Evaluation of the critical points of the most adequate nonlinear model in adjusting growth data of ‘green dwarf’ coconut fruits

Abstract

‘Green Dwarf’ coconut is a fruit of great economic interest, since all its components are used, in addition to water, its main component. It is a culture of humid tropics, widely produced in northeastern Brazil, being an important income source for the region. The phenology study of this type of fruit is extremely important, but there are few studies in literature. Regression models, especially nonlinear growth models, can be of great value to understand how fruit growth behaves. The scarcity of works of this nature may be linked to some difficulties in estimating parameters of nonlinear models, such as assigning initial values to the itterative process. Overcoming this difficulty, for regression analysis, linear or not, several steps need to be respected to ensure the validity of information. Much information can be extracted from nonlinear growth models, such as the asynotic value, growth rate and critical points (maximum acceleration point, inflection point, maximum deceleration point and asynotic deceleration point). The aim of this work was to describe the stages of nonlinear regression analysis and to estimate the critical points of ‘Green Dwarf ’ coconut growth curves. After initial adjustments, the only unmet assumption was independence, adding a first order autoregressive term. Again, models were adjusted and all parameters were significant, with both models, Gompertz and Logistic, adjusting well to data, with slight advantage for the Logistic model with better adjustment quality criteria values, with maximum expected LED and LEDKP values of 21.4037 cm and 21.5478 cm, respectively. The x and y axis of critical points were estimated, with values that can help producers to make more objective decisions about the appropriate time to harvest coconut fruits, considering the most diverse uses of this type of fruit.