03289naa a2200289 a 450000100080000000500110000800800410001902200140006002400370007410000200011124501290013126000090026050008530026952015220112265300270264465300220267165300150269365300180270870000200272670000180274670000150276470000200277970000170279970000210281670000220283777301400285910604742022-09-05       2020    bl uuuu     u00u1 u    #d  a1678-992X7 a10.1590/1678-992x-2018-02632DOI1 aLAMPERT, V.D.N.  aModelling beef cattle production systems from the pampas in brazil to assess intensification options.h[electronic resource]  c2020  aArticle history: Received August 08, 2018 /Accepted January 18, 2019. Corresponding author (julio.barcellos@ufrgs.br). Acknowledgments: To the Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul (FUNDECT), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) ?  Programa Nacional de Pós-Doutorado (PNPD) (Project - 2842/2017). Authors? Contributions: Conceptualization: Lampert, V.N.; Barcellos, J.O.J. Data acquisition: Lampert, V.N.; Barcellos, J.O.J. Data analysis: Lampert, V.N.; Barcellos, J.O.J.; Mercio, T.Z.; Mcmanus, C.M.; Dill, M.D. Design of methodology:Lampert, V.N.; Barcellos, J.O.J. Writing and editing:Lampert, V.N.; Barcellos, J.OJ.; Teixeira, O.S.; Oliveira,T.E.; Canozzi, M.E.A.  aABSTRACT: 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.  aADOPTION OF TECHNOLOGY  aANIMAL PRODUCTION  aMANAGEMENT  aSTOCKING RATE1 aCANOZZI, M.E.A.1 aMCMANUS, C.M.1 aDILL, M.D.1 aOLIVEIRA, T.E.D1 aMERCIO, T.Z.1 aTEIXEIRA, O.D.S.1 aBARCELLOS, J.O.J.  tScientia Agricola, 2020, Volume 77, Issue 4, Article number e20180263. OPEN ACCESS. DOI: http://dx.doi.org/10.1590/1678-992x-2018-0263.