Modelos duplo sigmoidais para o crescimento de frutos do cafeeiro

• Ano de defesa: 2016
• Autor(a) principal: Fernandes, Tales Jesus
• Tipo de documento: Tese
• 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: Inferência Bayesiana; Café; Duplo Logístico; Reamostragem por importância; Regressão não linear; Bayesian inference; Coffee; Double Logistic; Importance resampling; Nonlinear regression; Probabilidade e Estatística Aplicadas
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/11215

Coffee is one of the main products of Brazilian agriculture, the country is currently the largest producer and exporter. Knowing the growth pattern of a fruit can assist in the development of culture indicating for example, the times of increased fruit weight and its optimum harvest, essential to improve the management and quality of coffee. Some authors indicate that the growth curve of the coffee fruit has a double sigmoid shape. However, it consists of just a visual observation without exploring the use of regression models. The aims of this study were: i) determine if the growth pattern of the coffee fruit is really double sigmoidal; ii) to propose a new approach in weighted importance re-sampling to estimate the parameters of regression models and select the most suitable double sigmoidal model to describe the growth of coffee fruits; iii) to study the spatial distribution effect of the crop in the growth curve of coffee fruits. In the first article the aim was determine if the growth pattern of the coffee fruit is really double sigmoidal. The models double Gompertz and double Logistic showed significantly superior fit to models of simple sigmoid confirming that the standard of coffee fruits growth is really double sigmoidal. In the second article we propose to consider an approximation of the likelihood as the candidate distribution of the weighted importance resampling, aiming to facilitate the process of obtaining samples of marginal distributions of each parameter. This technique was effective since it provided parameters with practical interpretation and low computational effort, therefore, it can be used to estimate parameters of double sigmoidal growth curves. The nonlinear model double Logistic was the most appropriate to describe the growth curve of coffee fruits. In the third article aimed to verify the influence of different planting alignments and sun exposure faces in the fruits growth curve. A difference between the growth rates in the two stages of fruit development was identified, regardless the side. Although it has been proven differences in productivity and quality of coffee, there was no difference between the growth curves in the different planting alignments herein studied.