Evaluation of non-linear models for genetic parameters estimation of growth curve traits in Kermani sheep

Abstract

In the present study, 10,116 body weight-age records were measured on 2537 Kermani lambs. The records were collected from Kermani Sheep Breeding Station, located in Shahrbabak city, Kerman Province, south-eastern part of Iran, between 1993 and 2013 and used for evaluation of non-linear models describing growth curve from birth to yearling age and estimation of genetic parameters for growth curve traits in Kermani sheep. Six non-linear models including Brody, negative exponential, von Bertalanffy, Richards, Verhulst, and Gompertz were compared applying Akaike’s information criterion (AIC), root mean square error (RMSE) and Durbin-Watson statistic (DW) for determining the most appropriate model describing the growth curve in Kermani sheep. The von Bertalanffy model showed the lowest AIC and RMSE among the tested models. Furthermore, positive autocorrelations were found between residuals under the all tested model with the lowest value under the von Bertalanffy model. Therefore, von Bertalanffy model was selected as the best one for describing growth curve in Kermani sheep. A multivariate animal model was used for genetic analysis of the growth curve traits including parameters A (estimated mature weight), B (an integration constant related to initial animal weight), K (maturation rate), inflection age (IA), and inflection weight (IW) under a Bayesian approach. Posterior means for heritability estimates of A, B, K, IA, and IW were significant values of 0.10, 0.03, 0.04, 0.15, and 0.10, respectively. The parameter A had significant and positive genetic and phenotypic correlations with parameters B, IA, and IW. The posterior means for genetic and phenotypic correlations between parameters A and K were negative estimates of − 0.32 and − 0.22, respectively, implied that the lambs with slower maturation rate had higher mature weight. Positive and medium estimates were obtained for posterior means of phenotypic (0.31) and genetic (0.35) correlations between B and K. The posterior means for phenotypic and genetic correlations of B with IA and IW were not statistically significant. High and positive estimates were obtained for posterior means of genetic (0.6) and phenotypic (0.84) correlations between IA and IW. Generally, von Bertalanffy model showed high level of adequacy for describing the growth curve in Kermani sheep. Low additive genetic variations were found for all the studied growth curve traits. Therefore, the traits highly influenced by environmental which necessitate improving environmental influencing factors on the studied traits for achieving desired shape of growth curve and developing an efficient breeding strategy in Kermani sheep.

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Acknowledgments

The authors wish to thank all Breeding Station staff of Kermani sheep, especially Mr. M. Meimandi-Nia which involved in data collection and maintaining the flock through the years.

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Correspondence to Morteza Sattaei Mokhtari.

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Mokhtari, M.S., Borzi, N.K., Fozi, M.A. et al. Evaluation of non-linear models for genetic parameters estimation of growth curve traits in Kermani sheep. Trop Anim Health Prod 51, 2203–2212 (2019). https://doi.org/10.1007/s11250-019-01927-w

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Keywords

  • Growth pattern
  • Non-linear functions
  • Sheep
  • Bayesian approach