Estudo da rastreabilidade bovina através de um modelo integrado de decisão: avaliação inicial em sistemas produtivos no Rio Grande do Sul

• Autor(a) principal: Nicoloso, Carolina da Silveira
• Data de Publicação: 2012
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/8882
• topic: Tomada de decisão; Custos; Sisbov; Decision making; Cost; Sisbov; CNPQ::CIENCIAS AGRARIAS::AGRONOMIA::EXTENSAO RURAL

With the growing international trade in beef, certification systems were developed for this product, which must be accepted worldwide, in any type of transaction. These systems were termed "traceability systems for cattle." In January 2002, through Normative Instruction No. 01, the Ministry of Agriculture, Livestock and Supply (MAPA), promulgated the Brazilian System of Identification and Certification of Bovine and buffalo SISBOV. In 2006, after the publication of several regulatory instructions and orders, the Normative Instruction 17 which established the new SISBOV. In the Rural properties the traceability can become operationally expensive and costs must be accounted for. The objective of this study is to analyze the economic impact of bovine traceability, through modeling and simulation in different production systems in Rio Grande do Sul. The methodology used was proposed by Silveira (1998), for the development of an Integrated Model of Decisions and the data were collected in the Estância do Vinte e Oito , owned by Maronna Foundation, located in Alegrete - RS. The real cost calculated for the system of production conducted in the Estância do Vinte e Oito proved to be adequate when analyzing the Gross Margin and Return on Investment in Sisbov, indicating that the system is economically feasible in the short term. In the short term, with compensation differentiated product, the Sisbov represents a profit generation for the production system. The Integrated Decision Model for simulation of costs Sisbov proved efficient in the generation of various scenarios, making it possible to identify which factors, and its nature, cause a greater impact on system costs, giving an understanding that different decisions for the system production can generate different impacts on the costs of Sisbov. This study was able to demonstrate, through scenarios generated and simulation of costs in a real production system, the type of production system (complete cycle or termination), number of animals in the herd, costs of work and costs for certifying companies are critical points that influence more forcefully the model outputs with the simulated costs for different scenarios.