Global warming is affecting agribusiness in its economic aspects. Therefore, the prediction of the evolution of Brazilian beef cattle production cost was made using the IPCC forecast scenario for global warming. The methodology consisted of two steps: (i) the development of a fuzzy model that estimated the grazing land capacity (RP) decrease risk as a function of the changes in the average total rain index, air temperature and increase in extension of the dry season; and (ii) the design of an algorithm for predicting the decrease in production as function of the RPfuzzy model, that results in the impact in beef cattle productivity, and consequent increase in production costs. Historical environmental data from important producing counties in the Cerrado were organized and a set of fuzzy Gaussian functions were developed, and three possible settings (optimistic, medium and pessimistic) were considered. The decrease in beef cattle productivity was estimated using the losses in production due to the increase in air temperature and vulnerability of pasture capacity. The boundary settings for the total increase of production cost scenario used the number of animals per area of grazing land, the adoption of grain supplement and its future scenario; and the result output function pointed to a threshold within a variation from an increase in production cost of 80% (optimistic) to 160% (pessimistic). Under the optimistic scenario the total cost of Brazilian beef cattle production in the Cerrado became near to US$ 2.88 kg-1, while in the pessimistic scenario this cost reached US$ 4.16 kg-1, challenging the international competitiveness of this economic segment.
dry season; environmental temperature; fuzzy simulation; mathematical modeling
