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.

scholarly journals Random regression models for milk, fat and protein in Colombian Buffaloes

2015 ◽  
pp. 4415-4426
Author(s):  
Naudin Hurtado-Lugo ◽  
Humberto Tonhati ◽  
Raul Aspilcuelta-Borquis ◽  
Cruz Enríquez-Valencia ◽  
Mario Cerón-Muñoz
Keyword(s):  
Environmental Effects ◽  
Milk Fat ◽  
Fixed Effects ◽  
Regression Models ◽  
Random Regression ◽  
Residual Effects ◽  
Covariance Functions ◽  
Lp Residual ◽  
Quadratic Effects ◽  
Residual Variances

Objective. Covariance functions for additive genetic and permanent environmental effects and, subsequently, genetic parameters for test-day milk (MY), fat (FY) protein (PY) yields and mozzarella cheese (MP) in buffaloes from Colombia were estimate by using Random regression models (RRM) with Legendre polynomials (LP). Materials and Methods. Test-day records of MY, FY, PY and MP from 1884 first lactations of buffalo cows from 228 sires were analyzed. The animals belonged to 14 herds in Colombia between 1995 and 2011. Ten monthly classes of days in milk were considered for test-day yields. The contemporary groups were defined as herd-year-month of milk test-day. Random additive genetic, permanent environmental and residual effects were included in the model. Fixed effects included the contemporary group, linear and quadratic effects of age at calving, and the average lactation curve of the population, which was modeled by third-order LP. Random additive genetic and permanent environmental effects were estimated by RRM using third- to- sixth-order LP. Residual variances were modeled using homogeneous and heterogeneous structures. Results. The heritabilities for MY, FY, PY and MP ranged from 0.38 to 0.05, 0.67 to 0.11, 0.50 to 0.07 and 0.50 to 0.11, respectively. Conclusions. In general, the RRM are adequate to describe the genetic variation in test-day of MY, FY, PY and MP in Colombian buffaloes.Key words: Cattle, genetics, zootechnics (Source: EuroVoc).

scholarly journals Estimation of (co)variance components and genetic parameters for weights of red-winged tinamou using random regression models

2011 ◽  
Vol 40 (4) ◽  
pp. 781-787 ◽  
Author(s):  
P. Tholon ◽  
S.A. Queiroz
Keyword(s):  
Body Weight ◽  
Environmental Effects ◽  
Regression Models ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Information Criterion ◽  
Random Regression ◽  
Additive Genetic Effect ◽  
First Eigenvalue ◽  
Permanent Effect

The objective of this work was to determine genetic parameters for body weight of tinamou in captivity. It was used random regression models in analyses of data by considering the direct additive genetic (DA) and permanent environmental effects of the animal (PE) as random effects. Residual variances were modeled by using a fifth-order variance function. The mean population growth curve was fitted by sixth-order Legendre orthogonal polynomials. Direct additive genetic effects and animal environmental permanent effect were modeled by using Legendre polynomials of order two to nine. The best results were obtained by models with orders of fit of 6 for direct additive genetic effect and of order 3 for permanent effect by Akaike information criterion and of order 3 for both additive genetic effect and permanent effect by Schwarz Bayesian information criterion and likelihood ratio test. Heritability estimates ranged from 0.02 to 0.57. The first eigenvalue explained 94% and 90% of the variation from additive direct and permant environmental effects, respectively. Selection of tinamou for body weight is more effective after 112 days of age.

scholarly journals Random regression models for the evaluation of the growth of goats of the Anglonubian breed

2020 ◽  
Vol 72 (3) ◽  
pp. 961-969
Author(s):  
G.C. Castro ◽  
J.E.G. Campelo ◽  
J.L.R. Sarmento ◽  
M.D.F. Carvalho ◽  
D.H. Cavalcante ◽  
...  
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Regression Models ◽  
Genetic Correlations ◽  
Random Regression ◽  
Random Regression Model ◽  
Variance Estimates ◽  
Additive Genetic Effects ◽  
Maternal Heritability ◽  
Quadratic Order

