• Journal of Animal Science and Technology
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• v.48 no.3
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• pp.337-344
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• 2006

The objective of this study was to compare of genetic parameter estimates on carcass traits of Hanwoo(Korean Cattle) according to modeling with Gibbs sampler and MTDFREML. The data set consisted of 1,941 cattle records with 23,058 animals in pedigree files at Hanwoo Improvement Center. The variance and covariance among carcass traits were estimated via Gibbs sampler and MTDFREML algorithms. The carcass traits considered in this study were longissimus dorsi area, backfat thickness, and marbling score. Genetic parameter estimates using Gibbs sampler and MTDFREML from single-trait analysis were similar with those from multiple-trait analysis. The estimated heritabilities using Gibbs sampler were .52～.54, .54 ～.59, and .42～.44 for carcass traits. The estimated heritabilities using MTDFREML were .41, .52～.53, and .31～.32 for carcass traits. The estimated genetic correlation using Gibbs sampler and MTDFREML of LDA between BF and MS were negatively correlated as .34～.36, .23～.37. Otherwise, genetic correlation between BF and MS was positive genetic correlation as .36～.44. The correlations of breeding value for marbling score between via MTDFREML and via Gibbs sampler were 0.989, 0.996 and 0.985 for LDA, BF and MS respectively.

• Journal of Animal Science and Technology
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• v.48 no.6
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• pp.759-766
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• 2006

This study was conducted to investigate the genetic correlations among the traits used to select young bulls and proven bulls in Hanwoo Performance and Progeny Test Program in Korea. For the estimation of heritabilities and correlations among the growth traits of bulls and carcass traits of progeny steers, 2,532 records of performance tested bull calves and 1,819 records of progeny tested steers were collected from Livestock Improvement Main Center (LIMC), National Agricultural Cooperative Federation (NACF). Fixed effects of mixed model for each traits were selected by using stepwise regression analysis and prior values of variance components were estimated by MTDFREML. The prior values of variance components were estimated with pairwise 2 traits model followed by single trait analysis. The estimated heritability of backfat thickness(BF), dressing percentage(DP), loin-eye muscle area(LMA), marbling score(MS) and weight at 12 months(WT12) was 0.51, 0.32, 0.27, 0.33, 0.50 and 0.26, respectively. Genetic correlation of WT12 of bull calves with backfat thickness, carcass weight and loin-eye muscle area of steers was positive correlation as 0.05, 0.35 and 0.21, respectively. However genetic correlation of WT12 with DP and MS showed negative correlation as 󰠏0.09 and 󰠏0.27, respectively and these negative genetic correlations implies that bulls that may be superior in carcass traits can be lost at the first step of selection and current selection method should be modified to solve this problem.

• Journal of Animal Science and Technology
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• v.44 no.2
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• pp.171-180
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• 2002

Data were collected from 1996 through 2000 on Korean Native Goats by the National Livestock Research Institute of Korea were used to estimate genetic parameters for birth, 3 month, and 6 month body weights. Estimates were obtained with MTDFREML. Model included animal and maternal genetic and residual effects. The model included sex, birth year-season, and feeding type as fixed factors. Average body weights and standard deviation were 1.78${\pm}$0.32 at birth of age, 7.99${\pm}$2.66 at 3 month of age, and 12.08${\pm}$3.20 kg at 6 month of age, respectively. Average body measurements were 36.46cm for withers height, 38.06cm for body length, and 45.56cm for heart girth at 3 month of age, and were 40.27cm for withers height, 42.01cm for body length, and 51.07cm for heart girth at 6 month of age, respectively. Estimates of heritability were 0.66 for birth weight, 0.34 for 3 month body weight, and 0.27 for 6 month body weight, respectively. Maternal effects would be important for birth and 3 month body weights and may not be needed in a model for 6 month body weight.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.2
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• pp.160-164
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• 2006

Currently, boars selected for commercial use as AI sires are evaluated on grow-finish performance and carcass characteristics. If AI sires were also evaluated and selected on semen production, it may be possible to reduce the number of boars required to service sows, thereby improving the productivity and profitability of the boar stud. The objective of this study was to estimate genetic correlations between production and semen traits in the boar: average daily gain (ADG), backfat thickness (BF) and muscle depth (MD) as production traits, and total sperm cells (TSC), total concentration (TC), volume collected (SV), number of extended doses (ND), and acceptance rate of ejaculates (AR) as semen traits. Semen collection records and performance data for 843 boars and two generations of pedigree data were provided by Smithfield Premium Genetics. Backfat thickness and MD were measured by real-time ultrasound. Genetic parameters were estimated from five four-trait and one five-trait animal models using MTDFREML. Average heritability estimates were 0.39 for ADG, 0.32 for BF, 0.15 for MD, and repeatability estimates were 0.38 for SV, 0.37 for TSC, 0.09 for TC, 0.39 for ND, and 0.16 for AR. Semen traits showed a strong negative genetic correlation with MD and positive genetic correlation with BF. Genetic correlations between semen traits and ADG were low. Therefore, current AI boar selection practices may be having a detrimental effect on semen production.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.10
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• pp.1379-1383
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• 2006

