Modelagem bioeconômica para populações bovinas da raça Nelore em diferentes sistemas de produção

• Ano de defesa: 2024
• Autor(a) principal: Renata Felisberto Henriques
• Orientador(a): Ricardo Carneiro Brumatti
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Modelagem bioeconômica; raça Nelore; sistemas de produção.
• Link de acesso: https://repositorio.ufms.br/handle/123456789/8805

The economic importance of beef cattle farming in the Brazilian Cerrado biome is well known, however, by optimizing processes it is possible to overcome the sector's expectations. By considering performance and financial factors through simulated computer models, it is possible to establish bioeconomic evaluations, which take productivity and economic viability into account in beef cattle production. Aiming to develop a bioeconomic model, a simulation model was developed for the first time to generate information on Nelore herds in different production systems under the Cerrado biome environmental conditions. Data gathered from the literature was used to design six simulated models, representing different production systems: modal (extensive) system, improved breeding system 1, improved breeding system 2, improved breeding system 3, improved breeding system 4 and improved breeding system 5. Stochastic simulation was carried out using the Leslie matrix to describe age-structured model with age specific probability of producing calf survival and survival rates. The main target variables in the herd simulation models were quantitative, including number of animals and weight variables associated with heifer, steer and mature cows categories. In order to use the modeling economic data, a second algorithm was developed from the herd data, simulating values for income, costs and profit for all six simulated production systems. System income was simulated according to the average of arroba prices between 2021 and 2023, based on the CEPEA/B3 cattle indicator, as well as the variance related to carcass yield and fat was taken into account. Parameters related to production costs were derived from ABIEC's Beef Report 2023. The resulting gross profit for each system was derived by taking the difference between income and costs. Correlation and regression analyses were carried out to verify and evaluate the fit quality of the simulated variables. Significance was declared at p≤0.05. The modeling and statistical analyses performed were carried out by using programmed commands in the R environment. The results show a strong and positive correlation (from 0.93 to 0.99) (p < 0.05) between the observed and simulated data showing the current bioeconomic simulation model's ability to replicate all the systems studied. Regression analysis was applied to compare the observed and simulated data, showing significant linear regression for all the variables considered (p<0.05). The significance of the regression, as well as the high coefficient of determination, suggests that the bioeconomic simulation models can adequately predict the variables. The evaluated models proved to be able to predict herds and economic data, from extensive to more intensive beef cattle production in full-cycle systems. The developed solution can be applied in different contexts, providing complete evaluations to provide support for both farmers and researchers in the management of animal and economic resources in the cattle production.