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

2011 ◽  
Vol 40 (1) ◽  
pp. 85-94 ◽  
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.

scholarly journals Estimation of genetic parameters for test-day milk yield in Khuzestan buffalo

2016 ◽  
Vol 51 (7) ◽  
pp. 890-897 ◽  
Author(s):  
Mostafa Madad ◽  
Navid Ghavi Hossein-Zadeh ◽  
Abdol Ahad Shadparvar
Keyword(s):  
Genetic Correlation ◽  
Milk Yield ◽  
Environmental Effects ◽  
Regression Models ◽  
Genetic Parameters ◽  
Information Criterion ◽  
Step Function ◽  
Random Regression ◽  
Residual Variance ◽  
Covariance Functions

Abstract: The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects, as well as to obtain genetic parameters for buffalo test-day milk yield using random regression models on Legendre polynomials (LPs). A total of 2,538 test-day milk yield (TDMY) records from 516 first lactation records of Khuzestan buffalo, calving from 1993 to 2009 and belonging to 150 herds located in the state of Khuzestan, Iran, were analyzed. The residual variances were modeled through a step function with 1, 5, 6, 9, and 19 classes. The additive genetic and permanent environmental random effects were modeled by LPs of days in milk using quadratic to septic polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by cubic and third order LP, respectively, and with the residual variance modeled through a step function with nine classes was the most adequate one to describe the covariance structure. The model with the highest significant log-likelihood ratio test (LRT) and with the lowest Akaike information criterion (AIC) and Bayesian information criterion (BIC) was considered to be the most appropriate one. Unexpected negative genetic correlation estimates were obtained between TDMY records of the twenty-fifth and thirty-seventh week (-0.03). Genetic correlation estimates were generally higher, close to unity, between adjacent weeks during the middle of lactation. Random regression models can be used for routine genetic evaluation of milk yield in Khuzestan buffalo.

scholarly journals Estimation of genetic parameters and comparison of random regression animal and sire models of production traits in the first three lactations of Iranian Holsteins

2014 ◽  
Vol 30 (2) ◽  
pp. 261-279 ◽  
Author(s):  
A. Mohammadi ◽  
S. Alijani
Keyword(s):  
Milk Fat ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Random Regression ◽  
Lactation Period ◽  
Production Traits ◽  
Environmental Variance ◽  
In The Beginning ◽  
Residual Variances

This study was conducted to compare of random regression (RR) animal and sire models for estimation of the genetic parameters for production traits of Iranian Holstein dairy cows. For this purpose, the test day records were used belonged to first three lactations of cows and for, milk, fat and protein yields traits where, collected from 2003 to 2010, by the national breeding center of Iran. The genetic parameters were estimated using restricted maximum likelihood algorithm. To compare the model, different criterion -2logL value, AIC, BIC and RV were used for considered traits. Residual variances were considered homogeneous over the lactation period. Obtained results showed that additive genetic variance was highest in the beginning and end lactation and permanent environmental variance was highest in beginning of lactation than other lactation period. Heritabilities estimate for milk, fat and protein yields by RR animal and sire models were found to be lowest during early lactation (0.05, 0.04 and 0.07; 0.05, 0.19 and 0.13; 0.14, 0.19 and 0.15, for milk, fat and protein yields and in first, second and third lactation respectively). However, estimated heritabilities during lactation did not vary among different order Legendre polynomials, and also between RR animal and sire models. The variation in genetic correlations estimate in the RR animal and sire models was larger in the first lactation than in the second and third lactations. Thus, based on the results obtained, it can be inferred that the RR animal model is better for modeling yield traits in Iranian Holsteins.

scholarly journals Covariance functions and random regression models for cow weight in beef cattle1

2004 ◽  
Vol 82 (1) ◽  
pp. 54-67 ◽  
Author(s):  
J. A. Arango ◽  
L. V. Cundiff ◽  
L. D. Van Vleck
Keyword(s):  
Regression Models ◽  
Random Regression ◽  
Covariance Functions

scholarly journals Genetic relationship between milk dry matter and other milk traits in extended lactations of Polish Holstein cows

2010 ◽  
Vol 55 (No. 3) ◽  
pp. 91-104 ◽  
Author(s):  
K. Yazgan ◽  
J. Makulska ◽  
A. Węglarz ◽  
E. Ptak ◽  
M. Gierdziewicz
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Fixed Effects ◽  
Dry Matter ◽  
Genetic Correlations ◽  
Random Regression ◽  
Holstein Cows ◽  
Milk Traits ◽  
Data Set ◽  
The Third

The objective of this research was to examine heritabilities and genetic, phenotypic and permanent environmental relationships between milk dry matter (DM) and milk traits such as milk, fat, protein and lactose yields, milk urea nitrogen (MUN) and somatic cell score (SCS) in extended (to 395 days) lactations of Holstein cows from a big farm in Poland. The data set consisted of 78 059 test day records from the first, second and third lactations of 3 792 cows, daughters of 210 sires and 1 677 dams. Single- or two-trait random regression models were used with fixed effects of calving year, calving month, dry period and calving interval and random additive genetic and permanent environmental effects. The last two fixed effects were not included in the analysis of first lactation data. The highest values of heritabilities for all traits, except DM, were observed in the second lactation. First lactation heritabilities for all traits – except milk yield and SCS – were smaller than those in the third lactation. Lactose yield was highly heritable, with average h<SUP>2</SUP> equal to 0.25, 0.29 and 0.28 in lactations 1, 2 and 3, respectively. Heritability for DM was slightly lower than that for lactose (0.22, 0.26 and 0.28 for lactations 1, 2 and 3, respectively). In all lactations heritabilities for SCS were below 0.1. Genetic correlations between DM and milk yield (0.64–0.74) were lower than those between MUN and milk yield (0.67–0.79) as well as between lactose and milk yield (0.72–0.82). In general, DM was much more closely correlated with fat or protein yield (0.55–0.79) than with MUN or lactose (0.38–0.76). Only in the third lactation the correlation between DM and protein (0.72) was lower than between lactose and protein (0.76). For all lactations there were very high genetic correlations between DM and lactose (0.96–0.98) and high correlations between DM and MUN (0.63–0.83) and between lactose and MUN (0.70–0.85). The results suggest that further research is needed, focused on DM and its relationship with other traits in larger populations. &nbsp;

