• Journal of Korean Society of Forest Science
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• v.42 no.1
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• pp.74-82
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• 1979

Pinus densiflora S. et Z. which has the widest distribution and highest stock at present in Korea and has used as materials for fuel, house construction, furniture and many other purposes for several hundred years, is considered as one of major species of economic importance, although there are a few epidemic insect injuries and silvicultural difficulties in regeneration. However, since disorderly cutting has been conducted for long time, the valuable local stands have disappeared. Therefore immediate attempts should be taken on the gene conservation and genetic studies including heritabilities and genetic gains of desirable characters. One hundred and twently five plus trees have so far been selected from the nationwide area and kept for the purpose of seed orchard establishment and other theoretical studies. In this study, the wind pollinated seeds of grafted stocks of 13 plus trees in clone bank located in Suweon and the seeds of 4 Japanese plus trees were collected and their progenies were used for heritability study. As indicated in figure 1, thirteen plus trees are from the middle part of Korea and two experimental plantations were laid out in ]972 (1-1 stock) by the randomized block design with five replications, consisting of 10 trees line plots of each family in each replication. Tree height, root collar diameter and branch diameter at 1cm apart from the main stem were measured. The results are summarized as follows 1. The rank of height growth of each plus tree progenies by age was greatly changed under age 3 and it was affected more in poor site than good site. 2. The heritabilities of height growth were estimated to be 7.2% at age 3, negative sign at age 4, 9.4% at age 5, 13.0% at age 6, 8.1% at age 7 and abrupt increase of 63.8% at age 8. The heritabilities were generally increased with increase of age. 3. The heritabilities of root collar diameter and branch diameter (average of the three biggest branches) was 3.2% and 11.8% at age 8 respectively. 4. The genetic gain was largest at age 8 and it was 46.6% when a selection intensity, 1/500 was taken. It, therefore, seems to be reasonable that selection should not be made under age 7.

• Korean Journal of Poultry Science
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• v.22 no.2
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• pp.67-75
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• 1995

The present study was conducted to estimate production performances, heritabilities, and genetic and phenotypic correlations on several economic traits in Korean native chicken. Data analyzed were the records of 1,096 pullets produced from 180 dams and 26 sires of Korean native chicken from April 19,1994 to February 26, 1995. Results obtained are surnmarized as follows: 1. The body weights(X${\pm}$SD) at 2, 8, 14 and 20 weeks of age were 114${\pm}$13, 690${\pm}$114, 1,163${\pm}$238, and 1,687${\pm}$349g, respectively. The age at first egg was 165.95${\pm}$14.54 days, and the number of eggs produced by 300 days of age were 70.78i23.47. The egg weights of the first egg and at 300 days of age were 37.88${\pm}$3.73 and 50.97${\pm}$3.69 g, respectively. 2. The heritability estimates of body weight based on the variance of sires, dams and combined components were 0.149, 0.298, and 0.224 at 8 weeks of age: 0.162, 0.220, and 0.192 at 20 weeks of age, respectively. 3. The heritability estimates of egg production traits based on the variance of sires, dams, and combined components were 0.232, 0.504, and 0.368 for age at first egg; 0.113, 0.172, and 0.143 for number of egg production by 300 days of age: 0.174, 0.352, and 0.236 for egg weight at 300 days of age, respectively. 4. The genetic correlation coefficients of some economic traits were as follows: between body weight and age at first egg, -0.354~-0.048; between body weight and number of egg production, -0.279~ -0.002; between body weight and egg weight, 0.338~0.977; between age at first egg and number of egg production, -0.791; between age at first egg and egg weight, 0.009~0.178; between number of egg production and egg weight, -0.572~ -0.256, respectively. 5. The phenotypic correlation coefficients of some economic traits were as follows: between body weight and age at first egg, -0.179~-0.006 between body weight and number of egg production, -0.045~0.074: between body weight and egg weight, 0.229~0.404: between age at first egg and number of egg production, -0.588: between age at first egg and egg weight, -0.029~0.597: between number of egg production and egg weight, -0.376~0. 019, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.8
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• pp.1085-1090
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• 2002

