The world goat herd has increased more compared to other livestock species mainly due to ease of adaptation of the goat to different environments. Thus, the nutritional requirements of these animals change according to the environment to which they are, in addition, other physiological factors can affect their nutritional requirements , such as gender, breed and reproductive stage. In this sense, researchers have focused on developing mathematical models that can better predict the nutritional requirements in order to optimize animal performance. The objective of this study is to develop a dynamic-empirical model that can better predict protein and energy requirements of pregnant goats. The database to be used to develop the models is from data generated in the Project FAPESP 2009/10125-0, 2007/58239-8 and 2006/60480-2, which involve development of fetus and pregnancy products, as well as nutritional requirements of pregnant goats. The equations will be developed using the Marquadt method in the NLIN procedure of SAS. Criteria used to select the model that best fit the characteristics are: convergence of the analysis, mean square error and coefficient of determination of the model (R2). The models will be evaluated with an independent database by regressing residual (observed minus predicted) values on the predicted values centered on their mean values.
News published in Agência FAPESP Newsletter about the scholarship: