• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.1-6
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• 2013

This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

• Food Science of Animal Resources
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• v.37 no.5
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• pp.663-669
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• 2017

This study were estimated the contribution of carcass traits to unit price, to analyze the marbling score as a categorical variable rather than a numerical variable, and to develop an optimal model that also includes the holiday effect and the raising period. The data for this study were acquired from the Quality Evaluation of the Korea Institute for Animal Products, and consisted of the trading records of 1,613,699 heads at 12 wholesale markets from 2010 to 2014. The unit price of a cow was estimated from the following parameters: -52.50 Won/mm, $8.93Won/cm^2$, 7.20 Won/kg, and -1.04 Won/day for backfat thickness, eye muscle area, carcass weight, and raising period, respectively. Parameters for the dummy variables of marbling scores varied from 0 to 8328.74 Won/kg, which means that each marbling score grade had a different price value. The unit price of a steer was estimated from the following parameters: - 92.12 Won/mm, $20.22Won/cm^2$, 1.30 Won/kg, and -1.72 Won/day for backfat thickness, eye muscle area, carcass weights, and raising period, respectively. Parameters for dummy variables of marbling scores varied from 0 to 7338.80 Won/kg, which means that the grades of each marbling score had different price values. The unit price of sales during traditional holidays was significantly higher (827.71 Won/kg for cows, and 645.15 Won/kg for steers) than during non-holidays.We conclude that the use of categorical values for marbling scores would be needed to evaluate the price of Hanwoo beef using multiple regression analysis based on carcass traits and environmental factors.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.974-981
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• 2021

The aim of this study was to evaluate genetic parameters of growth traits for improving selective breeding in olive flounder Paralichthys olivaceus produced in April 2019. The total length and body weight at 11-, 18-, and 22-months-old were measured for 7,479, 2,831 and 1,904 individuals, respectively. Since 2004, we have been conducting a selective breeding program to improve growth traits in the olive flounder. Data were analyzed using the restricted maximum likelihood method using the multiple traits animal model. The effect of sex and production period showed significant differences in all traits (P<0.05). The heritability of all traits was 0.428-0.520, which is relatively high by measurement month. Therefore, it is considered that individual selection will be more advantageous than family selection. However, to maintain an appropriate degree of inbreeding and genetic diversity for future generations, it is necessary to consider family selection adequately. Results of the correlation analysis between the same traits according to the measurement period indicated that considering production costs such as feed cost, selection at 18-months-old will be advantageous. Olive flounder is a major aquaculture species in Korea, and continuous selective breeding research is essential to improve productivity.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.7
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• pp.944-948
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• 2002

The aim of this study was to estimate heritability and repeatability for the number of embryos and transferable embryos collected per flush in Holstein population in Hokkaido, Japan. Data consisted of 306 MOET (Multiple Ovulation and Embryo Transfer) treatments on 224 Holstein cows from 1997 to 2000. Variance components for these traits were estimated using the REML procedure. The model included only non-genetic factors that were significant at the 0.05 level, through using generalized linear models, maximum likelihood methods, and stepwise regression procedure as fixed effects and sire and residual for heritabilities, donor and residual for repeatabilities as random effects. The factor identified as important in determining the results was the donor''s estrous condition after superovulation. Heritabilities for the number of embryos and transferable embryos collected per flush were 0.14 and 0.09, respectively. The corresponding repeatabilities were 0.43 and 0.32, respectively. These results show that it was difficult to genetically improve these traits, thus, environmental and physical factors affecting the donor must be improved. These results also show that it is necessary to take the donor''s estrous condition after superovulation and repeatabilities for the number of embryos and transferable embryos collected per flush into account when the genetic gains and inbreeding rates for MOET breeding schemes are predicted by a computer simulation.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.89-94
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• 2012

