scholarly journals Genetic Parameters of Conformation Traits in Young Polish Holstein-Friesian Bulls

2014 ◽  
Vol 14 (4) ◽  
pp. 831-840
Author(s):  
Agnieszka Otwinowska-Mindur ◽  
Ewa Ptak ◽  
Wojciech Jagusiak ◽  
Andrzej Żarnecki
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Dominant Role ◽  
Genetic Correlations ◽  
Progeny Testing ◽  
Multiple Trait ◽  
Holstein Friesian ◽  
Type Traits ◽  
Genetic And Phenotypic Correlations ◽  
Final Score

Abstract The objective of this study was to estimate the genetic parameters of conformation traits in Polish Holstein-Friesian bulls evaluated for registration in the herd book and for entry into progeny testing. Data were 8 linearly scored (1-9 scale) and 6 composite (scored from 50 to 100) conformation traits of 2,738 young bulls born between 2001 and 2011. The multiple-trait REML method was applied for (co)variance component estimation. The linear model included fixed linear regressions on age at evaluation (from 10 to 23 months), fixed effects of year of birth, fixed effects of herd-classifier, and random animal effect. Heritability estimates for all analysed traits were within the range of 0.04-0.37. Among the 6 composite type traits, heritability was highest for size and for overall conformation score. The lowest heritability was for feet and legs. Among the linearly scored traits, heritability was the lowest for rear legs - side view and foot angle, and the highest for rump angle and muscularity of front end. Composite traits showed the highest genetic correlations with muscularity and final score playing the dominant role. Genetic correlations among linear traits were low and moderate (0.02-0.53). The relatively low genetic and phenotypic correlations indicated that no conformation trait of bulls can be improved by indirect selection alone. More research is needed to establish relationship between bull conformation traits and the conformation of their progeny.

scholarly journals EFFECT OF FIXED FACTORS AND ESTIMATION OF GENETIC PARAMETERS OF GROWTH TRAITS FOR MOUNTAIN KIDS

2019 ◽  
Vol 50 (6) ◽  
Author(s):  
Hermiz & Baper
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Maximum Likelihood Method ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Likelihood Method ◽  
Phenotypic Correlations ◽  
Body Weights ◽  
Genetic And Phenotypic Correlations

Body weights at birth (469), weaning (394) and at six month of age (358) for kids utilized in this study were raised at private project in Duhok governorate, Iraq during two kidding season (2016-2017) and (2017-2018). GLM within SAS programme was used to analyze the data which include the fixed effects (age of doe, year and season of kidding, sex of kid and type of birth, regression on doe weight at kidding, and the regression of later weights of kids on earlier weights) influencing the studied traits. Restricted Maximum Likelihood Method was used to estimate repeatability, heritability, genetic and phenotypic correlations after adjusting the records for fixed effects. Variance components of random effects were tested for positive definite. Overall mean of weights at birth (BWT), weaning (WWT) and 6 month of age (WT6M) were 2.92, 15.32 and 24.45 kg, respectively. Differences among groups of age of doe in all studied traits were not significant, while year of kidding and sex of kid affect all traits significantly (p<0.01). Season of kidding affect BWT and WWT significantly (P<0.01). Single born kids were heavier (P<0.01) than twins in BWT only. Regression of BWT on doe weight at kidding (0.033 kg/kg) was significant (P<0.01), while the regressions of WWT and WT6M were not significant. The regression coefficients of WWT on BWT (1.906 kg/kg) and of WT6M on WWT (0.835 kg/kg) were highly significant (P<0.01). Repeatability estimates for BWT, WWT and WT6M were 0.47, 0.45 and 0.35, respectively; on the same order the estimates of heritability were 0.41, 0.61 and 0.79. Genetic correlations between BWT with each of WWT (0.45) and WT6M (0.55), and between WWT and WT6M (0.68) were highly significant. All phenotypic correlations between each pair of body weights were higher than genetic correlations and ranged between 0.48 and 0.73.

scholarly journals Estimation of genetic parameters and relationships between type traits and milk yield of Holstein cows in Turkey

2021 ◽  
Vol 73 (6) ◽  
pp. 1371-1380
Author(s):  
O. Ermetin ◽  
B. Dağ
Keyword(s):  
Milk Yield ◽  
Selection Criteria ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Scoring Systems ◽  
Holstein Cows ◽  
Phenotypic Correlations ◽  
Type Traits ◽  
Final Score ◽  
Selection For

