Parametric and non-parametric indexes applied in the selection of sour passion fruit progenies

• Autor(a) principal: Dalbosco,Edinéia Zulian
• Data de Publicação: 2018
• Outros Autores: Krause,Willian, Neves,Leonarda Grillo, Araújo,Dejânia Vieira de, Hiega,Kemely Mara Ramalho, Silva,Cintia Graciele da
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista brasileira de fruticultura (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-29452018000100801
• topic: Genetic gains; recurrent selection; Passiflora edulis

Abstract Several traits must be observed in the selection of sour passion fruit progenies. For such, selection indices could be used for gradually increasing the frequency of favorable genotypes for the set of the traits of interest. This study aimed to compare parametric and non-parametric selection indices to be used in the selection of passion fruit progenies and identify the best economic weights. Thus, 118 full-sib families and three controls were assessed for days regarding flowering, productivity in kg ha-1 year, fruit mass in g, number of fruits, average length of fruits in mm, average fruit diameter in mm, fruit shape, average shell thickness in mm, pulp yield, pulp color, total soluble solids, titratable acidity and SS/ATT ratio. The non-parametric selection indexes used to obtain genetic gains were Mulamba and Mock, genotype-ideotype distance, multiplicative and Elston. Smith and Hazel, Williams and Pesek and Baker parametric indexes were used, with different economic weights attributed. The Mulamba and Mock, genotype-ideotype distance nonparametric selection indexes and the Williams parametric index showed satisfactory and balanced gains. The genetic variation coefficient, genetic standard deviation and random weight economic weights provided higher gains for non-parametric selection indexes. Similar gains were obtained for parametric indexes, regardless of assigned weight, except for Pesek and Baker, whose genetic standard deviation provided the highest gain.