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Fitting of nonlinear models to data on plant growth: models comparison

Abstract

Growth curves have various applications of great importance in several areas. Quantitative methods are a useful tool to aid in the understanding of biological phenomena. To describe growth curves, regression models are efficient quantitative method. Growth curves have sigmoidal shape with an upper asymptote and sometimes also exhibit lower asymptote. The logistic, Gompertz, monomolecular, von Bertalanffy and Richards are functions with various applications in biological areas .The objective of this research is to study the logistic function with three structures: model of fixed effects, models with weighting adjustments and mixed models, with applications to data of fruit weight of sweet orange Citrus sinensis (L.) Osbeck second 4 types of rootstocks and 3 scions data from an experiment conducted in Lageado and also adjusting the logistic, Gompertz, von Bertalanffy and Richards functions to data of volume of the trunk of Eucalyptus grandis, from three regions belonging to Votorantim Celulose e Papel, with two structures: models of fixed effects and mixed models. For comparison of the models will be used criteria: the residual mean square, Akaike Information Criterion, Bayesian Information Criterion Schwarz, residue at point zero, mean prediction error, Breusch Pagan test and coefficient of determination. (AU)

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VEICULO: TITULO (DATA)