scholarly journals Genetic parameter estimates for birth and weaning weights in Raeini goats

2010 ◽  
Vol 55 (No. 1) ◽  
pp. 30-36 ◽  
Author(s):  
M. Gholizadeh ◽  
G. Rahimi Mianji ◽  
M. Hashemi ◽  
H. Hafezian
Keyword(s):  
Birth Weight ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Residual Effects ◽  
Parameter Estimates ◽  
Genetic Covariance ◽  
Weaning Weight ◽  
Variance And Covariance Components ◽  
Estimate Variance ◽  
Additive Genetic Effects

The aim of the present study was to estimate variance components and genetic parameters for birth and weaning weights in Raeini goats. The data were collected from the Breeding Centre of Raeini (BCR) cashmere goats in Kerman province of Iran from 1986 to 2008. Random effects included direct and maternal additive genetic effects, maternal permanent environmental effects with direct-maternal genetic covariance and random residual effects. Variance and covariance components and genetic parameters were estimated using the DFREML program by fitting six single-trait animal models. Depending on the model, h<sub>d</sub><sup>2</sup> varied from 0.057 to 0.323 for birth weight and from 0.043 to 0.229 for weaning weight. Estimates of <I>m</I><sup>2</sup> ranged from 0.016 to 0.289 for birth weight and from 0.01 to 0.184 for weaning weight. The maternal permanent environmental effect was significant for both traits and ignoring maternal effects in the model caused the overestimation of direct heritability.

Variance components due to direct and maternal effects for birth weight of Brown Swiss cattle

2018 ◽  
Author(s):  
Ercan Soydan
Keyword(s):  
Variance Components ◽  
Genetic Parameters ◽  
Least Square ◽  
Residual Effects ◽  
State Farm ◽  
Genetic Covariance ◽  
Brown Swiss ◽  
Variance And Covariance Components ◽  
Estimate Variance ◽  
Additive Genetic Effects

This study was conducted to estimate variance components and genetic parameters for birth weights of Brown Swiss calves. Experimental data were gathered from the records of a State Farm of Turkey (Konuklar) covering the years between 1995 and 2005. Random effects considered in this study included direct and maternal additive genetic effects, maternal permanent environmental effects with direct-maternal genetic covariance and random residual effects. AI-REML algorithm of WOMBAT software was used to estimate variance and covariance components, genetic parameters and breeding values. The general mean for birth weights of all calves was calculated as 38.12±0.006 kg. The least square for mean birth weights was calculated as 38.99±0.007 kg for male calves and as 37.26±0.008 for female calves. Direct heritability (hD2), maternal heritability (hM2), total heritability (hT2), rAM and cAM estimates were respectively calculated as 0.15, 0.10, 0.39, 0.96 and 0.13

scholarly journals Estimation of direct and maternal genetic parameters for weaning weight in Hungarian Simmental cattle

2021 ◽  
pp. 17-22
Author(s):  
Afees Abiola Ajasa ◽  
Imre Füller ◽  
Barnabás Vágó ◽  
István Komlósi ◽  
János Posta
Keyword(s):  
Fixed Effects ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Random Effect ◽  
Ratio Test ◽  
Genetic Covariance ◽  
Weaning Weight ◽  
Simmental Cattle ◽  
Estimate Variance ◽  
Best Fit

The aim of the current research was to estimate variance components and genetic parameters of weaning weight in Hungarian Simmental cattle. Weaning weight records were obtained from the Association of Hungarian Simmental Breeders. The dataset comprised of 44,278 animals born from 1975 to 2020. The data was analyzed using the restricted maximum likelihood methodology of the Wombat software. We fitted a total of six models to the weaning weight data of Hungarian Simmental cattle. Models ranged from a simple model with animals as the only random effect to a model that had maternal environmental effects as additional random effects as well as direct maternal genetic covariance. Fixed effects in the model comprised of herd, birth year, calving order and sex. Likelihood ratio test was used to determine the best fit model for the data. Results indicated that allowing for direct-maternal genetic covariance increases the direct and maternal effect dramatically. The best fit model had direct and maternal genetic effects as the only random effect with non-zero direct-maternal genetic correlation. Direct heritability, maternal heritability and direct maternal correlation of the best fit model was 0.57, 0.16 and -0.78 respectively. The result indicates that problem of (co-)sampling variation occurs when attempting to partition additive genetic variance into direct and maternal components.

