• Journal of Animal Science and Technology
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• v.48 no.2
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• pp.161-168
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• 2006

Genetic parameters for linear type and composite traits were estimated by using Bayesian inference via Gibbs sampling with a multiple threshold animal model in Holstein cows. Fifteen linear type traits and 5 composite traits were included to estimate genetic variance and covariance components in the model. In this study, 30,204 records were obtained in the cows from 305 sires. Heritability estimates for linear type traits had the estimates as high as 0.28~0.64. Heritability estimates for composite traits were also high, when the traits were assumed to be categorical traits. Final score was more correlated with the composite traits than with the linear type traits.

• Journal of Korean Academy of Nursing
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• v.16 no.2
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• pp.29-35
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• 1986

The Purposes of this study are for the assessment of anxiety level and for identification for factors relating to the anxiety of the normal Pregnant women who are impendign or entering labor. The State-Trait Anxiety Inventory is used as the measure of anxiety. The results of the study are as follows: 1. The correlation between state-anxiety and trait-anxiety is 0.459 and the linear regression is y(State-anxiety) : 0.251$\chi$(Trait -anxiety)＋29.27. 2. The maternal state-anxiety is not related to the variables of the age, the educational level, the occupation, the prenatal care, parity, show, labor pain and delivery type except for the premature or early rupture of the fetal membranes. 3. The maternal trait-anxiety is not related to the above-mentioned variables.

• Animal Bioscience
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• v.35 no.3
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• pp.377-384
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• 2022

Objective: This study was conducted to estimate multi-trait genetic parameters for somatic cell score (SCS), milk yield and type traits in Nigerian Dwarf (ND) goats from the United States. Methods: Data from 1,041 ND goats in the United States with kiddings in 95 herds were used to estimate multi-trait genetic parameters for SCS, milk (MILK), fat (FAT), and protein (PROT) yields, and 14 type traits. An 18-trait mixed linear animal model for lactation mean SCS (Log₂), MILK, FAT, PROT, and 14 type traits was applied. A factor analytic approach (FA1) in ASReml software was used to obtain convergence. Results: Averages for SCS were low (2.85±1.29 Log₂), and were 314±110.6, 20.9±7.4, and 14±4.9 kg, respectively, for MILK, FAT, and PROT. Heritabilities for SCS, MILK, FAT, and PROT were 0.32, 0.16, 0.16, and 0.10, respectively. The highest heritabilities for type traits were for stature (0.72), teat diameter (0.49), and rump width (0.48), and the lowest estimates were for dairyness (0.003) and medial suspensory ligament (0.03). Genetic correlations of SCS with MILK, FAT, and PROT were positive but low (0.25, 0.18, and 0.23, respectively). Genetic and phenotypic correlations between MILK, FAT, and PROT were high and positive (≥0.66). Absolute values of genetic correlations involving SCS with type traits were generally low or no different from zero. Most of the phenotypic correlations involving SCS with type traits were low. No serious unfavorable genetic correlations between milk yield traits and SCS or between milk yield traits or SCS and type traits were found. Conclusion: Genetic variation exists in the ND breed for most studied traits. The development of selection programs based on these estimates may help accelerate favorable multi-trait genetic changes in this breed.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.19-33
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• 2008

Linear regression method, proposed by Haseman and Elston(1972), for detecting linkage to a quantitative trait of sib pairs is a linkage testing method for a single locus and a single trait. However, multivariate methods for detecting linkage are needed, when information from each of several traits that are affected by the same major gene are available on each individual. Amos et al. (1990) extended the regression method of Haseman and Elston(1972) to incorporate observations of two or more traits by estimating the principal component linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. But, it is impossible to control the probability of type I errors with this method at present, since the exact distribution of the statistic that they use is yet unknown. In this paper, we propose a multivariate nonparametric trend test for detecting linkage to multiple traits. We compared with a simulation study the efficiencies of multivariate nonparametric trend test with those of the method developed by Amos et al. (1990) for quantitative traits data. For multivariate nonparametric trend test, the results of the simulation study reveal that the Type I error rates are close to the predetermined significance levels, and have in general high powers.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.4
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• pp.476-484
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• 2015

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

• Animal Bioscience
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• v.34 no.4
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• pp.506-515
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• 2021

Objective: Initial consequence of inbreeding is inbreeding depression which impairs the performance of growth, production, health, fertility and survival traits in different animal breeds and populations. The effect of inbreeding on economically important traits should be accurately estimated. The effect of inbreeding depression on growth traits in sheep has been reported in many breeds. Based on this, the main objective of the present research was to evaluate the impact of inbreeding on some growth traits of Iranian Baluchi sheep breed using quantile regression model. Methods: Pedigree and growth traits records of 13,633 Baluchi lambs born from year 1989 to 2016 were used in this research. The traits were birth weight, weaning weight, six-month weight, nine-month weight, and yearling weight. The contribution, inbreeding and co-ancestry software was used to calculate the pedigree statistics and inbreeding coefficients. To evaluate the impact of inbreeding on different quantiles of each growth trait, a series of quantile regression models were fitted using QUANTREG procedure of SAS software. Annual trend of inbreeding was also estimated fitting a simple linear regression of lamb's inbreeding coefficient on the birth year. Results: Average inbreeding coefficient of the population was 1.63 percent. Annual increase rate of inbreeding of the flock was 0.11 percent (p<0.01). The results showed that the effect of inbreeding in different quantiles of growth traits is not similar. Also, inbreeding affected differently on growth traits, considering lambs' sex and type of birth. Conclusion: Quantile regression revealed that inbreeding did not have similar effect on different quantiles of growth traits in Iranian Baluchi lambs indicating that at a given age and inbreeding coefficient, lambs with different sex and birth type were not equally influenced by inbreeding.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.5
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• pp.463-469
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• 1998