The objective of this study was to estimate the genetic parameters and breeding value of swine using their economic traits. The traits considered were age at 90 kilograms body weight (D90 kg), backfat thickness (BF) and eye muscle area (EMA). Estimation of genetic parameters and breeding value from 18,668 heads considering the economic traits were based on farm performance data from May 2007 to April 2011. Estimation of genetic parameters based on economic traits revealed that the single best model was fitted after finding source of variance on fixed and random effects and estimated by a multiple trait model using DF-REML (Derivative-FREE Restricted Maximum Likelihood). In this study, the estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire were about 0.22-0.59 for the D90 kg, 0.47-0.62 for the BF and 0.23-0.37 for the EMA. Genetic correlation of D90 kg with BF and EMA of the four breeds were -0.01-0.24 and -0.35--0.23, respectively. Moreover, the genetic correlation of BF with EMA was -0.68--0.17. On the other hand, the phenotypic correlation of D90 kg with BF and EMA of the four breeds were about 0.01-0.11 and -0.37--0.21, respectively, while the phenotypic correlation of BF with EMA was -0.68--0.17. Results showed that the genetic trends of breeding value every year were decreasing for D90 kg, increasing for BF while for EMA inconsistent values were obtained.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.83-87
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• 2012

The purpose of this study was to estimate genetic parameters for productive traits in swine. Productive traits were considered on average daily gain (ADG), body height (BH) and body length (BL). Genetic analysis was consisted of 18,668 heads for productive traits which were based on on-farm performance tested from May, 2007 to Apr, 2011. For estimating genetic parameters on productive traits, single best model was fitted after finding source of variance on fixed and random effects and estimated with a multiple trait animal model by using DF-REML (Derivative-Free Restricted Maximum Likelihood). The estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire 0.22-0.58 for the average daily gain, 0.34-0.41 for the body height and 0.4-0.52 for the body length, respectively. Phenotypic correlations of average daily gain with body height and body length for the four breeds were 0.42-0.48, 0.53-0.58, 0.34-0.46 and 0.47-0.56, respectively. Phenotypic correlations of body height with body length were 0.41, 0.57, 0.52, 0.59, respectively. The estimated genetic correlation coefficients of average daily gain with body height and body length estimated for the four breeds were 0.34-0.47, 0.70-0.75, 0.17-0.38 and 0.50-0.53, respectively. The estimated genetic correlation coefficients of body height with body length were 0.57, 0.69, 0.61 and 0.71, respectively.

• Korean Journal of Poultry Science
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• v.27 no.1
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• pp.51-61
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• 2000

This study was conducted to estimate the general production performance, heritabilities, and genetic phenotypic correlations on several economic traits by multiple trait animal model in Korean native chicken. The data were collected from the records of 5,192 pullets produced from 2,029 dams and 250 sires in Daejon Branch, National Livestock Research Institute from April 10. 1994 to February 10. 1997. Body weights of Red Brown (RB), Yellow Brown (YB), Grey Brown (GB) and Black (B) strains were 1,649.9, 1,439.6, 1,455.6 and 1,575.3g at age of 150 days and 1,923.5, 1,689.6, 1,812.4 and 1,924.0g at age of 270 days, respectively. The ranges of coefficient of variation for body weight were 11.52 to 14.02 at age of 150 days and 12.82 to 14.59% at age of 270 days, respectively. The first eggs of RB, YB, GB and B strains were produced at 147.4, 146.5, 151.1 and 152.1 days, respectively and the coefficients of variation were 7.80 to 8.41%. Egg weight at 270 days were 49.7, 47.6, 48.8 and 48.7 g for RB, YB, GB nd B strains, and coefficients of variation were 6.99 to 7.94% . The number of eggs at age of 270days were 75.8, 78.0, 76.7 and 68.8 for RB, YB, GB and B strains, respectively, and coefficient of variations were 23.87 to 29.89%. On heritability estimates in RB, YB, GB and strains body weight were 0.40, 0.10, 0.09 and 0.57 for RB, YB, GB and B strains at age of 150 days, and 0.23, 0.09, 0.38 and 0.24 at age of 270 days were 0.39, 0.47, 0.60 and 0.62, and egg weights at 270 days and age at 1st egg were 0.36, 0.12, 0.38 and 0.26, number of egg production at 270 days were 0.44, 0.36, 0.58 and 0.49, respectively. The genetic correlation coefficients of body weight with the age of first egg, egg weight and number of egg production at 270days were -0.07∼0.67, -0.24∼0.70 and 0.12∼0.41, respectively ; age of first egg with number of egg production at 270days and egg weight were -0.75∼0.91 and 0.34∼0.97 ; and egg weight with number of egg production at 270days were 0.18∼0.68. The phenotypic correlation coefficients of body weight with at age of first egg, egg weight and number of egg production at 270days were -0.01∼0.74, -0.04∼0.72 and 0.25∼0.57 ; age of first egg with number of egg production at 270days and egg weight were 0.26∼0.52 and 0.52∼0.92, respectively ; and egg weight with number of egg production at 270days were 0.34∼0.91.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.7-11
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• 2013

