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| Puiatti,Guilherme Alves; Cecon,Paulo Roberto; Nascimento,Moysés; Nascimento,Ana Carolina Campana; Carneiro,Antônio Policarpo Souza; Silva,Fabyano Fonseca e; Puiatti,Mário; Cruz,Cosme Damião. |
| ABSTRACT: The objective of this study was to adjust nonlinear quantile regression models for the study of dry matter accumulation in garlic plants over time, and to compare them to models fitted by the ordinary least squares method. The total dry matter of nine garlic accessions belonging to the Vegetable Germplasm Bank of Universidade Federal de Viçosa (BGH/UFV) was measured in four stages (60, 90, 120 and 150 days after planting), and those values were used for the nonlinear regression models fitting. For each accession, there was an adjustment of one model of quantile regression (τ=0.5) and one based on the least squares method. The nonlinear regression model fitted was the Logistic. The Akaike Information Criterion was used to evaluate the goodness of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Quantile regression; Nonlinear regression; Allium sativum L.; Growth rate; Cluster analysis.. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000100203 |
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