Details

Autor(en) / Beteiligte

• Tariq, M.M. (University of Balochistan, Quetta (Pakistan). Centre of Advanced Studies in Vaccinology and Biotechnology)
• Iqbal, F. (University of Balochistan, Quetta (Pakistan). Dept. of Statistics)
• Eyduran, E. (Igdir Univ., Igdir (Turkey). Dept. of Animal Science)
• Bajwa, M.A. (University of Balochistan, Quetta (Pakistan). Centre of Advanced Studies in Vaccinology and Biotechnology)
• Zil-e-Huma (Sardar Bahadur Khan Women's Univ., Quetta (Pakistan). Dept. of Zoology)
• Waheed, A. (Bahauddin Zakariya Univ., Multan (Pakistan). Faculty of Veterinary Science)

Titel

Comparison of non-linear functions to describe the growth in Mengali sheep breed of Balochistan

Ist Teil von

• Pakistan journal of zoology, 2016, Vol.45 (3), p.661-665

Erscheinungsjahr

2016

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• The objectives of this study were to estimate and compare the goodness of fit six non-linear growth models, i.e. Gompertz, Logistic, Von Bertalanffy, Richards, Weibull and Morgan-Mercer-Flodin (MMF), in Mengali sheep of Balochistan. For this purpose, monthly body weight data from 2377 sheep from birth up to 360 days of age were used. The average body weights in each period were used to define the weight - age relationship in these sheep. The models parameters, adjusted coefficient of determination (R2 Adj), root mean square error (RMSE), Akaike's and Bayesian information criteria (AIC and BIC), predicted body weights and residuals were calculated for each model. Among six growth functions, the MMF model was found appropriate for its accuracy of fit according to the highest R2 Adj (0.9991) and the lowest RMSE (0.3348) followed by the Von Bertalanffy and Weibull models. The MMF model was also selected the best based on the lowest values of AIC (9.6516) and BIC (10.0489). The results of this study suggest that the MMF model can be used to accurately predict the growth in body weight of Mengali sheep.