scholarly journals Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

2013 ◽  
Vol 96 (9) ◽  
pp. 5923-5932 ◽  
Author(s):  
Rusbel Raul Aspilcueta Borquis ◽  
Francisco Ribeiro de Araujo Neto ◽  
Fernando Baldi ◽  
Naudin Hurtado-Lugo ◽  
Gregório M.F. de Camargo ◽  
...  
Keyword(s):  
Milk Fat ◽  
Regression Models ◽  
Genetic Parameters ◽  
Protein Yield ◽  
Random Regression ◽  
Multiple Trait ◽  
Estimation Of Genetic Parameters

scholarly journals Reaction norms in weights at 365 days old in nellore bulls in northern Brazil

2015 ◽  
Vol 36 (6Supl2) ◽  
pp. 4613 ◽  
Author(s):  
Jorge Luís Ferreira ◽  
Alliny Souza de Assis ◽  
Fernando Brito Lopes ◽  
Thomas Wayne Murphy ◽  
Marcelo Corrêa da Silva ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Reaction Norm ◽  
Genotype By Environment Interaction ◽  
Random Regression ◽  
Residual Effects ◽  
Breeding Value ◽  
Environment Interaction ◽  
Nellore Cattle ◽  
Regression Techniques ◽  
Northern Brazil

<p>Genotype by environment interaction (GxE) studies are of particular interest in Brazil because of the regional diversity of environmental effects and the wide variety of management systems. The present study evaluates GxE effects on 365 d weight (365W) of Nellore cattle raised on pasture in northern Brazil. The analysis utilized random regression techniques to model the reaction norm. Fixed effects consisted of sex, contemporary group, and the covariate of age of cow at calving. The environmental gradient, defined by the concatenation of a bull and the state in which the calf was born, was modeled by second order Legendre polynomials. Direct additive genetic and residual effects were fit as random. Results showed differences in the magnitude of expression of genotype in proportion to decreasing favorability of the environment. As the environment became more unfavorable, the correlation of breeding value to different environments decreased. The correlations between the intercept and the level slope for 365W feature were of moderate magnitude, predominantly indicating the reclassification of sires in different environments. Reaction standard model was coherent from a technical and biological view point and enabled the perception of GxE in the genetic evaluation of Nellore cattle in the states of Maranhão, Pará and Tocantins.</p><p> </p>

scholarly journals Milk fatty acid characterization and genetic parameter estimates for milk conjugated linoleic acid in buffaloes

2011 ◽  
Vol 78 (2) ◽  
pp. 178-183 ◽  
Author(s):  
Humberto Tonhati ◽  
André LF Lima ◽  
Dante PD Lanna ◽  
Gregório MF de Camargo ◽  
Fernando Baldi ◽  
...  
Keyword(s):  
Linoleic Acid ◽  
Conjugated Linoleic Acid ◽  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameter ◽  
Buffalo Milk ◽  
Parameter Estimates ◽  
Lactation Length ◽  
Quadratic Effects ◽  
Delta 9 Desaturase

The objectives of this study were to analyse buffalo milk fat composition, to verify the activity of Delta(9)-desaturase enzyme in the mammary gland, as well as to estimate additive genetic variances for milk, fat and protein yield, and milk cis-9,trans-11 conjugated linoleic acid percentage (cis-9,trans-11 CLA%). A total of 3929 lactation milk yields (MY) records from 2130 buffaloes and 1598 lactation fat (FY) and protein (PY) yield records from 914 buffaloes were analysed. For cis-9,trans-11 CLA%percentage, a total of 661 milk samples from 225 buffaloes, daughters of 8 sires, belonging to 4 herds and calving in 2003 and 2004, were used. The genetic parameters and variance components were estimated by Restricted Maximum Likelihood applying an animal model. The fixed effects considered in the model were: contemporary group (herd, year, calving season) and age at calving (linear and quadratic effects) and lactation length (linear and quadratic effects) as covariables. Additive genetic and permanent environment effects were considered as random. The MY, FY, PY and CLA% means were 1482±355 kg, 90·1±24·6 kg, 56·9±15·2 kg and 0·69±0·16%, respectively. Heritability estimates for MY, FY, PY and CLA% were 0·28±0·05, 0·26±0·11, 0·25±0·11 and 0·35±0·14, respectively. There is enough additive genetic variation for buffalo milk, protein and fat yield to improve these traits through selection. The cis-9,trans-11 CLA% can be enhanced by selection in buffaloes and will contribute to improving human health. The activity and efficiency of Delta(9)-desaturase in the mammary was measured and confirmed.

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