Genetic parameters for birth weights (BWT), calving ease scores observed from calves born by heifers (CEH), and calving ease scores observed from calves born by cows (CEC) were estimated using Bayesian methodology with Gibbs sampling in different threshold animal models. Data consisted of 77,458 records for calving ease scores and birth weights in Gelbvieh cattle. Gibbs samplers were used to obtain the parameters of interest for the categorical traits in two univariate threshold animal models, a bivariate threshold animal model, and a three-trait linear-threshold animal model. Samples of heritabilities and genetic correlations were calculated from the posterior means of dispersion parameters. In a univariate threshold animal model with CEH (model 1), the posterior means of heritabilities for calving ease was 0.35 for direct genetic effects and 0.18 for maternal genetic effects. In the other univariate threshold model with CEC (model 2), the posterior means of heritabilities of CEC was 0.28 for direct genetic effects and 0.18 for maternal genetic effects. In a bivariate threshold model with CEH and CEC (model 3), heritability estimates were similar to those in unvariate threshold models. In this model, genetic correlation between heifer calving ease and cow calving ease was 0.89 and 0.87 for direct genetic effect and maternal genetic effects, respectively. In a three-trait animal model, which contained two categorical traits (CEH and CEC) and one continuous trait (BWT) (model 4), heritability estimates of CEH and CEC for direct (maternal) genetic effects were 0.40 (0.23) and 0.23 (0.13), respectively. In this model, genetic correlation estimates between CEH and CEC were 0.89 and 0.66 for direct genetic effects and maternal effects, respectively. These estimates were greater than estimates between BWT and CEH (0.82 and 0.34) or BWT and CEC (0.85 and 0.26). This result indicates that CEH and CEC should be high correlated rather than estimates between calving ease and birth weight. Genetic correlation estimates between direct genetic effects and maternal effects were -0.29, -0.31 and 0.15 for BWT, CEH and CEC, respectively. Correlation for permanent environmental effects between BWT and CEC was -0.83 in model 4. This study can provide genetic evaluation for calving ease with other continuous traits jointly with assuming that calving ease from first calving was a same trait to calving ease from later parities calving. Further researches for reliability of dispersion parameters would be needed even if the more correlated traits would be concerned in the model, the higher reliability could be obtained, especially on threshold model with property that categorical traits have little information.

• Journal of Animal Science and Technology
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• v.52 no.3
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• pp.187-190
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• 2010

The objective of this study was to estimate genetic parameters for total number of born (TNB), number of born alive (NBA) and teat numbers (TN) of Landrace and Yorkshire breeds in Korean swine population using multiple trait animal model procedures. Total numbers of 4,653 records for teat numbers and 8,907 records for TNB and NBA collected from 2004 to 2008 on imported breeding pigs and their litter size records were used in this study. To find the appropriate model for estimation of genetic parameters (heritabilities and genetic correlations), five statistical models (two models for reproductive traits, two models for teat numbers, one model for combining these traits) considering only direct additive genetic effects, including maternal effects were used and Akaike information criteria (AIC) of each two models for reproductive traits and teat trait were compared. The means and standard deviations of TNB, NBA, and TN were $11.52{\pm}3.34$, $10.55{\pm}2.96$ and $14.30{\pm}0.83$, respectively. Estimated heritabilities for TNB and NBA traits using the model which considered only additive genetic effect were low (0.06 and 0.05, respectively). However, estimated heritabilities considering maternal genetic effects were a little bit higher than that of the model considering only additive genetic effect (0.09 for TNB and NBA, respectively). Estimated heritability for TN using the model which considered only additive genetic effect was 0.40. However, estimated heritability of direct genetic effects from a model considering maternal genetic effect was high (0.60). All results of AIC statistics, the models considering maternal effect was more appropriate than the models considering only additive genetic effect. Genetic correlations of direct additive genetic effect between litter size (TNB, NBA) and teat numbers were low (-0.18 and -0.14, respectively). However, genetic correlations of maternal effect between litter size (TNB, NBA) and teat numbers were a little bit higher than those of direct additive genetic effect (0.08 and 0.16, respectively).

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.229-236
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• 2014

This study presents the estimates of heritabilities of body measurement traits and carcass traits, and genetic and phenotypic correlations of those traits for crossbred pigs in Korea. Body and ultrasound (A mode: Piglog 105) measurements in 221 pigs including body weight, length, height and width, three back fat thickness at the points of 4th, 14th rib and chine bone, eye muscle area and lean meat percent were collected at the ages of 70, 145 and 180 days and then slaughtered to measure carcass weight, back fat, belly, collar butt, spare rib, picnic shoulder, hind leg, loin, tenderloin, lean meat yield and intramuscular rough fat content in loin. Genetic analysis was done using a multi-trait animal model. Heritabilties of the body measurements were ranged from 0.331 to 0.559 and three measurements of back fat thickness were also high as range varying from 0.402 to 0.475 for the ages of 145 and 180 days. However, eye muscle area was moderate (0.296) at the age of 180 days. Heritabilities of retail cut yields were also high as ranged from 0.387 to 0.474 and of IMF content in loin was 0.499. Heritabilities of the cut percent traits were ranged from 0.249 to 0.488. Important positive genetic and phenotypic correlations were noted for all carcass yield traits (0.298 to 0.875 and 0.432 to 0.922, respectively). IMF showed low negative genetic correlations with carcass yield traits, such as carcass weight, picnic shoulder, hind leg, loin, tenderloin and lean meat yield whereas low positive genetic correlations with back fat, belly, collar butt and spare rib. Loin, tenderloin and lean meat percent showed negative genetic correlations with carcass weight, back fat thickness, collar butt, spare rib and picnic shoulder percent. The four body measurements at the ages of 70, 145 and 180 days had positive genetic correlations with belly, shoulder butt, spare rib, picnic shoulder and hind leg percent, but negative genetic correlations were shown with loin and tenderloin percent except body measurements at 70 days. The results suggest that carcass yield are negatively correlated with intramuscular fat content, which is a major factor deciding pork quality and the yield of loin and tenderloin are not increased as much as increase in body size. However, the proportions of belly and collar butt are increased with the body size. In conclusion, selection strategy should be designed according to the preference on composition of carcass in each country.

