Prediction of genetic gains by selection indexes and REML/BLUP methodology in a population of sour passion fruit under recurrent selection

Autores

  • Fernando Higino de Lima e Silva Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor
  • Alexandre Pio Viana Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor
  • Jôsie Cloviane de Oliveira Freitas Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor
  • Eileen Azevedo Santos Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor
  • Daniele Lima Rodrigues Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor
  • Antonio Teixeira do Amaral Junior Universidade Estadual do Norte Fluminense Darcy Ribeiro Autor

DOI:

https://doi.org/10.4025/actasciagron.v39i2.32554

Palavras-chave:

mixed models, Passiflora edulis Sims, predicted genotypic values, simultaneous selection.

Resumo

Breeding programmes must be improved to accelerate the development of new cultivars due to the commercial importance of passion fruit. This study compared four selection indexes and the REML/BLUP methodology in an assessment of predicted genetic gains in the traits of interest. A total of 81 full-sib progenies derived from the third cycle of recurrent selection were assessed for one harvest in one environment. The experiment was arranged in a randomized complete block design with five plants per plot. The following traits were assessed: number of fruits, total yield, fruit mass, fruit longitudinal diameter, fruit transverse diameter, fruit pulp percentage, shell thickness and content of soluble solids. The Mulamba & Mock index produced the best results for the selection of progenies. The REML/BLUP method was the most efficient and selected progenies with predicted genetic gains better than the selection indexes tested.

 

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Publicado

2017-04-11

Edição

Seção

Genética e Melhoramento

Como Citar

Prediction of genetic gains by selection indexes and REML/BLUP methodology in a population of sour passion fruit under recurrent selection. (2017). Acta Scientiarum. Agronomy, 39(2), 183-190. https://doi.org/10.4025/actasciagron.v39i2.32554

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