improved pasture.     

Genetic parameters for physical and quality traits of mohair in South African Angora goats

The continuous evaluation and genetic improvement of fleece traits in Angora goats are of major importance to the Angora goat industry. The objective of this study was to estimate variance components and genetic parameters for both physical and quality traits of mohair in South African Angora goats. The data used for this study were collected on between 898 and 6211 kids (depending on the trait measured) born between 2000 and 2006 in 11 different Angora goat studs. Variance components and genetic parameters were estimated with the ASREML programme for fleece weight, fibre diameter, coefficient of variation of fibre diameter, standard deviation of fibre diameter, comfort factor, spinning/effective fineness and standard deviation of fibre diameter along the length of the staple. Most of these traits (excluding fleece weight) are measured using OFDA technology exclusively, and this study was the first attempt to calculate genetic parameters for these traits in South Africa. A model including the direct additive genetic effects only, were the most appropriate for estimation of all parameters. Heritability estimates were 0.24 ± 0.03 for fleece weight, 0.45 ± 0.03 for fibre diameter, 0.37 ± 0.10 for coefficient of variation of fibre diameter, 0.32 ± 0.11 for standard deviation of fibre diameter, 0.63 ± 0.10 for comfort factor, 0.61 ± 0.10 for spinning/effective fineness and 0.14 ± 0.08 for standard deviation of fibre diameter along the length of the staple. Results from this study can now be applied for the estimation of breeding values for fleece production of South African Angora goats and in incorporation into selection programs.