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Estimation of calving difficulty (Co)variance components of Iranian Holstein heifers using a sire-maternal grandsire threshold model

Published online by Cambridge University Press:  23 November 2017

R Abdullahpour*
Affiliation:
Animal Science Department, Science and Research Branch of Islamic Azad University, Tehran, Iran
M Moradi-Shahrebabak
Affiliation:
Animal Science Department, University of Tehran, Karaj, Tehran, Iran
H Mehrabani-Yeganeh
Affiliation:
Animal Science Department, University of Tehran, Karaj, Tehran, Iran
M Sayadnezhad
Affiliation:
Animal Breeding Center, Karaj, Iran
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Extract

Calving difficulty, biologically and statistically, have special characteristics which require researchers to use more complex models for its analysis. First, it is influenced by maternal effect and therefore the models should take this aspect into account. This is why animal models with maternal effect or sire-maternal grandsire models are employed. Secondly, it is recorded subjectively using usually five scores, one for a normal delivery to five for a Caesarean parturition. In other words, calving difficulty is a discrete trait and is not distributed normally. In theory, methods for analyzing continuous data are not appropriate for categorical data. In the 1980s, researchers developed a standard threshold model (a nonlinear model) for genetic analysis of these traits (Harville et. al. 1984). In the threshold model each phenotype in the categorical scale is associated with an unobservable underlying continuous variable with normal distribution. The objective of this study was to estimate (co)variance components of calving difficulty and genetic parameters using a threshold model.

Type
Poster presentations
Copyright
Copyright © 2016 The American Society of International Law

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References

Abdullahpour, R. 2005. The effects of using sperms from low-dystocia bulls on the calving ease and production traits in Holstein cattle, M.Sc. thesis, Department of Animal Science, University of Tehran.Google Scholar
Harville, D. A., Mee, R. W.. 1984. A mixed-model procedure for analyzing ordered categorical data. Biometrics. 40:393-408.CrossRefGoogle Scholar
Kachman, D. Stephan. 2001. Analysis of generalized linear mixed models with MATVEC, Department of Biometry, University of Nebraska, Lincoln.Google Scholar
Van Tassel, C. P., Wiggans, G. R. and Misztal, I.. 2003. Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States. Journal of Dairy Science. 86:3366-3373.CrossRefGoogle Scholar

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Estimation of calving difficulty (Co)variance components of Iranian Holstein heifers using a sire-maternal grandsire threshold model
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