Iranian Journal of animal Science

Iranian Journal of animal Science

Estimation of genetic and phenotypic parameters for milk fat to protein ratio of Holstein dairy cattle in Iran using random regression model

Document Type : Research Paper

Authors
Laleh Hakami 1
Hossein Mehrban 2
Ali Moharrery 3
Mohamad bagher Sayyadnejad 4
1 M.Sc. Student, Department of Animal Science, Faculty of Agriculture, University of Shahrekord, Shahrekord, Iran
2 Assistant Professor in Genetics and Animal Breeding, Department of Animal Science, Faculty of Agriculture, University of Shahrekord, Shahrekord, Iran
3 Professor in Animal Nutrition, Department of Animal Science, Faculty of Agriculture, University of Shahrekord, Shahrekord, Iran
4 Former M. Sc. Student, National Animal Breeding Center and Promotion of Animal Products, Iran
10.22059/ijas.2018.254475.653627
Abstract
The aim of this research was to estimate (co) variance components, heritability, genetic and phenotypic correlations between different stages of lactation for milk fat to protein ratio (FPR) of Holstein dairy cattle in Iran using a random regression model. The data used included 1302984 test day records of 149440 cows in 307 herds that were calved during the years of 1996 to 2017. Contemporary groups herd-month of recording (herd test day (HTD)), the age at the calving and lactation curve were considered as fixed effects in the model. Additive genetic and permanent environment effects were fitted by the Legendre’s orthogonal polynomial with forth order. The results showed that FPR had an adequate genetic variation, but due to the high environmental variations, the estimates of heritability were low in different stages of lactation and varied from 0.06 to 0.08. Genetic correlations of FPR in different stages of lactation were in the rage of 0.24 to 0.99. The genetic correlations between first and second stage was high (0.84); but its decreased dramatically with other stages and ranged from 0.24 to 0.52. However, the genetic correlation between the other lactation stages was gradual decreased with increasing the interval between them. The phenotypic correlations between lactation stages were lower than the genetic correlation and were observed in the range of 0.02-0.25. Genetic improvement is possible for FPR because of genetic variation; however, more daughters are needed for each sire to achieve appropriate accuracy of breeding values due to low heritability.
Keywords
genetic parameters
milk fat to protein ratio
random regression
  1. Buaban, S., Duangjinda, M., Suzuki, M., Masuda, Y., Sanpote, J. & Kuchida, K. (2016). Genetic relationships of fertility traits with test-day milk yield and fat-to-protein ratio in tropical smallholder dairy farms. Journal of Animal Science, 87, 627-637.
  2. Buttchereit, N. E., Stamer, N., Junge, W. & Thaller, G. (2010). Evaluation of five lactation curve models fitted for fat: protein ratio of milk and daily energy balance. Journal of Dairy Science, 93, 1702-1712.
  3. Buttchereit, N., Stamer, E., Junge, W. & Thaller, G. (2011). Short communication: Genetic relationships among daily energy balance, feed intake, body condition score, and fat to protein ratio of milk in dairy cows. Journal of Dairy Science, 94, 1586-1591.
  4. Cobuci, J. A., Euclydes, R. F., Lopes, P. S., Costa, C. N., Torres, R. D. A. & Pereira, C. S. (2005). Estimation of genetic parameters for test-day milk yield in Holstein cow using a Random Regression Model. Genetics and Molecular Biology, 28(1), 75-83.
  5. Coffey, M. P., Emmans, G. C. & Brotherstone, S. (2001). Genetic evaluations of dairy bulls for energy balance traits using random regression. Journal of Dairy Science, 85, 2669-2678.
  6. Coffey, M. P., Simm, G. & Brotherstone, S. (2002). Energy balance profiles for the first three lactations of dairy cows estimated using random regression. Journal of Dairy Science, 85, 2669-2678.
  7. Collard, B. L., Boettcher, P. J., Dekkers, J. C., Petitclerc, D. M. & Schaeffer, L.R. (2000). Relationships between energy balance & health traits of dairy cattle in early lactation. Journal of Dairy Science, 83, 2683-2690.
  8. de Roos, A. P. W., Harbers, A. G. F. & de Jong G. (2004). Random Herd Curves in a Test-Day Model for Milk, Fat, and Protein Production of Dairy Cattle in the Netherlands. Journal of Dairy Science, 87, 2693-2701.
  9. Falconer, D. S. & Mackay, T. F. C. (1996). Introduction to Quantitative Genetics. (4th ed.). Longman, London
  10. Geishauser, T., Leslie, K., Duffield, T. & Edge, V. (1999). The association between first DHI milk-test parameters and subsequent displaced abomasum diagnosis in dairy cows. Berl Munch Tierarztl Wochenschr, 112(1), 1-4.
  11. Goff, J. P & Horst, R. L. (1997). Physiological changes at parturition and their relationship to metabolic disorders. Journal of Dairy Science, 80, 1260-1268.
