• Korean Journal of Breeding Science
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• v.40 no.3
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• pp.263-268
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• 2008

Estimates of genetic gain (in volume growth) and diversity (expressed as status number, $N_s$) were determined in a clonal seed orchard of Pinus koraiensis. The genetic thinning was based on clonal breeding values (represented by general combining ability) obtained from progeny tests, clonal fertility estimated by strobilus production, and clonal size variation determined by the ramet numbers per clone. Parental GCA values for volume growth were calculated, based on height and diameter at breast height measured from field trials. Clonal fertility was estimated from the assessments of strobilus production over twelve years from 1991 to 2003, and used for the calculation of status number. There are 179 clones and 5,268 ramets in 12ha area of P. koraiensis clonal seed orchard. Genetic gain and diversity estimates were determined under assumptions of 30% pollen contamination and inferior genetic value of contaminating pollen. Genetic gain increased as thinning rates were set from 10% to 60%. However, for the higher thinning intensities, the increase of genetic gain was not remarkable. Genetic thinning by means of truncation selection resulted in a greater genetic gain but a large decrease in status number. Status number was represented around 40 clones for 10% through 60% thinning intensities, but for the higher thinning intensities, it was a bit fluctuated. Based on the present results, it could be concluded that thinning rate should not be stronger than 60% to optimize genetic gain while conserving genetic diversity. Consequently 50% or 60% thinning rate might be appropriate for genetic thinning in the clonal seed orchard of P. koraiensis. The effect of pollen contamination on the genetic gain and the consequence of genetic thinning for seed production in the clonal seed orchard, and seed orchard management scheme were also discussed.

• Animal Bioscience
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• v.34 no.6
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• pp.949-956
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• 2021

Objective: This study was focused on the estimation of parameters of Wood's model and description of the lactation curve using the cows which were lactated over 24 months on the first lactation. Methods: The database included 1,333 pure-bred dairy Simmental primiparous cows which lactated for 24 months (732 days). The initial dataset entering the procedure of assessment of parameters of Wood's function included 35,826 milk yield records. Milk yield was recorded throughout lactation, with the earliest record taken on day 6 and the latest on day 1,348 of lactation. This dataset was used for the assessment of parameters a, b, c of Wood's model using the non-linear statistical procedure. These parameters were estimated for different length of lactation. The assessed parameters were used for calculation of some characteristics of lactation curves. Results: The lowest value of a parameter (15.2317) of Wood's model of lactation curve was found out in lactations up to 305 days long, contrary to b and c parameters which were highest in those lactations (0.1029 and 0.0015, respectively). The maximum value of a parameter (17.4329) was found out in lactations up to 640 days long, unlike b and c parameters which were minimal in those lactations (0.0603 and 0.0010, respectively). Conclusion: It can be concluded that the parameters of Wood's model and the shape of lactation curve are changing with the growing number of milk yield records. Also, the assessed parameters revealed a significant milk production potential after 305 days of lactation.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.366-373
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• 2024

This study aims to estimate the connectedness rating (CR) of Korean swine breeding herds. Using 104,380 performance and 83,200 reproduction records from three swine breeds (Yorkshire, Landrace and Duroc), the CR was estimated for two traits: average daily gain (ADG) and number born alive (NBA) in eight breeding herds in the Republic of Korea (hereafter, Korea). The average CR for ADG in the Yorkshire breed ranges from 1.32% to 28.5% depending on the farm. The average CR for NBA in the Yorkshire herd ranges from 0% to 12.79%. A total of 60% of Yorkshire and Duroc herds satisfied the preconditions suggested for genetic evaluation among the herds. The precondition for the genetic evaluation of CR for ADG, as a productive trait, was higher than 3% and that of NBA, as a reproductive trait, was higher than 1.5%. The ADG in the Yorkshire herds showed the highest average CR. However, the average CR of ADG in the Landrace herds was lower than the criterion of the precondition. The prediction error variance of the difference (PEVD) was employed to assess the validation of the CR, as PEVDs exhibit fluctuations that are coupled with the CR across the herds. A certain degree of connectedness is essential to estimate breeding value comparisons between pig herds. This study suggests that it is possible to evaluate the genetic performance together for ADG and NBA in the Yorkshire herds since the preconditions were satisfied for these four herds. It is also possible to perform a joint genetic analysis of the ADG records of all Duroc herds since the preconditions were also satisfied. This study provides new insight into understanding the genetic connectedness of Korean pig breeding herds. CR could be utilized to accelerate the genetic progress of Korean pig breeding herds.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.359-365
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• 2013

