A Comparison of Nonlinear Models for Describing Weight-Age Data in Anglo-Nubian Does

Abstract

The objective of this study was to determine the optimum age at last weighing and compare the goodness of fit of nonlinear models used to fit longitudinal weight-age data to describe the growth pattern of Anglo-Nubian does. Weights of 104 animals from birth to 60 months of age were grouped into 10 age groups at six-month intervals. In each age group, parameters A (asymptotic weight), B (integration constant), and K (maturity index) were estimated using the Brody, Gompertz, logistic, and von Bertalanffy models. Data were analyzed using analysis of variance in a factorial design (10 age groups × 4 nonlinear models). The age group × model interaction was not significant. Mean estimates of A, B, and K were significantly different between age groups up to 30 months (p < 0.05), indicating that the estimated curve is affected by weights taken before this age independent of the model. The values of mean squared error (MSE), mean absolute deviation (MAD), coefficient of determination (R2) and Rate of convergence (RC) at each age group up to 30 months were compared to determine the goodness of fit of nonlinear models. The ranking of fit was logistic, Brody, von Bertalanffy, and Gompertz. The logistic and Brody models respectively estimated the smallest and largest asymptotic weight. Longitudinal weight records taken until 30 months of age are most appropriate for estimating the growth of Anglo-Nubian does using nonlinear models.

The growth of domestic goats and sheep: A meta study with Bertalanffy-Pütter models

“…As to the sources and the breeds of goats, G01-G02 were Anglo Nubian (and crossbreds) from Brazil (Arre et al., 2019 ; Cavalcante et al., 2013 ; Santos et al., 2018 ), G03-G08 colored and white Angora from Turkey (Cak et al., 2017 ; Ödzdemir et al., 2009 ), G09-G10 Beetal from Pakistan ( Teleken, Galvão & Weber, 2017 ; Waheed, Khan & Sarwar, 2010 ), G11-G22 Boer from Mexico ( Garcia-Muñiz, Ramirez-Valverde, Núñez-Domínguez & Hidalgo, 2019 ), G23 Repartida from Brazil ( Pires et al., 2017 ), G24 Saanen from Turkey ( Kor, Baspinar, Karaca & Keskin, 2006 ), and G25-G29 unspecified breeds from Tunisia and Turkey ( Mabrouk et al., 2010 ; Tatar, Tekel, Özkan, Baritci & Dellal, 2009 ).…”

Generation of models from existing models composition: An application to agrarian sciences

“…However, have questions about which is the most appropriate model. The evaluation of the quality of adjustments of these models can be done several ways [35, 13].…”