  12. Heuer, C., Schukken, Y. H. & Dobbelaar, P. (1999). Postpartum BCS and results from the first test day milk as predictors of disease, fertility, yield, and culling in commercial dairy herds. Journal of Dairy Science, 82, 295-304.
  13. Huttmann, H., Stamer, E., Junge, W., Thaller, G. & Kalm, E. (2009). Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models. Animal, 3, 181-188.
  14. Jafari Torbaghan, M., Farhangfar, e., Bastani, M., Mohammad Nazari, B. & Worry, E. (2012). Genetic evaluation of cows for milk protein yield trait using fixed and random regression test day models. Animal production research, 2, 9-20. (in Farsi)
  15. Jamrozik, J. & Schaeffer, L. R. (1997). Estimates of Genetic Parameters for a Test Day Model with Random Regressions for Yield Traits of First Lactation Holsteins. Journal of Dairy Science, 80, 762-770.
  16. Jamrozik, J & Schaeffer, L. R. (2012). Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle. Journal of Animal Breeding and Genetics, 129, 11-19.
  17. Jensen, J. (2001). Genetic evaluation of dairy cattle using test-day models. Journal of Dairy Science, 84, 2803-2812.
  18. Kessel, S., Stroehl, M., Meyer, H. H., Hiss, S., Sauerwein, H., Schwarz, F. J. & Bruckmaier, R. M. (2008). Individual variability in physiological adaptation to metabolic stress during early lactation in dairy cows kept under equal conditions. Journal of Animal Science, 86, 2903-2912.
  19. Kirkpatrick, M., Lofsvold, D. & Bulmer, M. (1990). Analysis of the Inheritance Selection and Evolution of Growth Trajectories. Genetics, 124, 979-993.
  20. Misztal, I., Tsuruta, S., Strabel, T., Auvray, B., Druet, T. & Lee, D.H. (2002). BLUPF90 and related programs (BGF90). In: Proceedings of 7th World Congress on Genetics Applied to Livestock Production, 19-23 Aug., Montpellier, France, pp. 1-2.
  21. Mrode, R. A. (2005). Linear models for the prediction of animal breeding value. Cambridge. pp. 505.
  22. Namjo, M., Farhangfar, H., Bashteni, M. & Eghbal, A.R. (2016). Assessment of the impacts of different factors on the occurrence of negative energy balance in Iranian dairy cows using a logistic generalised linear model. Journal of Ruminant Research,4(3), 96-116. (in Farsi)
  23. Negussie, E., Stranden I. & Mantysaari, E. A. (2013). Genetic associations of test-day fat: protein ratio with milk yield, fertility, and udder health traits in Nordic Red cattle. Journal of Dairy Science, 96, 1237-1250.
  24. Negussie, E., Stranden, I. & Mantysaari, E. A. (2008). Genetic associations of clinical mastitis with test-day somatic cell count and milk yield during first lactation of Finnish Ayrshire. Journal of Dairy Science, 91, 1189-1197.
  25. Nishiura, A., Sasaki, O., Aihara, M., Takeda, H. & Satoh, M. (2015). Genetic analysis of fat-to-protein ratio, milk yield and somatic cell score of Holstein cows in Japan in the first three lactations by using a random regression model. Animal Science Journal, 86, 961-969.
  26. Pool, M. H. & Meuwissen, T. H. E. (1999). Reduction of the number of parameters needed for a polynomial random regression test day model. Livestock Production Science, 64, 133-145.
  27. Pool, M. H., Janss, L. L. G. & Meuwissen, T. H. E. (2000). Genetic Parameters of Legendre Polynomials for First Parity Lactation Curves. Journal of Dairy Science, 83, 2640-2649.
  28. Puangdee, S., Duangjinda, M., Boonkum, W., Katawatin, S., Buaban, S. & Thepparat, M. (2016). Genetic associations between milk fat-to-protein ratio, milk production and fertility in the first two lactations of Thai Holsteins dairy cattle. Journal of Animal Science, 88(5), 723-730.
  29. Razmkabir M., Moradi Shahrbabak, M., Pakdel, A. S. & Nejati-javaremi, A. (2010). Estimation of Genetic Parameters of test day records of milk yield in Iranian Holstein Cows. Iranian Journal of Animal Science, 2, 171-178. (in Farsi)
  30. Schaeffer, L. R. & Dekkers, J. C. M. (1994). Random regressions in animal models for test-day production in dairy cattle. In: Proceedings of 5th World congress genetics applied livestock production, Guelph, Ontario, Canada, pp.443-446.
  31. Shadparvar, A. A. & Yazdanshenas, M. S. (2005). Genetic Parameters of Milk Yield and Milk Fat Percentage Test Day Records of Iranian Holstein Cows. Asian-Australasian Journal of Animal Science, 18(9):1231-1236.
  32. Veerkamp, R. F. & Koenen, E. P. C. (1999). Genetics of food intake live weight, condition score and energy balance. in: J.D. Oldham, G. Simm, A.F. Groen, B.L. Nielsen, J.E. Pryce, T.L.J. Lawrence (eds), Metabolic Stress in Dairy Cows. British Society of Animal Science, Occasional publication. 24, 63-73.
Iranian Journal of animal Science
Volume 49, Issue 2 - Serial Number 2
Summer 2018
Pages 213-221

  • Receive Date 13 March 2018
  • Revise Date 09 June 2018
  • Accept Date 08 July 2018