• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.83-87
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• 2012

The purpose of this study was to estimate genetic parameters for productive traits in swine. Productive traits were considered on average daily gain (ADG), body height (BH) and body length (BL). Genetic analysis was consisted of 18,668 heads for productive traits which were based on on-farm performance tested from May, 2007 to Apr, 2011. For estimating genetic parameters on productive traits, single best model was fitted after finding source of variance on fixed and random effects and estimated with a multiple trait animal model by using DF-REML (Derivative-Free Restricted Maximum Likelihood). The estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire 0.22-0.58 for the average daily gain, 0.34-0.41 for the body height and 0.4-0.52 for the body length, respectively. Phenotypic correlations of average daily gain with body height and body length for the four breeds were 0.42-0.48, 0.53-0.58, 0.34-0.46 and 0.47-0.56, respectively. Phenotypic correlations of body height with body length were 0.41, 0.57, 0.52, 0.59, respectively. The estimated genetic correlation coefficients of average daily gain with body height and body length estimated for the four breeds were 0.34-0.47, 0.70-0.75, 0.17-0.38 and 0.50-0.53, respectively. The estimated genetic correlation coefficients of body height with body length were 0.57, 0.69, 0.61 and 0.71, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.29 no.2
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• pp.175-178
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• 1984

Varietal differences, heritabilities and the relationships of the characters including peduncle size of barley cultivars (Hordeum vulgare L.) were studied. Significant difference of the peduncle size was observed among the varieties. Flag leaf size and flag leaf sheath length also showed significant differences among varieties. Heritabilities of broad sense for peduncle length and diameter were 0.9638 and 0.5652. Heritabilities for flag leaf sheath length, flag leaf length and flag leaf width were 0.8143, 0.7929 and 0.8980, respectively. The peduncle length was significantly correlated with peduncle diameter, stem length, flag leaf sheath length, flag leaf length and kernels per spike. However, no relationship existed between peduncle length and spike length.

• Journal of Animal Science and Technology
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• v.49 no.3
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• pp.303-308
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• 2007

In order to investigate the relation of production traits and reproduction traits the data from Gyungnam heugdon(Berkshire) were analyzed. Pearson correlation coefficients of the reproductive traits including days to first farrowing, days to first breeding and no. of breeding for first litter with back fat thickness were ranged -.24 to -.26. Estimates of heritability and genetic correlation for the reproductive traits including days to first farrowing, days to first breeding and no. of breeding for first litter showed frequent and wide fluctuation due to lack of reproductive records. Pearson correlation coefficients of back fat with litter traits were low, but genetic correlation coefficients were relatively high. Genetic correlation coefficients of back fat with total litter size, pigs born alive, litter weight at birth and litter weight at weaning were .21, .24, .11 and .07 respectively. It suggests that thin back fat thickness deteriorates performance of litter traits. Genetic correlation coefficients of days to 90kg with total litter size, pigs born alive, litter weight at birth and litter weight at weaning were .14, .17, .09 and .00 respectively. This result imply that genetic improvement on the production traits reduce the litter trait performance.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.89-94
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• 2012

The objective of this study was to estimate the genetic parameters and breeding value of swine using their economic traits. The traits considered were age at 90 kilograms body weight (D90 kg), backfat thickness (BF) and eye muscle area (EMA). Estimation of genetic parameters and breeding value from 18,668 heads considering the economic traits were based on farm performance data from May 2007 to April 2011. Estimation of genetic parameters based on economic traits revealed that the single best model was fitted after finding source of variance on fixed and random effects and estimated by a multiple trait model using DF-REML (Derivative-FREE Restricted Maximum Likelihood). In this study, the estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire were about 0.22-0.59 for the D90 kg, 0.47-0.62 for the BF and 0.23-0.37 for the EMA. Genetic correlation of D90 kg with BF and EMA of the four breeds were -0.01-0.24 and -0.35--0.23, respectively. Moreover, the genetic correlation of BF with EMA was -0.68--0.17. On the other hand, the phenotypic correlation of D90 kg with BF and EMA of the four breeds were about 0.01-0.11 and -0.37--0.21, respectively, while the phenotypic correlation of BF with EMA was -0.68--0.17. Results showed that the genetic trends of breeding value every year were decreasing for D90 kg, increasing for BF while for EMA inconsistent values were obtained.

