Ajuste de modelos de cinética na descrição da mineralização do nitrogênio de resíduos da pupunheira

Abstract

The peach palm (Bactris gasipaes Kunth) is a tropical palm used for both heart of palm production and edible fruits. Its cultivation generates a large amount of organic residues which, when properly managed, significantly contribute to the supply of organic matter and nutrients to the soil. The mineralization process of these organic residues is fundamental for the gradual release of nutrients into the soil, especially nitrogen, which has a direct impact on soil fertility and agricultural productivity. The objective of this study was to fit and select nonlinear kinetic models to describe nitrogen mineralization in peach palm residues applied to the soil under two management systems: incorporated and surface-applied, under both field and laboratory conditions. The analyzed data were obtained from Pereira et al. (2015) and correspond to the results of an experiment with peach palm residues under field and laboratory conditions. The models used were Stanford & Smith, Michaelis–Menten, Cabrera, and Broadbent & Nakashima. The assumptions of normality, homoscedasticity, and independence were verified using the Shapiro–Wilk, Breusch–Pagan, and Durbin–Watson tests, respectively. The models were fitted using the least squares method with the Gauss–Newton algorithm through the R statistical software. Model performance was evaluated based on adjusted coefficient of determination (R2 ad j), residual standard deviation (RSD), and Akaike Information Criterion (AIC). The results indicated that, under field conditions, the Cabrera model (incorporated management) and the Michaelis–Menten model (surface management) provided the best fits. Under laboratory conditions, the Stanford & Smith and Michaelis–Menten models showed better performance. The Broadbent & Nakashima model showed inferior performance under the tested conditions. It is concluded that the selection of the most appropriate model depends on residue management and environmental conditions, providing a useful tool to predict nitrogen release and support the sustainable management of peach palm residues.