Modelos não lineares na descrição do crescimento da planta de pinhão manso

• Ano de defesa: 2018
• Autor(a) principal: Miranda, Lucivânia Ferreira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Estatística e Experimentação Agropecuária; UFLA; brasil; Departamento de Ciências Exatas
• Palavras-chave em Português: Biodiesel; Energias Renováveis; Curva de Gompertz; Renewable energy; Gompertz model; Estatística
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/41018

The increasing demand for renewable energy sources, also known as clean energy, places Brazil in a prominent place in this sector, mainly because of the objective of total or partially replacing the production of mineral diesel for biodiesel. Biodiesel is a fuel made from vegetable oils, residual oils, and animal fats. Crops that store oil substances in fruits and seeds have been researched as alternative sources of energy. Among these crops, jatropha has been attracting the interest of many researchers for its productivity, oil use quality, and the ability to develop well in semi-arid regions. Therefore, a quantitative study is necessary to investigate the agronomic aspects of this culture since the literature is very scarce. Thus, the study of the growth of jatropha over time is of paramount importance, given that it is an informative tool for the proper management and detection of factors that affect plant development. The modeling of this type of growth can better subsidize the knowledge and application of efficient agricultural practices techniques. The objective of this paper is to adjust and compare the nonlinear Logistic and Gompertz models with four parameters in the description of the growth of the jatropha plant. The data refer to the measurement of plant height, considering the days after the beginning of the phenological cycle, and its measurement occurred in the second year of plant development. We adjusted the Logistics and Gompertz models with four parameters and found them to be suitable for analyzing plant growth. Furthermore, it was necessary to add a first-order autoregressive parameter. In conclusion, the Logistic model was the most suitable for the CNPAE-102 access and the Logistic and Gompertz with AR(1) for CNPAE-169 and CNPAE-259, respectively. We also found that CNPAE-102 access had the greatest height when compared to the others.