Estimate breeding value can be used as single trait animal model was developed directly using the Fortran language program. The program is based on data computed by using the indirect method repeatedly. The program develops a common algorithm and imprves efficiency. Algorithm efficiency was compared between the two programs. Estimated using the solution is easy to farm and brand the service, pedigree data base was associated with the development of an improved system. The existing program that uses the single trait animal model and the comparative analysis of efficiency is weak because the estimation of the solution and the conventional algorithm programmed through regular formulation involve many repetition; therefore, the newly developed algorithm was conducted to improve speed by reducing the repetition. Single trait animal model was used to analyze Gauss-Seidel iteration method, and the aforesaid two algorithms were compared thorough the mixed model equation which is used the most commonly in estimating the current breeding value by applying the procedures such as the preparation of information necessary for modelling, removal of duplicative data, verifying the parent information of based population in the pedigree data, and assigning sequential numbers, etc. The existing conventional algorithm is the method for reading and recording the data by utilizing the successive repetitive sentences, while new algorithm is the method for directly generating the left hand side for estimation based on effect. Two programs were developed to ensure the accurate evaluation. BLUPF90 and MTDFREML were compared using the estimated solution. In relation to the pearson and spearman correlation, the estimated breeding value correlation coefficients were highest among all traits over 99.5%. Depending on the breeding value of the high correlation in Model I and Model II, accurate evaluation can be found. The number of iteration to convergence was 2,568 in Model I and 1,038 in Model II. The speed of solving was 256.008 seconds in Model I and 235.729 seconds in Model II. Model II had a speed of approximately 10% more than Model I. Therefore, it is considered to be much more effective to analyze large data through the improved algorithm than the existing method. If the corresponding program is systemized and utilized for the consulting of farm and industrial services, it would make contribution to the early selection of individual, shorten the generation, and cultivation of superior groups, and help develop the Hanwoo industry further through the improvement of breeding value based enhancement, ultimately paving the way for the country to evolve into an advanced livestock country.

• 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.

• Journal of Animal Science and Technology
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• v.53 no.1
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• pp.1-6
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• 2011

This simulation study was performed to investigate the accuracy of the estimated breeding value by using genomic information (GEBV) by way of Bayesian framework. Genomic information by way of single nucleotide polymorphism (SNP) from a chromosome with length of 100cM were simulated with different marker distance (0.1cM, 0.5cM), heritabilities (0.1, 0.5) and half sibs families (20 heads, 4 heads). For generating the simulated population in which animals were inferred to genomic polymorphism, we assumed that the number of quantitative trait loci (QTL) were equal with the number of no effect markers. The positions of markers and QTLs were located with even and scatter distances, respectively. The accuracies of estimated breeding values by way of indicating correlations between true and estimated breeding values were compared on several cases of marker distances, heritabilities and family sizes. The accuracies of breeding values on animals only having genomic information were 0.87 and 0.81 in marker distances of 0.1cM and 0.5cM, respectively. These accuracies were shown to be influenced by heritabilities (0.87 at $h^2$ =0.10, 0.94 at $h^2$ =0.50). According to half sibs' family size, these accuracies were 0.87 and 0.84 in family size of 20 and 4, respectively. As half sibs family size is high, accuracy of breeding appeared high. Based on the results of this study it is concluded that the amount of marker information, heritability and family size would influence the accuracy of the estimated breeding values in genomic selection methodology for animal breeding.

• Journal of Animal Science and Technology
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• v.56 no.8
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• pp.28.1-28.6
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• 2014

This study was conducted to estimate the effective population size using SNPs data of 240 Jeju horses that had raced at the Jeju racing park. Of the total 61,746 genotyped autosomal SNPs, 17,320 (28.1%) SNPs (missing genotype rate of >10%, minor allele frequency of <0.05 and Hardy-Weinberg equilibrium test P-value of < $10^{-6}$) were excluded after quality control processes. SNPs on the X and Y chromosomes and genotyped individuals with missing genotype rate over 10% were also excluded, and finally, 44,426 (71.9%) SNPs were selected and used for the analysis. The measures of the LD, square of correlation coefficient ($r^2$) between SNP pairs, were calculated for each allele and the effective population size was determined based on $r^2$ measures. The polymorphism information contents (PIC) and expected heterozygosity (HE) were 0.27 and 0.34, respectively. In LD, the most rapid decline was observed over the first 1 Mb. But $r^2$ decreased more slowly with increasing distance and was constant after 2 Mb of distance and the decline was almost linear with log-transformed distance. The average $r^2$ between adjacent SNP pairs ranged from 0.20 to 0.31 in each chromosome and whole average was 0.26, while the whole average $r^2$ between all SNP pairs was 0.02. We observed an initial pattern of decreasing $N_e$ and estimated values were closer to 41 at 1 ~ 5 generations ago. The effective population size (41 heads) estimated in this study seems to be large considering Jeju horse's population size (about 2,000 heads), but it should be interpreted with caution because of the technical limitations of the methods and sample size.