• Plant Resources
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• v.8 no.1
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• pp.9-12
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• 2005

TO select the most suitable crop and variety of forage for productivity at the southern part of Korea, The crops of wheat, barley and rye were grown from Oct. 1999 to June 2000. Paldanghomil variety of rye crop was shown to have the highest productivity in comparison to other varieties of crops used in this experiment. It showed relatively high plant height, number of tiller, forage yield and dry matter yield. There fore, it was concluded that Paldanghomil of rye crop was the most suitable crop with high yield in the southern part of Korea. The heritabilities of all characters were estimated to be high.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1252-1256
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• 2006

This study estimated the effects of parity (1-3) and stage of lactation (early, mid and late) on daily milk yield (DMY), somatic cell score (SCS), milk urea nitrogen (MUN), blood glucose, and immunoglobulin G (IgG), their heritabilities and genetic correlations between them in Holsteins (n = 200). Means and standard deviations of DMY, SCS, MUN, blood glucose, and IgG in the experimental herd were $23.35{\pm}7.75kg$, $3.81{\pm}2.00$, $13.99{\pm}5.68mg/dl$, $44.91{\pm}13.12mg/dl$, and $30.36{\pm}6.72mg/ml$, respectively. DMY was the lowest in first parity, and in late lactation. SCS increased with parity; however, it was lowest in mid-lactation. MUN was lowest in first parity, and no difference was noted across stage of lactation. Blood glucose was similar between parities, however the highest blood glucose was observed during mid lactation. IgG level was significantly different between first and second parity; however, stage of lactation did not affect its level. Heritability of DMY was 0.16. Its genetic correlations with SCS and with blood glucose were -0.67 and 0.98, respectively. Heritability of SCS was 0.15. Genetic correlations of SCS with MUN, glucose, and IgG were -0.72, -0.59, and 0.68, respectively. Heritability of MUN was estimated to be 0.39 and had a genetic correlation of -0.35 with IgG. Heritabilities of blood glucose and IgG were 0.21 and 0.33, respectively. This study suggested that MUN, blood glucose and IgG could be considered important traits in future dairy selection programs to improve milk yield and its quality with better animal health and welfare. However, further studies are necessary involving more records to clarify the relationship between metabolic and immunological traits with DMY and its quality.

• Korean Journal of Poultry Science
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• v.25 no.1
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• pp.1-9
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• 1998

This study was carried out to get the basic and applicable data for breeding plan and selection in order to improve the body shape components in Korean native chicken. The hentabilities and genetic correlations on body shape components were estimated by sire, dam and combined components of variance. Data analyzed were records of 1,096 progenies produced from 180 dams and 26 sires from April, 1994 to September, 1995. On body shape components at 4, 8 and 16 weeks of age, the shank lengths were 55.63, 82.94 and 103.8Omm: breast girths were 15.087, 21.069, and 26.137mm: breast widths were 40.910, 54.575 and 73.088mm, respectively. The estimates of hentabilities of body shape components based on the variance of sires, dams, and combined components at 4, 8 and 16 weeks of age were O.O65~O.197, O.25O~O.794 and O.185~O.495 for shank length: O.123~O. 215, O.033~O.513 and 0.063~0.257 for breast girth; 0.024~0.158, 0.118~0.410 and 0.111~0.222 for breast width, respectively. The coefficients of genetic correlations among the body shape components at 4 weeks of age were 0.565, 0.725 and 0.678 for breast girth with breast width, shank length and tibia length : 0.690 and 0.804 for breast width with shank length and tibia length; 0.972 between shank length and tibia length.

• Journal of the Korean Society of Tobacco Science
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• v.14 no.2
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• pp.126-132
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• 1992

This experiment was conducted to examine estimates of heterosis, degree of dominance, heritability and phenotypic and genotypic correlation for several mutant characters in flue-cured tobacco variety. Significant heterosis was noted, recording 2.73 and 6.16% for leaf width, -6.86 and -4.72 for leaf shape index, 19.8 and 23.4% for bacterial wilt disease index in Fl an4 F2 generation, respectively, and -1.44 for days to flower in F2 generation. And also leaf width was appeared partial dominance in Fl, and leaf shape index in Fl and F2, Leaf width in F2 was appeared overdominance. Estimated heritabilities in the broad sense ranged from 0.77 to 0.87 for plant and stalk height and days to flower, while those of leaf number, leaf length and width, leaf shape index and bacterial wilt disease index ranged from 0.50 to 0.65. And the heritabilities in the narrow sense were appeared 0.64 and 0.72 for stalk and plant height, respectively, and the others were ranged from 0.32 to 0.47 Positive genotpic correlations appeared among plant height, stalk height, leaf length and leaf width, and between leaf shape index ands day to flower. And negative genotypic correlations appeared between leaf shape index and plant height and stalk height and leaf width, and between bacterial wilt disease index and leaf length.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1387-1399
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• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.