• Asian-Australasian Journal of Animal Sciences
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• 제21권7호
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• pp.961-966
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• 2008

Direct and maternal genetic parameters for production traits in 1,642 pigs and maternal genetic correlations among production (1,642 pigs) and feed efficiency (380 boars) traits were estimated in 7 generations of a Duroc population. Traits studied were daily gain (DG), intramuscular fat (IMF), loineye area (LEA), backfat thickness (BF), daily feed intake (FI), feed conversion ratio (FCR) and residual feed intake (RFI). The RFI was calculated as the difference between actual and predicted feed intake. The predicted feed intake was estimated by adjusting the initial test weight, DG and BF. Data for production traits were analyzed using four alternative animal models (including direct, direct+maternal permanent environmental, or direct+maternal genetic+maternal permanent environmental effects). Direct heritability estimates from the model including direct and all maternal effects were $0.41{\pm}0.04$ for DG, $0.27{\pm}0.04$ for IMF, $0.52{\pm}0.06$ for LEA and $0.64{\pm}0.04$ for BF. Estimated maternal heritabilities ranged from $0.04{\pm}0.04$ to $0.15{\pm}0.05$ for production traits. Antagonistic relationships were observed between direct and maternal genetic effects ($r_{am}$) for LEA (-0.21). Maternal genetic correlations of feed efficiency traits with FI ($r_g$ of FI with FCR and RFI were $0.73{\pm}0.06$ and $0.90{\pm}0.05$, respectively) and LEA (rg of LEA with FCR and RFI were $-0.48{\pm}0.05$ to $-0.61{\pm}0.05$, respectively) were favorable. The estimated moderate genetic correlations between direct and maternal genetic effects for IMF and LEA indicated that maternal effects has an important role in these traits, and should be accounted for in the genetic evaluation system.

• Asian-Australasian Journal of Animal Sciences
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• 제11권4호
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• pp.441-444
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• 1998

The negative direct-maternal genetic correlation $(r_{dm})$ for weaning weight is inflated when data are analyzed with model ignoring sire-by-year interactions (SY). An analytical study investigating the consequences of ignoring SY was undertaken. The inflation of negative correlation could be due to a functional relationship of design matrices for additive direct and maternal genetic effects to that for sire effects within which SY effects were nested. It was proven that the maternal genetic variance was inflated by the amount of reduction for sire variance; the direct genetic variance was inflated by four times the change for maternal genetic variance; and the direct-maternal genetic covariance was deflated by twice the change for maternal genetic variance. The findings were agreed to the results in previous studies.

• Asian-Australasian Journal of Animal Sciences
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• 제23권3호
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• pp.302-307
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• 2010

The present study aimed to investigate the effects of maternal factors on body weight at hatching (day-old) and at six weeks of age in a commercial broiler line. A total of 6,765 records on body weight at day-old (BWTDO) and 115,421 records on body weight at six weeks of age (BWT6W), originated from a commercial broiler line during 14 generations, were used to estimate genetic parameters related to the effects of maternal traits on body weight of chicks immediately after hatch or six weeks thereafter. The data were analyzed using restricted maximum likelihood procedure (REML) and an animal model with DFREML software. Direct heritability ($h^{2}{_a}$), maternal heritability ($h^{2}{_m}$), and maternal environmental variance as the proportions of phenotypic variance ($c^{2}$) for body weight at day-old were estimated to be 0.050, 0.351, and 0.173, respectively. The respective estimated values for body weight at six weeks of age were 0.340, 0.022, and 0.030. The correlation coefficient between direct and maternal genetic effects for six-week-old body weight was found to be -0.335. Covariance components and genetic correlations were estimated using a bivariate analysis based on the best model determined by a univariate analysis. Between weights at hatching and at six week-old, the values of -0.07, 0.53 and 0.47 were found for the direct additive genetic variance, maternal additive genetic variance and permanent maternal environmental variance, respectively. The estimated correlation between direct additive genetic effect influencing weight at hatch and direct additive maternal effect affecting weight at six weeks of age was -0.21, whereas the correlation value of 0.15 was estimated between direct additive maternal effect influencing weight at hatch and direct additive genetic effect affecting weight at six-week-old. From the present findings, it can be concluded that the maternal additive genetic effect observed for weight at six weeks of age might be a factor transferred from genes influencing weight at hatch to weight at six-week-old.

