Modelagem do desenvolvimento corporal e da glândula mamária de cabritas Saanen alimentadas para diferentes ganhos em pesos

Abstract

A proper nutritional management of growing kids is very important, since they will be future milk producers. The aim of this work was to evaluate the use of nonlinear models to estimate body mass growth, biometric measurements and mammary gland (MG) growth of Saanen goats fed with different protein levels. For this experimente it was used 40 Saanen goats, provided by a single farm, with 109.1 ± 21.4 days and live weight (LW) of 12.9 ± 2.9 kg. These goats were monitored from weaning until 30 days of gestation, from February to December 2015. The experiment presented four groups with different diets, each group was composed of ten animals, whose objective was to obtain different weight gains. The diets predicted an average daily weight gain (ADWG) of 90, 130, 170 and 210 g. The diets predicted crude protein was 15, 17, 18 and 19%. Diets were low gain, medium-low gain, medium-high gain and high gain. Animals were weighed and had their mammary gland measured weekly, as biometric measurements were done biweekly. There was no effect (p <0.05) of pre-pubertal diets. The model that stood out to estimate body mass growth was the Logistic model. For the biometric measures of the rump height (HG), body length (CC), rump width (LG), breast width (LP) and trunk depth (PROF), the model that stood out was the generalized Michaelis-Menten. For length of croup (CG) the best was Gompertz model. MG growth was best evaluated by exponential model. It is worth metioning that there was no significant difference (p <0.05) in MG growth in pre- and post-pubertal periods. The use of hormonal protocols did not negatively influence MG growth. The use of models to estimate body mass growth, biometric measurements and MG growth is effective. For growing Saanen kids, it is recommended 18% diet CP in order to obtain maximum body and MG growth