Genetic variability in domesticated Capsicum spp as assessed by morphological and agronomic data in mixed statistical analysis.
Capsicum species are very important in Brazil because of economic, cultural and biological factors, and the country is considered to be a diversity center for this genus. Collection and maintenance of the genetic diversity in Capsicum are important to avoid genetic erosion. Besides the identification of species, the characterization and evaluation of accessions maintained in gene banks are of fundamental importance. For this purpose, multivariate methods have become an important tool in the classification of conserved genotypes. The objectives of this study were: i) to identify and characterize accessions of the Capsicum spp collection and draw conclusions about the potential use of certain accessions in different production sectors; ii) to estimate the genetic divergence among accessions using the Ward-MLM procedure, and iii) to evaluate the efficiency of the analysis of continuous and categorical data using the Ward-MLM procedure. Fifty-six Capsicum spp accessions were evaluated based on 25 descriptors, 14 of which were morphological and 11 agronomic. Based on the qualitative descriptors, it was possible to identify all species and, together with the agronomic descriptors, genotypes could be indicated with potential for use in various production sectors. Five was determined as the ideal number of groups by the criteria pseudo-F and pseudo-t2. The Ward-MLM procedure allowed the differentiation of the species C. annuum, C. frutescens, C. baccatum, and C. chinense in separate groups. The Ward-MLM procedure showed some level of efficiency in clustering Capsicum species analyzing morphological and agronomic data simultaneously.
Sudré
C P
CP
Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, RJ, Brasil.
Gonçalves
L S A
LS
Rodrigues
R
R
do Amaral Júnior
A T
AT
Riva-Souza
E M
EM
Bento
C Dos S
Cdos S
D000383:Agriculture; D002212:Capsicum / Q000033:anatomy & histology* / Q000235:genetics*; D016000:Cluster Analysis; D014644:Genetic Variation; D015233:Models, Statistical; D019655:Quantitative Trait, Heritable