Genetic divergence between bocaiuva acrocomia aculeata (jacq.) lodd. ex mart. genotypes through fruit morphometry.

This research aimed to analyze the genetic divergence between genotypes of Acrocomia aculeata (Jacq.) Lodd. Ex Mart collected in natural vegetation in the municipality of Cáceres-Mato Grosso based on morphological characters of fruits and seeds. Bocaiuva fruits were collected at three points of natural occurrence: point 1 - Sítio Peniel dos Sonhos - Barreiro Vermelho Community (15°53'53"S, 57°30'49"W), point 2 - Chácara Boa Esperança (16°05'57"S, 57°39'03"W) point 3 - Santana Community-Morraria Region (15°55'36"S, 57°26'50"W). To estimate the genetic divergence between the bocaiuva genotypes through the morphometry of the fruits and seeds, 420 fruits of 21 genotypes were collected and the following characteristics were evaluated: Horizontal diameter of the fruit, Vertical diameter of the fruit, Total weight of the fruit, Total weight of fresh mesocarp (pulp), Horizontal diameter of almonds, Vertical diameter of almonds and Weight of fresh almond. To estimate the genetic divergence between the genotypes, the standardized Average Euclidean Distance was used as a measure of dissimilarity. Based on this matrix, the Tocher optimization clustering methods and the Hierarchical Clustering Average Between Groups (UPGMA) method were used. The criterion of Singh (1981) was also used to quantify the relative contribution of traits in the estimation of genetic divergence. All analyzes were performed using the computational resources of the Genes software. Through the results obtained, it was possible to verify the greatest dissimilarity between genotypes 3 and 8. The groupings by the Tocher method and the Hierarchical Average Grouping Between Groups (UPGMA) were partially similar in the groupings of genotypes and the characteristics of total fruit weight, followed by characteristic total weight of fresh pasta were the ones that most contributed to estimate the genetic divergence of the evaluated genotypes. The use of multivariate analyzes was efficient in estimating the genetic divergence in which the genotypes evaluated in the present research present genetic divergence and can be used in future pre-genetic improvement research. [ABSTRACT FROM AUTHOR]