• Journal of agriculture & life science
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• v.51 no.4
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• pp.111-119
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• 2017

The objective of this study is to check the applicability of the improved trait through the nutritional value of loin and the estimation of genetic parameter through the chemical composition analysis(moisture, crude fat, crude protein, crude ash) for Hanwoo carcass traits and loin. The data of 1kg of loin sampled and analyzed for 2,033 Hanwoo progeny test(steers) from $47^{th}$ to $57^{th}$ were used as the disclosure material used in this study. The study resulted that the heritability for carcass weight, eye muscle area, back fat thickness and marbling score which are Hanwoo carcass traits was estimated to be 0.37, 0.51, 0.44 and 0.57, respectively and the heritability for moisture, crude fat, crude protein and crude ash which are the chemical composition analysis to be 0.62, 0.64, 0.58 and 0.12, respectively. And the genetic correlation estimate between carcass weight and crude fat was 0.35, and marbling score with moisture, crude fat, crude protein and crude ash was -0.966, 0.964, -0.924 and -0.664, respectively. The genetic correlation between moisture and crude fat, crude protein was analyzed to be -0.998, 0.969 and a high genetic correlation was shown in crude fat and crude protein, -0.979. As the chemical composition analysis value showed high heritability in moisture, crude fat and crude protein, improved traits are considered to be available.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.15
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• pp.33-59
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• 1974

A series of experiments were conducted at Crop Experiment Station from 1968 to 1971 to obtain basic information on effects of selection on yield of wheat varieties. Heritability estimates, correlation and path coefficients computed for yield and yield related characters from fixed variety groups-Korean, U.S., and Japan; early and late-$F_2$ and $F_3$ generations were studied. The same estimates for fixed variety groups grown under different fertilizer levels and years were also studied. The results were summarized as follow: 1. Three variety groups classified by their origins as Korea, United States and Japan showed high heritability estimates for heading date, plant height and spike length. The heritability estimates for grain number per spike and 1, 000 grain weight were moderate and those for the number of spikes per plant and grain yield were low. Very low estimates of heritability were obtained for grain number per spike and yield of variety group from the Unites States. 2. High genotypic correlation coefficients between 1, 000 grain weight and yield were obtained for all variety groups originated from Korea, United States and Japan and early variety group, except late variety group. The genotypic correlation coefficients between grain number per spike and yield were also high for all variety groups except variety group originated from the United States. 3. The direct effects of 1, 000 grain weight in terms of path-coefficients to yield were high for all variety groups except late variety group. 4. High genotypic correlation coefficients were obtained between 1, 000 grain weight and yield in $F_2$ from. two crosses. The same degree of genotypic correlation coefficients were obtained between grain number per spike and yield, although slight differences in its magnitude were found depending upon the cross combination. 5. The analysis of path-coefficients in $F_2$ shows that the direct effects of yield components to yield were negligible. 6. The characters that showed high genotypic correlation coefficients with yield in $F_3$ were 1, 000 gnain weight and grain number per spike. These characters showed also high direct effects to yield. 7. No great variations of heritability estimates for heading date, plant height and spike length were obtained for either fertilizer responsive or non responsive variety group due to fertilizer levels applied. 8. Heritability estimates of 1, 000 grain weight in fertilizer responsive group and yield in fertilizer nonresponsive group were high as level of fertilizer increased. 9. Heritability estimates for grain number per spike and 1, 000 grain weight of fertilizer non-responsive-group were higher than those of fertilizer. responsive group. 10. Genotypic corretation coefficients between yield and 1, 000 grain weight in fertilizer responsive group were getting lower as the level of fertilizer increased and those in fertilizer non-responsive group were vice versa. 11. Genotypic correlation coefficient between yield and spike number per plant in fertilizer responsive group was high. However, the genotypic correlation coefficient between yield and spike number per plant in fertilizer non-responsive group was low. 12. The direct effects of 1, 000 grain weight to yield were higher than other yield components either in fertilizer responsive or non-responsive group regardless of levels of fertilizer applied. The spike number per plant, however, was high only when high level of fertilizers were applied to fitilizer responsive group. 13. Slight variations of heritability estimates for heading dates, plant height, spike length, grain number per spike and 1, 000 grain weight were obtained between years. However, the spike number per plant with low heritabilility showed great variation between years. 14. The character that showed high genotypic correlation coefficients with yield in two years was 1, 000 grain weight, and this character was also high in direct effect to yield in terms of path-coefficients. 15. From the above experimental results, it might be concluded that 1, 000 grain weight would be one of the most important characters to increase the effects of selection for yield in wheat breeding in Korea.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.617-626
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• 2009

A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a ${\delta}$-sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the ${\delta}$-sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.

