• 제목/요약/키워드: Genetic variance

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Estimation of Genetic Variance and Covariance Components for Litter Size and Litter Weight in Danish Landrace Swine Using a Multivariate Mixed Model

  • Wang, C.D.;Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제12권7호
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    • pp.1015-1018
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    • 1999
  • Single trait mixed models have been dominantly utilized for genetic evaluation of the reproductive traits in swine. However employing multiple trait approach may lead to more accurate genetic evaluations. For 5 litter size and litter weight traits of Danish Landrace, genetic parameters were estimated with a multiple trait mixed model. The heritability estimates were 0.02, 0.03, 0.03, 0.05, and 0.07, respectively for litter size at birth, litter size born alive, litter weight at birth, litter size at weaning, and litter weight at weaning. Negative genetic correlations were all positive. The litter weight at birth showed genetic antagonism with litter size born alive (-0.65) and litter size at weaning (-0.31), but positive with litter size at birth (0.47) and litter weight at weaning (0.31). The estimates of environmental correlations were larger than their corresponding genetic correlation estimates except for those between litter weight at birth and the other four traits. This study recommends simultaneous selection for two or more traits with multivariate mixed models in order to improve overall economic response.

퍼지 규칙 최적화를 위한 유전자 알고리즘 (A genetic algorithm for generating optimal fuzzy rules)

  • 임창균;정영민;김응곤
    • 한국정보통신학회논문지
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    • 제7권4호
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    • pp.767-778
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    • 2003
  • 이 논문은 유전자 알고리즘을 이용한 최적의 퍼지 규칙을 만드는 방법을 제시한다. 퍼지 규칙은 첫 번째 단계에서 학습 데이터를 이용해 생성된다. 이 단계에서 퍼지 c-Means 군집화 알고리즘과 군집 유효성을 사용해 구조를 결정하고 퍼지 규칙 수가 되는 군집 수를 결정한다. 첫 번째 단계에서 구조가 결정되면 퍼지규칙의 매개변수들은 유전자 알고리즘을 이용해서 조율된다. 또한, 비대칭 가우시안 소속 함수를 위해 분산 매개변수는 좌ㆍ우값을 따로 관리하여 조율한다. 이 방법은 가중치와 분산 공간에서 유전자 알고리즘을 사용함으로서 전역 최소 쪽으로 수렴하도록 한다.

인공신경망과 유전알고리즘 기반의 쌍대반응표면분석에 관한 연구 (A Study on Dual Response Approach Combining Neural Network and Genetic Algorithm)

  • ;김영진
    • 대한산업공학회지
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    • 제39권5호
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    • pp.361-366
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    • 2013
  • Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

Genetic Variability of Show Jumping Attributes in Young Horses Commencing Competing

  • Prochniak, Tomasz;Rozempolska-Rucinska, Iwona;Zieba, Grzegorz;Lukaszewicz, Marek
    • Asian-Australasian Journal of Animal Sciences
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    • 제28권8호
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    • pp.1090-1094
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    • 2015
  • The aim of the study was to select traits that may constitute a prospective criterion for breeding value prediction of young horses. The results of 1,232 starts of 894 four-, five-, six-, and seven-year-old horses, obtained during jumping championships for young horses which had not been evaluated in, alternative to championships, training centres were analyed. Nine traits were chosen of those recorded: ranking in the championship, elimination (y/n), conformation, rating of style on day one, two, and three, and penalty points on day one, two, and three of a championship. (Co)variance components were estimated via the Gibbs sampling procedure and adequate (co)variance component ratios were calculated. Statistical classifications were trait dependent but all fitted random additive genetic and permanent environment effects. It was found that such characteristics as penalty points and jumping style are potential indicators of jumping ability, and the genetic variability of the traits was within the range of 14% to 27%. Given the low genetic correlations between the conformation and other results achieved on the parkour, the relevance of assessment of conformation in four-years-old horses has been questioned.

Investigation of Biases for Variance Components on Multiple Traits with Varying Number of Categories in Threshold Models Using Bayesian Inferences

  • Lee, D.H.
    • Asian-Australasian Journal of Animal Sciences
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    • 제15권7호
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    • pp.925-931
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    • 2002
  • Gibbs sampling algorithms were implemented to the multi-trait threshold animal models with any combinations of multiple binary, ordered categorical, and linear traits and investigate the amount of bias on these models with two kinds of parameterization and algorithms for generating underlying liabilities. Statistical models which included additive genetic and residual effects as random and contemporary group effects as fixed were considered on the models using simulated data. The fully conditional posterior means of heritabilities and genetic (residual) correlations were calculated from 1,000 samples retained every 10th samples after 15,000 samples discarded as "burn-in" period. Under the models considered, several combinations of three traits with binary, multiple ordered categories, and continuous were analyzed. Five replicates were carried out. Estimates for heritabilities and genetic (residual) correlations as the posterior means were unbiased when underlying liabilities for a categorical trait were generated given by underlying liabilities of the other traits and threshold estimates were rescaled. Otherwise, when parameterizing threshold of zero and residual variance of one for binary traits, heritability estimates were inflated 7-10% upward. Genetic correlation estimates were biased upward if positively correlated and downward if negatively correlated when underling liabilities were generated without accounting for correlated traits on prior information. Residual correlation estimates were, consequently, much biased downward if positively correlated and upward if negatively correlated in that case. The more categorical trait had categories, the better mixing rate was shown.

Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

  • Singh, Ajay;Singh, Avtar;Singh, Manvendra;Prakash, Ved;Ambhore, G.S.;Sahoo, S.K.;Dash, Soumya
    • Asian-Australasian Journal of Animal Sciences
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    • 제29권6호
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    • pp.775-781
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    • 2016
  • A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

Genetic parameters and principal components analysis of breeding value for birth and weaning weight in Egyptian buffalo

  • Salem, Mohamed Mahmoud Ibrahim;Amin, Amin Mohamed Said;Ashour, Ayman Fouad;Ibrahim, Mohamed Mohamed El-said;Abo-Ismail, Mohammed Kotb
    • Animal Bioscience
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    • 제34권1호
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    • pp.12-19
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    • 2021
  • Objective: The objectives of the current study were to study the main environmental factors affecting birth weight (BW) and weaning weight (WW), estimate variance components, genetic parameters and genetic trend and to evaluate the variability and relationships among breeding value of BW and WW using principal components analysis (PCA). Methods: A total of 16,370 records were collected from 8,271 buffalo calves. Genetic parameters and breeding values were estimated using a bivariate animal model which includes direct, maternal and permanent maternal effects. These estimates were standardized and used in PCA. Results: The direct heritability estimates were 0.06 and 0.41 for BW and WW, respectively whereas direct maternal heritability values were 0.03 and 0.14, respectively. Proportions of variance due to permanent environmental effects of dam were 0.455 and 0.280 for BW and WW respectively. The genetic correlation between BW and WWs was weak approaching zero, but the maternal correlation was 0.26. The first two principal components (PC1 and PC2) were estimated utilizing the standardized breeding values according to Kaiser method. The total variance explained by the first two PCs was 71.17% in which 45.91% and 25.25% were explained by PC1 and PC2, respectively. The direct breeding values of BW were related to PC2 but those of WW and maternal breeding values of BW and WWs were associated with PC1. Conclusion: The results of genetic parameters and PCA indicate that BW and WWs were not genetically correlated and improving growth traits of Egyptian buffaloes could be achieved using WW without any adverse effect by BW.

Likelihood-Based Inference on Genetic Variance Component with a Hierarchical Poisson Generalized Linear Mixed Model

  • Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제13권8호
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    • pp.1035-1039
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    • 2000
  • This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

SNP 정보를 활용한 재래흑염소와 교잡종 염소의 유전적 다양성 및 유연관계 분석 (SNP-based Genetic Diversity and Relationships Analysis of the Korean Native Black Goat and Crossbred Goat)

  • 이상훈;이진욱;이은도;김승창;이성수;김관우
    • 한국산학기술학회논문지
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    • 제21권11호
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    • pp.102-108
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    • 2020
  • 본 연구는 국내 재래흑염소 집단 (당진 계통, 장수 계통, 통영 계통 및 경상대 계통)과 교잡종 염소 집단의 유전적 다양성 및 유전적 유연관계를 조사하기 위해 수행되었다. 각 집단에 존재하는 공통 SNP 45,658개를 이용하여 분석에 이용하였다. 유전적 다양성의 지표가 될 수 있는 기대, 관측 이형접합도는 교잡종, 경상대, 장수, 통영 계통 순으로 나타났다. 집단 사이의 유전적 다양성 정도를 나타내는 분산 성분은 당진과 경상대 계통 사이에서 19.98%로 가장 높게 나타났으며, 장수와 통영 계통 사이에서 8.87%로 가장 낮게 나타났다. 또한, 집단 사이의 유전적 거리는 장수, 통영 계통에서 하나의 분지를 형성하였으며, 당진, 경상대 계통이 하나의 분지로 나타냈다. 또한, 교잡종 집단은 당진, 경상대 계통과 하나의 분지를 이루는 것으로 나타났다. 따라서 본 연구 결과는 국내 계통 간의 불필요한 근친교배와 유전자원 흐름을 줄이기 위한 기초자료 및 국내 재래흑염소 유전자원의 고유성을 나타내는 기초자료로 활용이 가능할 것으로 사료된다.

Trends in Heritability of Daily Milk Yield by Periods in Korean Cattle

  • Choi, J.G.;Jeon, K.J.;Na, K.J.;Lee, C.W.;Kim, J.B.;Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제16권9호
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    • pp.1239-1241
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    • 2003
  • Korean cattle breeders have shown interest in genetic improvement of milking ability because poor milking ability and short suckling period of Korean cattle is a hindrance to growth of calves. In this study, daily milk yields by period in Korean cattle were analyzed with an animal model. The milk yields were actually measured at sequential intervals from 1 to 4 months after calving: daily milk yields from delivery to 1 month (DMY1), from 1 to 2 months (DMY2), from 2 to 3 months (DMY3), and from 3 to 4 months (DMY4). Genetic variance estimates gradually increased by the periods while environmental variance estimates gradually decreased. This resulted in a dramatic increase in the heritability by periods: 0.02 for DMY1, 0.11 for DMY2, 0.16 for DMY3, and 0.42 for DMY4. In multi-trait analyses with daily milk yield and body weight of calf, genetic correlation estimates between milk yield and body weight were quite small (-0.08 to 0.02 for birth weight and -0.10 to 0.00 for weaning weight). The trends of the heritability estimated in this study showed that the genetic effects were more influential when the milking period was longer, suggesting genetic evaluations with daily milk yield collected at a longer period.