Modelos de crescimento para cultivares de trigo mourisco em épocas de semeadura

Abstract

The objectives of this study were to adjust the non-linear Gompertz and Logistics models to describe the morphological and productive traits of two buckwheat cultivars, IPR91-Baili and IPR92-Altar, during sowing times and to indicate the model that best describes the growth of the crop. Twenty uniformity trials with buckwheat crop were conducted in two agricultural years, 2017/2018 and 2018/2019. Sowing was carried out in rows, spaced 0.5 m between rows. Each uniformity trial covered an area of 9 m × 17 m (153 m²). Five plants from each trial were evaluated twice a week. The plant height, number of nodes, fresh matter of aerial part and dry matter of aerial part were evaluated. The Gompertz and Logistics models were adjusted for each trait according to the days after sowing. The parameters of each model were estimated, the confidence intervals of the parameters and critical points of the growth curves were determined. To analyze the behavior of the models, the intrinsic nonlinearities and the parameter effect were quantified. The fit quality of the models was verified by the determination coefficient, Akaike information criterion and residual standard deviation. Both models proved to be adequate to describe the morphological and productive traits of buckwheat, at sowing times. However, the Logistics model is the most suitable for presenting the best fit quality indicators.