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Modelling growth curve in Moghani sheep: comparison of non-linear mixed growth models and estimation of genetic relationship between growth curve parameters

Published online by Cambridge University Press:  08 June 2017

N. GHAVI HOSSEIN-ZADEH Open the ORCID record for N. GHAVI HOSSEIN-ZADEH [Opens in a new window]
N. GHAVI HOSSEIN-ZADEH*
Affiliation:
Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
*
*To whom all correspondence should be addressed. Email: nhosseinzadeh@guilan.ac.ir or navid.hosseinzadeh@gmail.com
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Summary

In order to describe the growth curves in Iranian Moghani sheep, five non-linear mixed mathematical equations (Brody, Negative exponential, Logistic, Gompertz and von Bertalanffy) were compared. After selecting the best-fitted model based on purely statistical criteria, variance components and genetic parameters for growth curve characteristics were estimated. The data set and pedigree information used in the current study were obtained from the breeding station of Moghani sheep and included 7905 weight records of 1581 lambs from birth to 400 days of age between the years 1994 and 2012 inclusive. Each model was fitted to body weight records for all lambs, males, females, single and twin lambs using the NLMIXED procedure in SAS and the parameters were estimated. Animal was considered as subject in the models. The non-linear mixed models were examined for goodness of fit using Akaike's information criterion (AIC) and residual variance. Marginal posterior distribution of genetic parameters and variance components were estimated using the Threshold Model programme. The Gibbs sampler was run for 1 000 000 rounds and the first 200 000 rounds were discarded as a burn-in period. Logistic model provided the best fit of growth curve in males, females, singles, twins and all lambs due to the lower values of AIC and residual variance compared with other models. Posterior mean estimates of direct heritabilities for asymptotic weight (A), initial animal weight (B) and maturation rate (K) parameters of Logistic model were 0·21, 0·24 and 0·29, respectively. Also, posterior mean estimates of maternal heritabilities for A, B and K were 0·27, 0·24 and 0·19, respectively. Estimate of correlation between direct and maternal genetic effects for A, B and K parameters were −0·33, −0·69 and −0·51, respectively. Estimates of direct genetic correlation between A–B, A–K and B–K were positive and equal to 0·19, 0·07 and 0·28, respectively. Also, maternal genetic correlations between A–B, A–K and B–K were positive and equal to 0·43, 0·34 and 0·55, respectively. In general, evaluation of different growth equations used in the current study indicated the potential of the non-linear functions to fit body weight records of Moghani sheep. Also, the results of the current study showed that improvement of growth curve parameters of Moghani sheep could be possible in selection programmes. Therefore, development of an optimal selection strategy to achieve a desired shape of growth curve through changing genetically the parameters of model would be very important.

Type
Animal Research Papers
Information
The Journal of Agricultural Science , Volume 155 , Issue 7 , September 2017 , pp. 1150 - 1159
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Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

