NONLINEAR MODELS BASED ON QUANTILES IN THE FITTING OF GROWTH CURVES OF PEPPER GENOTYPES

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Ana Carolina Ribeiro de OLIVEIRA
http://orcid.org/0000-0001-8262-8667
Paulo Roberto CECON
http://orcid.org/0000-0001-8213-0199
Guilherme Alves PUIATTI
http://orcid.org/0000-0003-0769-049X
Maria Eduarda da Silva GUIMARÃES
Cosme Damião CRUZ
http://orcid.org/0000-0003-3513-3391
Fernando Luiz FINGER
http://orcid.org/0000-0002-4046-9634
Moysés NASCIMENTO
http://orcid.org/0000-0001-5886-9540
Mário PUIATTI
Maurício Silva LACERDA

Abstract

This study aimed to fit nonlinear regression models to model the growth of the characters fruit length (FL) and fruit width (FW) of pepper genotypes (Capsicum annuum L.) over time using the method of ordinary least squares (OLS); and identify the model with the best fit and compare it to the model obtained via nonlinear quantile regression (QR) in the 0.25, 0.5, and 0.75 quantiles. Three regression models (Logistic, Gompertz, and von Bertalanffy) and four fit quality evaluators were adopted: Akaike information criterion, residual mean absolute deviation, and parametric and intrinsic curvature measurements. Five commercial genotypes of pepper were evaluated. Characters FL and FW were evaluated weekly from seven days after flowering, totaling ten measurements. In the estimation by OLS, the Logistic and von Bertalanffy models were considered adequate according to the quality evaluators. In the comparison between the models above by OLS and QR, the superiority of models obtained by QR was verified for the character FL. For the character FW, QR was efficient in three out of the five genotypes, being a valuable alternative in the study of fruit growth.

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Author Biography

Ana Carolina Ribeiro de OLIVEIRA, Universidade Federal de Viçosa

Universidade Federal de Viçosa, Campus Viçosa, Departamento de Estatística, CEP: 36570-900, Viçosa, MG, Brasil.