ABSTRACT In this study, milk yield, reproductive yield, and type traits of 533 Holstein cows in the first lactation raised in 54 farms were examined. In the three-year study, phenotypic (rP) and genetic (rG) correlations between type traits and milk yield were estimated based on the variance elements and heritability of the type traits of Holstein cows in the first lactation. Linear identification and scoring systems have been applied to classify the cows according to type traits. Heritability and correlations were estimated with ASREML models. The type traits included stature, angularity, rump width, hocks, rear udder height, central ligament, teat length, body capacity, feet and legs, udder composite and final score for genetic correlations with 305-day milk yield were estimated as -0.49, -0.14, -0.93, 0.35, 0.40, 0.11, -0.65, 0.70, 0.31, 0.54, and 0.70, for phenotypic correlations were estimated as 0.28, 0.28, 0.30, 0.21, 0.35, 0.39, -0.06, 0.46, 0.48, 0.56, and 0.58 respectively. Among the phenotypic correlations between the type traits, especially the phenotypic correlations between the final score and various type traits were found to be high and significant. The fact that these traits are in high correlation with other traits and milk yield may enable these to be used as indirect selection criteria in the selection for milk yield.

Genetic and phenotypic correlations between linear type traits and production traits in Holstein-Friesian dairy cattle

1994 ◽  
Vol 59 (2) ◽  
pp. 183-187 ◽  
Author(s):  
S. Brotherstone
Keyword(s):  
Milk Fat ◽  
Genetic Correlations ◽  
Protein Yield ◽  
Yield Traits ◽  
Production Traits ◽  
Linear Type ◽  
Phenotypic Correlations ◽  
Holstein Friesian ◽  
Type Traits ◽  
Genetic And Phenotypic Correlations

AbstractFirst lactation production and linear type records of 72 559Holstein-Friesian cows, calving from 1982 to 1989, were analysed by multivariate restricted maximum likelihood, using a sire model. The data comprised offspring of 1066 randomly used sires, and 91 proven i.e. widely used bulls. All phenotypic correlations between the type traits and the yield traits were small, but moderate genetic correlations were obtained between milk, fat and protein yield and angularity (~—0·43) and between the yield traits and udder depth (~0·44), indicating that higher yielding heifers are more angular and have deeper udders. The heritabilities of the type traits were in line with previous analyses, but those for milk, fat and protein yield were rather high at 0·47, 0·52 and 0·45 respectively

scholarly journals Estimation of genetic parameters for daily milk yields of primiparous Iranian Holstein cows

2013 ◽  
Vol 56 (1) ◽  
pp. 455-466
Author(s):  
K. Kheirabadi ◽  
S. Alijani ◽  
L. Zavadilová ◽  
S. A. Rafat ◽  
G. Moghaddam
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
National Level ◽  
Genetic Correlations ◽  
Protein Yield ◽  
Random Regression ◽  
Production Traits ◽  
Multiple Traits ◽  
Multiple Trait

Abstract. Applying a multiple trait random regression (MT-RR) in national level and for whole test day records of a country is a great advance in animal breeding context. Having reliable (co) variance components is a critical step in applying multiple traits genetic evaluation especially in developing countries. Genetic parameters of milk, fat and protein yields were estimated for Iranian Holstein dairy cows. Data included 276 692 test day (TD) production traits records collected of 30 705 primiparous cows belonging to 619 sires. An animal multi-trait random regression model was employed in the analyses using the restricted maximum likelihood (REML) method. The model included herd-test-date, age-season of calving (by applying a fixed regression for each subclass of this effect) and year of calving as fixed effects and random regression (RR) coefficients for additive genetic (AG) and permanent environmental (PE) effects. Obtained results showed that daily heritabilities ranged from 0.10 to 0.21 for milk, from 0.05 to 0.08 for fat and from 0.08 to 0.18 for protein yield. Estimated heritability for 305-d milk, fat and protein yields were 0.25, 0.20 and 0.25, respectively. Correlations between individual test day records within traits were high for adjacent tests (nearly 1) and decreased as the interval between tests increased. Correlations between yields of milk, fat and protein on a given test day are also high and greater during late lactation than during early or mid-lactation. Genetic correlations between 305-d yield traits ranged from 0.75 to 0.92. The largest genetic correlation, as well as permanent environmental correlation, was observed between milk and protein yield.

