Paulo Roberto Oliveira Carneiro

Universidade Estadual Paulista (Unesp)

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Fernando A. Souza

Instituto Cultural Cravo Albin

Euclides Braga Malheiros

Universidade Estadual Paulista (Unesp)

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Universidade Estadual Paulista (Unesp)

Núcleo de Pesquisas Aplicadas (Brazil)

Instituto Cultural Cravo Albin

Instituto de Estudos Avançados da Universidade de São Paulo

Instituto de Estudios Avanzados

National Institute for Space Research

National Council for Scientific and Technological Development

Universidade de São Paulo

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Positioning and number of nutritional levels in dose-response trials to estimate the optimal-level and the adjustment of the models

Ciência Rural (2014)

Fernando A. Souza Euclides Braga Malheiros Paulo Roberto Oliveira Carneiro

The aim of this research was to evaluate the influence of the number and position of nutrient levels used in dose-response trials in the estimation of the optimal-level (OL) and the goodness of fit on the models: quadratic polynomial (QP), exponential (EXP), linear response plateau (LRP) and quadratic response plateau (QRP). It was used data from dose-response trials realized in FCAV-Unesp Jaboticabal considering the homogeneity of variances and normal distribution. The fit of the models were evaluated considered the following statistics: adjusted coefficient of determination (R²adj), coefficient of variation (CV) and the sum of the squares of deviations (SSD).It was verified in QP and EXP models that small changes on the placement and distribution of the levels caused great changes in the estimation of the OL. The LRP model was deeply influenced by the absence or presence of the level between the response and stabilization phases (change in the straight to plateau). The QRP needed more levels on the response phase and the last level on stabilization phase to estimate correctly the plateau. It was concluded that the OL and the adjust of the models are dependent on the positioning and the number of the levels and the specific characteristics of each model, but levels defined near to the true requirement and not so spaced are better to estimate the OL.

Coefficient of variation

Goodness of fit

10.1590/0103-8478cr20130694

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