Selection of nonlinear models for the description of the growth curves of coffee fruit - Fernandes, Tales Jesus; Pereira, Adriele Aparecida; Muniz, Joel Augusto; Savian, Taciana Villela (Coffee Science - ISSN 1984-3909, 2014)
Coffee is one of the most important products of Brazilian agriculture, therefore studies aimed at improving the final quality of the coffee cherry has increasingly been the target of research. To know the growth curves of fruits allows a best crop management, as well as identify times of higher demand for nutrients. The aim of this work was to compare the nonlinear regression models Logistic e Gompertz in the description of the growth curves of coffee fruit, considering the heterogeneity of sampling variances, in the different faces of sunlight exposure. The data sets corresponds to the results of an experiment conducted in the College of Agriculture and Veterinary Sciences, UNESP, Jaboticabal-SP, with the cultivar Obatã IAC 1669-20, which belongs to the species Coffea arabica (CUNHA;VOLPE, 2011). We analyzed the data by using the nonlinear models Gompertz and Logistic, weighted (heterogeneous sample variance) and unweighted. We estimated the parameters by “gnls” function from library “nlme” from the statistical software R, which uses the least squares method and the Gauss-Newton algorithm for convergence. We compared the fit of the models by using the following criteria: adjustment coefficient of determination (Ra2 ); Akaike information criterion (AIC) and measures Bates and Watts curvature. The nonlinear models described fairly the coffee fruit growth, providing parameters with practical interpretations. The icorporation of heteroscedasticity was effective because the parameters estimates become more reliable. The model that best described the growth of coffee fruit was weighted Gompertz model, in both faces of sunlight exposure.