Genetic diversity in creole genotypes of Amazon chicory

• Autor(a) principal: GONÇALVES,Viviane Pereira
• Data de Publicação: 2022
• Outros Autores: ANDRADE,Francisco Laurimar do Nascimento, GOMES,Rafaelle Fazzi, SANTOS,Lucas da Silva
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Acta Amazonica
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672022000200089
• topic: Eryngium foetidum; non-conventional food plants; genetic variability; plant breeding

ABSTRACT Amazon chicory is still a little-known vegetable despite its great agronomic potential. The characterization of chicory genotypes concerning genetic divergence is a key step for breeding programs, as it allows the selection of superior individuals and to explore the variability and complementarity of characteristics via interbreeding between newly generated genotypes. In this context, this study aimed to evaluate the genetic divergence among Amazon chicory creole genotypes from the northern Brazilian states of Pará and Rondônia based on morpho-agronomic traits. We conducted an experiment in a randomized block design with eight chicory genotypes (treatments) and four replications. Both quantitative and qualitative characteristics were evaluated. Genetic divergence was estimated via squared generalized Mahalanobis distance (D2), considering only quantitative characters, and the genotypes were subsequently clustered via the UPGMA method. Analysis of variance showed significant differences among genotypes for all studied characteristics, except shoot fresh weight. The UPGMA grouped the genotypes into three clusters, which demonstrated that the genotypes from Colares and Santarém Novo (Pará) (Chic-02 and Chic-04) were the most divergent as compared to the genotypes from Castanhal and Santa Isabel do Pará (Pará). Qualitative characteristics showed a monomorphic behavior and, therefore, were not used to assess genetic divergences. To obtain segregating populations with complementary characteristics, crossbreeding between the two most divergent clusters is recommended.