Estimation of Genetic Trends for Test-Day Milk Yield by the Logarithmic Form of Wood Function Using a Random Regression Model
الموضوعات :ز. پزشکیان 1 , ع.ا. شادپرور 2 , س. جوزی شکالگورابی 3
1 - Department of Animal Science, Faculty of Agricultural Science, University of Guilan, Rasht, Iran
2 - Department of Animal Science, Faculty of Agricultural Science, University of Guilan, Rasht, Iran
3 - Department of Animal Science, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
الکلمات المفتاحية: milk yield, Holstein, wood function, genetic trend, random regression model,
ملخص المقالة :
Estimation of genetic trends is necessary to monitor and evaluate selection programs. The objective of this study was to estimate the genetic trends for milk yield in Iranian Holsteins cows using random regression test day model. Data set was consisted of 743205 test-day records from 1991 to 2008, which were collected by the Animal Breeding Centre of Iran. Breeding, environmental and phenotypic values were estimated using a random regression test-day model. The logarithmic form of Wood function was chosen to fit the additive genetic and permanent environmental effects of milk yield. Genetic, environmental, phenotypic trends were estimated by regressing the mean of breeding values, environmental values and phenotypic values on birth year. The genetic and phenotypic trends were positive and significant, whereas environmental trends were not significant. Genetic trends of sires and dams were estimated separately and it was positive and significant for dams, but it was not significant for sires. The phenotypic, environmental and genetic correlation between each days in milk and total 305 days were estimated. The correlations related to breeding values were weak and it showed that with the logarithmic transformation of milk yield, persistency can be improved independently from milk production.
Abdullahpour R., Moradi Shahrbabak M., Nejati-Javaremi A., Vaez Torshizi R. and Mrode R. (2013). Genetic analysis of milk yield, fat and protein content in Holstein dairy cows in Iran: legendre polynomials random regression model applied. Arch. Tierzucht. 56(48), 497-508.
Chegini A., Shadparvar A.A. and Ghavi Hossein-Zadeh N. (2013). Genetic trends for milk yield, persistency of milk yield, somatic cell count and calving interval in Holstein dairy cows of Iran. Iranian J. Appl. Anim. Sci. 3(3), 503-508.
Elahi Torshizi M., Aslamenejad A.A., Nassiri M.R., Farhangfar H., Solkner J., Kovac M., Meszaros G. and Malovrh S. (2013). Analysis of test day milk yield by random regression models and evaluation of persistency in Iranian dairy cows. Iranian J. Appl. Anim. Sci. 3(1), 67-76.
Ghavi Hossein-Zadeh N., Nejati Javaremi A., Miraei Ashtiani S. R. and Kohram H. (2008). An observational analysis of twin births, calf stillbirth, calf sex ratio and abortion in Iranian Holsteins. J. Dairy Sci. 91, 4198-4205.
Jakobsen J.H., Madsen P., Jensen J., Pedersen J., Christensen L. G. and Sorensen D.A. (2002). Genetic parameters for milk production and persistency for Danish Holsteins estimated in random regression models using REML. J. Dairy Sci. 85, 1607-1616.
Jamrozik J. and Schaeffer L.R. (1997). Estimates of genetic parameters for test-day model with random regressions for yield traits of first lactation Holsteins. J. Dairy Sci. 80, 762-770.
Katkasame S., Tumwasorn S., Thanindratarn B. and Pasanpanich S. (1996). Trend analysis on milk production traits in the dairy farming promotion organization of Thailand. Kasetsart J. Natal. Sci. 30, 211-219.
Katok N. and Yanar M. (2012). Milk traits and estimation of genetic, phenotypic and Environmental trends for milk and milk fat yields in Holstein Friesian cows. Int. J. Agric. Biol. 14, 311-314.
Khanzadeh H., Ghavi Hossein-Zadeh N. and Naserani M. (2013). Estimation of genetic parameters and trends for milk fat and protein percentages in Iranian Holsteins using random regression test day model. Arch. Tierzucht. 56(47), 487-496.
Khorshidie R., Shadparvar A.A., Ghavi Hossein-Zadeh N. and Joezy-Shakalgurabi S. (2012). Genetic trends for 305-day milk yield and persistency in Iranian Holsteins. Livest. Sci. 144, 211-217.
Koonawootrittriron S., Elzo M.A. and Thongprapi T. (2009). Genetic trends in Holstein × other breeds multibreed dairy population in central Thailand. Livest. Sci. 122, 186-192.
Lasslo L.L., Bradford G.E., Torell D.T. and Kennedy B.W. (1985). Selection for weaning weight in Targhee sheep in two environments. II. Correlated effects. J. Dairy Sci. 61, 387-395.
Meyer K. (2007). WOMBAT Version 1.0 User Notes. Uni New England, Armidale, NSW, Australia.
Miglior F., Muir B.L. and Van Doormaal B.J. (2005). Selection indices in Holstein cattle of various countries. J. Dairy Sci. 88(3), 1255-63.
Moradi Shahr Babak M. (2001). Persistency in dairy cattle. Iranian J. Agric. Sci. 32(1), 193-202.
Ruiz R., Oregui L.M. and Herrero M. (2000). Comparison of models for describing the lactation curve of latxa sheep and an analysis of factors affecting milk yield. J. Dairy Sci. 83, 2709-2719.
Sadeghi-Sefidmazgi A., Moradi-Shahrbabak M., Nejati-Javaremi A.,, Miraei-Ashtiani S.R. and Amer P.R. (2012). Breeding objectives for Holstein dairy cattle in Iran. J. Dairy Sci. 95(6), 3406-3418.
Sahebhonar M. (2007). Estimation of genetic trends for production traits and specification of some effective factors on these trends in Iranian Holsteins. MS Thesis. TehranUniv., Tehran, Iran.
Sahebhonar M., ShahrBabak M.M., Ashtiani S.R.M. and SayadNezhad M.B. (2011). An estimation of genetic trend for production traits and a determination of the impact of some factors on it in Iranian Holstein cattle. Iranian J. Anim. Sci. 41, 173-174.
SAS Institute. (2007). SAS®/STAT Software, Release 9.2. SAS Institute, Inc., Cary, NC. USA.
Savar Sofla S. and Pasha Eskandari Nasab M. (2008). Estimation of genetic parameters of production traits of Holstein cows in different climate regions of Iran. J. Agric. Natur. Res. 65, 152-158.
Wood P.D.P. (1967). Algebraic model of the lactation curve in cattle. Nature. 216, 164-165.
