• 한국약용작물학회지
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• 제18권3호
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• pp.180-185
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• 2010

We investigated genetic diversity among and within the populations of cultivated ginseng (Panax ginseng C. A. Meyer ) using SRAP profiles. A total of 24 ginseng plants were sampled from the three populations (two from China, one from Korea). Since all these populations are previously shown closely related to each other assister groups, we used Panax quinquefolium L. and wild ginseng as a reference species, which is not "within the sister group". All individuals from the three populations were screened with a total of 36 primer pairs with 26 primers generated from 328 SRAP bands of DNA gels. The mean gene diversity ($H_E$) was estimated to be 0.057 within populations (range 0.032-0.067), and 0.086 at the species level. The genetic differentiation (Gst=0.31) indicates that genetic variation apportioned 30% among populations and 70% within populations. Generally, the result of this study indicates that ginseng contains high molecular variation in its populations.

• 생명과학회지
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• 제25권12호
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• pp.1347-1353
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• 2015

대하(Fenneropenaeus chinensis)는 우리나라에서 경제적으로 가장 중요한 양식생물 중 하나이다. 그러나 대하의 유전적 특성에 대한 연구는 전무하다. 본 연구에서는 새로 개발된 13개 미세위성체 유전자좌를 이용하여 우리나라에 서식하는 4개 지역 대하의 유전 다양성 및 집단간 관련성을 분석하였다. 평균 대립유전자 richness =16.87, 평균 이형접합률 =0.845를 보여 유전 다양성은 비교적 높은 수준을 보였다. 52개 유전좌중에서 13개 유전자좌가 집단간 분석에서 Hardy–Weinberg 평형에서 유의적인 차이로 벗어났다. Neighbor-joining, principal coordinate 및 molecular variance 분석 결과로 우리나라 대하 집단은 3개 집단(나라도, 천수만, 법성포 및 채석포)으로 구성되어 있으며, 이 결과는 유전적 거리에 근거한 군집 결과와 일치하였다. 본 연구에서 조사된 유전 다양성 및 분화결과는 앞으로 대하의 지속 가능한 자원관리 및 선발 육종을 통한 유전적 개량에 적용될 수 있을 것이다.

• Asian-Australasian Journal of Animal Sciences
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• 제24권8호
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• pp.1031-1040
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• 2011

The objective of this study was to characterize factors influencing genetic improvement of dairy cattle for milk production at farm level. Data were accumulated from 305-day milk yields and pedigree information from 1,921 first-lactation dairy cows that calved from 1990 to 2007 on 161 farms in Central Thailand. Variance components were estimated using average information restricted maximum likelihood procedures. Animal breeding values were predicted by an animal model that contained herd-year-season, calving age, and regression additive genetic group as fixed effects, and cow and residual as random effects. Estimated breeding values from cows that calved in a particular month were used to estimate genetic trends for each individual farm. Within-farm genetic trends (b, regression coefficient of farm milk production per month) were used to classify farms into 3 groups: i) farms with negative genetic trend (b<-0.5 kg/mo), ii) farms with no genetic trend (-0.5 kg/$mo{\leq}b{\leq}0.5$ kg/mo), and iii) farms with positive genetic trend (b>0.5 kg/mo). Questionnaires were used to gather information from individual farmers on educational background, herd characteristics, farm management, decision making practices, and opinion on dairy farming. Farmer's responses to the questionnaire were used to test the association between these factors and farm groups using Fisher's exact test. Estimated genetic trend for the complete population was $0.29{\pm}1.02$ kg/year for cows. At farm level, most farms (40%) had positive genetic trend ($0.63{\pm}4.67$ to $230.79{\pm}166.63$ kg/mo) followed by farms with negative genetic trend (35%; $-173.68{\pm}39.63$ to $-0.62{\pm}2.57$ kg/mo) and those with no genetic trend (25%; $-0.52{\pm}3.52$ to $0.55{\pm}2.68$ kg/mo). Except for educational background (p<0.05), all other factors were not significantly associated with farm group.

• Animal Bioscience
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• 제35권7호
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• pp.955-963
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• 2022

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

• Animal Bioscience
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• 제34권5호
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• pp.789-800
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• 2021