ABSTRACT A total of 6593 weight records collected from 796 male and female Anglo-Nubian goats aged up to 130 days, offspring from 29 sires and 225 dams, were used to compare models and estimate genetic parameters throughout the growth curve by applying random regression models. Direct and maternal additive genetic effects and direct and maternal permanent environmental effects were included as random in the models. The contemporary groups were included as fixed effects and goat age at kidding was included as a covariable (linear and quadratic). The choice of the best model was based on the AIC, BIC and AICc criteria. Variance estimates of the four random effects increased as the animals aged. Direct heritability (h2) rose from 0.13 to 0.40 with age, whereas maternal heritability showed a low value. Genetic correlations of weight between closer ages were high. The most suitable random regression model to compare the fitting of random effects was that which employed the Legendre polynomials of quadratic order with homogeneous variance (3333-1).

scholarly journals Genetic evaluation of daily gains of dual-purpose bulls using a random regression model

2008 ◽  
Vol 53 (No. 6) ◽  
pp. 227-237 ◽  
Author(s):  
H. Krejčová ◽  
J. Přibyl ◽  
J. Přibylová ◽  
M. Štípková ◽  
N. Mielenz
Keyword(s):  
Environmental Effects ◽  
Legendre Polynomials ◽  
Regression Models ◽  
Compensatory Growth ◽  
Genetic Correlations ◽  
Random Regression ◽  
Dual Purpose ◽  
Random Regression Model ◽  
Additive Genetic Effects ◽  
Daily Gain

Daily gains of 8 243 dual-purpose bulls from 100 to 400 days of age during the years 1971 to 2007 were analyzed by random regression models. Orthogonal Legendre polynomials (LP) of degree 4 were applied to daily gains calculated at 30-day intervals over the test period. Fixed curves were estimated within the station-year-season of birth. The models also included a fixed station-year-season of weighing, animal additive genetic effects and animal permanent environmental effects. The peak daily gain was attained between 230 and 280 days of age, which corresponded to the period of the lowest variance in daily gains. Heritability estimates of daily gain were in the range of 0.014 to 0.043. The reliability of composite trait – cumulative gains over the entire period was 0.87. Genetic correlations between gains at different ages were high for adjacent ages and decreased with increasing difference in ages. Correlations of permanent environmental effects were high for adjacent ages, but became negative for ages that were far apart, indicating the possibility of compensatory growth. The phenotypic correlations were close to zero. The correlations for cumulative daily gains were higher than those for individual daily gains.

scholarly journals Genetic analysis of weight, fat and muscle depth in growing lambs using random regression models

2006 ◽  
Vol 82 (1) ◽  
pp. 13-22 ◽  
Author(s):  
T. M. Fischer ◽  
J. H. J. van der Werf ◽  
R. G. Banks ◽  
A. J. Ball ◽  
A. R. Gilmour
Keyword(s):  
Orthogonal Polynomials ◽  
Environmental Effects ◽  
Repeated Measures ◽  
Regression Models ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Error Variance ◽  
Random Regression ◽  
Eye Muscle ◽  
Management Group

AbstractGenetic parameters were estimated using uni- and bi-variate random regression models for weight, eye-muscle depth and fat depth measures between 60 and 360 days of age. Each trait was measured up to five times in 50-day intervals following weaning on approximately 4000 Australian Poll Dorset Sheep. The model accounted for rearing type, dam age, management group and age of recording. The model used for analysing weight included quadratic, orthogonal polynomials for direct genetic and environmental effects, a linear polynomial for maternal genetic effects and heterogeneous error variance across ages. The fat and muscle analysis used linear orthogonal polynomials for direct genetic and environmental effects and heterogeneous error variance. Throughout the 300-day trajectory heritability for weight traits ranged from 0·20 to 0·31, while heritability for fat depth ranged from 0·24 to 0·34 and heritability for eye-muscle depth ranged from 0·24 to 0·40. Genetic correlations between repeated measures of the same trait at different ages were positive and declined as the age interval increased, to minimum values of 0·60, 0·31 and 0·50 for weight, fat and muscle respectively between 60 and 360 days of age. Genetic correlations between weight and fat and weight and eye muscle were moderate to high (0·6 to 0·8) and positive but decreased slightly with age. The genetic correlations between fat and muscle were moderate to high (0·5 to 0·7) throughout the 300-day trajectory. In all cases, the estimates produced in this study were reasonably consistent with the limited number of studies that exist in the reported literature. This study demonstrated the relationships that exist between repeated measures of weight, fat and muscle measures over time, which is of interest to prime lamb producers looking to select for specific breeding objectives or market end points requiring precise weight, fat and muscle combinations at certain ages.

