• Journal of Animal Reproduction and Biotechnology
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• v.38 no.1
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• pp.32-37
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• 2023

This study has evaluated the genomic estimated breeding value (GEBV) of the commercial Hanwoo population using the genomic best linear unbiased prediction (GBLUP) method and genomic information. Furthermore, it analyzed the accuracy and realized accuracy of the GEBV. 1,740 heads of the Hanwoo population which were analyzed using a single nucleotide polymorphism (SNP) Chip has selected as the test population. For carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS), the mean GEBVs estimated using the GBLUP method were 3.819, 0.740, -0.248, and 0.041, respectively and the accuracy of each trait was 0.743, 0.728, 0.737, and 0.765, respectively. The accuracy of the breeding value was affected by heritability. The accuracy was estimated to be low in EMA with low heritability and high in MS with high heritability. Realized accuracy values of 0.522, 0.404, 0.444, and 0.539 for CWT, EMA, BFT, and MS, respectively, showing the same pattern as the accuracy value. The results of this study suggest that the breeding value of each individual can be estimated with higher accuracy by estimating the GEBV using the genomic information of 18,499 reference populations. If this method is used and applied to individual selection in a commercial Hanwoo population, more precise and economical individual selection is possible. In addition, continuous verification of the GBLUP model and establishment of a reference population suitable for commercial Hanwoo populations in Korea will enable a more accurate evaluation of individuals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.27-38
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• 2006

The storage function model (SFM) has been used for the flood forecasting in Korea. The SFM has a simple calculation process and it is known that the model is more reasonable than linear model because it considers non-linearity of flood runoff. However, the determination of parameters is very difficult. In general, the trial and error method which is an manual calibration by the decision of a model manager. This study calibrated the parameters by the trial and error method and optimization technique. The calibrated parameters were compared with the representative parameters which are used in the Flood Control Centers in Korea. Also, the evaluation indexes on objective functions and calibration methods for the comparative analysis of simulation efficiency. As a result, the Genetic Algorithm showed the smallest variation in objective functions and, in this study, it is known that the objective function of SSR (Sum of Squared of Residual) is the best one for the flood forecasting.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• Korean Journal of Medicinal Crop Science
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• v.20 no.4
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• pp.277-285
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• 2012

In this study, Expressed Sequence Tag-Simple Sequence Repeat (EST-SSR) analyses were used to clarify the genetic polymorphisms among Korean ginseng cultivars and breeding lines and to classify them into distinct genetic groups. Polymorphic and reproducible bands were produced by 14 primers out of total 30 primers used in this study. Fourteen EST-SSR loci generated a total of 123 bands. Amplified PCR products showed the highly reproducible banding patterns at 110~920 bp. The number of amplified bands for each EST-SSR primers ranged from 2 to 19 with a mean of 8.8 bands. P26 and P35 primers showed 13 and 12 banding patterns, respectively. The number of alleles for each EST-SSR locus ranged from 1.67 to 2.00 with a mean of 1.878 alleles. P34 and P60 primers showed the highest and the lowest genetic polymorphism, respectively. Cluster analysis based on genetic similarity estimated by EST-SSR markers classified Korean cultivars and breeding lines into 4 groups. Group included Gopoong and Chunpoong and 9 breeding lines (55%), group included 2 breeding lines (10%), group included 3 breeding lines (15%), group included Gumpoong and 3 breeding lines (20%). Consequently, the EST-SSR marker developed in this study may prove useful for the evaluation of genetic diversity and differentiation of Korean ginseng cultivars and breeding lines.

• Korean Journal of Agricultural Science
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• v.40 no.4
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• pp.339-345
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• 2013

The objective of this study was to establish genetic evaluation systems with carcass data collected by 68 individual farms from 2007 to 2011 in Pyeongchang area of Kangwon province. All the possible of environment effects were corrected by analysis of variance (ANOVA) to estimate more accurate genetic parameters. Heritabilities and genetic correlations were estimated from carcass data collected from Hanwoo steers(n=10,441) born in Pyeongchang region from 2005 to 2008. Traits evaluated included carcass weight (CWT), eye muscle area (EMA), back fat thickness (BF) and marbling score (MS). As for the mean value and standard deviation for carcass traits, CWT, EMA, BF and MS were 424.5, 92, 13.7 and 5.7. Parameters were estimated using a multiple trait animal model and derivative-free restricted maximum likelihood procedures. Estimated heritabilities for CWT, EMA, BF and MS were 0.30, 0.21, 0.42 and 0.42, respectively. Genetic correlation of CWT with EMA, BF and MS were estimated to 0.24, 0.36 and 0.07, respectively. Genetic correlation of EMA with BF and MS was -0.27 and 0.61, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1741-1754
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• 2020

