scholarly journals Estimates of (co)variance function for growth to yearling in Horro sheep of Ethiopia using random regression model

2010 ◽  
Vol 53 (6) ◽  
pp. 689-700
Author(s):  
S. Abegaz ◽  
J. B. van Wyk ◽  
J. J. Olivier
Keyword(s):  
Fixed Effects ◽  
Model Comparison ◽  
Information Criterion ◽  
Coefficient Matrix ◽  
Random Regression ◽  
Ratio Test ◽  
Residual Variance ◽  
Genetic Covariance ◽  
Heritability Estimates ◽  
One Year

Abstract. Random regression analyses of weight data from birth to 396 days were done using 22 141 weight records of 1 951 Horro lambs. Six different models formed from three different orthogonal polynomial regressions (legendre scale)orders (quadratic, cubic, quartic) of fit for both additive genetic and animals’ permanent environmental effects, with assumption of either homogeneous or heterogeneous residual variance, were compared. Fixed effects of year and type of birth, sex and age of dam were fitted along with a fourth order polynomial. Both likelihood ratio test (LRT) and Akaike's Information Criterion (AIC) were used for model comparison. Model fit improved with increased order of polynomial and assumption of heterogeneity of residual variance. Components for additive genetic and permanent environmental (co)variance increased from 0.03 and 0.09 at birth to 23.8 and 37.6 at 396 days of age, respectively. The first three eigenvalues of the coefficient matrix of the additive genetic covariance accounted for about 98 % of the sum of all the eigenvalues. Heritability estimates have shown a declining and increasing trend at different parts of the trajectory, the lowest estimate being 0.14 for weight at birth while the highest being 0.36 for weight at about 390 days of age. Higher heritability estimates in previous uni- and bi-variate models and in the current study and also strong correlation with weight at early age makes weight at one year of age the most important trait to consider in improving productivity in Horro sheep.

scholarly journals Estimates of covariance functions for growth of Anglo-Nubian goats

2011 ◽  
Vol 40 (1) ◽  
pp. 106-114 ◽  
Author(s):  
José Ernandes Rufino de Sousa ◽  
Martinho de Almeida e Silva ◽  
José Lindenberg Rocha Sarmento ◽  
Wandrick Hauss de Sousa ◽  
Maria do Socorro Medeiros de Souza ◽  
...  
Keyword(s):  
Bayesian Information Criterion ◽  
Regression Models ◽  
Genetic Effect ◽  
Information Criterion ◽  
Random Regression ◽  
Additive Genetic Effect ◽  
Ratio Test ◽  
Residual Variance ◽  
Covariance Functions ◽  
Heritability Estimates

It was used 4,313 weight records from birth to 196 days of age from 946 Anglo-nubiana breed goats, progenies from 43 sires and 279 dams, controlled in the period from 1980 to 2005, with the objective of estimating covariance functions and genetic parameters of animals by using random regression models. It was evaluated 12 random regression models, with degrees ranging from 1 to 7 for direct additive genetic and maternal and animal permanent environment effect and residual variance adjusted by using animal age ordinary polynomial of third order. Models were compared by using likelihood ratio test and by Bayesian information criterion of Schwarz and Akaike information criterion. The model selected based on Bayesian information criterion was the one that considered the maternal and direct additive genetic effect adjusted by a quadratic polynomial and the animal permanent environmental effect adjusted by a cubic polynomial (M334). Heritability estimates for direct effect were lower in the beginning and at the end of the studied period and maternal heritability estimates were higher at 196 days of age in comparison to the other growth phases. Genetic correlation ranged from moderate to high and they decreased as the distance between ages increased. Higher efficiency in selection for weight can be obtained by considering weights close to weaning, which is a period when the highest estimates of genetic variance and heritability are obtained.

