Genetic Parameters for Milk Yield and Persistency in Carora Dairy Cattle Breed Using Random Regression Model

Abstract The aim of this research was to compare different polynomial functions including Legendre polynomials (LP), Wilmink (WRR) and Ali-Schaeffer (ARR) functions, in random regression model (RRM) for estimation of genetic parameters for milk production traits of Iranian Holstein dairy cattle. For this purpose the performance records obtained from test-day (TD) regarding milk yield, fat and protein contents of the cows calving for the first time were used. The numbers of records for the above mentioned traits were 701212, 657004, and 560775, respectively. These records were collected from the years 2006 to 2010 by the National Breeding Center of Iran. The genetic parameters were estimated using Restricted Maximum Likelihood (REML) method by applying RRM. Residual variances were considered homogeneous over the lactation period. To compare the model, different criteria (-2Logl, AIC, BIC and RV) were used for considered traits. Based on the results obtained, for all traits, RRM with LP function (2,5) were chosen as the best model. Considering residual variance (RV), LP (2,2) was proved to be a model which has the lowest performance, while using -2Logl, AIC, BIC criteria, RRM with ARR function was the worst model. According to the results, it is recommended to use LP with low orders for the additive genetic effects and with more orders for the permanent environment effects in the RRM for Iranian Holstein cattle. Permanent environment variance was higher in early lactation than during lactation and additive genetic variance in the early lactation was lower than at the end of lactation. Heritability range of milk yield, fat and protein contents was estimated to be from 0.08 to 0.23, 0.05 to 0.20 and 0.08 to 0.14, respectively. Phenotypic variance of the considered traits during lactation was not constant and it was higher at the beginning and the end of lactation. The additive genetic correlation between adjacent test days was higher than between distant test days.

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Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

Genetics and Molecular Biology ◽

10.1590/s1415-47572005000100013 ◽

2005 ◽

Vol 28 (1) ◽

pp. 75-83 ◽

Cited By ~ 35

Author(s):

Jaime Araujo Cobuci ◽

Ricardo Frederico Euclydes ◽

Paulo Sávio Lopes ◽

Claudio Napolis Costa ◽

Robledo de Almeida Torres ◽

...

Keyword(s):

Regression Model ◽

Milk Yield ◽

Genetic Parameters ◽

Random Regression ◽

Holstein Cows ◽

Random Regression Model ◽

Estimation Of Genetic Parameters

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Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model

Arquivo Brasileiro de Medicina Veterinária e Zootecnia ◽

10.1590/1678-4162-12071 ◽

2021 ◽

Vol 73 (1) ◽

pp. 18-24

Author(s):

E.P.B. Santos ◽

G.L. Feltes ◽

R. Negri ◽

J.A. Cobuci ◽

M.V.G.B. Silva

Keyword(s):

Regression Model ◽

Milk Yield ◽

Legendre Polynomials ◽

Genetic Parameters ◽

Genetic Correlations ◽

Random Regression ◽

Third Order ◽

Good Tool ◽

Components Of Variance ◽

Random Regression Model

ABSTRACT The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records.

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ESTIMATION OF GENETIC PARAMETERS FOR MILK YIELD IN THE FIRST THREE LACTATIONS OF HOLSTEIN COWS USING RANDOM REGRESSION MODEL

Egyptian Journal of Animal Production ◽

10.21608/ejap.2007.93151 ◽

2007 ◽

Vol 44 (1) ◽

pp. 49-62

Keyword(s):

Regression Model ◽

Milk Yield ◽

Genetic Parameters ◽

Random Regression ◽

Holstein Cows ◽

Random Regression Model ◽

Estimation Of Genetic Parameters

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Impact of the Order of Legendre Polynomials in Random Regression Model on Genetic Evaluation for Milk Yield in Dairy Cattle Population

Frontiers in Genetics ◽

10.3389/fgene.2020.586155 ◽

2020 ◽

Vol 11 ◽

Author(s):

Jianbin Li ◽

Hongding Gao ◽

Per Madsen ◽

Rongling Li ◽

Wenhao Liu ◽

...

Keyword(s):

Dairy Cattle ◽

Regression Model ◽

Milk Yield ◽

Legendre Polynomials ◽

Genetic Evaluation ◽

Random Regression ◽

Cattle Population ◽

Random Regression Model

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The relationship between temperature-humidity index and test-day milk yield of Iranian Holstein dairy cattle using random regression model

Livestock Science ◽

10.1016/j.livsci.2013.09.005 ◽

2013 ◽

Vol 157 (2-3) ◽

pp. 414-420 ◽

Cited By ~ 17

Author(s):

Mehdi Bohlouli ◽

Jalil Shodja ◽

Sadegh Alijani ◽

Alireza Eghbal

Keyword(s):

Dairy Cattle ◽

Regression Model ◽

Milk Yield ◽

Random Regression ◽

Temperature Humidity Index ◽

Random Regression Model ◽

Humidity Index ◽

The Relationship

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ASSOCIATION ANALYSIS BETWEEN MICROSATELLITE DNA MARKERS AND MILK YIELD AND ITS COMPONENTS IN EGYPTIAN BUFFALOES USING A RANDOM REGRESSION MODEL

Egyptian Journal of Animal Production ◽

10.21608/ejap.2012.94341 ◽

2012 ◽

Vol 49 (1) ◽

pp. 9-18

Keyword(s):

Regression Model ◽

Association Analysis ◽

Milk Yield ◽

Dna Markers ◽

Microsatellite Dna ◽

Random Regression ◽

Random Regression Model ◽

Microsatellite Dna Markers

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Test-day or 305-day milk yield for genetic evaluation of Gir cattle

Pesquisa Agropecuária Brasileira ◽

10.1590/s1678-3921.pab2019.v54.00325 ◽

2019 ◽

Vol 54 ◽

Cited By ~ 1

Author(s):

Rodrigo Junqueira Pereira ◽

Denise Rocha Ayres ◽

Mário Luiz Santana Junior ◽

Lenira El Faro ◽

Aníbal Eugênio Vercesi Filho ◽

...

Keyword(s):

Regression Model ◽

Milk Yield ◽

Genetic Evaluation ◽

Random Regression ◽

Breeding Values ◽

Random Regression Model ◽

The Mean ◽

Yield Record ◽

Genetic Evaluations ◽

Dairy Breed

Abstract: The objective of this work was to compare genetic evaluations of milk yield in the Gir breed, in terms of breeding values and their accuracy, using a random regression model applied to test-day records or the traditional model (TM) applied to estimates of 305-day milk yield, as well as to predict genetic trends for parameters of interest. A total of 10,576 first lactations, corresponding to 81,135 test-day (TD) records, were used. Rank correlations between the breeding values (EBVs) predicted with the two models were 0.96. The percentage of animals selected in common was 67 or 82%, respectively, when 1 or 5% of bulls were chosen, according to EBVs from random regression model (RRM) or TM genetic evaluations. Average gains in accuracy of 2.7, 3.0, and 2.6% were observed for all animals, cows with yield record, and bulls (sires of cows with yield record), respectively, when the RRM was used. The mean annual genetic gain for 305-day milk yield was 56 kg after 1993. However, lower increases in the average EBVs were observed for the second regression coefficient, related to persistency. The RRM applied to TD records is efficient for the genetic evaluation of milk yield in the Gir dairy breed.

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