Influência de variáveis climáticas no peso de colmeias Apis mellifera por meio de modelos estatísticos

• Ano de defesa: 2023
• Autor(a) principal: Ziegler, Cristiano
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia de Produção; UFSM; Programa de Pós-Graduação em Engenharia de Produção; Centro de Tecnologia
• Palavras-chave em Português: Abelha; Modelo; Mel; Manuseio; Bee; Model; Honey; Handling; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/29675

Increased bee mortality around the world has worried the researchers due to their environmental and economic importance, especially for pollination. New technologies are being developed to reduce this problem, such as the use of hive sensors. Data from these sensors can be used for various statistical applications, such as evaluating variables that interfere with swarm behavior. The present study aims to investigate the influence between climate variables and the weight of the hives of Apis mellifera through economic models, aiming at management in specific and qualified periods. The research begins with a literature review, presenting aspects related to the development of the Apis Mellifera bee, the statistical methods that will be used in the study and scientific publications on the subject. In materials and methods, the classification of the research is exposed, as the data collection and the methodological procedures used was performed. In the results, two scientific articles related to the theme of the study, already published in an international journal, along with a topic of the application of VAR, control charts, ARIMA and ARMAX in five different hives are exhibited. In the first article, a mapping of technologies focused on decreasing the mortality of bees of the species Apis Mellifera, through the use of patents and scientific articles. In the second article, the interrelation between climatic variables and the weight of a bee can be explained with the application of a Self-Teaching Vector model (VAR). In the other results, using statistical models and tests, it is proven that climate variables affect the weight of the hive and make it possible to identify the best periods of the year to collect honey or apply a supplementary diet. The study fulfills with the objective and has important innovations for the scientific literature, such as the application of VAR, control charts, ARIMA and ARMAX in hive weight data along with climate data and proves how much climatic variables affect the weight of the hives of Apis Mellifera.