scholarly journals Genetic parameters for growth of young beef bulls

2012 ◽  
Vol 55 (3) ◽  
pp. 245-254
Author(s):  
L. Vostrý ◽  
Z. Veselá ◽  
J. Přibyl
Keyword(s):  
Fixed Effects ◽  
Genetic Effect ◽  
Information Criterion ◽  
Ratio Test ◽  
Residual Variance ◽  
Multiple Trait ◽  
Environment Effect ◽  
Body Weights ◽  
Direct Genetic Effect ◽  
Maternal Heritability

Abstract. The average daily gains of young bulls on test stations (ADGT) were analysed for the most frequent breeds of beef cattle in the Czech Republic using a multiple-trait animal model. Body weights at birth (W0), at 120 days of age (W120) and at weaning at 210 days (WW) were considered in this model as pre-weaning growth. The tested models comprised some of the random effects: direct genetic effect, maternal genetic effect, permanent animal environment effect, permanent maternal environment effect, and some of the fixed effects: dam’s age, sex, herd-year-season, linear and quadratic regression on age at the beginning of the test. For optimization of the models Akaike information criterion (AIC), residual variance and likelihood ratio test were used. Coefficients of direct and maternal heritability across breeds of about 0.25 for W0, about 0.17 for W120, about 0.17 for WW and about 0.29 for ADGT were estimated by all models. All criteria selected models including the permanent animal environment effect, which was the most important effect in the model.

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.

scholarly journals Random regression for modeling yield genetic trajectories in Jatropha curcas breeding

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244021
Author(s):  
Marco Antônio Peixoto ◽  
Rodrigo Silva Alves ◽  
Igor Ferreira Coelho ◽  
Jeniffer Santana Pinto Coelho Evangelista ◽  
Marcos Deon Vilela de Resende ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Repeated Measures ◽  
Variance Components ◽  
High Reliability ◽  
Genetic Selection ◽  
Information Criterion ◽  
Random Regression ◽  
Ratio Test ◽  
Sib Families ◽  
Over Time

Random regression models (RRM) are a powerful tool to evaluate genotypic plasticity over time. However, to date, RRM remains unexplored for the analysis of repeated measures in Jatropha curcas breeding. Thus, the present work aimed to apply the random regression technique and study its possibilities for the analysis of repeated measures in Jatropha curcas breeding. To this end, the grain yield (GY) trait of 730 individuals of 73 half-sib families was evaluated over six years. Variance components were estimated by restricted maximum likelihood, genetic values were predicted by best linear unbiased prediction and RRM were fitted through Legendre polynomials. The best RRM was selected by Bayesian information criterion. According to the likelihood ratio test, there was genetic variability among the Jatropha curcas progenies; also, the plot and permanent environmental effects were statistically significant. The variance components and heritability estimates increased over time. Non-uniform trajectories were estimated for each progeny throughout the measures, and the area under the trajectories distinguished the progenies with higher performance. High accuracies were found for GY in all harvests, which indicates the high reliability of the results. Moderate to strong genetic correlation was observed across pairs of harvests. The genetic trajectories indicated the existence of genotype × measurement interaction, once the trajectories crossed, which implies a different ranking in each year. Our results suggest that RRM can be efficiently applied for genetic selection in Jatropha curcas breeding programs.

scholarly journals Selection of a suitable definition of environment for the estimation of genotype × environment interaction in the weaning weight of beef cattle

2008 ◽  
Vol 53 (No. 10) ◽  
pp. 407-417 ◽  
Author(s):  
L. Vostrý ◽  
J. Přibyl ◽  
V. Jakubec ◽  
Z. Veselá ◽  
I. Majzlík
Keyword(s):  
Beef Cattle ◽  
Evaluation Model ◽  
Economic Value ◽  
Information Criterion ◽  
Ratio Test ◽  
Residual Variance ◽  
Environment Interaction ◽  
Weaning Weight ◽  
Genotype Environment Interaction ◽  
And Performance

