• 한국동물생명공학회지
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• 제38권1호
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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.

• 대한토목학회논문집
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• 제26권1B호
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• pp.27-38
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• 2006

현재 국내의 홍수예보시스템의 예측 모형으로 저류함수모형을 사용하고 있다. 저류함수모형은 계산절차가 간편하고 홍수유출의 비선형성을 고려할 수 있는 방법이므로 선형모형보다 합리적이라고 알려져 있다. 그러나 저류함수모형을 실제 홍수사상에 적용하는데 있어 매개변수를 결정하는 것이 매우 어렵다. 저류함수모형의 매개변수 보정을 모형 운영자의 주관적인 판단아래 시행착오에 의한 수동보정 방법을 사용하여 왔다. 본 논문에서는 홍수통제소에서 사용하고 있는 저류함수 모형의 대표(평균) 매개변수와 시행착오법(Trial & Error Method) 그리고 최적화기법(Optimization Technique)에 의해 보정된 매개변수를 비교 분석하였다. 또한 모의효율을 평가하기 위하여 목적함수별, 보정방법별로 평가지표들을 산정하고 비교 분석하였다. 분석 결과, 최적화기법의 하나인 유전자 알고리즘(Genetic Algorithm)이 목적함수에 따른 변동성이 가장 적었으며, 목적함수로는 SSR(Sum of Squared of Residual)이 가장 적합한 것으로 판단하였다.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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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.

• 한국약용작물학회지
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• 제20권4호
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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.

• 농업과학연구
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• 제40권4호
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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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• 제33권11호
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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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• 제30권11호
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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.

• 한국가금학회지
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• 제38권2호
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• pp.81-87
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• 2011

초위성체(MS) 표지를 이용하여 한국 재래닭 집단의 각각의 분자유전학적 특성을 조사하고, 그 평가를 통해 한국 재래닭에 대한 품종 및 계통 분류의 기초를 마련하고자 본 연구를 수행하였다. 또한, 한국 재래닭 집단 내 및 집단간 유전적 변이성을 확인하고, 그 분류 및 특성 평가를 위한 MS 분석 체계를 마련하여 국내 가축유전자원의 관리에 활용코자 하였다. 국내 관리 기관 및 농가 보유 11개 계통의 한국 재래닭 및 상용계 462 수를 대상으로 19개 MS 표지로 분석한 결과, 한국 재래닭 집단은 상용계부터 분자유전학적으로 별개의 집단으로 구분되며, 특히 한국 재래닭 중 긴꼬리닭 계통은 상용계와 국내 토종닭 어느 집단과도 확연히 분리되는 것을 확인하였다. 한국 재래닭 집단 간의 유전거리는 0.11~0.18로 비교적 낮게 나타났으나, 유전적 균일도는 R 계통을 제외하고 0.86~0.88로 코니쉬 계통을 제외한 상용계의 0.95~0.97보다 비교적 낮았다. 다만, 긴꼬리닭 집단의 유전적 균일도는 0.91~0.97로 높게 나타났다. 본 연구를 통하여 한국 재래닭 집단 간의 유전적 차이 및 동질성, 그리고 집단내의 유전적 균일성을 확인하고, 긴꼬리닭 계통의 위치를 확인하였다. 이러한 결과는 국내 유전자원의 고유성을 인정할 수 있는 과학적인 근거로서, 국가 수준의 가축유전자원 평가, 관리의 기초자료로 활용될 수 있을 것이다.

• 한국약용작물학회지
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• 제21권6호
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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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• 제55권1호
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• pp.7-11
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• 2013

본 연구의 목적은 여러 산차를 이용한 모델을 사용하여 유전평가 분석을 하기위하여 3개의 유량생산 형질에 대한 (공)분산 성분을 추정하고자 하였다. 모수추정을 위한 자료는 2001년부터 2009년까지의 검정자료를 이용하였고 원시자료수는 1,416,589개이며 5개의 산차형질에 대해 각각 다른 형질로 가정하여 추정하였다. 동기그룹 내 10두 이하 및 씨수소의 딸소가 10두 미만인 개체는 삭제를 하였으며 305일 유량생산이 15,000 kg을 초과하는 비유개체에 대하여 사전 데이터 가공을 실시하였다. 혈통파일은 총292,382개의 혈통자료와 1,456두의 씨수소로 구성되어진 혈통자료가 연구에 사용되었다. Sire 모형은 herd-year-season의 동기그룹과 분만월령 그리고 혈통과 5산까지 상가적 유전효과들이 적용되었으며 VCE를 이용하여 유전 (공)분산이 추정되었다. 유전율과 유전상과 그리고 잔차상관은 R 패키지를 이용하여 계산하였다. 유량에 대한 산차간 유전 상관은 0.76에서 0.98였고, 유지방량은 0.79~0.10, 유단백질량은 0.75~1.00로 나타났다. 각 산차별 유량, 유지방량, 유단백질량은 상대적으로 낮은 유전력인 0.14~0.23, 0.13~0.20이 추정되었으며 산차에 가중치로 결합된 유전력은 각 형질에서 0.29, 0.28, 0.26로 나타났다. 본 연구에서 추정된 모수들은 국가단위 유전평가분석에 사용될 수 있을 것으로 판단된다.