A total of 6,804 records for Duroc breed were collected from three farms registered at the Korean Animal Improvement Association (KAIA) from 1998 to 2004 of which both records from two ultrasound modes (A and B) were analyzed to estimate the variance components of carcass traits. Three carcass traits backfat thickness (bf), loin eye muscle area (lma) and lean meat percentage (lmp) were measured. These traits were analyzed separately as bf1, lma1 and lmp1 for ultrasound mode A and bf2, lma2 and lmp2 for ultrasound mode B with multiple trait animal model by using MTDFREML (Boldman et al., 1993). All the traits revealed medium heritability values. Estimated heritabilities for bf1, bf2, lma1, lma2, lmp1 and lmp2 were 0.45, 0.39, 0.32, 0.25, 0.28 and 0.39, respectively. Estimated genetic correlations for traits bf1 and bf2, lma1 and lma2, lmp1 and lmp2 were positive but low. Specifically, genetic correlations between bf1 and bf2 was 0.30 while the estimates for lean traits between lma1 and lma2 and between lmp1 and lmp2 were 0.15 and 0.18, respectively. Conversely, high negative genetic correlations existed between bf1 and the lean traits lma2, lmp2. Likewise, the estimated genetic correlations between lma1 and lma2 and lmp1 and lmp2 were low.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.5
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• pp.627-632
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• 2002

Genetic parameters for dairy performance traits were estimated, breeding values for the traits of all breeding sires and cows were predicted and the genetic trends were estimated using the breeding values in the Central Cattle Breeding Station (CCBS). A total of 3,801 records for Bangladeshi Local, 756 records for Red Sindhi and 959 records for Sahiwal covering the period from 1961 to 1997 were used in this analysis. Traits considered were total milk production per lactation (TLP), lactation length (LL) and daily milk yield (DMY). The genetic parameters were estimated by the REML using MTDFREML program. The breeding values were predicted by a best linear unbiased prediction (BLUP). In all sets of data, the genetic trends for the dairy performance traits were computed as averages of breeding values for cows born in the particular year. The estimates of heritability for TLP (0.26 and 0.27) and DMY (0.28 and 0.27) were moderate in Bangladeshi local and Red Sindhi breed, respectively. Furthermore, the heritability estimate for LL (0.24) was moderate in Red Sindhi. The estimates of heritabilities for all traits were low in Sahiwal. The repeatability estimate was high for TLP, moderate for LL and moderate to high for DMY. All variances estimated in Bangladeshi Local were low, comparing the respective values estimated in both Red Sindhi and Sahiwal. On the other hand, additive genetic variances for the three traits were estimated very low in Sahiwal. The genetic trends for the three dairy production traits have not been positive except for the recent trend in Bangladeshi Local.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.1
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• pp.13-18
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• 2006

Two different animal models, which differ in whether or not taking maternal genetic effect into account, for estimating genetic parameters of cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter, and fiber length in Inner Mongolia White Cashmere Goat were compared via likelihood ratio test. The results indicate that maternal genetic effect has significant influence on live body weight and cashmere thickness, but no significant influence on the other traits. Using models suitable for each trait, both genetic parameters and trends were analyzed with the MTDFREML program. Heritability estimates from single trait models for cashmere weight, live body weight, cashmere thickness, staple length, fiber diameter and fiber length were found to be 0.30, 0.07, 0.21, 0.29, 0.28 and 0.21, respectively. Genetic correlation estimates from two-trait models between live body weight and all other traits (-0.06~0.07) was negligible, as were those between fiber diameter and all other traits (-0.01~0.03) except cashmere thickness (0.19). Cashmere weight and staple length had moderate to low genetic correlations with other traits (-0.24~0.39 and -0.24~0.34, respectively) except for live body weight and fiber diameter. Cashmere thickness had a strong genetic correlation with fiber length (0.81), and low genetic correlation with other traits (0.19~0.34) except live body weight. Genetic trend analysis suggests that selection for cashmere weight was very effective, which has led to the slow genetic progress of cashmere thickness and fiber length due to their genetic correlations with cashmere weight. The selection for live body weight was not effective, which was consistent with its low inheritability.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.359-365
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• 2013