scholarly journals Heritability, Genetic and Phenotypic Correlations, and Predicted Selection Response of Quantitative Traits in Peach: II. An Analysis of Several Fruit Traits

1998 ◽  
Vol 123 (4) ◽  
pp. 604-611 ◽  
Author(s):  
Valdomiro A.B. de Souza ◽  
David H. Byrne ◽  
Jeremy F. Taylor
Keyword(s):  
Fruit Development ◽  
Fixed Effects ◽  
Prunus Persica ◽  
Genetic Correlations ◽  
Soluble Solids ◽  
Direct Selection ◽  
Multiple Trait ◽  
Phenotypic Correlations ◽  
Development Period ◽  
Genetic And Phenotypic Correlations

Thirteen peach [Prunus persica (L.) Batsch] fruit characteristics were investigated for 3 years, 1993, 1994, and 1995, in College Station, Texas, to determine heritability, genetic and phenotypic correlations, and predicted response to selection. Seedlings of 108 families resulting from crosses among 42 peach cultivars and selections were used in the evaluations. A mixed linear model, with years treated as fixed and additive genotypes as random factors, was employed to analyze the data. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances between traits. Genetic and phenotypic correlations ≥0.65 and <0.30 were considered strong or very strong and weak, respectively. Date of ripening, fruit development period (FDP) and date of full bloom had the highest heritability (h2) estimates, 0.94, 0.91, and 0.78, respectively. Fruit cheek diameter and titratable acidity (h2 = 0.31) were the traits with the lowest estimates. Fruit development period, fruit blush, and date of ripening had the highest predicted selection responses, whereas fruit suture, fruit cheek, L/W12 (ratio fruit length to average fruit diameters), and fruit tip had the lowest values. Most genetic correlations were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. All four measures of fruit size were genetically and phenotypically very strongly correlated. Important genetic correlation estimates were also observed for date of ripening with FDP (ra = 0.93), date of ripening and FDP with fruit blush (ra = -0.77, ra = -0.72), SS (percent soluble solids) (ra = 0.63, ra = 0.62) and TA (ra = 0.55, ra = 0.64), and SS with TA (ra = -0.56). Direct selection practiced solely for early ripening and short FDP is expected to have a greater effect on correlated traits than direct selection for early bloom and large fruit mass.

scholarly journals Estimation of Genetic Parameters of Type Traits in First Parity Cows of the Autochthonous Cika Cattle in Slovenia

2021 ◽  
Vol 12 ◽  
Author(s):  
Mojca Simčič ◽  
Barbara Luštrek ◽  
Miran Štepec ◽  
Betka Logar ◽  
Klemen Potočnik
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Body Frame ◽  
Herd Effect ◽  
Long Time ◽  
Type Traits

The aim of this study was to estimate genetic parameters of 26 individual and four composite type traits in first parity Cika cows. An analysis of variance was performed with the generalized linear model procedure of the SAS/STAT statistical package, where the fixed effects of year of recording, cow’s age at recording and days after calving as a linear regression were included in the model. The variance components for the direct additive genetic effect and the herd effect in all type traits were estimated using the REML method in the VCE-6 software package. The estimated heritabilities ranged from 0.42 to 0.67 for the measured body frame traits, from 0.36 to 0.80 for the scored autochthonous traits, from 0.11 to 0.61 for the scored body frame traits, and from 0.20 to 0.47 for the scored udder traits. The estimated heritabilities for the composite traits called “autochthonous characteristics”, “muscularity”, “body frame” and “udder” were 0.55, 0.19, 0.19, and 0.26, respectively. The estimated genetic correlations among the measured body frame traits were positive and high, while the majority of them among the scored body frame traits were low to moderate. The estimated proportions of variance explained by the herd effect for the composite traits “autochthonous characteristics,” “muscularity,” “body frame” and “udder” were 0.09, 0.28, 0.14, and 0.10, respectively. The estimated heritabilities for the type traits of first parity Cika cows were similar to those reported for other breeds where breeding values have been routinely predicted for a long time. All estimated genetic parameters are already used for breeding value prediction in the Cika cattle population.

scholarly journals The evaluation of genetic parameters of the type of calving in the population of Holstein Friesian cows