scholarly journals Genetic evaluation of growth traits in Nellore cattle through multi-trait and random regression models

2018 ◽  
Vol 63 (No. 6) ◽  
pp. 212-221 ◽  
Author(s):  
B.B. Teixeira ◽  
R.R. Mota ◽  
R.B. Lôbo ◽  
L.P. Silva ◽  
A.P. Souza Carneiro ◽  
...  
Keyword(s):  
Random Effects ◽  
Variance Components ◽  
Regression Models ◽  
Growth Traits ◽  
Growth Curves ◽  
Genetic Evaluation ◽  
Information Criteria ◽  
Random Regression ◽  
Nellore Cattle ◽  
Heritability Estimates

We aimed to evaluate different orders of fixed and random effects in random regression models (RRM) based on Legendre orthogonal polynomials as well as to verify the feasibility of these models to describe growth curves in Nellore cattle. The proposed RRM were also compared to multi-trait models (MTM). Variance components and genetic parameters estimates were performed via REML for all models. Twelve RRM were compared through Akaike (AIC) and Bayesian (BIC) information criteria. The model of order three for the fixed curve and four for all random effects (direct genetic, maternal genetic, permanent environment, and maternal permanent environment) fits best. Estimates of direct genetic, maternal genetic, maternal permanent environment, permanent environment, phenotypic and residual variances were similar between MTM and RRM. Heritability estimates were higher via RRM. We presented perspectives for the use of RRM for genetic evaluation of growth traits in Brazilian Nellore cattle. In general, moderate heritability estimates were obtained for the majority of studied traits when using RRM. Additionally, the precision of these estimates was higher when using RRM instead of MTM. However, concerns about the variance components estimates in advanced ages via Legendre polynomial must be taken into account in future studies.

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.

Genetic evaluation of weekly body weight in Japanese quail using random regression models

2016 ◽  
Vol 58 (1) ◽  
pp. 13-18 ◽  
Author(s):  
K. Karami ◽  
S. Zerehdaran ◽  
M. Tahmoorespur ◽  
B. Barzanooni ◽  
E. Lotfi
Keyword(s):  
Body Weight ◽  
Japanese Quail ◽  
Regression Models ◽  
Genetic Evaluation ◽  
Random Regression

RELATIONSHIPS OF REPRODUCTION TRAITS, BODY WEIGHT AND MILK YIELD IN DAIRY CATTLE

1986 ◽  
Vol 66 (1) ◽  
pp. 53-65 ◽  
Author(s):  
T. R. BATRA ◽  
A. J. LEE ◽  
A. J. McALLISTER
Keyword(s):  
Body Weight ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Calving Interval ◽  
Phenotypic Correlations ◽  
Reproduction Traits ◽  
Heritability Estimates ◽  
National Cooperative

The relationships between reproduction traits, body weight and milk yield were investigated using data from 1611 heifers and 733 cows from two lines of the National Cooperative Dairy Cattle Breeding Project. The data were analyzed separately for heifers and cows within lines using a mixed linear model containing fixed effects for station, year of birth, season of birth and random effect of sires. Heritability estimates and genetic correlations were estimated by a paternal half-sib analysis. Heritability estimates for heifer and cow reproduction traits ranged between 0 and 26% while those of body weights at calving and 112 d postpartum and milk yield ranged from 24 to 43%. Heifers with difficult calving had a higher incidence of retained placenta than those with normal calving. Phenotypic correlations between heifer reproduction traits and milk yield during first lactation were small. High milk production in cows was associated with longer calving interval. Phenotypic correlations between heifer's and cow's reproduction traits were small. Difficult calving in heifers impairs reproductive performance after calving resulting in greater number of days from calving to first and last breeding and leading to a longer calving interval. Key words: Reproduction traits, heifers, cows, milk yield, dairy cattle

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