• Asian-Australasian Journal of Animal Sciences
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• v.28 no.8
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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.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.11
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• pp.1523-1526
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• 2002

Genetic parameters of carcass weight (CWT), dressing percent (DP), cook loss (CL), eye muscle area (EMA), back fat thickness (BFT), and meat tenderness in terms of mastication (MAS), shear force (SFR) and penetration (PEN) in Korean native cattle were estimated in this study. Effects of sire, location and their interaction on these traits were also evaluated. Sire effects were found to be significant on all the traits studied except for PEN. The CWT and DP were also significantly affected both by location (p<0.01) and by interaction effect between sire${\times}$location (p<0.05). The EMA was significantly (p<0.05) affected by location but not by interaction effect between sire${\times}$location. All the traits were positively correlated ($r_g$ and $r_p$) with each other except between CL and meat tenderness (negatively correlated). Moderate to high genetic correlations between CWT and other important traits were obtained; indicating that selection for CWT would lead to improve carcass quality. Heritability estimates were 0.64, 0.52, 0.37, 0.25, 0.19 and 0.18 for MAS, SFR, CWT, PEN, DP and EMA, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.914-918
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• 2004

The random regression model methodology was applied into the estimation of genetic parameters for body weights in Chinese Simmental cattle to replace the traditional multiple trait models. The variance components were estimated using Gibbs sampling procedure on Bayesion theory. The data were extracted for Chinese Simmental cattle born during 1980 to 2000 from 6 national breeding farms, where records from 3 months to 36 months were only used in this study. A 3 orders Legendre polynomial was defined as the submodel to describe the general law of that body weight changing with months of age in population. The heritabilities of body weights from 3 months to 36 months varied between 0.31 and 0.48, where the heritabilities from 3 months to 12 months slightly decreased with months of age but ones from 13 months to 36 months increased with months of age. Specially, the heritabilities at eighteenth and twenty-fourth month of age were 0.33 and 0.36, respectively, which were slightly greater than 0.30 and 0.31 from multiple trait models. In addition, the genetic and phenotypic correlations between body weights at different month ages were also obtained using regression model.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.59-69
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• 1998

A regression model with basin physiographic characteristics as independent variables was calibrated for regional flood frequency analysis. In case that high correlations existing among the independent variables the ridge regression has been known to have capability of overcoming the problems of multicollinearity. To optimize the ridge regression model the cost function including regularization parameter must be minimized. In this research the genetic algorithm was applied on this optimization problem. The genetic algorithm is a stochastic search method that mimic the metaphor of natural biological heredity. Using this method the regression model could have optimized and stable weights of variables.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.10
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• pp.1347-1352
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• 2000

The objectives of the study were to examine non-genetic factors that influence somatic cell counts in dairy cattle and to estimate the genetic parameters of somatic cell counts. A total of 34, 097-test day somatic cell count records were obtained from the Zimbabwe Dairy Services Association (ZDSA). The data were from 5, 615 Holstein daughters of 390 sires and 2, 541 dams tested between May 1994 and December 1998. First lactation cows contributed 22, 147 records to the data set, while 11, 950 records were from second and later parity cows. The model for analysis included fixed effects of month of calving, year of calving, stage of lactation, calving interval and test date. Milk yield and age on test day were fitted in the model as covariates. The additive genetic effects pertaining to cows, sires and dams and the residual error were the random effects. The Average Information Restricted Maximum Likelihood algorithm was used for analysis. The heritability of somatic cell scores was low at $0.027{\pm}0.013$ for parity one cows and $0.087{\pm}0.031$ for parity two and above. Repeatability estimates were $0.22{\pm}0.01$ and $0.30{\pm}0.01$ for the two lactation groups, respectively. Genetic and phenotypic correlations between the somatic cell scores and test day milk production were small and negative. It seems that there is no genetic link between somatic cell counts and milk yield in Holstein cattle in Zimbabwe. The results also seem to indicate that somatic cell count is a trait that is mainly governed by environmental factors.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.741-747
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• 2016

The aim of study was to estimate genetic parameter of carcass traits in commercial Hanwoo steer using national animal model for selection of superior bull. Analyzed data (n=5,843) on carcass traits was collected from 107,020 Hanwoo steer. The animal model was used to estimate heritability and genetic correlations. The estimated heritability of carcass traits were 0.19, 0.17, 0.20 and 0.23 for carcass weight, eye muscle area, backfat thickness and marbling score, respectively. The estimated heritability for carcass traits in commercial Hanwoo are low than estimated heritability of national progeny test population for selection of superior bull because breeding environment, genetic performance of cow and feeding day was different. Therefore, we suggests that animal model can include practical genetic variable based on national animal model to improve genetic performance in commercial Hanwoo.

