INTRODUCTION Growth can be defined as an increase in body size per unit of time (Tompić et al., 2011). Modeling growth curves of animals is a necessary tool for optimizing the management and efficiency of animal production (Köhn et al., 2007). However, growth can only be at- tained under nonlimiting conditions. For example, food needs to be available ad libitum; the nutrient content must at least meet the required ratios in relation to energy; intake must not be constrained by the bulk of the food or the presence of toxins; and environmental factors such as high temperature and disease must not constrain intake (Emmans and Kyriazakis, 1999). An animal’s genetic potential for growth can described in terms of its growth curve (Emmans and Fisher, 1986). The available literature on ostrich growth used data from South African farms and modeled only the Gom- pertz growth function (du Preez et al., 1992; Cilliers et al., 1995; Cooper, 2005). In Brazil, ostrich production began in 1995 with the importation of the first animals from Italy (Carrer et al., 2005). In 2006, the estimated number of commercially farmed birds in the country was 335,425, according to the Brazilian Ostrich-Rear- ing Yearbook (Anuário da Estrutiocultura Brasileira, 2005/2006). Despite the size of the national flock, no studies describing its growth are available. The objec- tive of this study was to fit growth curves using non- linear and linear functions to describe the growth of ostriches in the Brazilian population. MATERIALS AND METHODS The data used for the growth analysis came from commercial flocks and were provided by the Brazilian Ostrich Rearers’ Association (Associação dos Criadores de Avestruz do Brasil), based in São Paulo, SP, Brazil. This institute approved the use of this data to perform this research. A total number of 441 BW records from 58 hens and 54 cockerels measured from hatching to 383 d of age were used. The animals were crossbreds from the African Black, Red Neck, and Blue Neck breeds. The exact proportions of these genetic groups within each animal were unknown. Figure 1 shows animals of the African Black breed. Figure 1a shows a triplet consisting of 1 cockerel (at the center) and 2 hens. They are 8-yr-old animals with an approximate BW of 150 kg and approximate height of 2.20 m. Figure 1b shows 8-mo-old male and female chicks, with no visible sexual differentiation in plum- age, with approximate BW and height of 75 kg and 1.80 m, respectively. After the chicks had hatched, they were weighed, tagged around the neck for identification, and trans- Growth curves for ostriches (Struthio camelus) in a Brazilian population S. B. Ramos,* S. L. Caetano,* R. P. Savegnago,* B. N. Nunes,* A. A. Ramos,† and D. P. Munari* 1 *Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, 14884-900, Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, São Paulo, Brazil; and †Departamento de Produção e Exploração Animal, Faculdade de Medicina Veterinária e Zootecnia, Universidade Estadual Paulista, 18618-970, Botucatu, São Paulo, Brazil ABSTRACT The objective of this study was to fit growth curves using nonlinear and linear functions to describe the growth of ostriches in a Brazilian popula- tion. The data set consisted of 112 animals with BW measurements from hatching to 383 d of age. Two non- linear growth functions (Gompertz and logistic) and a third-order polynomial function were applied. The parameters for the models were estimated using the least-squares method and Gauss-Newton algorithm. The goodness-of-fit of the models was assessed using R 2 and the Akaike information criterion. The R 2 calculat- ed for the logistic growth model was 0.945 for hens and 0.928 for cockerels and for the Gompertz growth model, 0.938 for hens and 0.924 for cockerels. The third-order polynomial fit gave R 2 of 0.938 for hens and 0.924 for cockerels. Among the Akaike information criterion cal- culations, the logistic growth model presented the low- est values in this study, both for hens and for cockerels. Nonlinear models are more appropriate for describing the sigmoid nature of ostrich growth. Key words: growth, nonlinear models, ostrich, Struthio camelus 2013 Poultry Science 92:277–282 http://dx.doi.org/10.3382/ps.2012-02380 PRODUCTION, MODELING, AND EDUCATION 277 Received April 3, 2012. Accepted September 8, 2012. 1 Corresponding author: danisio@fcav.unesp.br ©2013 Poultry Science Association Inc. Downloaded from https://academic.oup.com/ps/article-abstract/92/1/277/1555006 by guest on 30 July 2018