Components of (co)variance of the days open in Siboney dairy cows

The records of 63,406 calvings of Siboney dairy cows (5/8 Holstein 3/8 Cuban Zebu) were used to estimate the components of covariance of the days open (DO). Five models were used: of repeatability; univariate; bivariate; of random regression with Legendre polynomials and the parity number as predicting variable; and a model of random regression with Legendre polynomials and heterogeneity of the residual variance. The heritability obtained with the univariate model was 0.09 in the first calving and decreased to 0.05 in the fifth. A higher estimate of heritability (0.12) was obtained with the repeatability model. When the model of random regression with heterogeneity of the residual variance was used, the heritability was higher than the values estimated with the previous models. The genetic correlations among the DO in different calvings, estimated with the models of random regression with and without heterogeneity of the residual variance, were close to 1.0. It is concluded that the estimates of heritability increased with the use of the random regression models. The genetic correlations among the DO of different calvings indicated that in the first three, the DO are regulated for the most part by the same genes.

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

Ciência Rural ◽

10.1590/0103-8478cr20150473 ◽

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.

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Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials

Revista Brasileira de Zootecnia ◽

10.1590/s1516-35982008000400003 ◽

2008 ◽

Vol 37 (4) ◽

pp. 602-608 ◽

Cited By ~ 26

Author(s):

Claudio Napolis Costa ◽

Claudio Manoel Rodrigues de Melo ◽

Irineu Umberto Packer ◽

Ary Ferreira de Freitas ◽

Nilson Milagres Teixeira ◽

...

Keyword(s):

Variance Components ◽

Legendre Polynomials ◽

Genetic Parameters ◽

Genetic Correlations ◽

Random Regression ◽

Holstein Cows ◽

Residual Variance ◽

Environmental Variance ◽

Environmental Correlations ◽

Lp Estimates

Data comprising 263,390 test-day (TD) records of 32,448 first parity cows calving in 467 herds between 1991 and 2001 from the Brazilian Holstein Association were used to estimate genetic and permanent environmental variance components in a random regression animal model using Legendre polynomials (LP) of order three to five by REML. Residual variance was assumed to be constant in all or in some classes of lactation periods for each LP. Estimates of genetic and permanent environmental variances did not show any trend due to the increase in the LP order. Residual variance decreased as the order of LP increased when it was assumed constant, and it was highest at the beginning of lactation and relatively constant in mid lactation when assumed to vary between classes. The range for the estimates of heritability (0.27 - 0.42) was similar for all models and was higher in mid lactation. There were only slight differences between the models in both genetic and permanent environmental correlations. Genetic correlations decreased for near unity between adjacent days to values as low as 0.24 between early and late lactation. A five parameter LP to model both genetic and permanent environmental effects and assuming a homogeneous residual variance would be a parsimonious option to fit TD yields of Holstein cows in Brazil.

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Using Random Regression Models to Genetically Evaluate Functional Longevity Traits in North American Angus Cattle

Animals ◽

10.3390/ani10122410 ◽

2020 ◽

Vol 10 (12) ◽

pp. 2410

Author(s):

Hinayah R. Oliveira ◽

Luiz F. Brito ◽

Stephen P. Miller ◽

Flavio S. Schenkel

Keyword(s):

North American ◽

Regression Models ◽

Genetic Correlations ◽

Genetic Selection ◽

Random Regression ◽

Pedigree Information ◽

Residual Variance ◽

Multiple Trait ◽

Structural Problems ◽

Angus Cattle

This study aimed to propose novel longevity indicators by comparing genetic parameters for traditional (TL; i.e., the cow’s lifespan after the first calving) and functional (FL; i.e., how long the cow stayed in the herd while also calving; assuming no missing (FLa) or missing (FLb) records for unknown calving) longevity, considering different culling reasons (natural death, structural problems, disease, fertility, performance, and miscellaneous). Longevity definitions were evaluated from 2 to 15 years of age, using single- and multiple-trait Bayesian random regression models (RRM). The RRM fitting heterogenous residual variance and fourth order Legendre polynomials were considered as the optimal models for the majority of longevity indicators. The average heritability estimates over ages for FLb (from 0.08 to 0.25) were always higher than those for FLa (from 0.07 to 0.19), and higher or equal to the ones estimated for TL (from 0.07 to 0.23), considering the different culling reasons. The average genetic correlations estimated between ages were low to moderate (~0.40), for all longevity definitions and culling reasons. However, removing the extreme ages (i.e., 2 and >12 years) increased the average correlation between ages (from ~0.40 to >0.70). The genetic correlations estimated between culling reasons were low (0.12 and 0.20 on average, considering all ages and ages between 3 and 12 years old, respectively), indicating that longevity based on different culling reasons should be considered as different traits in the genetic evaluations. Higher average genetic correlations (estimated from 3 to 12 years old) were observed between TL and FLb (0.73) in comparison to TL and FLa (0.64), or FLa and FLb (0.65). Consequently, a higher average proportion of commonly-selected sires, for the top 1% sires, was also observed between TL and FLb (91.74%), compared to TL and FLa (59.68%), or FLa and FLb (61.01%). Higher prediction accuracies for the expected daughter performances (calculated based on the pedigree information) were obtained for FLb in comparison to TL and FLa. Our findings indicate that FLb is preferred for the genetic evaluation of longevity. In addition, it is recommended including multiple longevity traits based on different groups of culling reasons in a selection sub-index, as they are genetically-different traits. Genetic selection based on breeding values at the age of four years is expected to result in greater selection responses for increased longevity in North American Angus cattle.

