2011
DOI: 10.1590/s0103-84782011005000022
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Abstract: RESUMO Este trabalho foi desenvolvido com o objetivo de ajustar um modelo de regressão não-linear para estimar

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Cited by 4 publications
(5 citation statements)
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“…The normality, independence and homogeneity assumptions of the residues were met regarding the fresh and dry matter of aerial part, in the Gompertz and Logistic models using the BRS Progresso and Temprano cultivars, in five sowing seasons (Table 2) as also occurred in Fernandes et al (2014), in which the assumptions were met for the accumulation of fresh matter of coffee fruits.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The normality, independence and homogeneity assumptions of the residues were met regarding the fresh and dry matter of aerial part, in the Gompertz and Logistic models using the BRS Progresso and Temprano cultivars, in five sowing seasons (Table 2) as also occurred in Fernandes et al (2014), in which the assumptions were met for the accumulation of fresh matter of coffee fruits.…”
Section: Resultsmentioning
confidence: 99%
“…Among the nonlinear mathematical models, the Gompertz and Logistic models are the most used to describe plant growth behavior based on the observation of the crop itself. Thus, these models have been adjusted to assess coffee fruit growth curves (Fernandes et al, 2014), cashew fruit development (Muianga et al, 2016), and cocoa fruit growth (Muniz et al, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…As much as authors defend the use of linear models to estimate germination times, considering the assumption of normality of the data [12,14,36], often a simple transformation of the percentages of germination using a certain link function, such as the Probit model (inv. Norm function in Microsoft Excel) does not allow the dataset to be linearized [14,16]. Thus, an approach considering germination as a binary variable, in which seeds may or may not germinate, has been more indicated [13,18].…”
Section: Cornmentioning
confidence: 99%
“…However, such approaches are imprecise, as they consider the response variable to be continuous. For instance, in the use of non-linear regressions, the proportions of germinated seeds are cumulative and residual autocorrelation may occur [15], whereas in the use of linearization, the germination percentages are transformed into Probit units, considering that the data follow normal distribution, which ends up generating inaccurate models or simply a lack of linearization [14,16].…”
Section: Introductionmentioning
confidence: 99%
“…Several growth models, such as Logistico, Gompertz, Von Bertalanffy, Richards and Weibull, can be employed to model the seed (Espigolan et al, 2013). Some of these models have already been used to compare the potential of different seed batches (Gazola et al, 2011;Sousa et al, 2014); however, their use remains restricted to fit the model to the data; their interpretation is limited to model parameters. Growth models have biological interpretation parameters capable of increasing result inferences.…”
Section: Introductionmentioning
confidence: 99%