• Korean Journal of Poultry Science
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• v.39 no.4
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• pp.279-282
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• 2012

Clinical-chemical traits are commonly used biomarkers to examine the health status of individuals. There is an appreciable range of normal variation in most clinical-chemical traits and the determining factors of this variation have been relatively uninvestigated in chickens. The aim of this study was to estimate the genetic parameters (i.e., heritability, genetic correlation) for 8 clinical-chemical traits (glucose, total protein, creatinine, high-density lipoprotein cholesterol, total cholesterol, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase and amylase) in an $F_1$ intercross established by purebred breeding among the 5 lines of Korean native chickens. Phenotypic data were collected from approximately 600 $F_1$ animals. The genetic parameters for the clinical-chemical traits estimated by a mixed animal model using the restricted maximum likelihood method were presented. Estimated heritabilities ranged from 8.9% (glucose) to 39.6% (high-density lipoprotein cholesterol). Interestingly, both the sign and the size of the genetic and phenotypic correlations were largely different between the same several pair of clinical-chemical traits. The findings in this study will provide useful information to address issues in both quantitative trait locus study and genetic management in Korean native chickens.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.9
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• pp.1242-1246
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• 2003

Data pertained to 335 crossbred cows comprising of 1/2 Friesian (F) + 1/2 Hariana (H), 1/2 F + 1/4 Jersey (J) + 1/4 H, 1/2 F + 1/4 Brown Swiss (BS) + 1/4 H, 1/2 F + 1/4 Red Dane (R) + 1/4 H, FR (I) and FRH (I) genetic groups extending over a period of 21 years (1970-1990) maintained at Animal Farm of CCS HAU, Hisar. The averages for first lactation milk yield was $2,486.24{\pm}80.26kg$ and peak yield of first three lactation were $11.35{\pm}0.72kg$, $13.97{\pm}0.60kg$ and $16.02{\pm}0.42kg$, respectively. The lifetime milk production was observed as $11,305.16{\pm}1,004.52kg$ in crossbred cattle. The average first lactation fat yield was observed as $102.06{\pm}0.01kg$ and peak fat yield of first three lactation were $0.458{\pm}0.01$, $0.490{\pm}0.01$ and $0.500{\pm}0.02kg$, respectively. The lifetime fat production was estimated as $502.31{\pm}45.90kg$. LTMP and LTFP had reasonably good additive genetic variance which could be exploited either through mass selection/combined with family or pedigree selection. FLMY, peak yields and LTMP had significant positive phenotypic correlation with FLFY and LTFP and the correlation at the genetic level were also higher and positive for these traits. Finally, peak week milk yield of first lactation (PMY1) was the earliest available trait having desirable and significant correlation at phenotypic and positive at genetic level with FLFY, PFY1 and PFY2, PFY3 and LTFP and selection for this trait will help in early evaluation of sires and dams and will increase genetic advancement per unit of time.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.7
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• pp.909-914
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• 2005

This study was conducted to estimate phenotypic and genetic parameters of body condition score (BCS) and reproductive traits in Hanwoo cows. DFREML procedures were applied to obtain variance-covariance components and heritability estimates with single or two-trait models. Estimates of phenotypic correlations of BCS at service with BCS at calving was 0.16 and 0.26 with calving interval, 0.08 with gestation length, and 0.06 with number of services per conception, respectively. Estimates of phenotypic correlation of BCS at calving was 0.10 with calving interval, 0.13 with gestation length, and 0.10 with number of services per conception, respectively. Estimates of phenotypic correlation were low and negative, -0.11 between calving interval and gestation length and -0.13 between gestation length and number of services per conception. Estimates of direct genetic correlation were -0.06, between BCS at service and BCS at calving, 0.37 between BCS at service and BCS at weaning, and -0.18 between BCS at calving and BCS at weaning. Estimates of direct genetic correlation of days from calving to the 1st service were 0.17 with number of services per conception and -0.21 with BCS at service. Estimates of direct genetic correlation for BCS at calving were -0.02 with number of services per conception and -0.08 with BCS at service. Estimates of direct genetic correlation for BCS at weaning were 0.02 with number of services per conception and -0.07 with BCS at service. Estimates of direct heritability from single trait analyses were 0.13 for BCS at service, 0.20 for BCS at calving, 0.02 for BCS at weaning, and 0.20 for number of service per conception, respectively. Estimates of direct heritability were 0.20 for birth weight and 0.10 for weaning weight.