Modelos mistos no ajuste de curvas de crescimento de Ricinus communis L.

Abstract

The world energy demand must be met, however, the conventional sources are nearing exhaustion, and cause harmful effects to the environment. In this sense, it has been researched renewable energy sources as an alternative to bioenergy, which could contribute substantially in the future supply of energy. One of the aspects of bioenergy is that of biodiesel, a biodegradable fuel alternative to diesel oil, created from renewable energy sources, free of sulfur in its composition. In the field of oil seed, castor bean (Ricinus communis L.) has stood out as a supplier of raw material to manufacture biodiesel. In Rio Grande do Sul, for the ricinoculture becomes sustainable production-level scale as raw material for biodiesel production in the increment becomes crucial. And this depends on the development of agricultural technologies adapted to the conditions of the state. In this context, there is a paucity of research to study the influence of density on the cultivation of oilseeds and their connection with the form of plant growth. Since this factor can influence significantly the development of castor bean, reflecting production. This research aims to evaluate the influence of three planting densities 1.0, 1.2 and 1.4 m, keeping constant the distance between the row of 1.0 m, on the growth of castor bean. To explain this influence will be used the technique of analysis of longitudinal data using growth curve modeling using mixed model methodology. It was found that this allows to explore more fully the information provided by the data, because it is possible to accommodate the correlation of these through the selection of covariance structures. Thus, the six covariance structures tested to model the G and R were selected UN (1) and VC. The strategy used to select both of these structures as for the random effects proved to be simpler alternative in this part of modeling. In univariate analysis of profile to choose the fixed effects model with some information provided by both techniques, you can check which one best fits the data. Shaped curve is a two densities 1 and 1.4 m that provided the greatest plant height did not differ significantly. For the cultivation density of 1.2 m, the plant showed a lower growth, its growth behavior was modeled by another curve. Even considering the computational complexity of the procedures used, it is hoped, through the SAS routines compiled this material, contribute to greater facilitation in the use of these procedures.