Abdollahy, H., Hasani, S., Zerehdaran, S., Shadparvar, A. A. & Mahmoudi, B. (2012). Determination of economic values for some important traits in Moghani sheep. Small Ruminant Research 105, 161–169.CrossRefGoogle Scholar
Abegaz, S., Van Wyk, J. B. & Olivier, J. J. (2010). Estimation of genetic and phenotypic parameters of growth curve and their relationship with early growth and productivity in Horro sheep. Archiv Tierzucht 53, 85–94.Google Scholar
Bahreini Behzadi, M. R., Aslaminejad, A. A., Sharifi, A. R. & Simianer, H. (2014). Comparison of mathematical models for describing the growth of Baluchi sheep. Journal of Agricultural Science and Technology 16, 57–68.Google Scholar
Bathaei, S. S. & Leroy, P. L. (1998). Genetic and phenotypic aspects of the growth curve characteristics in Mehraban Iranian fat-tailed sheep. Small Ruminant Research 29, 261–269.CrossRefGoogle Scholar
Brody, S. (1945). Bioenergetics and Growth with Special Reference to the Efficiency Complex in Domestic Animals. New York, USA: Reinhold Publishing Corporation.Google Scholar
Brown, J. E., Fitzhugh, H. A. Jr. & Cartwright, T. C. (1976). A comparison of nonlinear models for describing weight-age relationships in cattle. Journal of Animal Science 42, 810–818.CrossRefGoogle Scholar
da Silva, L. S. A., Fraga, A. B., da Silva, F. D. L., Beelen, P. M. G., Silva, R. M. D. O., Tonhati, H. & Barros, C. D. C. (2012). Growth curve in Santa Inês sheep. Small Ruminant Research 105, 182–185.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N. (2011). Genetic parameters and trends for calving interval in the first three lactations of Iranian Holsteins. Tropical Animal Health and Production 43, 1111–1115.CrossRefGoogle ScholarPubMed
Ghavi Hossein-Zadeh, N. (2014). Comparison of non-linear models to describe the lactation curves of milk yield and composition in Iranian Holsteins. Journal of Agricultural Science, Cambridge 152, 309–324.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N. (2015 a). Modeling the growth curve of Iranian Shall sheep using non-linear growth models. Small Ruminant Research 130, 60–66.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N. (2015 b). Estimation of genetic relationships between growth curve parameters in Guilan sheep. Journal of Animal Science and Technology 57, 19. DOI: 10.1186/s40781-015-0052-6.CrossRefGoogle ScholarPubMed
Ghavi Hossein-Zadeh, N. (2015 c). Bayesian estimates of genetic relationships between growth curve parameters in Shall sheep via Gibbs sampling. Iranian Journal of Applied Animal Science 5, 897–904.Google Scholar
Ghavi Hossein-Zadeh, N. & Ardalan, M. (2010). Estimation of genetic parameters for body weight traits and litter size of Moghani sheep, using a Bayesian approach via Gibbs sampling. The Journal of Agricultural Science, Cambridge 148, 363–370.CrossRefGoogle Scholar
Goliomytis, M., Orfanos, S., Panopoulou, E. & Rogdakis, E. (2006). Growth curves for body weight and carcass components, and carcass composition of the Karagouniko sheep, from birth to 720 d of age. Small Ruminant Research 66, 222–229.CrossRefGoogle Scholar
Hyndman, R. J. (1996). Computing and graphing highest density regions. American Statistician 50, 120–126.Google Scholar
Kachman, S. D. & Gianola, D. (1984). A Bayesian estimator of variance and covariance components in nonlinear growth models. Journal of Animal Science 59(Suppl. 1), 176.Google Scholar
Kachman, S. D., Baker, R. L. & Gianola, D. (1988). Phenotypic and genetic-variability of estimated growth curve parameters in mice. Theoretical and Applied Genetics 76, 148–156.CrossRefGoogle ScholarPubMed
Laird, A. K. (1965). Dynamics of relative growth. Growth 29, 249–263.Google ScholarPubMed
Lambe, N. R., Navajas, E. A., Simm, G. & Bünger, L. (2006). A genetic investigation of various growth models to describe growth of lambs of two contrasting breeds. Journal of Animal Science 84, 2642–2654.CrossRefGoogle ScholarPubMed
Legarra, A., Varona, L. & Lopez de Maturana, E. (2011). TM: Threshold Model. Available online from: http://snp.toulouse.inra.fr/~alegarra/manualtm.pdf (Accessed 05 May 2017).Google Scholar
Lewis, R. M. & Brotherstone, S. (2002). A genetic evaluation of growth in sheep using random regression techniques. Animal Science 74, 63–70.CrossRefGoogle Scholar
Magnabosco, C. U., Lôbo, R. B. & Famula, T. R. (2000). Bayesian inference for genetic parameter estimation on growth traits for Nelore cattle in Brazil, using the Gibbs sampler. Journal of Animal Breeding and Genetics 117, 169–188.CrossRefGoogle Scholar
Malhado, C. H. M., Carneiro, P. L. S., Affonso, P. R. A. M., Souza, A. A. O. Jr & Sarmento, J. L. R. (2009). Growth curves in Dorper sheep crossed with the local Brazilian breeds, Morada Nova, Rabo Largo, and Santa Inês. Small Ruminant Research 84, 16–21.CrossRefGoogle Scholar
Maniatis, N. & Pollott, G. E. (2003). The impact of data structure on genetic (co)variance components of early growth in sheep, estimated using an animal model with maternal effects. Journal of Animal Science 81, 101–108.CrossRefGoogle ScholarPubMed
Mavrogenis, A. P. & Constantinou, A. (1990). Relationships between pre-weaning growth, post-weaning growth and mature body size in Chios sheep. Animal Production 50, 271–275.Google Scholar
McManus, C., Evangelista, C., Fernandes, L. A. C., Miranda, R. M., Moreno-Bernal, F. E. & Santos, N. R. (2003). Growth curves of Bergamácia sheep raised in the Federal District. Revista Brasileira de Zootecnia 32, 1207–1212.CrossRefGoogle Scholar
Näsholm, A. (1990). Mature weight of ewe as a trait in sheep breeding. In Proceedings of the 4th World Congress on Genetics applied to Livestock Production. XV. Beef Cattle, Sheep and Pig Genetics and Breeding, Fibre, Fur and Meat Quality, 23–27 July, Edinburgh, UK (Eds Hill, W. G., Thompson, R. & Woolliams, J.), pp. 88–91. Edinburgh, UK: Organising Committee.Google Scholar
Nelder, J. A. (1961). The fitting of a generalization of the logistic curve. Biometrics 17, 89–110.CrossRefGoogle Scholar
SAS (2002). SAS User's Guide v. 9·1: Statistics. Cary, NC, USA: SAS Institute, Inc.Google Scholar
Smith, B. J. (2005). Bayesian Output Analysis Program (BOA), Version 1.1.5. Ames, IA, USA: The University of Iowa. Available online from: http://www.public-health.uiowa.edu/boa (Accessed 05 May 2017).Google Scholar
Souza, L. A., Carneiro, P. L. S., Malhado, C. H. M., Silva, F. F. & Silveira, F. G. (2013). Traditional and alternative nonlinear models for estimating the growth of Morada Nova sheep. Revista Brasileira de Zootecnia 42, 651–655.CrossRefGoogle Scholar
Stobart, R. H., Bassett, J. W., Cartwright, T. C. & Blackwell, R. L. (1986). An analysis of body weights and maturing patterns in western range ewes. Journal of Animal Science 63, 729–740.CrossRefGoogle ScholarPubMed
Tosh, J. J. & Kemp, R. A. (1994). Estimation of variance components for lamb weights in three sheep populations. Journal of Animal Science 72, 1184–1190.CrossRefGoogle ScholarPubMed
von Bertalanffy, L. (1957). Quantitative laws in metabolism and growth. The Quarterly Review of Biology 32, 217–230.CrossRefGoogle ScholarPubMed