Investigation of growth curves with different nonlinear models and MARS algorithm in broiler chickens.

ABSTRACT: This study was conducted to determine the live weight model of the broiler chicks by using the most appropriate mathematical growth curves. Live weights were used in broiler chicks grown for 0-6 weeks. Logistics, Gompertz, Weibull, Hossfeld and Von Bertalanffy models and multivariate adaptive regression splines (MARS) data mining algorithm were used to define the live weights of the chickens. In the comparison of the models, the determination coefficient (R2), mean square error (MSE), Akaike's Information Criterion (AIC) and Schwarz Bayesian Information Criterion (BIC) values were used. As a result of the study, it is seen that Gompertz model is the best model to define live weight of the broilers in the Gompertz model, R2, MSE, RMSE, AIC, BIC and growth rates for male broiler were 0.9998,

SUBMITTER: Sengul T 

PROVIDER: S-EPMC11584083 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature