In Scientific reports ; h5-index 158.0
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.
Sant’Anna Isabela de Castro, Gouvêa Ligia Regina Lima, Martins Maria Alice, Scaloppi Junior Erivaldo José, de Freitas Rogério Soares, Gonçalves Paulo de Souza