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Search Result For 'AJVS. Vol. 52(1): 81-86. January, 2017 DOI: 10.5455/ajvs.248866 Using Nonlinear Models to Describe Body Weight Growth Curves in Three Different Lines of Japanese Quail Fatma D.M. Abdallah Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, 44511Egypt. Abstract Key words: Nonlinear model, growth curve, Japanese quail. The aim of this study was to choose the best predictive model for the accurate description of data of 240 quail' , Result Number : 1

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Fatma Desouky Mohamed Abdallah
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AJVS. Vol. 52(1): 81-86. January, 2017 DOI: 10.5455/ajvs.248866 Using Nonlinear Models to Describe Body Weight Growth Curves in Three Different Lines of Japanese Quail Fatma D.M. Abdallah Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, 44511Egypt. Abstract Key words: Nonlinear model, growth curve, Japanese quail. The aim of this study was to choose the best predictive model for the accurate description of data of 240 quail's body weight. Non-linear function models were used for estimating growth curves in three lines of Japanese quail, high, low and control. The non-linear models which used were Gompertz, Brody and Logistic model. The models were fitted to weight-age data, from hatch (0), 2, 4 to 6 weeks of age of 240 quails. The weight-age data were modeled by using non-linear regression procedure of Statgraphics statistical package program. Model parameters were estimated using the Levenberg–Marquardt algorithm and comparisons among models were done based on mean square error, adjusted coefficient of determination, Akaike information criterion (AIC) and number of iterations. The results showed that the body development of the three lines could be illustrated well by three models. The Logistic and Gompertz growth curve model were fitted to data especially in high group where adjusted coefficient of determination is 97.7246 and 97.5972 respectively. The smallest value of Akaike information criterion (AIC) was 1138.80 high line in Logistic model. The Gompertz model is better in case of low line and the Logistic model is better in case of high and control line. The logistic model gives the best fit of data followed by the Gompertz. The Brody equation was found to be unsuitable in control group.

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