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Identify the most accurate nonlinear mathematical function to fit the growth curve of commercial broiler chickens based on statistical goodness-of-fit criteria.

October 14, 2015American Journal of Applied Scientific Research

Growth Curve of Commercial Broiler as Predicted by Different Nonlinear Functions

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Identify the most accurate nonlinear mathematical function to fit the growth curve of commercial broiler chickens based on statistical goodness-of-fit criteria.
Monitored growth data over a 6-week period (April 6 to May 17, 2015) in N=80 day-old unsexed Ross 308 broiler chicks.
Fitted three nonlinear models—Weighted Least Squares (WLS), Gompertz, and Logistic—and evaluated fit using coefficient of determination (R²), adjusted R², and mean square error (MSE).
The Weighted Least Squares (WLS) function demonstrated the best fit for modeling broiler growth compared to the Gompertz and Logistic models.
Parameter estimates for the WLS model established an asymptotic weight (β0) of 2088, an integration constant (β1) of -3.68, and a maturity rate (β2) of 0.14.

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Implication

Comparative modeling study finds weighted least squares outperforms Gompertz and Logistic functions in Ross 308 broilers, indicating superior accuracy for poultry growth trajectory modeling.

Cite This Study

Firas Rashad Al-Samarai (2015) studied this question.

synapsesocial.com/papers/69fd8183ea4a61241c5d263e https://doi.org/10.11648/j.ajasr.20150102.11

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Implication

Comparative modeling study finds weighted least squares outperforms Gompertz and Logistic functions in Ross 308 broilers, indicating superior accuracy for poultry growth trajectory modeling.

Growth Curve of Commercial Broiler as Predicted by Different Nonlinear Functions

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Implication

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Growth Curve of Commercial Broiler as Predicted by Different Nonlinear Functions

Key Points

Discussion

Implication

Cite This Study

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