Genetika ◽  
2013 ◽  
Vol 45 (1) ◽  
pp. 41-49
Author(s):  
Radica Djedovic ◽  
Vladan Bogdanovic ◽  
Gligorije Trifunovic ◽  
Radmila Beskorovajni ◽  
Dragan Stanojevic
Keyword(s):  
Birth Weight ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Random Effect ◽  
Genetic Correlations ◽  
Correlation Coefficients ◽  
Cattle Breed ◽  
Least Square ◽  
Data Sets ◽  
Holstein Friesian

Genetic parameters (heritability coefficients and genetic correlations) of the type of calving, number of stillbirths and birth weight have been evaluated in the population of Holstein Friesian cattle breed. Data sets have been analysed by means of the Mixed Least Square Model (LSMLMW). Besides a random effect of bull-sires, the model has also included the fixed effects of farm, season, sex, the evaluation of viability of calves and types of birth. Estimated heritability values and heritability errors for the type of calving (TC), number of stillbirths (SB) and birth weight (BWT) were low: 0.190 ? 0.062; 0.018 ? 0.006 and 0.149 ? 0.051, respectively. Heritabilities of the analysed traits were evaluated on the grounds of the calves` bull-sires additive value (direct heritability). The values of the genetic correlation coefficients between examined traits ranged from - 0.251 (correlation between the type of calving and number of stillbirths) to 0.340 (correlation between the number of stillbirths and birth weight).

ESTIMATES OF VARIANCE COMPONENTS FOR HOLSTEIN-TYPE TRAITS

1983 ◽  
Vol 63 (4) ◽  
pp. 763-771 ◽  
Author(s):  
L. R. SCHAEFFER
Keyword(s):  
Key Words ◽  
Variance Components ◽  
Genetic Parameters ◽  
New Method ◽  
Multiple Trait ◽  
Stage Of Lactation ◽  
Holstein Friesian ◽  
Type Traits ◽  
Highly Correlated ◽  
Friesian Cows

Sire and error variances and covariances for 27 conformation traits were estimated from 424 875 Holstein-Friesian cows classified since June 1976. Estimates were obtained by Henderson's new method (Diagonal-MIVQUE) with a model that included 46 age by parity groups, 10 stage of lactation groups, herd-round-classifier effects, and nine covariates of dam's type and sire effects. Heritabilities were generally low from 0.10 for feet and legs to 0.29 for capacity, and from 0.05 for rear heel to 0.42 stature. Final class had a heritability of 0.17 and was highly correlated with traits related to mammary system (0.62–0.94). A multiple trait analysis of type could utilize the estimates from this study. Key words: Genetic parameters, type traits, Henderson's new method

Genetic parameters of British Large White bacon pigs

1962 ◽  
Vol 4 (1) ◽  
pp. 128-143 ◽  
Author(s):  
C. Smith ◽  
J. W. B. King ◽  
N. Gilbert
Keyword(s):  
Principal Components ◽  
Correlation Matrix ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Principal Component ◽  
Progeny Testing ◽  
Genetic Origin ◽  
Large White ◽  
Correlation Pattern ◽  
Genetic And Phenotypic Correlations

Estimates of heritabilities and genetic correlations among 35 measurements and scores of British Large White bacon pigs are reported. The data came from pigs tested at the five National Progeny Testing Stations during the period autumn 1957 to spring 1959, and comprised full records on 1936 pigs from 200 sires. Independent analyses were carried out for each sex, and adjustments were made to the data for differences among stations, six-monthly periods and weight at slaughter.Genetic parameters were estimated from sire components of variation and covariation obtained by conventional heirarchical analyses of variance and covariance. Estimates of the heritabilities and their standard errors are given in Table 2, and of genetic and phenotypic correlations in Table 3. These estimates, which agree in general with other estimates in the literature,, indicate that a large part of the variation and covariation is of genetic origin and that carcass traits, growth rate and food conversion efficiency are amenable to change by selection. Moreover, no serious antagonisms were found to exist with regard to improvement by selection.An attempt has been made to summarise the correlation matrix pattern among 24 of the more important traits by using a principal component analysis. The first two principal components account for a disproportionate fraction of the correlation pattern especially of the genetic correlation matrix. Two principal components are given for each trait; the first may be associated with measurements of fat depth.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

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