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and -0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1550-1556
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• 2017

Objective: This study estimated the genetic parameters for productive and reproductive traits. Methods: The data included production and reproduction records of animals that have calved between 1979 and 2013. The genetic parameters were estimated using multivariate mixed models (DMU) package, fitting univariate and multivariate mixed models with average information restricted maximum likelihood algorithm. Results: The estimates of heritability for milk production traits from the first three lactation records were $0.03{\pm}0.03$ for lactation length (LL), $0.17{\pm}0.04$ for lactation milk yield (LMY), and $0.15{\pm}0.04$ for 305 days milk yield (305-d MY). For reproductive traits the heritability estimates were, $0.09{\pm}0.03$ for days open (DO), $0.11{\pm}0.04$ for calving interval (CI), and $0.47{\pm}0.06$ for age at first calving (AFC). The repeatability estimates for production traits were $0.12{\pm}0.02$, for LL, $0.39{\pm}0.02$ for LMY, and $0.25{\pm}0.02$ for 305-d MY. For reproductive traits the estimates of repeatability were $0.19{\pm}0.02$ for DO, and to $0.23{\pm}0.02$ for CI. The phenotypic correlations between production and reproduction traits ranged from $0.08{\pm}0.04$ for LL and AFC to $0.42{\pm}0.02$ for LL and DO. The genetic correlation among production traits were generally high (>0.7) and between reproductive traits the estimates ranged from $0.06{\pm}0.13$ for AFC and DO to $0.99{\pm}0.01$ between CI and DO. Genetic correlations of productive traits with reproductive traits were ranged from -0.02 to 0.99. Conclusion: The high heritability estimates observed for AFC indicated that reasonable genetic improvement for this trait might be possible through selection. The $h^2$ and r estimates for reproductive traits were slightly different from single versus multi-trait analyses of reproductive traits with production traits. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended.

• Korean Journal of Poultry Science
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• v.38 no.2
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• pp.81-87
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• 2011

The study was conducted to select and optimize microsatellite (MS) markers for evaluate Korean Native Chicken (KNC) breeds in order to provide standard for the classification and breed definition of the indigenous breeds. The study also aimed to characterize and classify each KNC populations for inventory and management of avian genetic resources. A total of 462 chickens from 11 populations of chicken breeds including eight KNC breeds and three commercial chicken breeds were analyzed with 19 MS markers. KNC breeds, especially Long-Tail Chicken breeds, formed separate cluster from those commercial chicken breeds. Genetic distances between KNC populations (0.11~0.18) were relatively shorter. Genetic uniformity of KNC (except KNCR breed) (0.86~0.88) were higher than that of commercial breeds (except Cornish) (0.95~0.97). On the other hand, genetic uniformity of KNC Long Tail (KNCLT) were relatively higher (0.91~0.97). The result can be used to evaluate and manage animal genetic resources at national scale.

• Korean Journal of Medicinal Crop Science
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• v.21 no.6
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• pp.444-454
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• 2013

The development of random amplified polymorphic DNA (RAPD) and expressed sequence tag-derived simple sequence repeats (EST-SSRs) provided a useful tool for investigating Korean ginseng genetic diversity. In this study, 18 polymorphic markers (7 RAPD and 11 EST-SSR) selected to assess the genetic diversity in 31 ginseng accessions (11 Korean ginseng cultivars and 20 breeding lines). In RAPD analysis, a total of 53 unique polymorphic bands were obtained from ginseng accessions and number of amplicons ranged from 4 to 11 with a mean of 7.5 bands. Pair-wise genetic similarity coefficient (Nei) among all pairs of ginseng accessions varied from 0.01 to 0.32, with a mean of 0.11. On the basis of the resulting data, the 31 ginseng accessions were grouped into six clusters. As a result of EST-SSR analysis, 11 EST-SSR markers detected polymorphisms among the 31 ginseng accessions and revealed 49 alleles with a mean of 4.45 alleles per primer. The polymorphism information content (PIC) value ranged from 0.06 to 0.31, with an average of 0.198. The 31 ginseng accessions were classified into five groups by cluster analysis based on Nei's genetic distances. Consequently, the results of ginseng-specific RAPD and EST-SSR markers may prove useful for the evaluation of genetic diversity and discrimination of Korean ginseng cultivars and breeding lines.

• 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.