• Asian-Australasian Journal of Animal Sciences
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• 제29권2호
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• pp.170-175
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• 2016

The objective of this study was to assess variance components and genetic parameters for fat and protein content in Tsigai sheep using multivariate animal models in which fat and protein content in individual months of lactation were treated as different traits, and univariate models in which fat and protein content were treated as repeated measures of the same traits. Test day measurements were taken between the second and the seventh month of lactation. The fixed effects were lactation number, litter size and days in milk. The random effects were animal genetic effect and permanent environmental effect of ewe. The effect of flock-year-month of test day measurement was fitted either as a fixed (FYM) or random (fym) effect. Heritabilities for fat content were estimated between 0.06 and 0.17 (FYM fitted) and between 0.06 and 0.11 (fym fitted). Heritabilities for protein content were estimated between 0.15 and 0.23 (FYM fitted) and between 0.10 and 0.18 (fym fitted). For fat content, variance ratios of permanent environmental effect of ewe were estimated between 0.04 and 0.11 (FYM fitted) and between 0.02 and 0.06 (fym fitted). For protein content, variance ratios of permanent environmental effect of ewe were estimated between 0.13 and 0.20 (FYM fitted) and between 0.08 and 0.12 (fym fitted). The proportion of phenotypic variance explained by fym effect ranged from 0.39 to 0.43 for fat content and from 0.25 to 0.36 for protein content. Genetic correlations between individual months of lactation ranged from 0.74 to 0.99 (fat content) and from 0.64 to 0.99 (protein content). Fat content heritabilities estimated with univariate animal models roughly corresponded with heritability estimates from multivariate models: 0.13 (FYM fitted) and 0.07 (fym fitted). Protein content heritabilities estimated with univariate animal models also corresponded with heritability estimates from multivariate models: 0.18 (FYM fitted) and 0.13 (fym fitted).

• Asian-Australasian Journal of Animal Sciences
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• 제29권12호
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• pp.1682-1687
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• 2016

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage ($0.213{\pm}0.007$). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

• Asian-Australasian Journal of Animal Sciences
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• 제21권4호
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• pp.478-483
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• 2008

Records of a Northeastern Thai indigenous cattle line population were used to estimate genetic parameters and annual trends for calf weights. The data set comprised records of 1,922 and 1,489 animals for birth and weaning weight, respectively born from 1993 to 2004. A bivariate analysis was carried out for variance and covariance components estimations using average information restricted maximum likelihood procedure. Average estimated breeding value and maternal breeding value of the animals born in 1993 were set to zero as a base group. Genetic trends of each trait were calculated by regressing average estimated breeding values and maternal breeding values on birth year of calves. Phenotypic trends for each trait were calculated by regressing the yearly adjusted weight on birth year of calves. The results revealed that the estimate of direct heritability, maternal heritability and maternal permanent environmental variance as a proportion of phenotypic variance for birth and weaning weight was 0.40, 0.14 and 0.04; 0.27, 0.05 and 0.23, respectively. Direct heritability was moderately heritable and genetic improvement through selection can be achieved. The estimate of phenotypic, direct genetic, maternal genetic and maternal permanent environmental correlation between birth and weaning weight was 0.48, 0.65, 0.98 and 0.73, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for birth weight was 0.18, 0.04 and 0.01 kg/year, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for weaning weight was -1.36, 0.32 and 0.03 kg/year, respectively. As maternal genetic effect was considerably less important than direct genetic effect, selection for improved weaning weight of this Northeastern Thai indigenous cattle line can place more emphasis on the direct genetic effect.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• Animal Bioscience
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• 제34권12호
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• pp.1903-1911
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• 2021

Objective: The objective of this study was to estimate the genetic parameters and various litter trait trends of Danish pigs in South Vietnam, including the number born alive (NBA), number weaned (NW), and litter weight at the 21st day (LW21). Methods: Records of 936 Yorkshire sows with 3361 litters and 973 Landrace sows with 3161 litters were used to estimate the variance components, genetic parameters, and trends of NBA, NW, and LW21. The restricted maximum likelihood method was applied using VCE6 software to obtain the variance components and genetic parameters. Thereafter, the best linear unbiased prediction procedure with an animal model was applied using PEST software to estimate the breeding values of the studied traits. Results: The heritability estimates were low, ranging from 0.12 to 0.21 for NBA, 0.03 to 0.04 for NW, and from 0.11 to 0.13 for LW21. The genetic correlation between the NBA and NW was relatively strong in both breeds, at 0.77 and 0.60 for Yorkshire and Landrace, respectively. Similarly, the genetic correlation between the NW and LW21 was considerably stronger in Landrace pigs (0.71) than in Yorkshire pigs (0.48). The estimates of annual genetic progress were 0.0431, 0.0233, and 0.0461 for NBA, NW, and LW21 in Landrace pigs and 0434, 0.0202, and 0.0667 for NBA, NW, and LW21 in Yorkshire pigs, respectively. Conclusion: The positive genetic trends estimated for the additive genetic values of the selected traits indicated that the current breeding system has achieved favorable results.

