Diversidade genética entre e dentro de populações F3 de pimenteiras ornamentais

Abstract

The market for ornamental plants through their diversity has considerably increased the cultivation and demand for peppermints in pots. The genetic variability found in the species of Capsicum is the basic condition for the genetic improvement of this genus, allowing its use and knowledge for the development of new varieties. Genetic diversity is found from the genetic distance that can be determined through the use of biometric models based on multivariate techniques, allowing to combine the multiple information of a set of characteristics. The objective of this study was to evaluate the genetic diversity among and within the F3 populations of peppercorns (Capsicum annuum L.), selecting populations and promising genotypes for ornamental purposes. The experiment was carried out in a greenhouse at the Laboratory of Plant Biotechnology at the Center of Agricultural Sciences at the Federal University of Paraíba (CCA-UFPB). Twenty populations and 4 additional peppercorns (Capsicum annuum L.) were used for morphoagronomic characterization based on qualitative and quantitative descriptors. The experimental design was completely randomized. In the first chapter we used 17 quantitative descriptors of plant and fruit, the data were submitted to analysis of variance, the relative importance where it was determined by the method of Sing (1981), the analysis of canonical variables and the Scott-Knott test. In the second chapter we used 15 quantitative descriptors and 13 qualitative descriptors for plant and fruit. The relative contribution of the characteristics was obtained through Singh's criterion, followed by the grouping of Tocher based on the generalized distance of Mahalanobis for the quantitative variables; for the qualitative variables, the Gower distance was used; mixed analysis with quantitative and qualitative data. In addition to these analyzes, non-metric multidimensional scaling was also performed between qualitative, quantitative and mixed data. All analyzes were performed with R version 3.0.3 software. In the first chapter by the Singh method it was determined that seven of the seventeen characteristics contributed with 56.4% of the genetic divergence. In the analysis of canonical variables, the first two canonical variables explained 67.93% of the population discrimination and through the Scott-Knott test the populations were grouped into 9 groups. The populations exhibiting the desirable characteristics for ornamental pots were 5, 10, 22, 33, 49 and 69. In the second chapter genotypes were evaluated within each population. Population 8 presented all genotypes with high bearing size and were not ideal for small vessel cultures. The joint analysis of the quantitative and qualitative data was efficient in expressing the degree of genetic diversity among the evaluated genotypes within each analyzed family, being possible to practice selection.