• Asian-Australasian Journal of Animal Sciences
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• 제12권6호
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• pp.843-845
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• 1999

To evaluate direct and maternal effects on calf market weight (CMW) and carcass weight (CW) in Japanese Black cattle under an animal model, genetic parameters were estimated using 51,320 records of CMW and 11,944 records of CW, respectively. Direct and maternal heritabilities, and direct-maternal genetic correlation were estimated to be 0.22, 0.06 and 0.27 for CMW, and 0.23, 0.12 and -0.40 for CW, respectively. Correlation coefficient between maternal breeding values for CMW and CW was 0.521 for 157 sires appeared in both CMW and CW data sets. These results suggest that the maternal genetic effect on pre-weaning growth carries over to carcass weight. Maternal breeding values for both calf market weight and carcass weight could be used as the indicator traits of maternal ability in Japanese Black cattle.

• Asian-Australasian Journal of Animal Sciences
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• 제22권7호
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• pp.931-936
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• 2009

Body weights of 862 Angora goats between birth and 36 months of age, recorded on a semiyearly basis from 1988 to 2000, were used to estimate genetic, permanent environmental and phenotypic covariance functions. These functions were estimated by fitting a random regression model with 6th order polynomial for direct additive genetic and animal permanent environmental effects and 4th and 5th order polynomial for maternal genetic and permanent environmental effects, respectively. A phenotypic covariance function was estimated by modelling overall animal and maternal effects. The results showed that the most variable coefficient was the intercept for both direct and maternal additive genetic effects. The direct additive genetic (co)variances increased with age and reached a maximum at about 30 months, whereas the maternal additive genetic (co)variances increased rapidly from birth and reached a maximum at weaning, and then decreased with age. Animal permanent environmental (co)variances increased with age from birth to 30 months with lower rate before 12 months and higher rate between 12 and 30 months. Maternal permanent environmental (co)variances changed little before 6 months but then increased slowly and reached a maximum at about 30 months. These results suggested that the contribution of maternal additive genetic and permanent environmental effects to growth variation differed from those of direct additive genetic and animal permanent environmental effects not only in expression time, but also in action magnitude. The phenotypic (co)variance estimates increased with age from birth to 36 months of age.

• Asian-Australasian Journal of Animal Sciences
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• 제13권2호
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• pp.149-154
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• 2000

The objectives of this study of Hanwoo (Korean Cattle) were 1) to estimate genetic parameters for direct and maternal genetic effects for birth weight, weaning weight, and six months weight which can be used for genetic evaluations and 2) to compare models with and without grandmatemal effects. Data were obtained from the National Livestock Research Institute in Rural Development Administration (RDA) of Korea and were used to estimate genetic parameters for birth weight (BW, n=10,889), weaning weight at 120-d (WW, n=8,637), and six month weight (W6, n=8,478) in Hanwoo. Total number of animals in pedigrees was 14,949. A single-trait animal model was initially used to obtain starting values for multiple-trait animal models. Estimates of genetic parameters were obtained with MTDFREML using animal models and derivative-free REML (Boldman et al., 1995). Estimates of direct heritability for BW, WW, and W6 analyzed as single-traits were 0.09, 0.03, and 0.02 from Model 3 which included direct and maternal genetic, maternal permanental environmental effects, and effects due to sire ${\times}$ region ${\times}$ year-season interaction, respectively. Ignoring sire ${\times}$ region ${\times}$ year-season interaction effect in the model (Model 2) resulted in larger estimates for direct heritability than for Model 3. Estimates of maternal heritability for BW, WW and W6 were 0.04, 0.05, and 0.07 from Model 3, respectively. The estimates of direct-maternal genetic correlation were positive for BW, WW, and W6 with Model 3 but were negative with Model 2 for WW and W6. Estimates of direct genetic correlations between BW and WW, BW and W6, and WW and W6 were large: 0.52, 0.45, and 0.90, respectively. Genetic correlations were also large and positive for maternal effects for BW with maternal effects for WW and W6 (0.69 and 0.74), and even larger for WW with W6 (0.97). The log likelihood values were the same for models including grandmatemal effects as for models including maternal effects for all traits. These results indicate that grandmatemal effects are not important for these traits for Hanwoo or that the data structure was not adequate for estimating parameters for a grandmatemal model.

