Uso de modelos não lineares na descrição do acúmulo de boro em diferentes partes do feijoeiro cultivar Jalo

• Ano de defesa: 2016
• Autor(a) principal: Lima, Kelly Pereira de
• 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: Regressão (Estatística); Regressão não linear; Feijão; Nonlinear regression; Beans; Phaseolus vulgaris L.; Análise de Dados
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/11096

The study on bean growth through accumulation over time of the micro-nutrient Boro is interesting because it represents an information tool which helps to adequately manage the plant development and detect factors that affect it. Modeling this type of growth produces a better understanding and an effective application of agricultural practices. In this context, the present study aims at adjusting the nonlinear models Logistic, von Bertalanffy and Exponential using original and transformed data on Boro accumulation in two planting systems and three seeding densities of the cultivated bean Jalo. The experiment was conducted at the Federal University of Lavras during the water harvest period (spring-summer) of the years 2006-2007 in a randomized block with three repetitions. In each planting system the factorial scheme 3 x 7 was used. It consists of three seeding densities (75, 215 and 355 thousand plants per hectare) and seven evaluation periods (13, 23, 33, 43, 53, 63 , 73 days after emergence). The Boro accumulation in the following plant parts was analyzed: rods; stem and leaves; stem, leaf and pod, and the complete plant. The nonlinear models Logistical and von Bertalanffy are suitable for the description of Boron accumulation in the bean cv Jalo; the model Logistical presents better adjustment properties. Data transformation was used to ensure the normality and homogeneity of errors, but since the data do change the accumulation characteristics with the time, the use of an exponential model to represent them was necessary. As a result, the validity of the ANOVA analysis is guaranteed.