The purpose of this study was to estimate (co) variance components of three milk production traits for genetic evaluation using a multiple lactation model. Each of the first five lactations was treated as different traits. For the parameter estimation study, a data set was set up including lactations from cows calved from 2001 to 2009. The total number of raw lactation records in first to fifth parities reached 1,416,589. At least 10 cows were required for each contemporary group, herd-year-season effect. Sires with fewer than 10 daughters were discarded. Lactations with 305d milk yield exceeding 15,000 kg were removed. In total, 1,456 sires of cows were remained after all the selection steps. A complete pedigree consisting of 292,382 records was used for the study. A sire model containing herd-year-season, caving age, and sire additive genetic effects was applied to the selected lactation data and pedigree for estimating (co) variance components via VCE. Heritabilities and genetic or residual correlations were then derived from the (co) variance estimates using R package. Genetic correlations between lactations ranged from 0.76 to 0.98 for milk yield, 0.79~1.00 for fat yield, 0.75~1.00 for protein yield. On individual lactation basis, relatively low heritability values were obtained 0.14~0.23, 0.13~0.20 and 0.14~0.19 for milk, fat, and protein yields, respectively. For the combined lactation heritability values were 0.29, 0.28, and 0.26 for milk, fat, and protein yields. The estimated parameters will be used in national genetic evaluations for production traits.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.2
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• pp.162-172
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• 2011

In this paper, simulation was used to determine accuracies of genomic breeding values for polygenic traits associated with many thousands of markers obtained from high density genome scans. The statistical approach was based upon stochastically simulating a pedigree with a specified base population and a specified set of population parameters including the effective and noneffective marker distances and generation time. For this population, marker and quantitative trait locus (QTL) genotypes were generated using either a single linkage group or multiple linkage group model. Single nucleotide polymorphism (SNP) was simulated for an entire bovine genome (except for the sex chromosome, n = 29) including linkage and recombination. Individuals drawn from the simulated population with specified marker and QTL genotypes were randomly mated to establish appropriate levels of linkage disequilibrium for ten generations. Phenotype and genomic SNP data sets were obtained from individuals starting after two generations. Genetic prediction was accomplished by statistically modeling the genomic relationship matrix and standard BLUP methods. The effect of the number of linkage groups was also investigated to determine its influence on the accuracy of breeding values for genomic selection. When using high density scan data (0.08 cM marker distance), accuracies of breeding values on juveniles were obtained of 0.60 and 0.82, for a low heritable trait (0.10) and high heritable trait (0.50), respectively, in the single linkage group model. Estimates of 0.38 and 0.60 were obtained for the same cases in the multiple linkage group models. Unexpectedly, use of BLUP regression methods across many chromosomes was found to give rise to reduced accuracy in breeding value determination. The reasons for this remain a target for further research, but the role of Mendelian sampling may play a fundamental role in producing this effect.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.3
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• pp.319-323
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• 2006

Heritabilities and genetic correlations of economic traits were estimated with a multiple-trait animal model on 5 different strains of Korea Native Chickens (KNC): Red Brown (RB), Yellow Brown (YB), Gray Brown (GB), Black (B) and White (W). The data used for this study were collected from the Daejeon branch of the National Livestock Research Institute and included 11,233 performance records and 12,729 individual animals. DFREML and SAS BASE/STAT packages were used to estimate genetic parameters and descriptive statistics. The estimated heritabilities for strain RB, YB, GB, B and W, respectively, for age at 1st egg were 0.24, 0.27, 0.12, 0.32 and 0.18; for body weight at first egg were 0.39, 0.43, 0.38, 0.52 and 0.57; for body weight at age of 270 days were 0.43, 0.51, 0.30, 0.52 and 0.67; for egg weight at first egg were 0.08, 0.13, 0.07, 0.06 and 0.07; for egg weight at age of 270 days were 0.37, 0.43, 0.22, 0.34 and 0.41; and for number of eggs laid by age of 270 days were 0.24, 0.25, 0.37, 0.36 and 0.30. The genetic and phenotypic correlations were also estimated.