• Asian-Australasian Journal of Animal Sciences
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• 제17권2호
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• pp.153-158
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• 2004

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

• Asian-Australasian Journal of Animal Sciences
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• 제15권8호
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• pp.1085-1090
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• 2002

Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.

• Asian-Australasian Journal of Animal Sciences
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• 제5권3호
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• pp.567-570
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• 1992

Variance components were estimated for calf daily gain from birth to 45 days of age in small (S), medium (M) and large (L) lines of beef cattle. Analyses involved records collected on 682 (S), 510 (M) and 228 (L) calves in Iowa, USA from 1978 to 1986. Cytoplasmic lines were determined based on the foundation female in the maternal lineage of each animal. Data were analyzed separately by size line using a derivative-free restricted maximum likelihood procedure under an animal model including additive direct (a), additive maternal (m), cytoplasmic lineage effects and covariance (a, m). The heritabilities for direct and maternal, and the cytoplasmic effects, were 0.13, 0.35 and 0.00 for S, 0.14, 0.32 and 0.00 for M, and 0.05, 0.33 and 0.03 for L. Genetic correlations (a, m) for S, M and L were -0.33, -0.57 and -1.00, respectively. The maternal genetic effect was the most important for calf growth between birth and 45 dyas of age and cytoplasmic variances were not important in any line.

• Journal of Animal Science and Technology
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• 제52권3호
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• pp.187-190
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• 2010

The objective of this study was to estimate genetic parameters for total number of born (TNB), number of born alive (NBA) and teat numbers (TN) of Landrace and Yorkshire breeds in Korean swine population using multiple trait animal model procedures. Total numbers of 4,653 records for teat numbers and 8,907 records for TNB and NBA collected from 2004 to 2008 on imported breeding pigs and their litter size records were used in this study. To find the appropriate model for estimation of genetic parameters (heritabilities and genetic correlations), five statistical models (two models for reproductive traits, two models for teat numbers, one model for combining these traits) considering only direct additive genetic effects, including maternal effects were used and Akaike information criteria (AIC) of each two models for reproductive traits and teat trait were compared. The means and standard deviations of TNB, NBA, and TN were $11.52{\pm}3.34$, $10.55{\pm}2.96$ and $14.30{\pm}0.83$, respectively. Estimated heritabilities for TNB and NBA traits using the model which considered only additive genetic effect were low (0.06 and 0.05, respectively). However, estimated heritabilities considering maternal genetic effects were a little bit higher than that of the model considering only additive genetic effect (0.09 for TNB and NBA, respectively). Estimated heritability for TN using the model which considered only additive genetic effect was 0.40. However, estimated heritability of direct genetic effects from a model considering maternal genetic effect was high (0.60). All results of AIC statistics, the models considering maternal effect was more appropriate than the models considering only additive genetic effect. Genetic correlations of direct additive genetic effect between litter size (TNB, NBA) and teat numbers were low (-0.18 and -0.14, respectively). However, genetic correlations of maternal effect between litter size (TNB, NBA) and teat numbers were a little bit higher than those of direct additive genetic effect (0.08 and 0.16, respectively).