American Journal of Applied Scientific Research
Volume 1, Issue 2, November 2015, Pages: 6-9
Received: Sep. 25, 2015;
Accepted: Oct. 6, 2015;
Published: Oct. 14, 2015
Views 5291 Downloads 332
Firas Rashad Al-Samarai, Department of Veterinary Public Health, College of Veterinary Medicine, University of Baghdad, Baghdad, Iraq
This study was carried out to identify the better function that fit the growth curve in broiler depending on some criteria [coefficient of determination (R2), Adjusted R2 and mean square error (MSE)]. Eighty day-old unsexed broiler chicks (Ross 308) were used in this study for the period from 6/4/2015 to 17/5/2015. The growth data of broiler through 6th weeks were subjected to three nonlinear functions (Weighted Least Square (WLS), Gompertz, and Logistic). Results revealed that the WLS function was the best for fitting the growth curve in the broiler as compared with the two functions. The estimated values of asymptotic weight (β0), the integration constant (β1) and maturity rate (β2) parameters according to WLS model were 2088, -3.68 and 0.14 respectively. In conclusion: The results confirmed that WLS function was more appropriate to describe the growth curve in the broiler (Ross 308) as compared with other functions.
Firas Rashad Al-Samarai,
Growth Curve of Commercial Broiler as Predicted by Different Nonlinear Functions, American Journal of Applied Scientific Research.
Vol. 1, No. 2,
2015, pp. 6-9.
Abbas A.A., Yosif A.A., Shukur A.M., Ali F.H., 2014. Effect of genotypes, storage periods and feed additives in broiler breeder diets on embryonic and hatching indicators and chicks blood parameters. Sci. Agri. 7 (1): 44-48.
Aggrey, S.E. (2002) Comparison of Three Nonlinear and Spline Regression Models for Describing Chicken Growth Curves. Poultry Science, 81, 1782-1788. http://dx.doi.org/10.1093/ps/81.12.1782.
Gous, R.M., Moran, E.T., Stilborn, H.R., Bradford, G.D., Emmans, G.C., 1999. Evaluation of the parameters needed to describe the overall growth, the chemical growth, and the growth of feathers and breast muscles of broilers. Poultry Science 78:812-21.
Hruby, M.; Hamre, M.L. and Coon, C., 1996. Non-linear and linear functions in body protein growth. J. Appl. Res. 5: 109-115.
Knitztova, H.; Hyaek , J.; Knitze, B. and Roubicek, J., 1991. Analysis of
growth curves of fowl.1. Chickens. British Poultry Sci. 32:1027-1038.
Kuhi, H. D., Kebreab E., Lopez S., France J., 2003. An evalua¬tion of different growth functions for describing the profile of live weight with time (age) in meat and egg strains of chicken. Poultry Sci. 82, 1536–1543
Mohammed, F. A. 2015. Comparison of three nonlinear functions for describing chicken growth curves. Scientia Agriculturae, 9 (3): 120-123.
Moharrery, A., and Mirzaei, M. 2014. Growth characteristics of commercial broiler and native chickens as predicted by different growth functions. J Anim Feed Sci., 23: 82–89.
Roenick, W.P., 1998. Poultry will overtake pig meat consumption. World
Poultry. No 12. Vol 14: 14-16.
Prince, S.H. 2002. Modeling the broiler performance under small-scales and semi commercial management condition. Dissertation, Port Elizabeth Technician, George Campus.
Sabbioni A., Superchi P., BonomiA., Summer A. Boidi G.,1999. Growth curves of Ostriches in northern Italy. Paper presented in 50th EAAP Congress, Zorich, 22-26. Augest.
Santos A. L., Sakomura N.K., Freitas E.R., Fortes C.M.S., Carrilho E.N.V.M., 2005. Comparison of free range broiler chicken strains raised in confined or semi-confined systems. Rev. Bras. Cienc.Avicola 7:85–92.
SAS Institute, 2010. SAS/STAT User’s Guide, Version 9.1.SAS Institute Inc., Cary, NC.USA.
Schulze V., Rohe R., Looft H., and Kalm E., 2001. Genetic analysis of the course of individual growth and feed intake of group-penned performance tested boars. Arch. Tierz. Dummerstorf, 44:139-156.
Sun, G.R., Zhu, Z.M., He, D.G., Gong, S.M. and Shen, H.M. (2006) Development Regularity of Early Body-Weight and the Fitness of Growth Curve on Lai-Chuan cross Chicken. Chinese Journal of Animal Science, 42, 10-12.
Tompić T., Dobša J., Legen S., Tompić N., Medić H., 2011. Modeling the growth pattern of in-season and off-season Ross 308 broiler breeder flocks. Poultry Sci. 90, 2879–2887
Topal M., and Bolukbasi S.C., 2008.Comparison of Nonlinear Growth Curve Models in Broiler Chickens. JAPR 34: 149-152.
Tzeng, R.Y., Becker, W.A., 1981. Growth pattern of body and abdominal fat weight in male broiler chickens. Poultry Sci. 60:1101-1106.
Wang, D.Q., Lu L.Z., Ye W.C., Shen J.D., Tao Z.R., Tao Z.L., Ma F.L., Chen Y.C., Zhao A.Z. and Xu J. (2004) Study on the Growth Regularity of Jinyun Muscovy Duck. Zhejiang Journal of Animal Science and Veterinary Medicine, 6,3-5.
Yakupoglu, C. &Atil, H., 2001. Comparison of growth curve models on Broilers. II. Comparison of models. Online J. Biol. Sci. 7: 682-684.
Yalcin, S.; Seter, P.; Ozkan, S. and Cahaner, A., 1997. Comparative evaluation of three commercials stocks in hot versus temperate climates. Poultry Sci. 76: 921- 929.
Yang Y., Mekki D.M., Lv S.J., Wang L.Y., Wang J.Y., 2006. Analysis of fitting growth models in Jinghai mixed-sex yellow chicken. Int. J. Poult. Sci., 5: 517-521.
Zhao, Z., Li, S., Huang, H., Li, C., Wang, Q., Xue, L. 2015.Comparative study on growth and developmental model of indigenous chicken breeds in China. Open Journal of Animal Sciences, 5: 219-223