Genotype by environment interactions for weaning weight in beef cattle were tested using several definitions of environments. Four breeds of beef cattle (Hereford, Aberdeen Angus, Beef Simmental, and Charolais) were represented. The environments were defined according to five criteria: altitude, production areas, economic value of the land, less favourable areas, and performance levels of a breed within herds. Ten mixed models were compared including the effects of direct and maternal genetics, herd-year-season, maternal permanent environmental, breed, environment, genotype × environment interaction, sex of calf, and age of dam. The suitability of the models was tested by Akaike’s Information Criterion, likelihood ratio test, and magnitude of the residual variance. The most suitable definitions of environment were less favoured areas and herd levels of performance. Estimates of direct heritability ranged from 0.07 to 0.19. Genotype × environment interactions should be included in a genetic evaluation model for interbreed comparisons of beef cattle in the Czech Republic.

scholarly journals Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

2016 ◽  
Vol 46 (9) ◽  
pp. 1649-1655
Author(s):  
Mariana de Almeida Dornelles ◽  
Paulo Roberto Nogara Rorato ◽  
Luis Telo Lavadinho da Gama ◽  
Fernanda Cristina Breda ◽  
Carlos Bondan ◽  
...  
Keyword(s):  
Milk Production ◽  
Legendre Polynomials ◽  
Fixed Effects ◽  
Regression Models ◽  
Genetic Parameters ◽  
Random Regression ◽  
Residual Variance ◽  
Lower Estimation ◽  
The One ◽  
Residual Variances

ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.

scholarly journals Model comparison and estimation of genetic parameters for body weight in commercial broilers

2013 ◽  
Vol 93 (1) ◽  
pp. 67-77 ◽  
Author(s):  
G. Maniatis ◽  
N. Demiris ◽  
A. Kranis ◽  
G. Banos ◽  
A. Kominakis
Keyword(s):  
Body Weight ◽  
Akaike Information Criterion ◽  
Model Evaluation ◽  
Model Comparison ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Information Criterion ◽  
Biological Properties ◽  
Genetic Covariance ◽  
Estimation Of Genetic Parameters

Maniatis, G., Demiris, N., Kranis, A., Banos, G. and Kominakis, A. 2013. Model comparison and estimation of genetic parameters for body weight in commercial broilers. Can. J. Anim. Sci. 93: 67–77. The availability of powerful computing and advances in algorithmic efficiency allow for the consideration of increasingly complex models. Consequently, the development and application of appropriate statistical procedures for model evaluation is becoming increasingly important. This paper is concerned with the application of an alternative model determination criterion (conditional Akaike Information Criterion, cAIC) in a large dataset comprising 203 323 body weights of broilers, pertaining to 7 (BW7) and 35 (BW35) days of age. Seven univariate and seven bivariate models were applied. Direct genetic, maternal genetic and maternal environmental (c2) effects were estimated via REML. The model evaluation criteria included conditional Akaike Information Criterion (cAIC), Bayesian Information Criterion (BIC) and the standard Akaike Information Criterion (henceforth marginal; mAIC). According to cAIC the best-fitting model included direct genetic, maternal genetic and c2 effects. Maternal heritabilities were low (0.10 and 0.03) compared to the direct heritabilities (0.17 and 0.21), while c2 was 0.05 and 0.04 for BW7 and BW35, respectively. BIC and mAIC favoured a model that additionally included a direct-maternal genetic covariance, resulting in highly negative direct-maternal genetic correlations (−0.47 and −0.64 for BW7 and BW35, respectively) and higher direct heritabilities (0.25 and 0.28 for BW7 and BW35, respectively). Results suggest that cAIC can select different animal models than mAIC and BIC with different biological properties.

scholarly journals Inclusion of bioclimatic variables in genetic evaluations of dairy cattle

