| Autor: |
Mello, Anderson, Toebe, Marcos, Marchioro, Volmir Sergio, de Souza, Rafael Rodrigues, Paraginski, João Antônio, Somavilla, Junior Carvalho, Martins, Vinícius, Manfio, Guilherme Liberalesso, Junges, Diéssica Letícia, da Rocha Borges, Maria Eduarda |
| Předmět: |
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| Zdroj: |
Journal of Plant Growth Regulation; Nov2023, Vol. 42 Issue 11, p7215-7228, 14p |
| Abstrakt: |
Plant growth is complex, and involves many processes and its understanding is essential to maximize the crop's potential. The use of modeling is an essential tool to characterize the plant's growth and development, in addition, generates strategies for future plantings, adapting the management. Therefore, this study aimed to apply and make considerations based on parameters of the Logistic and Gompertz models to the fresh plants mass, of three sunflower cultivars, sown in three seasons, and select the best model for the cultivars. The data used came from nine uniformity trials with the sunflower cultivars Aguará 6, Nusol 4510, and Rhino and were adjusted according to the accumulated growing degree days, using the Logistic and Gompertz models. Parameters were estimated using the methods of ordinary least squares (OLS) and generalized least squares (GLS). In the presence of violations, the power method was used to structure the variance. Fit quality of the models to the data was assessed by the adjusted determination coefficient, Akaike information criterion, and Schwarz's Bayesian criterion. Logistic and Gompertz models fitted the data, converging on interpretable parameters, both by OLS and GLS methods. The insertion of the power structure into the models resulted in a better fit for the data. The cultivars Aguará 6 and Nusol 4510 are best described by the Logistic model and present a higher positive growth phase in the first trial. The sunflower cultivar Rhino is best described by the Gompertz model and presents a reduction in the positive growth phase in the first trial. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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