Predição de consumo de matéria seca de bovinos de corte confinados

Abstract

The projections for the production of beef in Brazil over the next 10 years indicate an annual increase of about 3.5% per year. For the same period, it is estimated an increase of 2.22% per annum in domestic consumption and 3.07% per annum in exports of beef that could reach the level of 3.4 million tons in 2019, consolidating the Brazil as the largest exporter of beef (MAPA / AGE, 2009). The beef production in Brazil is characterized by production systems based on pastures covered by tropical forage and predominantly zebu animals, with a Nelore the most frequent. More than 80% of the Brazilian herd has some genetic composition derived from Zebu (Ripamonte, 2002). The increasing environmental pressure should contain the advance of cattle on new areas, making it essential to increase productivity in existing areas to increase in production. Therefore, appropriate technologies should be developed and implemented to enable the expansion of cattle. According to Oliveira (2014) food consumption is the nutritional factor that most influences the performance of the animals. Thus, accurate prediction of CMS is essential to predict responses in nutritional and economic production systems. Alternatively, meta-analysis is a 'tool' that enables combine the results of individual studies independently and synthesize their findings or draw a new conclusion (LUIZ, 2002). Allows to make a synthesis of contradictory data, no matter how small their analytical potêcia, providing significant advance on the subject studied with greater representativeness (Lovatto; Sauvant, 2001). The meta-analysis is superior to traditional ix forms of literature review by more accurately estimate the effects of treatments, adjusting them to trial heterogeneity (Lovatto et al., 2007) .This work has as objective to develop a prediction equation for consumption dry matter in confined cattle cuts through the national experiments of data gathering from 2002 to 2014 of the Journal of Animal Science and Medicine Archives of Veterinary and Animal Science Brazilian