Measurement of genetic diversity in progenies of sour passion fruit by ward-mlm methodology: a strategy for heterotic group formation

Detalhes bibliográficos
Autor(a) principal: Silva,Fernando Higino de Lima e
Data de Publicação: 2014
Outros Autores: Viana,Alexandre Pio, Ferreira,Rulfe Tavares, Freitas,Jôsie Cloviane de Oliveira, Santos,Jardel Oliveira, Rodrigues,Daniele Lima
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência e Agrotecnologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542014000300003
Resumo: Passion fruit belongs to the family Passifloraceae, and the genus Passiflora is regarded the most economically important. The present study aimed to quantify genetic diversity among progenies of sour passion fruit, in order to define potential heterotic groups, based on morpho-agronomic descriptors, using the Ward-MLM procedure. It is useful for generation advancement in the passion fruit breeding program, via recurrent selection, under development at the Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF). For such, 81 full-sib progenies belonging to the third recurrent selection cycle (C03) were assessed. Twenty-three descriptors were used, five of which were qualitative and 18, quantitative. The quantitative and qualitative variables were analyzed simultaneously using the Ward-MLM procedure for the composition of groups. The likelihood function determined that five was the ideal number of groups. The Ward-MLM classification strategy for morpho-agronomic data analysis allowed the formation of five groups into 26, 5, 15, 16 and 19 progenies. A certain distance was observed for group III, compared to the other groups while groups I, II, IV and V showed approximation. This greater distance of group III compared to the other groups may indicate crosses, aiming at the exploitation of heterosis, for the pyramiding of favorable alleles for traits of interest. The Ward-MLM statistical procedure was a useful tool to detect genetic divergence and group progenies using simultaneously quantitative and qualitative variables.