Document Type : Research Paper
Authors
Abstract
In order to estimate the genetic parameters and comparison legendre polynomials for production traits of Iranian Holstein dairy cattle test-day records of first lactation cows for milk yield, fat yield, protein yield, fat percentage and protein percentage traits were used. These records collected from 2006 to 2010, by the Animal Breeding center of Iran. The genetic parameters were estimated using REML algorithm by random regression model with legendre polynomials of order 3 to 5. According to the results, order 5 of legendre polynomials were proposed for fitting permanent environment and additive genetic effects for the milk yield, fat and protein percentages traits, and order 4 of legendre polynomials for the fat and protein yields. Residual variances were considered homogeneous over the lactation period. The Phenotypic variance of the considered traits during lactation was not constant and it was higher at the beginning and the end of lactation. Additionally, the estimated permanent environment variance was larger than genetic variances throughout the lactation. Estimates of heritability were found to be lowest during early lactation. The additive genetic correlation between lactation adjacent days were more than between distant test days. The genetic trend of milk yield was showed an increasing phase during the10 past years, while this genetic trend for fat and protein percentages declined
Abdullahpour, R., Moradi Shahrbabak, M., Nejati Javaremi, A. and Vaez Torshizi, R. (2010). Genetic analysis of daily milk, fat percentage and protein percentage of Iranian first lactation Holstein cattle. World Applied Sciences Journal, Vol, 10, No, 9, pp: 1040-1046.
Biassus, L.D.O., Cobuci, J.A., Costa, C.N., Rorato, P.R.N., Neto, J.B. and Cardoso, L.L. (2011). Genetic parameters for production traits inprimiparous Holstein cows estimated by random regression models Genetic parameters for production traits in primiparous Holstein cows estimated by random regression models. Journal Revista Brasileira de Zootecnia, Vol, 40, No, 1, pp: 85-94.
Bignardi, A.B., El Faro, L., Cardoso, V.L., Machado, P.F. and Albuquerque, L.G.d. (2009). Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil. Livestock Science, Vol, 123, pp: 1-7.
Bohlouli, M. and Alijani, S. (2012). Genotype by environment interaction for milk production traits in Iranian Holstein dairy cattle using random regression model. Livestock Research for Rural Development, Vol, 24, No, 7, p: 7.
Cobuci, J.A., Costa, C.N., Neto, J.B. and Freitas, A.F. (2011). Genetic parameters for milk production by using random regression models with different alternatives of fixed regression modeling. Revist Brasileira de Zootecnia, Vol, 40, No, 3, pp:557-567.
Costa, N.C., Melo, C.M.R.D., Pakcer, l.U.A.F.D., Teixeira, N.M. and Cobuci J.A. (2008). Genetic parameters for test day milk yield of first lactation Holstein cows estimated by random regression using Legendre polynomials. Revist Brasileira de Zootecnia, Vol, 37, No, 4, pp: 602-608.
De Roos, A.P.W., Harbers, A.G.F. and Jong G. (2004). Random herd curves in a test-day model for milk, fat and protein production of dairy cattle in the Netherlands. Journal Dairy Science, Vol, 87, pp: 2693-2701.
El Faro, L., Cardoso, V.L. and Albuquerque, L.G.d. (2008). Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae). Genetics and Molecular Biology, Vol, 31, pp: 665-673.
Hammami, H. 2009. Genotype by Environment Interaction for Production Traits of Holsteins Using Two Countries as Model: Luxembourg and Tunisia. Ph.D. Thesis, Animal Science Unit, Gembloux Agricultural University, Gembloux, Belgium.
Henderson, C.R. (1984). Application of linear models in animal breeding. University of Guelph, Canada.
Jakobsen, J.H.P., Madsen, J., Jensen, J., Pedersen, L.G. and Sorensen, D.A. (2002). Genetic Parameters for Milk Production and Persistency for Danish Holsteins Estimated in Random Regression Models using REML. Journal Dairy Science, Vol, 85, pp:1607-1616.
Jamrozik, J., Schaeffer, L.R. and Dekkers, J.C.M. (1997). Genetic Evaluation of Dairy Cattle Using Test Day Yields and Random Regression Model. Journal of Genetics and Animal Breeding, Vol, 80, pp: 1217-1226.
