Study of the growth of Amaranthus weeds using non-linear models - Pedroso Azarias, Edilene Cristina; Marcelino Silva, Edilson; Augusto Muniz, Joel; Jesus Fernandes, Tales (Brazilian Journal of Biometrics, 2024)
There are several known weed species, especially the genus Amaranthus. They have rapid spread and growth, compete for water, light, and nutrients, and harm crops. Studying the growth of these plants allows to analyze their interference and contributes to the development of management techniques. The Logistic and Gompertz non-linear models were fit using the R software to the growth data of five Amaranthus weed species, with evaluations at 20, 30, 40, 50, 60, 70, 80, and 90 days after sowing, considering the autoregressive error structure (AR1) and heteroscedasticity of variances. The critical points of the fitted curves were analyzed and the best model for data description was evaluated. Models were evaluated by R², AIC, DPR, and Bates and Watts curvatures. For the root dry mass, the Gompertz model was the best for A. deflexus, A. hybridus, A. retroflexus, and A. spinosus, and the Logistic model for A. viridis. A. deflexus and A. hybridus presented the lowest and the highest maximum accumulations of total dry mass, respectively. A. viridis was the most precocious, in relation to root dry mass, A. spinosus was the latest.