Cenários de produção bovina no Rio Grande do Sul: o comportamento dos agentes sobre os sistemas

Abstract

The decision making process is singular due to the fact that each farmer attributes different levels of importance according to economic environment, physical characteristics of the farm, as well as previous experience. The need to adapt quickly to change in order to satisfy increasingly demanding consumers is a common factor. In order to do this, the use of simulation models is very important, since alternative scenarios can be simulated in reduced time. This work was developed in two stages. Firstly, the simulation results of biological development of beef cattle in the Pampa Corte Model were compared to available data taken from scientific papers, in order to verify its reliance. Secondly, a study of the beef cattle production chain was made under the technical-economical perspective. Simulations are presented in a mathematical model of technological alternatives and associated costs. This process, used by farmers results in products (in this case, meat) with distinct qualitative attributes, particular to the various regions of the state, which are differed by the natural and financial resources available and by farmer (agents) behaviour. The results demonstrate that the Pampa Corte model is a reliable tool in the prediction of beef cattle performance in pasture systems, and its database has to be enlarged according to forage availability and situations of favourable climate. The development of a market alliance in the North of Rio Grande do Sul, as a way of coordinating agents, has improved farmer income through additional benefit. However, the high standard required by these alliances inserts high production costs to the system, due to the use of supplements in cool and warm season cultivated pastures. Even when destined to the regular market, southern farmers may count on positive financial results. In this case, the logic of the economical analysis should emphasize the availability of land, as well as system sustainability.