2021 ◽  
Vol 34 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Renata Negri ◽  
Ignacio Aguilar ◽  
Giovani Luis Feltes ◽  
Juliana Dementshuk Machado ◽  
José Braccini Neto ◽  
...  
Keyword(s):  
Heat Stress ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Fixed Effects ◽  
Information Criterion ◽  
Least Square ◽  
Random Regression ◽  
Yield Losses ◽  
Bioclimatic Variables ◽  
Genetic Evaluations

Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models.Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models.Results: The THI and DTV thresholds for milk yield losses was THI = 74 (–0.106 kg/d/THI) and DTV = 13 (–0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (–2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model.Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.

scholarly journals Estimation of direct and maternal effects on body weight in Mehraban sheep using random regression models

2008 ◽  
Vol 51 (3) ◽  
pp. 235-246
Author(s):  
F. G. Kesbi ◽  
M. Eskandarinasab ◽  
M. H. Shahir
Keyword(s):  
Body Weight ◽  
Environmental Effects ◽  
Fixed Effects ◽  
Regression Models ◽  
Error Variance ◽  
Random Regression ◽  
Growth Data ◽  
Measurement Error Variance ◽  
Heritability Estimates ◽  
Additive Genetic Effects

Abstract. In the present study the growth data of Mehraban sheep were used to estimate direct and maternal additive genetic effects together with direct and maternal permanent environmental effects on body weight from birth to 270 days of age using random regression models. The fixed effects of the model were age of dam, type of birth and contemporary groups. Animal, dam, animal and maternal permanent environmental effects were considered as random effects. The models were fitted to the data using Legendre polynomials for age of lambs. Changes in residual (measurement error) variance with age were modeled by a variance function. Direct heritability estimates for the later ages with the least records tended to be overestimated, particularly heritability beyond 180 days. Maternal heritability estimates increased after birth to a maximum around 120 days of age and decreased thereafter. The results showed that covariance between weights of lambs for a considerable range of ages can be modelled properly using random regression.

Estimates of Genetic Variation for Angus Gestation Length

2021 ◽  
Vol 99 (Supplement_2) ◽  
pp. 14-15
Author(s):  
Carson Gilleland ◽  
Kelli J Retallick ◽  
Daniel H Poole ◽  
Zack Peppmeier ◽  
Mark Knauer
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Additive Genetic Variance ◽  
High Capacity ◽  
Gestation Length ◽  
Phenotypic Variance ◽  
Contemporary Group ◽  
Heritability Estimates ◽  
One Year ◽  
Estimate Variance

Abstract The objective of this study was to estimate variance components for gestation length within the American Angus breed. Data (n = 148,649) from the American Angus Association, containing cattle born between 2000 to 2020, were used for the analysis. Based on a cow’s reproductive biology, gestation length records were determined acceptable if between 266 and 290 days (n = 114,857). Gestation length mean and standard deviation were 278.6 and 4.6 days, respectively. Average Information Restricted Maximum Likelihood (AIREML) was used to estimate variance components for the gestation length. A single trait animal model included random effects of direct and maternal additive genetic variance and fixed effects of dam age rounded to the nearest year, calf gender and contemporary group. Contemporary group was determined as herd, year of birth and season of birth combinations. Contemporary groups containing less than five animals were excluded from analysis. Phenotypic variance for gestation length was estimated at 18.9. Direct and maternal heritability estimates for gestation length were 0.59±0.01 and 0.10±0.01, respectively. Further analysis evaluated the fixed effects of year and dam age on gestation length. From 2000 to 2020, an increase in one year decreased (P < 0.01) gestation length by 0.09 days. Gestation length differed (P < 0.01) by age of dam. Gestation length LSMEANS for 2, 3, 4, 5, 6, 7 and 8 year old cows were 277.7, 278.6, 279.0, 279.2, 279.3, 279.5 and 279.6, respectively. Heritability estimates within Angus breed suggest gestation length has a high capacity for genetic change. Results suggest gestation length has decreased over the past two decades and is shorter in younger cows.

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