Gompertz and Logistic models for morphological traits of sudangrass cultivars during sowing seasons

• Autor(a) principal: Pezzini, Rafael Vieira
• Data de Publicação: 2019
• Outros Autores: Cargnelutti Filho, Alberto, Bem, Cláudia Marques de, Souza, Jéssica Maronez de, Chaves, Gabriela Görgen, Neu, Ismael Mario Marcio, Procedi, Andréia
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Semina. Ciências Agrárias (Online)
• Texto Completo: https://ojs.uel.br/revistas/uel/index.php/semagrarias/article/view/34891
• topic: Nonlinear models; Cover crop; Sorghum sudanense (Piper) Stapf.; Modelos não lineares; Planta de cobertura; Sorghum sudanense (Piper) Stapf.

The use of mathematical models in the study plant growth allows the identification of phases important to the cultivars and comparison between cultivars of the same species. The objectives of this work were to fit the Gompertz and Logistic growth models for the traits of plant height and stem length as a function of the accumulated thermal sum and accumulated solar radiation, to compare the fittings and the behavior of the sudangrass cultivars and indicate the model that best describes the growth of the cultivars during four sowing seasons. Were conducted eight uniformity trials with sudangrass. At 15 days after emergence, were began the collect and evaluation of five plants from each trial. Were measured plant height and stem length. The models were fitted using the values obtained for the traits of the five plants in each evaluation as a function of the accumulated thermal sum and accumulated solar radiation. Were estimated the parameters, determined their interval of confidence, critical points in the growth curves and quality indicators of the fit. The intrinsic nonlinearities and the parameter effect were also quantified. The accumulated thermal sum and accumulated solar radiation are adequate for the use as an independent variable in the model fitted. Both models were adequate to describe the growth of the traits plant height and stem length of cultivars BRS Estribo and CG Farrapo. However, the Logistic model is more accurate.