• Asian-Australasian Journal of Animal Sciences
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• 제30권9호
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• pp.1239-1244
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• 2017

Objective: This study was conducted to estimate breed-specific variance components for total number born (TNB), number born alive (NBA) and mortality rate from birth through weaning including stillbirths (MORT) of three main swine breeds in Korea. In addition, the importance of including maternal genetic and service sire effects in estimation models was evaluated. Methods: Records of farrowing traits from 6,412 Duroc, 18,020 Landrace, and 54,254 Yorkshire sows collected from January 2001 to September 2016 from different farms in Korea were used in the analysis. Animal models and the restricted maximum likelihood method were used to estimate variances in animal genetic, permanent environmental, maternal genetic, service sire and residuals. Results: The heritability estimates ranged from 0.072 to 0.102, 0.090 to 0.099, and 0.109 to 0.121 for TNB; 0.087 to 0.110, 0.088 to 0.100, and 0.099 to 0.107 for NBA; and 0.027 to 0.031, 0.050 to 0.053, and 0.073 to 0.081 for MORT in the Duroc, Landrace and Yorkshire breeds, respectively. The proportion of the total variation due to permanent environmental effects, maternal genetic effects, and service sire effects ranged from 0.042 to 0.088, 0.001 to 0.031, and 0.001 to 0.021, respectively. Spearman rank correlations among models ranged from 0.98 to 0.99, demonstrating that the maternal genetic and service sire effects have small effects on the precision of the breeding value. Conclusion: Models that include additive genetic and permanent environmental effects are suitable for farrowing traits in Duroc, Landrace, and Yorkshire populations in Korea. This breed-specific variance components estimates for litter traits can be utilized for pig improvement programs in Korea.

• Asian-Australasian Journal of Animal Sciences
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• 제17권2호
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• pp.153-158
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• 2004

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.772-779
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• 2005

The objectives of this study were to examine problems with using F$_1$ data by simulation, association of marker loci and QTL from crosses of inbred parental lines and to enumerate the preliminary characterization of genetic superiority within inbred parental lines. In this study, the association between markers for QTL used as covariates and estimates of variance components due to effects of lines was investigated through computer simulation. The effects of size of population to develop inbred lines and initial frequencies and magnitudes of effects of QTL were also considered. Results show that estimates of variance components due to line effects are influenced by including marker information as covariates in the model for analysis. Estimates of line variance were increased by adding marker information into the analysis, because negative covariances between effects associated with the markers and the remaining effects associated with other loci existed. However, the fit of the model as indicated by the log likelihood improved by adding more markers as covariates into the analysis. Marker assisted selection will be beneficial when markers explain unexplained genetic difference during selection procedure. Markers can be used to identify QTLs affecting traits, and to select for favorable QTL alleles. To efficiently use genetic markers, location of markers at the genome must be identified. The estimates of variance due to effects of with and without marker information used as covariates in the analysis were investigated. The estimates of line variances were always increased when markers were included as covariates for the model because a negative covariance were existed.

• 한국작물학회지
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• 제63권1호
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• pp.1-7
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• 2018

Information on the patterns of genetic diversity and population structure is essential for the rational use and efficient management of germplasms; accurate information aids in monitoring germplasms, and can also be used to predict potential genetic gains. In this study, we assessed genetic diversity, focusing on Korean rice accessions for theand their sustainable conserved diversity. Using DNA profiling with 12 simple sequence repeat (SSR) markers, we detected a total of 333 alleles among 2,016 accessions. The number of alleles ranged from 21 to 53, with an average of 27.8. Average polymorphism information content was 0.797, with the lowest being 0.667 and the highest 0.940. CA cluster analysis and the model-based population structure revealed two main groups that could be subdivided into five subgroups. Analysis of the molecular variance study based on the SSR profile data showed 5% variance among the profiles, whereas we recorded 93% variance among individuals and 2% variance within individuals. Specifically, the utilized diversity for of the breeding program is restricted in that cultivars were located in limited clades. These results revealed that preserving the diversity of Korean landraces could be useful sources for breeding new rice cultivars, and cwould be the basis for the sustainable conservation and utilization of a Korean rice germplasm.

• Asian-Australasian Journal of Animal Sciences
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• 제31권9호
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• pp.1407-1414
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• 2018

Objective: The aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats. Methods: Data were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain. Results: Threshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude. Conclusion: Direct selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.