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Genetic parameters for production traits in primiparous Holstein cows estimated by random regression models

Revista Brasileira de Zootecnia ◽

10.1590/s1516-35982011000100012 ◽

2011 ◽

Vol 40 (1) ◽

pp. 85-94 ◽

Cited By ~ 6

Author(s):

Igor de Oliveira Biassus ◽

Jaime Araújo Cobuci ◽

Claudio Napolis Costa ◽

Paulo Roberto Nogara Rorato ◽

José Braccini Neto ◽

...

Keyword(s):

Milk Fat ◽

Legendre Polynomials ◽

Regression Models ◽

Genetic Parameters ◽

Genetic Correlations ◽

Random Regression ◽

Holstein Cows ◽

Lactation Period ◽

Production Traits ◽

Residual Variances

The objective of this study was to estimate genetic parameters for milk, fat and protein yields of Holstein cows using 56,508; 35,091 and 8,326 test-day milk records from 7,015, 4,476 and 1,114 cows, calves of 359, 246 and 90 bulls, respectively. The additive genetic and permanent environmental effects were estimated using REML. Random regression models with Legendre polynomials from order 3 to 6 were used. Residual variances were considered homogeneous over the lactation period. The estimates of variance components showed similar trends, with an increase of the polynomial order for each trait. The heritability estimates ranged from 0.14 to 0.31; 0.03 to 0.21 and 0.09 to 0.33 for milk, fat and protein yield, respectively. Genetic correlations among milk, fat and protein yields ranged from 0.02 to 1.00; 0.34 to 1.00 and 0.42 to 1.00, respectively. Models with higher order Legendre polynomials are the best suited to adjust test-day data for the three production traits studied.

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

Czech Journal of Animal Science ◽

10.17221/360-cjas ◽

2008 ◽

Vol 53 (No. 6) ◽

pp. 227-237 ◽

Cited By ~ 2

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.

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Definition of subgroups for fixed regression in the test-day animal model for milk production ofHolsteincattle in theCzech Republic

Czech Journal of Animal Science ◽

10.17221/3976-cjas ◽

2011 ◽

Vol 50 (No. 1) ◽

pp. 7-13 ◽

Cited By ~ 3

Author(s):

L. Zavadilová ◽

E. Němcová ◽

J. Přibyl ◽

J. Wolf

Keyword(s):

Animal Model ◽

Milk Production ◽

Legendre Polynomials ◽

Environmental Effect ◽

Random Regression ◽

Breeding Values ◽

Regression Test ◽

Days Open ◽

Calving Season ◽

Definition Of

The investigation was based on roughly 3.9, 2.7 and 1.7 million test-day records from first, second and third lactation, respectively, sampled from 596 200 Czech Holstein cows between the years 1991 and 2002. Breeding values were estimated from multi-lactation random-regression test-day models which contained the fixed effect of herd-test day, fixed regression on days in milk and random regressions on the animal level and the permanent environmental effect. Third degree Legendre polynomials (with four coefficients) were used for both the fixed and random regressions. The models differed in fixed regression. In Analysis I, 96 subclasses were defined according to age at calving, season and year of calving within lactation. In Analysis II, days open were additionally included as a grouping factor resulting in 480 subclasses. Rank correlations over 0.98 between both analyses were observed for breeding values for sires. Grouping according to Analysis I was recommended.  

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Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2014000500007 ◽

2014 ◽

Vol 49 (5) ◽

pp. 372-383 ◽

Cited By ~ 4

Author(s):

Maria Gabriela Campolina Diniz Peixoto ◽

Daniel Jordan de Abreu Santos ◽

Rusbel Raul Aspilcueta Borquis ◽

Frank Ângelo Tomita Bruneli ◽

João Cláudio do Carmo Panetto ◽

...

Keyword(s):

Milk Production ◽

Legendre Polynomial ◽

Legendre Polynomials ◽

Regression Models ◽

Environmental Effect ◽

Genetic Parameters ◽

Genetic Effect ◽

Random Regression ◽

Additive Genetic Effect ◽

Fifth Order

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

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