PHENOTYPIC AND GENETIC PARAMETER ESTIMATES FOR GESTATION LENGTH, CALVING EASE AND BIRTH WEIGHT IN SIMMENTAL CATTLE

1988 ◽  
Vol 68 (1) ◽  
pp. 291-294 ◽  
Author(s):  
R. A. KEMP ◽  
J. W. WILTON ◽  
L. R. SCHAEFFER
Keyword(s):  
Birth Weight ◽  
Random Mating ◽  
Genetic Parameter ◽  
Parameter Estimates ◽  
Gestation Length ◽  
Calving Ease ◽  
Phenotypic Correlations ◽  
Large Numbers ◽  
Genetic And Phenotypic Correlations ◽  
Variance And Covariance Components

Variance components, heritabilities and genetic and phenotypic correlations were estimated using progeny records of 73 sires on the Young Sire Proving Program (YSPP) of the Canadian Simmental Association. The YSPP was based on random mating of 58 test and 15 reference sires to cows in cooperating herds. Data were collected on several traits but the ones of interest in this study were gestation length (GL), calving ease (CE) and birth weight (BW). Variance and covariance components were estimated using Henderson's method 3. Heritability estimates were 0.24, 0.06 and 0.19 for GL, CE and BW, respectively. Genetic and phenotypic correlations were negative between GL and CE and CE and BW. Correlations between GL and BW were moderate and positive. Selection programs, utilizing large numbers of progeny per sire, would be effective but should incorporate the correlations between these traits. Key words: Heritabilities, genetic and phenotypic correlations, selection

Genetic parameter estimates for early growth traits in Naeini goat

2012 ◽  
Vol 52 (11) ◽  
pp. 1046 ◽  
Author(s):  
Hasan Baneh ◽  
Mojtaba Najafi ◽  
Ghodrat Rahimi
Keyword(s):  
Environmental Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Parameter ◽  
Average Daily Gain ◽  
Parameter Estimates ◽  
Estimate Variance ◽  
Daily Gain ◽  
Birth Type

The present study was carried out to estimate variance components for growth traits in Naeini goats. Bodyweight records were collected for two flocks under supervision of the Agriculture Organisation of the Esfahan province between 2000 and 2007. Investigated traits were birthweight (BW; n = 2483), weaning weight (WW; n = 1211) and average daily gain from birth to weaning (ADG; n = 1211). Environmental effects were investigated using fixed-effect models, while (co)variance components and genetic parameters were estimated with single- and three-trait analyses using REML methods and WOMBAT software. Six different animal models were fitted to the traits, with the best model for each trait determined by log-likelihood ratio tests (LRT). All traits were significantly influenced by herd, birth year, sex of the kid, birth type and dam age (P < 0.01). On the basis of LRT, maternal permanent environmental effects (c2) were significant for WW and ADG, while BW was affected only by direct genetic effects. Direct heritability estimates for BW, WW and ADG were 0.25 ± 0.05, 0.07 ± 0.06 and 0.21 ± 0.11, respectively. The estimate of c2 was 0.16 ± 0.06 for both WW and ADG. Estimates of genetic correlation for BW–ADG, BW–WW and ADG–WW were 0.49, 0.61 and 0.94, respectively. The estimated phenotypic correlations were positive and were between 0.03 (BW–ADG) and 0.95 (ADG–WW). These results indicate that selection can be used to improve growth traits in this goat breed.

scholarly journals Estimasi Parameter Genetik Sifat Pertumbuhan Kambing Boerawa di Kabupaten Tanggamus Propinsi Lampung (Genetic Parameters Estimation on Growth Traits of Boerawa Goat at Tanggamus Regency Lampung Province)

2012 ◽  
Vol 34 (3) ◽  
pp. 138
Author(s):  
Veronika Yuneriati Beyleto ◽  
Sumadi (Sumadi) ◽  
Tety Hartatik
Keyword(s):  
Birth Weight ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Parameter ◽  
Parameters Estimation ◽  
Weaning Weight ◽  
Estimate Heritability ◽  
Growth Character ◽  
Daily Gain

