Growth curve analysis in different generations of Boer x Central Highland goats using alternative estimation models.

ABSTRACT: Growth curve analysis can help to optimize the management, determine nutritional requirements, predict the weight of animals at a specific age, and to select highly productive animals. Therefore, this study aimed to find the best-fitted nonlinear functions to provide a specific shape of the growth curve from birth to yearling age in different generations of Boer x Central Highland goats. Gompertz, Logistic, Brody, Von Bertalanffy, Monomolecular, Negative exponential, and Richards models were evaluated to quantify their ability to describe the biological growth curve. Root mean square error (RMSE), Bayesian information criterion (BIC), adjusted coefficient of determination (AdjR2), and Akaike's information criterion (AIC) were used to evaluate the goodness of fit and flexibility of the mode

SUBMITTER: Tesema Z 

PROVIDER: S-EPMC10637673 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature