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Traditional livestock productivity is hard to estimate, since it depends on a gamut of animal production indicators that are difficult to measure for many farms. Thus, we propose an analytical method for estimating productivity and understanding the importance of animal production indicators under different full-cycle cattle production systems in Brazil. To evaluate the impact of these indicators, equations were derived from a comutational model of herd evolution for estimating the output parameters of the system as follows: productivity per hectare (PH) and offtake rate (COR), as a function of the indicators; calving rate (CR), mating age (AM), age of slaughter (AS) and stocking rate (SR). For this analysis, twenty-seven scenarios (simulation data) of low to high productivity were used, resulting from the combination of the following factors and levels: 1) calving rate of 50, 65 and 80 %; 2) mating age of heifers of one, two and three, years of age; and 3) age at slaughter of one, two and three year old steers. The scenario with the highest impact for each parameter and the indicator of highest impact for each scenario were identified for the production conditions in the region. Under most scenarios, a reduction in mating age had a greater impact on the productivity indexes compared to a reduction in slaughter age. Appropriate management of available technologies enables farmers to compare the marginal impacts of specific indicators on full-cycle production systems for beef cattle. Keywords: adoption of technology, animal production, management, stocking rate Made available in DSpace on 2019-12-17T18:08:19Z (GMT). No. of bitstreams: 1 v77n4a05SA20180263.pdf: 544104 bytes, checksum: f1a0f0cd33a1cb950ec0f788260b70ae (MD5) Previous issue date: 2020

Movement of livestock production within a country or region has implications for genetics, adaptation, well-being, nutrition, and production logistics, particularly in continental-sized countries, such as Brazil. Cattle production in Brazil from 1977 to 2011 was spatialized, and the annual midpoint of production was calculated. Changes in the relative production and acceleration of production were calculated and spatialized using ARCGIS1. Cluster and canonical discriminant analyses were performed to further highlight differences between regions in terms of cattle production. The mean production point has moved from the Center of Minas Gerais State (in the southeast region) to the North of Goiás State (in the Midwest region). This reflects changes in environmental factors, such as pasture type, temperature and humidity. Acceleration in production in the northern region of Brazil has remained strong over the years. More recently, “traditional” cattle-rearing regions, such as the south and southeast, showed a reduction in growth rates as well as a reduction in herd size or internal migration over the period studied. These maps showed that this movement tends to be gradual, with few regions showing high acceleration or deceleration rates.