Objective: Conservation and genetic improvement of cattle breeds require information about genetic diversity and population structure of the cattle. In this study, we investigated the genetic diversity and population structure of the three cattle breeds in the Korean peninsula. Methods: Jeju Black, Hanwoo, Holstein cattle in Korea, together with six foreign breeds were examined. Genetic diversity within the cattle breeds was analyzed with minor allele frequency (MAF), observed and expected heterozygosity (HO and HE), inbreeding coefficient (FIS) and past effective population size. Molecular variance and population structure between the nine breeds were analyzed using a model-based clustering method. Genetic distances between breeds were evaluated with Nei's genetic distance and Weir and Cockerham's FST. Results: Our results revealed that Jeju Black cattle had lowest level of heterozygosity (HE = 0.21) among the studied taurine breeds, and an average MAF of 0.16. The level of inbreeding was -0.076 for Jeju Black, while -0.018 to -0.118 for the other breeds. Principle component analysis and neighbor-joining tree showed a clear separation of Jeju Black cattle from other local (Hanwoo and Japanese cattle) and taurine/indicine cattle breeds in evolutionary process, and a distinct pattern of admixture of Jeju Black cattle having no clustering with other studied populations. The FST value between Jeju Black cattle and Hanwoo was 0.106, which was lowest across the pair of breeds ranging from 0.161 to 0.274, indicating some degree of genetic closeness of Jeju Black cattle with Hanwoo. The past effective population size of Jeju Black cattle was very small, i.e. 38 in 13 generation ago, whereas 209 for Hanwoo. Conclusion: This study indicates genetic uniqueness of Jeju Black cattle. However, a small effective population size of Jeju Black cattle indicates the requirement for an implementation of a sustainable breeding policy to increase the population for genetic improvement and future conservation.

• Asian-Australasian Journal of Animal Sciences
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• 제14권7호
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• pp.910-914
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• 2001

The teat number of a sow plays an important role for weaning pigs and has been utilized in selection of swine breeding stock. Various linear models have been employed for genetic analyses of teat number although the teat number can be considered as a count trait. Theoretically, Poisson error mixed models are more appropriate for count traits than Normal error mixed models. In this study, the two models were compared by analyzing data simulated with Poisson error. Considering the mean square errors and correlation coefficients between observed and fitted values, the Poisson generalized linear mixed model (PGLMM) fit the data better than the Normal error mixed model. Also these two models were applied to analyzing teat numbers in four breeds of swine (Landrace, Yorkshire, crossbred of Landrace and Yorkshire, crossbred of Landrace, Yorkshire, and Chinese indigenous Min pig) collected in China. However, when analyzed with the field data, the Normal error mixed model, on the contrary, fit better for all the breeds than the PGLMM. The results from both simulated and field data indicate that teat numbers of swine might not have variance equal to mean and thus not have a Poisson distribution.

• 산업공학
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• 제23권2호
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• pp.118-125
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• 2010

The determination of a regression model is important in using statistical designs of experiments. Generally, the exact regression model is not known, and experimenters suppose that a certain model form will be fit. Then an experimental design suitable for that predetermined model form is selected and the experiment is conducted. However, the initially chosen regression model may not be correct, and this can result in undesirable statistical properties. We develop model-robust experimental designs that have stable prediction variance for a family of candidate regression models over a cuboidal region by using genetic algorithms and the desirability function method. We then compare the stability of prediction variance of model-robust experimental designs with those of the 3-level face centered cube. These model-robust experimental designs have moderately high G-efficiencies for all candidate models that the experimenter may potentially wish to fit, and outperform the cuboidal design for the second-order model. The G-efficiencies are provided for the model-robust experimental designs and the face centered cube.

• 한국재료학회지
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• 제25권7호
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• pp.322-329
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• 2015

The magnitude of wear should be at a minimum for numerous automobile and aeronautical components. In the current work, composites were prepared by varying the cenosphere content using the conventional stir casting method. A uniform distribution of particles was ensured with the help of scanning electron microscopy (SEM). Three major parameters were chosen from various factors that affect the wear. A wear test was conducted with a pin-on-disc apparatus; the controlling parameters were volume percentages of reinforcement of 5, 10, 15, and 20%, applied loads of 9.8, 29.42, and 49.03 N, and sliding speeds of 1.26, 2.51, and 3.77 m/s. The design of the experiments (DOE) was performed by varying the different influencing parameters using the full factorial method. An analysis of variance (ANOVA) was used to analyze the effects of the parameters on the wear rate. Using regression analysis, a response curve was obtained based on the experimental results. The parameters in the resulting curve were optimized using the Genetic Algorithm (GA). The GA results were compared with those of an alternate efficient algorithm called Neural Networks (NNs).

• 한국통신학회논문지
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• 제31권11A호
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• pp.1037-1043
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• 2006

본 논문은 인터넷 상에서 동기화된 실시간 미디어 멀티캐스트 서비스에 적합한 오버레이 멀티캐스트 트리를 구성하는 알고리즘을 제안한다. 제안하는 알고리즘은 멀티캐스트 송신 단에서 각 종단 시스템 사이의 전송 지연에 대한 평균과 변이를 최소화하는 트리 구성을 찾는다. 그러나 위의 문제는 NP-완전하므로, 이러한 문제의 계산 복잡도를 낮추면서, 근사해를 찾기 위한 방법으로 OGA (Orthogonal Genetic Algorithm)을 이용하였다. 실험 결과에서 제안하는 알고리즘이 기존 알고리즘에 비해 통기화된 실시간 미디어 데이터 전송을 위한 효과적인 트리를 구성한다는 것을 보인다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.