<p>This research was conducted to estimate heritability, repeatability and genetic correlation values on growth traits of Boerawa goat at Sumber Rejeki farmer group at Campang Village, Gisting District and Karya Makmur I and Karya Makmur II farmer group at Wonoharjo and Sukoharjo Village, Sumber Rejo District, Tanggamus regency, Lampung province. Data consisted of production record and 238 Boerawa goat derived from 93 PE and 7 Boer buck.<br />The research was started on October 30, 2009 up to January 30, 2010. The results indicated that heritability value of birth weight, weaning weight, yearling weigth, average of preweaning daily gain, and average of postweaning weight<br />analyzed by paternal half-sibs correlation were 0.80±0.40; 0.30±0.17; 0.80±0.04; 0.32±0.18 and 0.30±0.17, respectively. The repeatability values of birth weight, weaning weight and yearling weight analyzed based on two<br />recording per every dam were 0.42±0.07; 0.32±0.08; 0.30±0.08; 0.30±0.08 and 0.53±0.06. The genetic correlation values among birth weight and weaning weight, birth weight and yearling weight, weaning weight and yearling weight,<br />average of preweaning weight and postweaning weight daily gain analyzed by paternal half-sibs correlation were 0.50±0.04; 0.44±0.08; 0.21±0.03 and 0.20±0.05, respectively. The result also indicated that the heritability and<br />repeatability values was high and the genetic correlation values were moderate to high.</p><p>(Key words: Boerawa goat, Genetic parameter, Growth character)</p>

scholarly journals Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

2022 ◽  
Author(s):  
Manuel Du ◽  
Richard Bernstein ◽  
Andreas Hoppe ◽  
Kaspar Bienefeld
Keyword(s):  
Genetic Parameters ◽  
Genetic Parameter ◽  
Estimation Algorithm ◽  
Parameter Estimates ◽  
Simplified Models ◽  
Parameter Estimations ◽  
Estimate Variance ◽  
Almost All ◽  
Variance Estimates ◽  
Genetic Contributions

Abstract Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models which attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations. We found that successful estimations with the colony model were only possible if at least some of the queens mated controlledly on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This work elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models.

Genetic parameters of growth of Ethiopian Boran cattle

1987 ◽  
Vol 44 (2) ◽  
pp. 201-208 ◽  
Author(s):  
Th. Arnason ◽  
H. Kassa-Mersha
Keyword(s):  
Birth Weight ◽  
Maternal Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Covariance ◽  
Weaning Weight ◽  
Genetic Components ◽  
Selection Indices ◽  
The Individual

ABSTRACTRecords on birth weight and pre-weaning growth of 3959 Boran calves, which were progeny of 51 sires and 979 dams, were analysed by least-squares analysis of variance. The variance components for sires, dams and maternal grandsires were estimated from the data. On the basis of assumed genetic correlations −0·44 and −0·55 between direct and maternal effects on birth weight and weaning weight, respectively, the maternal genetic component and the genetic covariance between direct and maternal effects were estimated. The heritabilities for direct effects on birth weight and weaning weight were 0·11 and 0·22, respectively, while the heritabilities of maternal effects were estimated as 0·02 and 0·11, respectively for the same traits. Selection indices for direct and maternal genetic components of weaning weight were constructed for practical use. These selection indices combined information on the individual, the parents and sibs.

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.

Genetic parameter estimates for feeding pattern and production traits in pigs

1997 ◽  
Vol 1997 ◽  
pp. 31-31
Author(s):  
A.D. Hall ◽  
W.G. Hill ◽  
P.R. Bampton ◽  
A.J. Webb
Keyword(s):  
Feed Intake ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Feeding Pattern ◽  
Parameter Estimates ◽  
Group Housing ◽  
Production Traits ◽  
Production Environment ◽  
Feeding Patterns ◽  
Potential Benefits

Until recently, to enable accurate recording of feed intake, pigs were kept in individual pens. The advent of electronic feeders has allowed accurate records of feed intake and feeding patterns in group housing which is more similar to that found in the production environment. The objectives of this study were to estimate genetic parameters for these feeding pattern traits and their correlations with production traits to show potential benefits in selection.

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