Jensen, J. (2001). Genetic Evaluation of Dairy Cattle Using Test-Day Models. Journal of Dairy Science, Vol, 84, pp: 2803-2812.
Kettunen, A. and Mantysaari, E A, Poso J. (2000). Estimation of genetic parameters for daily milk yield of primiparous Ayrshire cows by random regression test-day models. Livestock Production Science, Vol, 66, pp: 251-261.
Krikpatrick, M, Lofsvold, D. and Bulmer, M. (1990). Analysis of the inheritance, selection and evaluation of growth trajectories. Genetics, Vol, 124, pp: 979-993.
Liu, Z, Reinhart, F. and Reents, R. (2001). Application of a random regression model to genetic evaluations of test day yields and somatic cell scores in dairy cattle. Interbull Bulletin No, 26, pp: 159-166.
Lopez-Romero, P. and Carabano, M.J. (2003). Comparing alternative random regression models to analyses first lactation daily milk yield data in Holstein–Friesian cattle. Journal Livestock Production Science. Vol, 82, pp: 81-96.
Misztal, I., Tsuruta, S., Strabel, T., Auvray, B., Druet, T., Lee, D.H. (2002). BLUPF90 and related programs (BGF90), Proc, 7th WCGALPP, Montpellier, France. CD-ROM Communication, 28: 07.
Moghaddaszadeh Ahrabi, S., Pasha Eskandarinasab, M., Alijani, S. and Abbasi, M.A. (2004). Genetic Evaluation of a Holstein Dairy Cattle herd for milk and fat yield traits using test day records and Random Regression Model.1th congress on animal science and aquaculture Iran.(In Farsi)
Mohammadi, A., Alijani, S., Rafat, S.A., Taghizadeh, A. and Buhloli, M (2012). Comparison of Fitting Performance of Polynomial Functions in Random Regression Model for Test Day Milk Yield in of Iranian Holstein Dairy Cattle. Research on Animal productions 6, pp: 46-63. (In Farsi)
Razmkabir, M., Moradi Shahrbabak, M., pakdel, A. and Nejati Javaremi, A. (2008). Estimation of genetic parameters for milk production test day records in dairy cattle. 3th Iranian congress on animal science.(In Farsi)
Sahebhonar, M., Moradi Shahr Babak, M., Miraei Ashtiani, S.R. and Sayaadnejad, M.B. (2010). Estimation of genetic trends and factors affecting production traits in Iranian Holstein Cattle. Journal of Animal Science Iran, period 41, pp: 173-184.(In Farsi)
Sargolzae, M.(2002).Pedigree, user guide.Department of animal and genetic, Animal Science Research institute. Karaj. Iran.
SAS Institute Inc.(2003). SAS 9.1.3 Help and Documentation, Cary, NC: SAS Institute Inc.
Schaeffer, L.R. (2004). Application of random regression models in animal breeding. Journal Livestock Production Science, Vol, 86, pp: 35-45.
Schaeffer, L.R. and Dekkers, J.C.M. (1994). Random regressions in animal models for test-day production in dairy cattle. Proc. 5th World Congress of Genetics Applied to Livestock Production. Guelph, Ontario, kCanada, pp :443-446.
Shadparvar, A.A. and Yazdanshenas, M.S. (2005). Genetic parameters of milk yield and milk fat percentage test day records of Iranian Holstein cows. Journal Animal Science, Vol, 9, pp:1231-1236.
Swalve, H.H. (1995). The effect of test day models on the estimation of genetic parameters and breeding values for dairy traits. Journal Dairy Science, Vol, 78, pp: 929-938.
Takma, C. and Akbas, Y. (2009). Comparison of Fitting Performance of Random Regression Models to Test Day Milk Yields in Holstein Friesians. Journal Kafkas University Veterinary Fakultesi Dergisi. Vol, 15, No, 2, pp: 261-266.
Van der werf, J.H.J., Goddard, M.E. and Meyer, k. (1998). The use of covariance functions and random regressions for genetic evaluation of milk production based on test day records. Journal Dairy Science, Vol, 81, pp: 3300-3308.
)