The main objective of this study was to compare nonlinear regression models able to describe the dry matter accumulation in different parts of the garlic plant over time (60, 90, 120 and 150 days after planting). This study also aimed to identify similar accessions with respect to the characteristics evaluated through cluster analysis. We used 20 garlic accessions belonging to the Vegetable Germplasm Bank of Universidade Federal de Viçosa. The dry matter content of leaves, pseudostems, bulbs and roots were defined as variables in the cluster analysis (Ward algorithm using as dissimilarity measure the squared generalized Mahalanobis distance), which resulted in the appointment of an optimal number (Mojena criteria) of three groups of accessions, whose means of dry matter of bulbs, of roots and of the whole plant were used for fitting five nonlinear regression models (Mitscherlich, Gompertz, Logistic, von Bertalanffy and Brody). The identification of the model that best fitted the three characteristics of each group was carried out by coefficient of determination (R²), the error mean square and the average deviation absolut error. Comparing the values of these evaluators, we found that, for the three characteristics of the three groups, the best fitted model was the Logistic.
Allium sativum; clustering analysis; comparison of models
