• Asian-Australasian Journal of Animal Sciences
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• v.12 no.7
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• pp.1015-1018
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• 1999

Single trait mixed models have been dominantly utilized for genetic evaluation of the reproductive traits in swine. However employing multiple trait approach may lead to more accurate genetic evaluations. For 5 litter size and litter weight traits of Danish Landrace, genetic parameters were estimated with a multiple trait mixed model. The heritability estimates were 0.02, 0.03, 0.03, 0.05, and 0.07, respectively for litter size at birth, litter size born alive, litter weight at birth, litter size at weaning, and litter weight at weaning. Negative genetic correlations were all positive. The litter weight at birth showed genetic antagonism with litter size born alive (-0.65) and litter size at weaning (-0.31), but positive with litter size at birth (0.47) and litter weight at weaning (0.31). The estimates of environmental correlations were larger than their corresponding genetic correlation estimates except for those between litter weight at birth and the other four traits. This study recommends simultaneous selection for two or more traits with multivariate mixed models in order to improve overall economic response.

• Journal of Animal Science and Technology
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• v.54 no.4
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• pp.275-282
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• 2012

The data including milk yields, fat and protein percent for 628,395 heads collected by National Agricultural Cooperative Federation, 15 type traits and final score for 62,262 heads collected by Korea Animal Improvement Association, which were born in 1998 to 2004, and net profits calculated from milk price and raising expenses of individuals were used to estimate genetic parameters. The highest positive genetic correlation, 0.81, was shown between body depth (BD) and loin strength (SR). Genetic correlations between body depth (BD) and udder depth (UD), front teat placement (TP) and front teat length (TL) were -0.23, which were lowest among the linear type traits. Furthermore, medium level of negative genetic correlations were shown the milk yield with milk contents rate traits. Mostly low level of positive genetic correlations were shown between the milk traits and linear score traits except milk yield and stature. Most of the genetic correlations of between the linear score traits and net profit were low level of positive or negative genetic correlations. Among the genetic correlations, body depth (BD), angularity (DF) and rear attachment width (UW), and final score (FS) with net profit were high as 0.17, 0.17, 0.18 and 0.18, respectively. Finally all of the genetic correlations between net profit and milk traits were positive and higher than the linear traits with positive genetic correlations. The results of this study suggest that net profit has been related with the linear traits, such as body depth (BD), angularity (DF) and rear attachment width (UW) traits, and furthermore, milk traits including yield and contents rates influence positively and greatly on net profit.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.1
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• pp.1-6
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• 2010

The objectives of this study were to i) investigate genetic performance for linear type traits of individual Holstein dairy cows, especially focusing on comparative traits, and to estimate genetic variances for these traits using actual data, and ii) compare genetic performance and improvement of progeny by birth country of the cows. Linear type traits defined with five comparative traits on this study were general stature composite (GSC), dairy capacity composite (DCC), body size composite (BSC), foot and leg composite (FLC), and udder composite (UDC). These traits were scored from 1 to 6 with 1 = poor, 2 = fair, 3 = good, 4 = good plus, 5 = very good and 6 = excellent. Final scores (FS) were also included in this study. Data used was collected from the years 2000 to 2004 by the Korea Animal Improvement Association (KAIA). Only data of more than five tested cows by herd appraisal date and by sires having more than ten daughters were included to increase the reliability of the data analyses. A total of 30,204 records of the selected traits, which was collected from 26,701 individuals having pedigree information were used. Herd appraisal date, year of age, lactation stage (grouped by month), and time lagged for milking (in hours) were assumed as fixed effects on the model. Animal additive genetic effects considering pedigree relationship and residual errors were assumed with random effects. Year of age at appraisal date was classified from one to nine years of age, assigning the value of nine years of age for animals that were greater than or equal to nine years of age. From our results, the estimate for heritability was 0.463, 0.346, 0.473, 0.290, and 0.430 on GSC, DCC, BSC, FLC and UDC, respectively. The estimate for FS heritability was 0.539. The greatest breeding values for GSC were estimated for Canada, with the breeding values for American lines increasing for 10 years starting in 1989 but tending to decrease after that until 2004. For DCC, the breeding values for American and Canadian lines showed similar patterns until 1999, after which the breeding values for the American lines declined sharply. For BSC, data from Korea, Canada and the USA followed similar trends overall except when the breeding values of the American lines decreased starting in 1999. Overall, the methods used to evaluate genetic performance in this study were acceptable and allowed for the discovery of differences by country of genetic origin, likely due in part to the American use of selection indexes based primarily on milk yield traits until methods for evaluating other traits began to emerge.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.6
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• pp.789-793
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• 2003

An investigation was conducted on 729 Hariana cows maintained at Government Livestock Farm, Hisar, from 1973 to 1999, with an objective to compare the efficiency of various selection indices for attaining desired genetic gains in the index traits. The various traits included were age at first calving (AFC), service period (SP), calving interval (CI), days to first service (DFS), number of services per conception (NSPC), lactation milk yield (LY), peak yield (PY), dry period (DP). Except for LY, PY and AFC the heritabilities of all other traits were low. Desirable associations among reproductive traits are supportive of the fact that any one of these traits incorporated in simultaneous selection is expected to cause correlated response in other traits. Production traits (LY and PY) were positively correlated, while DP had low negative genetic correlation with LY, and high genetic correlation with PY. Thus, DP can be taken as additional criteria in selection index for better over all improvement. Almost all production traits except DP had low negative correlation with AFC, SP, DFS and CI meaning that reduction in reproduction traits up to certain level may increase production performance. While, the correlation of NSPC with LY and PY was moderate positive. Among four trait indices I23: incorporating PY, AFC, SP and NSPC and among three trait indices I1: incorporating LY, AFC and SP were the best as these required least number of generations (4.87 and 1.35, respectively) to attain desired goals. Next in order of preference were PY or LY along with DP and SP as the best indices (I20 and I16) of which, index with PY may be preferred instead of LY as it produced considerably high correlated response in LY and reduction in NSPC as well.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.5
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• pp.636-642
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• 2018

Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1074-1080
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• 2017

Objective: The growth, carcass and retail cut yield records on 1,428 Hanwoo steers obtained through progeny testing were analyzed in this study, and their heritability and genetic relationships among the traits were estimated using animal models. Methods: Two different models were compared in this study. Each model was fitted for different fixed class effects, date of slaughter for carcass traits and batch of progeny test live measurement traits, and a choice of covariates (carcass weight in Model 1 or backfat thickness in Model 2) for carcass traits. Results: The differences in body composition among individuals were deemed being unaffected by their age at slaughter, except for carcass weight and backfat thickness. Heritability estimates of body size measurements were 0.21 to 0.36. Heritability estimates of retail cut percentage were high (0.56 from Model 1 and 0.47 from Model 2). And the heritability estimates for loin muscle percentage were 0.36 from Model 1 and 0.42 from Model 2, which were high enough to consider direct selection on carcass cutability traits as effective. The genetic correlations between body size measurements and retail cut ratio (RCR) were close to zero. But, some negative genetic correlations were found with chest girths measured at yearling (Model 1) or at 24 months of age or with chest widths. Loin muscle ratio (LMR) was genetically negatively correlated with body weights or body size measurements, in general in Model 1. These relationships were low close to zero but positive in Model 2. Phenotypic correlation between cutability traits (RCR, LMR) and live body size measurements were moderate and negative in Model 1 while those in Model 2 were all close to zero. Conclusion: Therefore, the body weights or linear body measurements at an earlier age may not be the most desirable selection traits for exploitation of correlated responses to improve loin muscle or lean meat yield.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.741-747
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• 2016

The aim of study was to estimate genetic parameter of carcass traits in commercial Hanwoo steer using national animal model for selection of superior bull. Analyzed data (n=5,843) on carcass traits was collected from 107,020 Hanwoo steer. The animal model was used to estimate heritability and genetic correlations. The estimated heritability of carcass traits were 0.19, 0.17, 0.20 and 0.23 for carcass weight, eye muscle area, backfat thickness and marbling score, respectively. The estimated heritability for carcass traits in commercial Hanwoo are low than estimated heritability of national progeny test population for selection of superior bull because breeding environment, genetic performance of cow and feeding day was different. Therefore, we suggests that animal model can include practical genetic variable based on national animal model to improve genetic performance in commercial Hanwoo.

• Animal Bioscience
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• v.35 no.8
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• pp.1151-1161
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• 2022

Objective: This study was conducted to estimate the association of age at first calving (AFC) with first lactation traits as well as lifetime performance traits in Murrah buffaloes. Methods: Data on first lactation and life time performance of Murrah buffaloes (n = 679), maintained at Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, India during the period 1983 through 2017, were deduced to calculate heritability estimates, genetic and phenotypic correlation of different first lactation and lifetime traits. The univariate animal model was fitted to estimate variance components and heritability separately for each trait, while bivariate animal models were set to estimate genetic and phenotypic correlations between traits under study. Results: The heritability was high for first peak milk yield (FPY, 0.64±0.08), moderate for AFC (0.48±0.07) and breeding efficiency (BE 0.39±0.09). High genetic correlations of first lactation total milk yield (FLTMY) with first lactation standard milk yield (FLSMY, 305 days or less), FPY, and first lactation length (FLL) was seen. Likewise, genetic correlation of AFC was positive with FLTMY, FLL, first dry period (FDP), first service period (FSP), first calving interval (FCI), herd life (HL) and productive days (PD). Significant phenotypic correlation of FLTMY was observed with HL, productive life (PL), PD, total lifetime milk yield (LTMY), standard lifetime milk yield (standard LTMY). Moreover, positive genetic and phenotypic correlation of FPY was observed with HL, PL, PD, total LTMY and standard LTMY. Conclusion: This study reports that AFC had positive genetic correlation with FDP, FSP, FCI, and unproductive days while, negative association of AFC was observed with FLSMY, PL, total LTMY, standard LTMY, and BE. This suggests that reduction of AFC would results in improvement of lifetime performance traits.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.10
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• pp.1335-1340
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• 2011

Different genetic parameters for weaning weight and wool traits were estimated using restricted maximum likelihood (REML) in Angora rabbits. Total wool yield of first (I), second (II) and third (III) clips were taken as a separate trait under study. The records from more than 2,700 animals were analysed through fitting six animal models with various combinations of direct and maternal effects. A log likelihood ratio test was used to select the most appropriate model for each trait. Direct heritability estimates for the wool traits were found to be moderate to high across different models. Heritability estimates obtained from the best model were 0.24, 0.22, 0.20 and 0.21 for weaning weight, clip I, II and III; respectively. Maternal effects especially due to permanent environment had higher importance at clip I and found to be declining in subsequent clips. The estimates of repeatability of doe effect on wool traits were 0.44, 0.26 and 0.18 for clip I, II and III; respectively. Weaning weight had moderately high genetic correlations with clip I (0.57) and II (0.45), but very low (0.11) with clip III. Results indicated that genetic improvement for wool yield in Angora rabbit is possible through direct selection. Further, weaning weight could be considered as desirable trait for earliest indirect selection for wool yield in view of its high genetic correlation with wool traits.