Yazar "Sariyel, V." seçeneğine göre listele

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    A Bayesian approach for describing the growth of Chukar partridges
    (EUGEN ULMER GMBH CO, 2019) Iqbal, F.; Eyduran, E.; Mikail, N.; Sariyel, V.; Huma, Z. E.; Aygun, A.; Keskin, I.
    In this article, a Bayesian approach was employed for estimating the body growth of Chukar partridge (Alectoris chukar). Nonlinear growth models commonly used to estimate the growth curve of birds were fitted to weight-age data and estimates of model parameters and their credible intervals were obtained via a formal Bayesian framework. More specifically, the Gompertz, Brody, Logistic and von Bertalanffy growth models were fitted to weekly body weight data of 108 female and 72 male partridge chicks from hatch to 20 weeks of age. Deviance Information Criteria (DIC) and the coefficient of determination (R-2) were employed as the goodness of fit for comparing the fitted models. The DIC and R-2 values of the models ranged from 172.9 to 204.2 and 0.9765 to 0.9913, respectively. The von Bertalanffy model was found to provide the best fit in terms of lower DIC and higher R-2 values, followed by the Gompertz model for both male and female partridge data. The Bayesian approach was found to be adequate for fitting complex nonlinear functions to weight-age data of Chukar partridges.
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    Comparison of growth curve models in partridge
    (OXFORD UNIV PRESS, 2017) Sariyel, V.; Aygun, A.; Keskin, I.
    This study was conducted in order to determine the goodness of fit of Brody, Gompertz, Logistic, and von Bertalanffy growth curve models in partridge (Alectoris chukar). The growth curve parameters A (upper asymptote or mature weight parameter), B (scale parameter related to initial weight), and K (instantaneous growth rate parameter) were determined as 623.4, 1.05, and 0.075 for females and 723.8, 1.06, and 0.073 for males in the Brody model, respectively, 472.9, 3.47, and 0.207 for females and 565.3, 3.59, and 0.192 for males in the Gompertz model, respectively, 440.2, 12.89, and 0.332 for females and 517.0, 14.13, and 0.319 for males in the Logistic model, respectively, and 498.9, 0.77, and 0.164 for females and 608.8, 0.79, and 0.150 for males in the von Bertalanffy model, respec-tively. While determining which growth curve model presented the better fit, the coefficient of determination (R-2), adjusted the coefficient of determination (adj. R-2), mean square predicted error (MSPE), Durbin-Watson value, correlation between estimated live weight and residual values (RESC), Akaike's information criteria (AIC), and Bayesian information criterion (BIC) were used. As a consequence of the study, it was determined that the Gompertz model yields a better fit to the data for the partridge, as its coefficient of determination and adjusted coefficient of determination are high, its values of MSPE, RESC, AIC, BIC are low and there is not an autocorrelation between the residual values. As a result, the Gompertz model presented a better fit with the partridge data.
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    Estimation of growth curve parameters in Konya Merino sheep
    (SOUTH AFRICAN JOURNAL OF ANIMAL SCIENCES, 2009) Keskin, I.; Dag, B.; Sariyel, V.; Gokmen, M.
    The objective of this study was to determine the fitness Of Quadratic, Cubic, Gompertz and Logistic functions to the growth curves of Konya Merino lambs obtained by using monthly records of live weight from birth to 480 days of age. The models were evaluated according to determination coefficient (R-2), mean square prediction errors (MSPE) and Durbin Watson (DW) statistics. The R-2 values of the models ranged from 0.96 to 0.99 for females and from 0.96 to 0.99 for males. The Cubic model gave the best R value oF 0.99 in females, while the Logistic model gave the lowest R-2 value of 0.96 in females. The results indicated that the Quadratic and Gompertz models showed the best fit to growth of Konya Merino ewe lambs by having higher R-2 values, lower MSPE and non autocorrelation. By using these models live weights at later ages could be predicted from early partial live weight data. Further studies should be carried Out on growth curve characteristics at later ages including adult age.