Estimate breeding value can be used as single trait animal model was developed directly using the Fortran language program. The program is based on data computed by using the indirect method repeatedly. The program develops a common algorithm and imprves efficiency. Algorithm efficiency was compared between the two programs. Estimated using the solution is easy to farm and brand the service, pedigree data base was associated with the development of an improved system. The existing program that uses the single trait animal model and the comparative analysis of efficiency is weak because the estimation of the solution and the conventional algorithm programmed through regular formulation involve many repetition; therefore, the newly developed algorithm was conducted to improve speed by reducing the repetition. Single trait animal model was used to analyze Gauss-Seidel iteration method, and the aforesaid two algorithms were compared thorough the mixed model equation which is used the most commonly in estimating the current breeding value by applying the procedures such as the preparation of information necessary for modelling, removal of duplicative data, verifying the parent information of based population in the pedigree data, and assigning sequential numbers, etc. The existing conventional algorithm is the method for reading and recording the data by utilizing the successive repetitive sentences, while new algorithm is the method for directly generating the left hand side for estimation based on effect. Two programs were developed to ensure the accurate evaluation. BLUPF90 and MTDFREML were compared using the estimated solution. In relation to the pearson and spearman correlation, the estimated breeding value correlation coefficients were highest among all traits over 99.5%. Depending on the breeding value of the high correlation in Model I and Model II, accurate evaluation can be found. The number of iteration to convergence was 2,568 in Model I and 1,038 in Model II. The speed of solving was 256.008 seconds in Model I and 235.729 seconds in Model II. Model II had a speed of approximately 10% more than Model I. Therefore, it is considered to be much more effective to analyze large data through the improved algorithm than the existing method. If the corresponding program is systemized and utilized for the consulting of farm and industrial services, it would make contribution to the early selection of individual, shorten the generation, and cultivation of superior groups, and help develop the Hanwoo industry further through the improvement of breeding value based enhancement, ultimately paving the way for the country to evolve into an advanced livestock country.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1514-1524
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• 2011

A total of 4,752 monthly lactation records of Friesian cows during the period from 2000 to 2005 were used to estimate genetic parameters and to determine the effect of udder health on milk production traits. Three milk production traits were studied: 305-day milk yield (305-dMY), 305-day fat yield (305-dFY) and 305-day protein yield (305-dPY). Four udder health traits were studied: somatic cell count (SCC), mastitis (MAST), udder health status (UDHS) with 10 categories and udder quarter infection (UDQI) with 7 categories. Mixed model least square analysis was used to estimate the fixed effects of month and year of calving and parity (P) on different studied traits. Sire and dam within sire were included in the model as random effects. Data were analyzed using Multi-trait Derivative Free Restricted Maximum Likelihood methodology (MTDFREML) to estimate genetic parameters. Unadjusted means of 305-dMY, 305-dFY, 305-dPY and SCC were 3,936, 121, 90 kg and 453,000 cells/ml, respectively. Increasing SCC from 300,000 to 2,000,000 cells/ml increased UDQI from 5.51 to 23.2%. Losses in monthly and lactationally milk yields per cow ranged from 17 to 93 and from 135 to 991 kg, respectively. The corresponding losses in monthly and lactationally milk yields return per cow at the same level of SCC ranged from 29.8 to 163 and from 236 to 1,734 Egyptian pounds, respectively. Heritability estimates of 305-dMY, 305-dFY, 305-dPY, SCC, MAST, UDHS, UDQI were 0.31${\pm}$0.4, 0.33${\pm}$0.03, 0.35${\pm}$0.05, 0.23${\pm}$0.02, 0.14${\pm}$0.02, 0.13${\pm}$0.03, and 0.09${\pm}$0.01, respectively. All milk production traits showed slightly unfavorable negative phenotypic and genetic correlations with SCC, MAST, UDHS and UDQI. There were positive and high genetic correlations between SCC and each of MAST (0.85${\pm}$0.7), UDHS (0.87${\pm}$0.10) and UDQI (0.77${\pm}$0.06) and between MAST and each of UDHS (0.91${\pm}$0.11) and UDQI (0.83${\pm}$0.07). It could be concluded that the economic losses from mastitis and high SCC are considerable. The high genetic correlation between SCC and clinical mastitis (CM) suggest that the selection for lower SCC would help to reduce or eliminate the undesirable correlated responses of clinical mastitis associated with selection for increasing milk yield. Additionally, it is recommended also that if direct information on under health traits is not available, measures of SCC can be inclusion in a selection criteria to improve the income from dairy cows.

• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.507-518
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• 2002

A multiple-trait stochastic computer simulation model was constructed to predict the breeding schemes and selection methods on Hanwoo(Korean cattle). The model could be used four kinds of selection criteria (random, phenotype and true or estimated breeding values). At the test run in various population size for 20 years, all estimated parameters of the each simulated populations were resulted similar to input parameters. The deviations between input and output values of parameter in the large population were smaller than in the small population. The simulated results obtained from ten small populations consisted with one sire and ten dams in each population for 500 years were as follows; Inbreeding coefficients of population were similar to theoretical estimating function. Mean values of each traits selected were randomly drifted by generation, but they were converged into a value when inbreeding coefficients came close to one. Additive genetic variances within each population were reduced by generation, and they were converged into zero when inbreeding coefficients came close to one. These results indicated that the simulated populations hold to statistical properties of input parameters.