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Genetic Persistency of First Lactation Milk Yield Estimated Using Random Regression Model for Indian Murrah Buffaloes
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 Title & Authors
Genetic Persistency of First Lactation Milk Yield Estimated Using Random Regression Model for Indian Murrah Buffaloes
Geetha, E.; Chakravarty, A.K.; Vinaya Kumar, K.;
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A random regression model was applied for the first time for the analysis of test day records and to study the genetic persistency of first lactation milk yield of Indian Murrah buffaloes. Wilmink's Function was chosen to describe the shape of lactation curves. Heritabilities of test day milk yield varied from 0.33 to 0.58 in different test days. The highest heritability was found in the initial test day ( day) milk yield. Genetic correlations among test day milk yields were higher in the initial test day milk yield and decreased when the test day interval was increased. The magnitude of genetic correlations between test day and 305 day milk yield varied from 0.25 to 0.99. The genetic persistencies of first lactation milk yield were estimated based on daily breeding values using two methods. is the genetic persistency estimated as a summation of the deviation of estimated daily breeding value on days to attain peak yield from each day after days to attain peak yield to different lactation days. is the genetic persistency estimated as the additional genetic yield (gained or lost) from days to attain peak yield to estimated breeding value on different lactation days relative to an average buffalo having the same yield on days to attain peak yield. The mean genetic persistency on 90, 120, 180, 240, 278 and 305 days in milk was estimated as -4.23, -21.67, -101.67, -229.57, -330.06 and -388.64, respectively by , whereas by on same days in milk were estimated as -3.96 (-0.32 kg), -23.94 (-0.87 kg), -112.81 (-1.96 kg), -245.83 (-2.81 kg), -350.04 (-3.28 kg) and -407.58 (-3.40 kg) respectively. Higher magnitude of rank correlations indicated that the ranking of buffaloes based on their genetic persistency in both methods were similar for evaluation of genetic persistency of buffaloes. Based on the estimated range of genetic persistency three types of genetic persistency were identified. Genetic correlations among genetic persistency in different days in milk and between genetic persistencies on the same day in milk were very high. The genetic correlations between genetic persistency for different days in milk and estimated breeding value for 305 DIM was increased from 90 DIM to 180 DIM, and highest around 240 DIM which indicates a minimum of 240 days as an optimum first lactation length might be required for genetic evaluation of Indian Murrah buffaloes.
Indian Murrah Buffaloes;Wilmink Function;Daily Breeding Values;Genetic;Persistency;
 Cited by
Effect of Pregnancy on Lactation Milk Value in Dairy Buffaloes,Khan, Sarzamin;Qureshi, Muhammad Subhan;Ahmad, Nazir;Amjed, Muhammad;Durrani, Fazali Raziq;Younas, Muhammad;

Asian-Australasian Journal of Animal Sciences, 2008. vol.21. 4, pp.523-531 crossref(new window)
국내 홀스타인 젖소의 비유지속성 평가에 대한 고찰,조광현;윤호백;조충일;민홍립;이준호;공홍식;이학교;박경도;

Journal of Animal Science and Technology, 2013. vol.55. 3, pp.173-178 crossref(new window)
Ali, T. E. and L. R. Schaeffer. 1987. Accounting for covariances among test day milk yields in dairy cows. Can. J. Anim. Sci. 67:637-645

Dekkers, J. C. M., J. H. Ten Haag and A. Weersink. 1998. Economic aspects of persistency of lactation in dairy cattle. Livest. Prod. Sci. 53:237-252 crossref(new window)

Guo, Z. and H. H. Swalve. 1997. Comparison of different lactation curve sub-models in test day models. Interbull Bull. 16:75-79

Jakobsen, J. H. 2000. Genetic correlation between the shape of the lactation curve and disease resistance in dairy cattle. Ph.D. thesis, Dept. of Animal Breed. Genet. Danish Inst. Agric. Sci. Research centre, Foulum

Jamrozik, J., G. Jansen, L. R. Schaeffer and Z. Liu, 1998. Analysis of persistency of lactation calculated from a random regression test-day model. Interbull Bull. 17:64-69

Jamrozik, J., G. J. Kistemaker, J. C. M. Dekkers and L. R. Schaeffer. 1997. Comparison of possible covariates for use in a random regression model for analyses of test day yields. J. Dairy Sci. 80(10):2550-2556

Lin, C. Y. and K. Togashi. 2005. Maximization of lactation milk production without decreasing persistency. J. Dairy Sci. 88:2975-2980

Olori, V. E., W. G. Hill, B. J. McGuirk and S. Brotherstone. 1999. Estimating variance components for tesy day milk records by restricted maximum likelihood with a random regression animal model. Livest. Prod. Sci. 61:53-63 crossref(new window)

Schaeffer, L. R. and J. C. M. Dekkers. 1994. Random regressions in animal models for test-day production in dairy cattle. Proc. 5th WCGALP., Guelph. 18:443-446

Solkner, J. and W. Fuchs. 1987. A comparison of different measures of persistency with special respect to variation of test-day milk yields. Livest. Prod. Sci. 16:305-319 crossref(new window)

Strabel, T., W. Kopacki and T. Szwaczkowski. 1998. Genetic evaluation of persistency in random regression model. Proc. Interbull Evaluation Service, Uppsala, Sweden, Interbull Bull. 17:189-192

Togashi, K. and C. Y. Lin. 2003. Modifying the lactation curve to improve lactation milk and persistency. J. Dairy Sci. 86(4):1487-1493

Togashi, K. and C. Y. Lin. 2004.Efficiency of different selection criteria for persistency and lactation milk yield. J. Dairy Sci. 87:1528-1535

Van der Werf, J. H. J., M. E. Goddard and K. Meyer. 1998. The use of covariance functions and random regressions for genetic evaluation of milk production based on test day records. J. Dairy Sci. 81(12): 3300-3308

Wilmink, J. B. M. 1987. Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation. Livest. Prod. Sci. 16:335-348 crossref(new window)

Zimmermann, E. and H. Sommer. 1973. Zum Laktationskurvenverlauf von kuhen in Hochleistungsherden und dessen Beeinflussung durch nichterbliche Faktoren. Zuchtungskunde, 45:75-88