• Journal of Crop Science and Biotechnology
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• v.11 no.3
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• pp.215-222
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• 2008

Multilocation trials on 36 rice(Oryza sativa) genotypes of 3 different maturity groups were conducted at four different locations of Orissa for 3 years and 30 ragi(Eleusine coracana) genotypes of 2 different maturity groups were evaluated in three environmental conditions for 3 years. Grain yield data were subjected to stability analysis following linear regression model to estimate adaptability and stability parameters, i.e. b, and $S^2d$ Stability of performance of genotypes was also estimated by two other stability parameters viz., ecovalence W and AMMI stability value ASV. The rice and ragi genotypes of different duration groups showed wide variation in their mean yield, b, $S^2d$, W and ASV parameters. Seeds of the 36 rice and 30 ragi genotypes were treated with 500 and 100 ppm aqueous solution of maleic hydrazide(MH) for 24 hours, respectively to study MH-sensitivity. Sensitivity of genotypes to MH treatment was estimated in terms of seedling growth inhibition index(SGI). The rice and ragi genotypes showed wide differences in their MH-sensitivity in terms of SGI. Relationship of MH-sensitivity of genotypes with their yielding ability, adaptability and stability of performance was tested by contingency $x^2$ test. Low sensitivity of rice and ragi genotypes to MH in terms of SGI appeared to be good indicators of high yielding ability of genotypes. Also, low and high MH-sensitivity of genotypes would be a good indicator of better adaptability to rich and poor environments, respectively, in ragi but not in rice. Low MH-sensitivity of genotypes could be the good indicator of stability of yield performance in rice but not in ragi.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.3
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• pp.327-332
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• 2016

The genetic relationships between different populations and breeds of exotic dairy goats in Thailand were studied using 12 microsatellite markers. Blood samples were obtained from 211 goats from Department of Livestock Development breeding and research farms: 29 Anglonubian (AN), 21 Alpine (AP), 23 Jamunapari (JAM), 50 Saanen (SN), and 88 Toggenburg (TG). Five of the 12 microsatellite markers were found to be polymorphic. A mean of 7.40 alleles per locus was found, with a range from 5 (SPS115 and ETH225) to 11 (TGLA122). We found 24, 27, 19, 32, and 24 alleles in the AN, AP, JAM, SN, and TG breeds, respectively; 37 alleles were present in all breeds. The mean number of alleles in each population ranged from 3.2 (ETH225 locus) to 7.6 (TGLA122 locus). Genetic variability within the breeds was moderate as evidenced by the mean expected heterozygosity of 0.539. The average observed heterozygosity across the 5 markers in all breeds was 0.529 with the maximum observed at the BM1818 locus (0.772) and the minimum at the ETH225 locus (0.248). The observed and expected heterozygosity for all breeds for the 5 microsatellite markers ranged from 0.419 to 0.772 and 0.227 to 0.792, respectively. On the basis of their means, the TGLA122 and BM1818 loci were the most suitable markers for distinguishing genetic diversity among the goats. The estimated average $F_{is}$ value for the breeds ranged from -0.044 (ETH225) to 0.180 (SPS115), while the estimated average $F_{st}$ value ranged from 0.021 (SPS115) to 0.104 (ETH10). These results indicated that TGLA122 and BM1818 markers are suitable to be used for aiding conservation and breeding improvement strategies of dairy.

• Journal of Animal Science and Technology
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• v.62 no.4
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• pp.438-448
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• 2020

This study was performed to increase the accuracy of genomic estimated breeding value (GEBV) predictions for domestic pigs using single-breed and admixed reference populations (single-breed of Berkshire pigs [BS] with cross breed of Korean native pigs and Landrace pigs [CB]). The principal component analysis (PCA), linkage disequilibrium (LD), and genome-wide association study (GWAS) were performed to analyze the population structure prior to genomic prediction. Reference and test population data sets were randomly sampled 10 times each and precision accuracy was analyzed according to the size of the reference population (100, 200, 300, or 400 animals). For the BS population, prediction accuracy was higher for all economically important traits with larger reference population size. Prediction accuracy was ranged from -0.05 to 0.003, for all traits except carcass weight (CWT), when CB was used as the reference population and BS as the test. The accuracy of CB for backfat thickness (BF) and shear force (SF) using admixed population as reference increased with reference population size, while the results for CWT and muscle pH at 24 hours after slaughter (pH) were equivocal with respect to the relationship between accuracy and reference population size, although overall accuracy was similar to that using the BS as the reference.