• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.13-22
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• 2012

절사표본 추출법은 절사층, 표본층, 전수층으로 모집단을 분리한 후 표본층과 전수층의 조사결과를 이용하여 전체 모집단의 총합을 추정하는 방법이다. 이 방법은 왜도가 심한 사업체조사에서 흔히 사용하는 방법이다. 절사층의 총합 추정은 전체 모집단 총합 추정에 영향을 미치므로 절사층 총합의 정확한 추정은 매우 중요하다. 최근 김지학과 신기일 (2011)은 절사층에서 소수의 표본을 추출하여 얻은 결과와 기존의 추정량에서 얻은 결과를 선형결합하는 복합추정법을 제안하였다. 본 논문에서는 최량선형불편예측(best linear unbias predictor; BLUP)을 이용한 새로운 복합추정량을 제안하였으며 모의실험을 통하여 기존의 방법과 새로운 복합 추정량의 우수성을 비교하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제14권6호
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• pp.747-753
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• 2001

In this study, the Italian milk recorded buffalo population from 1974 to 1996 was analysed with the purpose to estimate genetic and environmental variability and provide genetic parameters for the most important economic traits. High variability between herds was evident due to the poor knowledge of feeding requirements and husbandry technology in this species compared to cattle. Age at first calving was reduced by 57 days during the considered years following efforts made in better feeding and management from 1990; on the contrary, calving interval has increased by 17 days as a consequence of forcing buffaloes to calve in spring, in order to have the peak milk yield when milk is much better paid. Average milk yield increased by 1853 kg during these years, while lactation duration was reduced by 30 days. Season of calving has no effect on all traits. Calving order has a positive effect on milk yield especially because older cows produce more milk in shorter lactations. Heritability for the age at first calving and calving interval was 0.26 and 0.05 respectively. Heritability of productive traits, milk yield and duration of the lactation was 0.19 and 0.13 respectively, with repeatabilities of 0.40 and 0.26. Genetic trend for milk yield was 2.1 kg milk/year for the bulls and 1 kg for all population. The high genetic variability of milk production as well as duration of the lactation, indicates that there are good opportunities for genetic improvement when including these traits in a selection scheme. The low genetic trend registered over 15 years of recording activity can be explained by the fact that neither progeny testing was performed or selection schemes were implemented, due to the difficulties to use artificial insemination in buffalo.

• Asian-Australasian Journal of Animal Sciences
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• 제24권2호
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• pp.162-172
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• 2011

In this paper, simulation was used to determine accuracies of genomic breeding values for polygenic traits associated with many thousands of markers obtained from high density genome scans. The statistical approach was based upon stochastically simulating a pedigree with a specified base population and a specified set of population parameters including the effective and noneffective marker distances and generation time. For this population, marker and quantitative trait locus (QTL) genotypes were generated using either a single linkage group or multiple linkage group model. Single nucleotide polymorphism (SNP) was simulated for an entire bovine genome (except for the sex chromosome, n = 29) including linkage and recombination. Individuals drawn from the simulated population with specified marker and QTL genotypes were randomly mated to establish appropriate levels of linkage disequilibrium for ten generations. Phenotype and genomic SNP data sets were obtained from individuals starting after two generations. Genetic prediction was accomplished by statistically modeling the genomic relationship matrix and standard BLUP methods. The effect of the number of linkage groups was also investigated to determine its influence on the accuracy of breeding values for genomic selection. When using high density scan data (0.08 cM marker distance), accuracies of breeding values on juveniles were obtained of 0.60 and 0.82, for a low heritable trait (0.10) and high heritable trait (0.50), respectively, in the single linkage group model. Estimates of 0.38 and 0.60 were obtained for the same cases in the multiple linkage group models. Unexpectedly, use of BLUP regression methods across many chromosomes was found to give rise to reduced accuracy in breeding value determination. The reasons for this remain a target for further research, but the role of Mendelian sampling may play a fundamental role in producing this effect.

• Asian-Australasian Journal of Animal Sciences
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• 제21권11호
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• pp.1559-1571
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• 2008

A rule was developed to constrain the annual rate of inbreeding to a predefined value in a population with different lifetimes between sires and dams, and to maximize the selection response over generations. This rule considers that the animals in a population should be divided into sex-age classes based on the theory of gene flow, and restricts the increase of average inbreeding coefficient for new offspring by limiting the increase of the mean additive genetic relationship for parents selected. The optimization problem of this rule was formulated as a quadratic programming problem. Inputs for the rule were the BLUP estimated breeding values, the additive genetic relationship matrix of all animals, and the long-term contributions of sex-age classes. Outputs were optimal number and contributions of selected animals. In addition, this rule was combined with the optimization of emphasis given to QTL, and further increased the genetic gain over the planning horizon. Stochastic simulations of closed nucleus schemes for pigs were used to investigate the potential advantages obtained from this rule by combining the standard QTL selection, optimal QTL selection and conventional BLUP selection. Results showed that the predefined rates of inbreeding were actually achieved by this rule in three selection strategies. The rule obtained up to 9.23% extra genetic gain over truncation selection at the same rates of inbreeding. The combination of the extended rule and the optimization of emphasis given to QTL allowed substantial increases in selection response at a fixed annual rate of inbreeding, and solved substantially the conflict between short-term and long-term selection response in QTL-assisted selection schemes.