• Korean Journal of Poultry Science
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• v.16 no.2
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• pp.83-89
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• 1989

This study was conducted to estimate heritabilities, genetic and phenotypic correlations on egg compositions in layers. The data analysis were a total of 6,097 eggs in S. C. W. Leghorn and R. I. Red from March 1, 1980 to July 31, 1981. The results obtained are summarized as follows； 1. The average albumen weight at first egg, 300 and 500 days of age were 28.67, 36.25 and 37.51g in the S. C. W. Leghorn, and 28.95, 36.01 and 36.85g in the R. I. Red, respectively. The yolk weigh at first egg ,300 and 500 days were 9.21, 15.94 and17.86g in the S. C. W. Leghorn,9.46, 16.43 and 18.54g in the R. I. Red, respectively. The shell weight at first egg, 300 and 500 days were 4.04, 5.39 and 5.40g in the S. C. W. Leghorn, and 3.66, 5.13 and 5.28g, respectively. 2. The heritability estimates based on the variance of sire and dam components were 0.631-0.164 and 0.412-0.496 in the S. C. W. Leghorn,0.234-0.563 and 0.477-0.610 in the R. I. Red for albumen weight； 0.213-0.530 and 0.343-0.613 in the S. C. W. Leghorn, 0.253-0.437 and 0.389-0.477 in the R. I. Red for yolk weight； 0.427-0.602 and 0.336-0.409 in the S. C. W. Leghorn, 0.141-0.281 in the R. I. Red for shell weight, respectively. 3. The genetic correlation coefficients of egg compositions were as follows； In the S. C. W. Leghorn and R. I. Red, the coefficients between albumen weight and yolk weight, 0.082-0.339 and 0.142-0.465； between albumen weight and shell weight, 0.674-0.952 and 0.216-0.546； between yolk weight and shell weight,0.173-0.171 and 0.121-0.749, respectively.

• Journal of the Korean GEO-environmental Society
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• v.13 no.12
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• pp.17-25
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• 2012

In this study, dielectrical constant of the ground was measured using TDR method and correlated with water contents and density of ground. In order to evaluate the applicability as a cavity exploration, model experiments were carried out to analyze the effects of cavity size on the dielectrical constant. Test result indicated that dielectrical constant of the ground tended to linearly increase with the increase in water contents and density, which can be represented in a certain relational expression. Also, the dielectrical constant of ground varied sensitively with the cavity size of ground. The results conclude that the dielectrical constant, water contents and density of the ground proved to have a correlation among them, and the dielectrical constant is expected to be a basic data on cavity exploration.

• Journal of Animal Science and Technology
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• v.54 no.1
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• pp.9-14
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• 2012

The purpose of this study was to estimate heritabilities and genetic correlations for reproductive and productive traits and to apply their estimates to selection strategies in a swine population. Reproductive and productive traits considered in this study were number of born alive piglet (NBA), number of weaned piglet (NW), loin eye area (LEA), days to 90 kg (D90KG), back fat thickness (BF), and lean meat content (LEAN). Data were collected from 9,886 litters on 2,447 sows for reproductive traits and 10,181 gilts and boars for productive traits from Jan. 2000 to Dec. 2008 in a swine GGP farm. The statistical model to estimate genetic parameters for considering traits was a multiple traits animal model with including animal and maternal additive effects and litter effects on reproductive traits and animal additive effects on productive traits as random as well as some of fixed effects. For estimating (co) variance components of several random effects, restricted maximum likelihood methodology was used on this assumed model. The estimated heritabilities by animal additive effects and maternal effects were 0.07 and 0.02 for NBA and 0.03 and 0.02 for NW, respectively. Genetic correlation estimate for direct genetic effects between NBA and NW was 0.14. Heritability estimates for direct genetic effects were 0.19, 0.39, 0.36, and 0.43 for LEA, D90KG, BF and LEAN, respectively. The genetic correlation of LEA with LEAN was 0.35. Productive traits were antagonistically correlated with reproductive traits. From these results it is concluded that, if selection is done for strong positive effects of reproductive traits, then this would decline productive performance.