Growth curve in Mengali sheep breed of Balochistan.
Mansoor Tariq, Masroor Ahmad Bajwa, Abdul Waheed, Ecevit Eyduran, Ferhat Abbas, Farhat Abbas Bokhari, Ahmad Saiful Akbar
Abstract
Mansoor Tariq, Masroor Ahmad Bajwa, Abdul Waheed, Ecevit Eyduran, Ferhat Abbas, Farhat Abbas Bokhari, Ahmad Saiful Akbar
Abstract
Growth, one of the most essential traits for farm animals, is defined as an increase in tissues and organs of the animals per unit time and affected by genetic and environmental factors. The growth that has sigmoid form is explained reliably by nonlinear growth models (such as Monomolecular, Brody, Gompertz, Richards and Logistic). Information about parameters of these nonlinear models enables researcher to obtain beneficial clues for selection studies. Data on 2377 Mengali sheep kept at four different research stations (Experimental Station CASVAB, Quetta, (ESC), Mastung, Noshki and Quetta) at three different locations in Balochistan were analyzed using Gompertz growth model, W(t) = A*exp(B*exp(-k*t) with non-linear regression methodology. Body weight values for all the sheep were recorded monthly from birth to 360th days of age. Body weight averages of these sheep in each period were used to define the weight-age relationship in Mengali sheep. Determination coefficient (R) and Root of Mean Square Error (RMSE) were used to decide whether Gompertz growth model was appropriate for the body weight – age data from Mengali Sheep. Convergence was achieved after 5 iterations. The parameters A, B, and k of Gompertz growth model were 36.924, 2.043 and 0.010083, respectively. These parameter estimates were statistically significant (P<0.01). Root of Mean Square Error (RMSE) and Determination Coefficient (R) were 1.022, 99.17% respectively. Besides, it was determined the observed and predicted weight values at each time period in Gompertz growth model were almost similar. These results reflected that Gompertz growth model reliably explained relationship between weight and age in Mengali sheep. As a result, Gompertz growth model fitted to the body weight – age data from Mengali sheep might help us to determine an accurate feed regime, maturity age, and problems in growth and development over time.
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Growth, one of the most essential traits for farm animals, is defined as an increase in tissues and organs of the animals per unit time and affected by genetic and environmental factors. The growth that has sigmoid form is explained reliably by nonlinear growth models (such as Monomolecular, Brody, Gompertz, Richards and Logistic). Information about parameters of these nonlinear models enables researcher to obtain beneficial clues for selection studies. Data on 2377 Mengali sheep kept at four different research stations (Experimental Station CASVAB, Quetta, (ESC), Mastung, Noshki and Quetta) at three different locations in Balochistan were analyzed using Gompertz growth model, W(t) = A*exp(B*exp(-k*t) with non-linear regression methodology. Body weight values for all the sheep were recorded monthly from birth to 360th days of age. Body weight averages of these sheep in each period were used to define the weight-age relationship in Mengali sheep. Determination coefficient (R) and Root of Mean Square Error (RMSE) were used to decide whether Gompertz growth model was appropriate for the body weight – age data from Mengali Sheep. Convergence was achieved after 5 iterations. The parameters A, B, and k of Gompertz growth model were 36.924, 2.043 and 0.010083, respectively. These parameter estimates were statistically significant (P<0.01). Root of Mean Square Error (RMSE) and Determination Coefficient (R) were 1.022, 99.17% respectively. Besides, it was determined the observed and predicted weight values at each time period in Gompertz growth model were almost similar. These results reflected that Gompertz growth model reliably explained relationship between weight and age in Mengali sheep. As a result, Gompertz growth model fitted to the body weight – age data from Mengali sheep might help us to determine an accurate feed regime, maturity age, and problems in growth and development over time.
Key concepts: Gompertz function, Growth curve (statistics), Sigmoid function, Mathematics, Breed, Mean squared error, Coefficient of determination, Body weight