• Animal Bioscience
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• 제34권4호
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• pp.516-524
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• 2021

Objective: The genetic evaluation of Santa Inês sheep was performed for resistance to gastrointestinal nematode infection (RGNI) and body size using different relationship matrices to assess the efficiency of including genomic information in the analyses. Methods: There were 1,637 animals in the pedigree and 500, 980, and 980 records of RGNI, thoracic depth (TD), and rump height (RH), respectively. The genomic data consisted of 42,748 SNPs and 388 samples genotyped with the OvineSNP50 BeadChip. The (co)variance components were estimated in single- and multi-trait analyses using the numerator relationship matrix (A) and the hybrid matrix H, which blends A with the genomic relationship matrix (G). The BLUP and single-step genomic BLUP methods were used. The accuracies of estimated breeding values and Spearman rank correlation were also used to assess the feasibility of incorporating genomic information in the analyses. Results: The heritability estimates ranged from 0.11±0.07, for TD (in single-trait analysis using the A matrix), to 0.38±0.08, for RH (using the H matrix in multi-trait analysis). The estimates of genetic correlation ranged from -0.65±0.31 to 0.59±0.19, using A, and from -0.42±0.30 to 0.57±0.16 using H. The gains in accuracy of estimated breeding values ranged from 2.22% to 75.00% with the inclusion of genomic information in the analyses. Conclusion: The inclusion of genomic information will benefit the direct selection for the traits in this study, especially RGNI and TD. More information is necessary to improve the understanding on the genetic relationship between resistance to nematode infection and body size in Santa Inês sheep. The genetic evaluation for the evaluated traits was more efficient when genomic information was included in the analyses.

• Journal of Mechanical Science and Technology
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• 제16권5호
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• pp.619-632
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• 2002

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

• Asian-Australasian Journal of Animal Sciences
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• 제20권3호
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• pp.453-460
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• 2007

An overview of developments important in the future of animal breeding is discussed. Examples from the application of quantitative genetic principles to selection in chickens and mice are given. Lessons to be learned from these species are that selection for production traits in livestock must also consider selection for reproduction and other fitness-related traits and inbreeding should be minimized. Short-term selection benefits of best linear unbiased predictor methodology must be weighed against long-term risks of increased rate of inbreeding. Different options have been developed to minimize inbreeding rates while maximizing selection response. Development of molecular genetic methods to search for quantitative trait loci provides the opportunity for incorporating marker-assisted selection and introgression as new tools for increasing efficiency of genetic improvement. Theoretical and computer simulation studies indicate that these methods hold great promise once genotyping costs are reduced to make the technology economically feasible. Cloning and transgenesis are not likely to contribute significantly to genetic improvement of livestock production in the near future.

• Communications for Statistical Applications and Methods
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• 제20권5호
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• pp.367-376
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• 2013

Cut-off sampling is widely used for a highly skewed population like a business survey by discarding a part of the population (the take-nothing stratum). In this paper, we suggest a new composite estimator of the take-nothing stratum total obtained by use of the survey results of the take-nothing stratum and a take-some sub-stratum (a part of take-some stratum) for a more accurate estimate of the population total. Small simulation studies are conducted to compare the performances of known estimators and the new composite estimator suggested in this study. In addition, we use briquette consumption survey data for real data analysis.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.381-394
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• 2005

In order to estimate the damage of orchards due' to natural disasters such as typhoon, severe rain, freezing or frost, it is necessary to estimate the number of fruit bearing before and after the damage. To estimate the fruit bearing after the damages are easily done by delegations, but it cost too high to survey every insured farm household and calculate the fruit bearing before the damage. In this article, we suggest to use a random coefficient model to predict the numbers of fruit bearing in the orchards before the damage based on the tree age and the area information.

• Asian-Australasian Journal of Animal Sciences
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• 제16권12호
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• pp.1705-1710
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• 2003

A small body size of Brown Tsaiya laying duck is desirable to reduce maintenance requirements, so the body weight at 40 weeks of age (BW40) has to be maintained at its current level. Egg weight has to be maintained at around 65 g to meet market requirements. Eggshell strength at 40 weeks of age (ES40) must to be increased in order to maintain a low incidence of broken eggs. Thus, number of eggs laid up to 52 weeks of age (EN52) has to be increased without negative correlated response on ES40. A new linear genetic selection index was used: $I_g=a_0{\times}GEW40\;(g)+a_1{\times}GBW40\;(g)+a_2{\times}GES40\;(kg/cm^2)+a_3{\times}GEN52\;(eggs)$ where GEW40, GBW40, GES40 and GEN52 were the multitrait best linear unbiased prediction (MT-BLUP) animal model predictors of the breeding values respectively of egg weight and body weight at 40 weeks of age (EW40, BW40), ES40 and EN52. The coefficients $a_0$, $a_1$, $a_2$ and $a_3$ were calculated with constraints of 0.0 g, 0.0 g and $0.013kg/cm^2$ for expected genetic gains in EW40, BW40 and ES40 respectively and maximum gain in EN52. Since 1997, the drakes and the ducks were selected according to their own indexes, with this new genetic selection index. From G0 to G4, the average per generation predicted genetic responses in female duck were +0.05 g for EW40, +0.92 g for BW40, $+0.035kg/cm^2$ for ES40 and +2.13 eggs for EN52. Which represented respectively 0.07%, 0.06%, 0.67% and 1.0% of the means of the EW40, BW40, ES40 and EN52. For ES40 and EN52, it represented also respectively 16.1% and 21.6% of the additive genetic standard deviation of these traits. Thevse results indicated that selection of laying Brown Tsaiya by a restricted genetic selection index and with MT-BLUP animal model could be an efficient tool for improving the efficiency of egg production, increasing egg shell strength and egg number while holding egg weight and body weight constants.