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The objective of this study was to evaluate the genetic variability of natural rubber latex traits among 44 elite genotypes of the rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell. Arg.]. Multivariate analysis and machine learning techniques were used, targeting the selection of parents that demonstrate superior characters. We analyzed traits related to technological or physicochemical properties of natural rubber latex, such as Wallace plasticity (P0), the plasticity retention index [PRI (%)], Mooney viscosity (VR), ash percentage (Ash), acetone extract percentage (AE), and nitrogen percentage (N), to study genetic diversity. Multivariate [unweighted pair group method with arithmetic means (UPGMA) and Tocher)] and machine learning techniques [K-means and Kohonen's self-organizing maps (SOMs)] were employed. The genotypes showed high genetic variability for some of the evaluated traits. The traits PRI, Ash, and PO contributed the most to genetic diversity. The genotypes were classified into six clusters by the UPGMA method, and the results were consistent with the Tocher, K-means and SOM results. PRI can be used to improve the industrial potential of clones. The clones IAC 418 and PB 326 were the most divergent, followed by IAC 404 and IAC 56. These genotypes and others from the IAC 500 and 400 series could be used to start a breeding program. These combinations offer greater heterotic potential than the others, which can be used to improve components of rubber latex quality. Thus, it is important to consider the quality of rubber latex in the early stage of breeding programs. [ABSTRACT FROM AUTHOR]

• For the first time for rubber tree breeding, this work investigate correlation, path analysis and canonical correlation. • There is an association between the production traits (yield, girth and the laticiferous system) and the morphological traits. • Selection for the number of leaf storeys may increase at least three of the traits (yield, girth, bark thickness and number of latex vessel rings). • Selecting for Girth and the number of leaf storeys will increase the efficiency of early selection for yield in young plants. The present work evaluated the relationship of rubber yield with morphological and structural traits of the laticiferous system in rubber tree [ Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg] open-pollinated progenies to understand the cause and effect relationships between traits in order to enable future early selection. The progenies were installed in Jaú, Pindorama and Votuporanga in a randomized block design, with five replications and 10 plants per plot at a spacing of 2.0 × 2.0 m. The traits evaluated at three years of age were rubber yield (Yld); girth (Grt), expressed by the stem perimeter; bark thickness (BT); number of latex vessel rings (RG); length (PL), diameter (PD) and petiole index (PI); leaflet length(LFL) and width (LFW); leaf width (LW), area (LA) and index (LI); and number of leaf storeys (NLS). Coefficients of the genotypic correlations were used for a graphical representation of the correlation network created in the Genes program. Subsequently, the diagnosis of multicollinearity, as well as the analysis of the direct and indirect genotypic correlations of bark anatomical traits, leaf morphological traits, girth, and rubber yield, were performed. The traits that showed significant genotypic correlations with rubber yield at the three evaluated sites were girth, bark thickness, and number of leaf storeys. The girth character had the largest direct effect on rubber yield. Canonical correlation analysis showed that selection for the number of leaf storeys may increase at least three of the traits (yield, girth, bark thickness, and number of latex vessel rings) for most locations studied. There is an association between the yield traits (yield, girth, and the laticiferous system) and the morphological traits. [ABSTRACT FROM AUTHOR]