Curva de crescimento em ovinos da raça Dorper

Abstract

Sheep farming plays a significant socioeconomic role in Brazil, particularly in semi-arid areas, where adapted breeds such as Dorper have helped to strengthen sheep meat production. Growth curve analysis is a fundamental tool for understanding animal weight development and supporting management and genetic improvement strategies. In this scenario, the objective of this study was to adjust and compare nonlinear mathematical models applied to the growth curve of Dorper sheep. The study was conducted in southern Piauí, involving 80 Dorper sheep, males and females, monitored from birth to maturity. The animals were weighed at adjusted ages, starting at birth (PN), weight at 15 (P15), 30 (P30), 45 (P45), 60 (P60), 75 (P75), 90 (P90), 115 (P115), 130 (P130), 145 (P145), 160 (P160), 175 (P175), and weight at 190 days (P190). The nonlinear models of Brody, Von Bertalanffy, Gompertz, and Logistic were used to adjust the body weight data, using the R software. The Akaike information criteria (AIC), coefficient of determination (R²), and mean square error (MSE) were used to evaluate the quality of the adjustments. The results showed that the lambs grew rapidly at first, but then gradually slowed down and stabilized at around 145 days of age. Among the models evaluated, the Logistic model stood out with the best performance, presenting the lowest AIC value (2761.60), high convergence rate, and biologically consistent parameters, appropriately portraying the sigmoid growth pattern observed in animals. The Gompertz and Von Bertalanffy models also fit well, although with a slight tendency to overestimate adult weight. Therefore, the Logistic model was the most appropriate to represent the growth curve of Dorper sheep, enabling an accurate estimate of adult weight and the stages of greatest weight gain.