• Journal of Animal Science and Technology
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• v.52 no.3
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• pp.167-174
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• 2010

The objectives of this study were to quantify the combination values of the principal components and factors calculated using body measurements of Hanwoo (Korean Cattle) and estimate their heritabilities. The technique of multivariate analysis was used to reduce a large number of variables to a smaller number of new variables and characterize cattle according to body shape. The analyses were performed using 1,979 cattle at 12 months of age and 936 cattle at 24 months of age. The data for the analyses was obtained from progeny tests performed on Korean Cattle for 6 years from 2003 to 2008. The phenotypic correlations among these traits were estimated to range from 0.32 to 0.90 at 12 months of age and from 0.21 to 0.82 at 24 months of age. The first principal components (PC1s) indicated a weighed average of overall body measurements, accounting for 99.91% of the total variation for both periods of test. The two first PCs had positive coefficients for all body measurements. The major sources of PC, such as chest girth (CG), body length (BL), rump height (RH), and wither height (WH) were similar for both test periods. The heritabilities for PC1, the first factor score (FS1), and the second factor score (FS2) were estimated by multivariate REML method. The estimated heritabilities for PC1, FS1, and FS2 were 0.33, 0.38, and 0.40, respectively, at 12 months of age and 0.26, 0.76, and 0.58 at 24 months of age. Further studies are needed to determine whether the heritabilities of FS1 and FS2 at 24 months of age were overestimated.

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.6
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• pp.764-771
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• 2012

Direct and maternal genetic heritabilities and their correlations with body weight at 5 stages in the life span of purebred Berkshire pigs, from birth to harvest, were estimated to scrutinize body weight development with the records for 5,088 purebred Berkshire pigs in a Korean farm, using the REML based on an animal model. Body weights were measured at birth (Birth), at weaning (Weaning: mean 22.9 d), at the beginning of a performance test (On: mean 72.7 d), at the end of a performance test (Off: mean 152.4 d), and at harvest (Finish: mean 174.3 d). Ordinary polynomials and Legendre with order 1, 2, and 3 were adopted to adjust body weight with age in the multivariate animal models. Legendre with order 3 fitted best concerning prediction error deviation (PED) and yielded the lowest AIC for multivariate analysis of longitudinal body weights. Direct genetic correlations between body weight at Birth and body weight at Weaning, On, Off, and Finish were 0.48, 0.36, 0.10, and 0.10, respectively. The estimated maternal genetic correlations of body weight at Finish with body weight at Birth, Weaning, On, and Off were 0.39, 0.49, 0.65, and 0.90, respectively. Direct genetic heritabilities progressively increased from birth to harvest and were 0.09, 0.11, 0.20, 0.31, and 0.43 for body weight at Birth, Weaning, On, Off, and Finish, respectively. Maternal genetic heritabilities generally decreased and were 0.26, 0.34, 0.15, 0.10, and 0.10 for body weight at Birth, Weaning, On, Off, and Finish, respectively. As pigs age, maternal genetic effects on growth are reduced and pigs begin to rely more on the expression of their own genes. Although maternal genetic effects on body weight may not be large, they are sustained through life.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.1
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• pp.7-12
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• 2004

Real time ultrasonic measurements for 13th rib fat thickness (LBF), longissimus muscle area (LEMA) and marbling score (LMS) of live animal at pre-harvest and subsequent carcass measurements for fat thickness (BF), longissimus muscle area (EMA), marbling score (MS) as well as body weight of live animal, carcass weight (CW), dressing percentage (DP), and total merit index (TMI) on 755 Korean beef steers were analyzed to estimate genetic parameters. Data were analyzed using multivariate animal models with an EM-REML algorithm. Models included fixed effects for year-season of birth, location of birth, test station, age of dam, linear and quadratic covariates for age or body weight at slaughter and random animal and residual effects. The heritability estimates for LEMA, LBF and LMS on RTU scans were 0.17, 0.41 and 0.55 in the age-adjusted model (Model 1) and 0.20, 0.52 and 0.55 in the weight-adjusted model (Model 2), respectively. The Heritability estimates for subsequent traits on carcass measures were 0.20, 0.38 and 0.54 in Model 1 and 0.23, 0.46 and 0.55 in Model 2, respectively. Genetic correlation estimate between LEMA and EMA was 0.81 and 0.79 in Model 1 and Model 2, respectively. Genetic correlation estimate between LBF and BF were high as 0.97 in Model 1 and 0.98 in Model 2. Real time ultrasonic marbling score were highly genetically correlated to carcass MS of 0.89 in Model 1 and 0.92 in Model 2. These results indicate that RTU scans would be alterative to carcass measurement for genetic evaluation of meat quality in a designed progeny-testing program in Korean beef cattle.