Economic values for growth and finishing production systems of Nellore and crossbred cattle

• Autor(a) principal: Peripolli, E. [UNESP]
• Data de Publicação: 2016
• Outros Autores: Oliveira, M. S.L. [UNESP], Baldi, F. [UNESP], Pereira, A. S.C., Vercesi, A. E. [UNESP], e Albuquerque, L. G. [UNESP]
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.21071/az.v65i250.481; http://hdl.handle.net/11449/228165
• topic: Beef management system; Bio-economic model; Carcass yield; Production system

A bio-economic model called Beef Management System was developed to obtain economic values for four growth and finishing cattle production system. A total of four rearing and finishing systems, two were composed by Nellore cattle and the others by crossbred cattle (½ Taurine; ½ Zebu) were tested. For each genetic group, two production systems were developed, one with full time grazing animals and the second with animals grazing during the rearing period and subsequent feedlot finishing. The economic values were estimated by simulations in electronic tables, using the Microsoft Office Excel, considering the average daily gain (ADG), dressing percentage (DP), feed intake (FI) and maintenance energy (ME) for each production system proposed. To obtain the economic values, ADG and DP were increased in 1 %, and ME and FI were reduced in 1 %. With an increase of 1 % in the DP and ADG, the cost to obtain 33.11 pounds decreased in all studied models. A 1 % reduction in animal’s ME resulted in a decrease of 0.45 % in the cost to produce 33.11 pounds in both grazing and subsequent feedlot models and decreased 0.55 % in both full grazing models. With the 1 % reduction in animal’s CA, the cost of 33.11 pounds decreased 0.83 and 0.84 % in the grazing and subsequent feedlot models with Nellore and Crossed cattle; and 0.85 and 0.83 % in full grazing models with Nellore and Crossed cattle. These traits shown an enormous impact on growth and fattening economic systems in cattle production, and DP shown an advantage over the others, once this variable resulted in the highest economic values for all systems analyzed. Thus, through the composition of the four models and the variables included in each of them, it was possible to measure the real genetic impact and its importance related to economic values in cattle production.