Estimation of Genetic Parameters for Milk Production Traits Using a Multiple Traits Model in Holstein Dairy Cattle

AbstractThis study provides estimates of genetic parameters for various diseases, fertility and 305-day milk production traits in dairy cattle using data from a UK national milk recording scheme. The data set consisted of 63891 multiple lactation records on diseases (mastitis, lameness, milk fever, ketosis and tetany), fertility traits (calving interval, conception to first service, number of services for a conception, and number of days to first service), dystocia and 305-day milk, fat and protein yield. All traits were analysed by multi-trait repeatability linear animal models (LM). Binary diseases and fertility traits were further analysed by threshold sire models (TM). Both LM and TM analyses were based on the generalized linear mixed model framework. The LM included herd-year-season of calving (HYS), age at calving and parity as fixed effects and genetic, permanent environmental and residual effects as random. The TM analyses included the same effects as for LM, but HYS effects were treated as random to avoid convergence problems when HYS sub-classes had 0 or 100% incidence. Because HYS effects were treated as random, herd effects were fitted as fixed effects to account for effect of herds in the data. The LM estimates of heritability ranged from 0•389 to 0•399 for 305-day milk production traits, 0•010 to 0•029 for fertility traits and 0•004 to 0•038 for diseases. The LM estimates of repeatability ranged from 0•556 to 0•586 for 305-day milk production traits, 0•029 to 0•086 for fertility traits and 0•004 to 0•100 for diseases. The TM estimates of heritabilities and repeatabilities were greater than LM estimates for binary traits and were in the range 0•012 to 0•126 and 0•013 to 0•168, respectively. Genetic correlations between milk production traits and fertility and diseases were all unfavorable: they ranged from 0•07 to 0•37 for milk production and diseases, 0•31 to 0•54 for milk production and poor fertility and 0•06 to 0•41 for diseases and poor fertility. These results show that future selection programmes should include disease and fertility for genetic improvement of health and reproduction and for sustained economic growth in the dairy cattle industry.

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ESTIMATION OF GENETIC PARAMETERS FOR MILK PRODUCTION TRAITS IN A HERD OF HOLSTEIN FRIESIAN CATTLE IN EGYPT

Journal of Animal and Poultry Production ◽

10.21608/jappmu.2014.69537 ◽

2014 ◽

Vol 5 (5) ◽

pp. 267-278

Author(s):

H. Rushdi ◽

M. Ibrahim; ◽

N. Shaddad ◽

A. Nigm

Keyword(s):

Milk Production ◽

Genetic Parameters ◽

Production Traits ◽

Milk Production Traits ◽

Holstein Friesian ◽

Friesian Cattle ◽

Estimation Of Genetic Parameters

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Comparison of different polynomial functions in Random Regression Model for milk production traits of Iranian Holstein dairy cattle

Annals of Animal Science ◽

10.2478/aoas-2013-0078 ◽

2014 ◽

Vol 14 (1) ◽

pp. 55-68 ◽

Cited By ~ 1

Author(s):

Ali Mohammadi ◽

Sadegh Alijani ◽

Hossein Daghighkia

Keyword(s):

Dairy Cattle ◽

Regression Model ◽

Milk Production ◽

Genetic Parameters ◽

Random Regression ◽

Polynomial Functions ◽

Early Lactation ◽

Production Traits ◽

Milk Production Traits ◽

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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Genetic parameters for milk production traits and breeding goals for Gir dairy cattle in Brazil

Genetics and Molecular Research ◽

10.4238/2015.october.19.2 ◽

2015 ◽

Vol 14 (4) ◽

pp. 12585-12594 ◽

Cited By ~ 1

Author(s):

M.A. Prata ◽

L.E. Faro ◽

H.L. Moreira ◽

R.S. Verneque ◽

A.E. Vercesi Filho ◽

...

Keyword(s):

Dairy Cattle ◽

Milk Production ◽

Genetic Parameters ◽

Production Traits ◽

Milk Production Traits ◽

Breeding Goals

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Estimation of Genetic Parameters for Lameness Trait and Its Relationship with Milk Production Traits in Iranian Holstein Cows

Research on Animal Production ◽

10.29252/rap.8.17.93 ◽

2018 ◽

Vol 8 (17) ◽

pp. 93-98

Author(s):

Sheida Varkoohi ◽

Meisam Shilanan ◽

Saheb Forotanifar ◽

Alireza Eghbal

Keyword(s):

Milk Production ◽

Genetic Parameters ◽

Holstein Cows ◽

Production Traits ◽

Milk Production Traits ◽

Estimation Of Genetic Parameters

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Estimation of Genetic Parameters for Milk Production Traits Using a Random Regression Test-day Model in Holstein Cows in Korea

Asian-Australasian Journal of Animal Sciences ◽

10.5713/ajas.2009.80110 ◽

2009 ◽

Vol 22 (7) ◽

pp. 923-930 ◽

Cited By ~ 7

Author(s):

Byeong-Woo Kim ◽

Deukhwan Lee ◽

Jin-Tae Jeon ◽

Jung-Gyu Lee

Keyword(s):

Milk Production ◽

Genetic Parameters ◽

Random Regression ◽

Holstein Cows ◽

Production Traits ◽

Milk Production Traits ◽

Regression Test ◽

Estimation Of Genetic Parameters

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Multivariate REML estimates of genetic parameters of monthly test day milk production traits in first parity Iranian Holstein cows with the use of a repeatability test day model

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200012989 ◽

2003 ◽

Vol 2003 ◽

pp. 139-139

Author(s):

H. Farhangfar ◽

P. Rowlinson ◽

M. B. Willis

Keyword(s):

Dairy Cattle ◽

Milk Production ◽

Genetic Parameters ◽

Large Population ◽

Genetic Evaluation ◽

Major Influence ◽

Production Traits ◽

Milk Production Traits ◽

Breeding Values ◽

Repeatability Test

In practical dairy cattle breeding programmes, usually a small number of animals (selected from a large population) have a major influence on the genetic gain of the concerned population over a period of time (Hofer, 1998). Candidate animals are usually selected based on their breeding values that are predicted by using animal models. In order to predict breeding values, genetic parameters (calculated from variance and covariance components) of the traits under consideration should be estimated to be used in genetic evaluation systems either based on lactation or test day models. The use of test day models has increasingly become of interest in genetic evaluation of dairy cattle due to the fact that they can take more accurate account of the effects of environmental factors influencing test day milk yield over the course of lactation. The main objective of this study was to use a repeatability test day animal model to estimate genetic parameters of monthly test day milk production traits in first parity Iranian Holsteins.

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