Factor analysis was applied as a multivariate statistical technique to official genetic evaluations of type classification traits for 1,265,785 Holstein cows and 10,321 sires computed from data collected between August 1982 and June 1994 in Canada. Type traits included eighteen linear descriptive traits and eight major score card traits. Principal components of the factor analysis showed that only five factors explain the information of the genetic value of linear descriptive traits for both cows and sires. Factor 1 included traits related to mammary system, like texture, median suspensory, fore attachment, fore teat placement and rear attachment height and width. Factor 2 described stature, size, chest width and pin width. These two factors had a similar pattern for both cows and sires. In constrast, Factor 3 for cows involved only bone-quality, while in addition for sires, Factor 3 included foot angle, rear legs desirability and legs set. Factor 4 for cows related to foot angle, set of rear leg and leg desirability, while Factor 4 related to loin strenth and pin setting for sires. Finally, Factor 5 included loin strength and pin setting for cows and described only pin setting for sires. Two factors only were required to describe score card traits of cows and sires. Factor 1 related to final score, feet and legs, udder traits, mammary system and dairy character, while frame/capacity and rump were described by Factor 2. Communality estimates which determine the proportion of variance of a type trait that is shared with other type traits via the common factor variant were high, the highest ${\geq}$ 80% for final score, stature, size and chest width. Pin width and pin desirability had the lowest communality, 56% and 37%. Results indicated shifts in emphasis over the twelve-year period away from udder traits and dairy character, and towards size, scale and width traits. A new system that computes fmal score from type components has been initiated.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.167-178
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• 2016

This study was conducted to estimate genetic parameters for milk production and linear type traits in Holstein dairy cattle in Korea. The data including milk yields, fat yields, protein yields, fat percent, protein percent, somatic score and 15 linear type traits for 10,218 first parity cows collected by Dairy Cattle Improvement Center, National Agricultural Cooperative, Korea, which were calving from January 2009 to April 2013. Genetic and error (co)variances between two traits selected form 19 traits were estimated using bi-trait pairwise analyses with WOMBAT package. The estimated heritabilities for milk yield(MY), fat yield(FY), protein yield(PY), fat percent(FP), protein percent(PP), somatic cell score(SCS), udder depth(UD), udder texture(UT), median suspensory(MS), fore udder attachment(FUA), front teat placement (FTP), rear attachment height(RAH), rear attachment width(RAW), rear teat placement(RTP), front teat length(FTL), foot angle(FA), heel depth(HD), bone quality(BQ), rear legs side view(RLSV), rear legs rear view(RLRV) and locomotion(LC) were 0.128, 0.144, 0.100, 0.273, 0.333, 0.090, 0.179, 0.066, 0.104, 0.109, 0.127, 0.099, 0.059, 0.069, 0.154, 0.014, 0.010, 0.052, 0.065, 0.175 and 0.031, respectively. Among the genetic correlations, UD, UT, FTP, RAW, FTL, FA and RLSV with MY were -0.334, 0.271, 0.445, 0.544, 0.076, -0.281 and -0.228, respectively, and MS, FTP, RTP, FTL, FA, BQ, RLSV, RLRV and LC with PP were -0.147, -0.182, -0.262, -0.136, 0.355, 0.311, 0.135, 0.233 and 0.143, respectively. Especially, MY had the highest positive genetic correlation with RAW (0.544), while SCS had the highest negative genetic correlation with LC (-0.603). FP had negative genetic correlation with most udder traits, whereas, FP had positive genetic correlation with leg and hoof traits (0.056 - 0.355).

• Journal of agriculture & life science
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• v.45 no.6
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• pp.109-114
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• 2011

The objective of this study was to investigate the effects of environments (farms born, testing groups, age at the tests, date at slaughter, ages at slaughter) on body weights at 6, 12, 18 and 24 months of ages, body type measurements at 18 months of age and carcass characteristics in Hanwoo steer populations that were collected from commercial farms and reared in a progeny testing station. Performances of a total of 1,838 steer calves set for tests from 2004 to 2008 were recorded. Carcass characteristics were the carcass grading results evaluated and data collected slaughter scores at 24 months of age. For growth traits of all age classes and body type traits measured at 18 months of age, farms born, test group and linear covariate of age at test were fit in the models. For carcass traits, date at slaughter and linear covariate of ages at slaughter were fit in the models. Effect of farm at birth was not significant for body weight at 24 months of age. Carcass weight, eye muscle area, yield score and back fat thickness were affected by dates at slaughter but not by the ages at slaughter. Marbling score, however, was affected by these two effects. Farms at birth did not seem to affect body type measures greatly. This study will be utilized for Hanwoo Steers genetic evaluation.

• 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.