Phenotypic Dispersion of Landrace Lima Bean Varieties Using Multidimensional Scaling

Abstract

Studies about phenotypic diversity are common in germplasm banks. The inference about this variability must be realized through several methods. The multidimensional scaling is a multivariate technique that has not yet been well explored in plant breeding programs. The objective of this study was to evaluate the phenotypic dispersion of landrace lima bean varieties using the non-metric multidimensional scaling technique (nMDS) based on seed morphology. Seeds of 25 lima bean accessions were characterized based on the morphological descriptors proposed by the International Plant Genetic Resources Institute. Distance matrices between the accessions were estimated based on the qualitative and quantitative variables, in addition to simultaneous analysis of the qualitative and quantitative data, using the Mahalanobis and Gower distances. The distances were represented by non-metric multidimensional scaling. The adjustment level of the nMDS mapping was calculated using Kruskal’s Stress. The scaling based on the quantitative and mixed data was efficient to represent the distances of the lima bean accessions in the bidimensional plane presenting Stress less than 20%. Divergent accessions, such as 11, 13, 17 and 25 were identified. The inclusion of qualitative characters provided the best discrimination of the accessions, confirming the importance of the simultaneous character analysis. The nMDS must be used as a complementary technique to those commonly employed in studies of phenotypic diversity in lima beans.

Selection in segregating populations of ornamental pepper plants (Capsicum annuum L.) using multidimensional scaling

“…Other works have demonstrated the distance of the genotypes in a graphic form through the non-metric multidimensional technique using quantitative data, such as that by , who used the non-metric multidimensional scaling analysis based on quantitative data for the identification of garlic genotypes based on different phenotypical characteristics. Barroso et al (2019) used the analysis in the selection of more divergent broad bean genotypes, having quantitative data as a base (Pessoa et al, 2019), and also selecting genotypes in a segregating population of pepper plants based on quantitative data. , color of the mature fruit (CMF), fruit shape (FS), fruit persistence with the pedicel (FPP), pedicel persistence with the stem (PPWS), stem color (SC), stem shape (SS), growth habit (GH), branching density (BD), leaf color (LF), and leaf shape (LS).…”

“…The individuals are, therefore, arranged as points in space, generally bidimensional or tridimensional, in which it is possible to observe the similarity and the dissimilarity between individuals (Borg & Groenen, 2005;Manly, 2008). The use of this analysis in the study of genetic diversity in improvement programs was performed in studies with cocoa (Leal et al, 2008), garlic , broad bean (Barroso et al, 2019), and a segregating population of Capsicum (Pessoa et al, 2019). Then, this analysis may be appropriate for studies on genotypic dispersion, since the conventional improvement program is based mainly on phenotypic data, which are based on qualitative and quantitative characters (Barroso et al, 2019).…”

“…The use of this analysis in the study of genetic diversity in improvement programs was performed in studies with cocoa (Leal et al, 2008), garlic , broad bean (Barroso et al, 2019), and a segregating population of Capsicum (Pessoa et al, 2019). Then, this analysis may be appropriate for studies on genotypic dispersion, since the conventional improvement program is based mainly on phenotypic data, which are based on qualitative and quantitative characters (Barroso et al, 2019). Furthermore, it may also be important in the selection of more divergent individuals with desirable features for the improvement program.…”