Modelagem não linear do crescimento em altura do cafeeiro irrigado e não irrigado em diferentes densidades

Abstract

Heterogeneity of variance and residual autocorrelation characteristics are inherent in the growth data over time that is not considered in the analysis may lead to inaccurate results. This study aimed to compare the settings of the Logistic and Gompertz models, considering the methods of least squares: ordinary and generalized. The data used refer to the height of the coffee plants, subjected to irrigation systems Si (non irrigated), 60 kPa and 140 kPa, the planting densities in 2500 and 5000 plants ha-1 . According to the residual standard deviation and the residual analysis, the fit of the Gompertz model by generalized least squares method, which incorporates the heterogeneity of residual variance and autocorrelation in modeling, showed the best results for all data analyzed, suitable for modeling the growth in height of the coffee over time. The adjustments related to the irrigated plants had the highest estimates for the asymptotic height, confirming that the crop irrigation provides greater plant growth.