Estimates of genetic parameters, path analysis and selection on vegetable sponge for agronomic traits

Authors

  • Ariel Dotto Blind Instituto Nacional de Pesquisas da Amazônia
  • Mágno Sávio Ferreira Valente Universidade Federal do Amazonas
  • Maria Teresa Gomes Lopes Universidade Federal do Amazonas
  • Marcos Deon Vilela de Resende Universidade Federal de Viçosa

DOI:

https://doi.org/10.5039/agraria.v13i2a5522

Keywords:

genetic gain, heritability, Luffa cylindrica L., mixed models

Abstract

The aim of this study was to estimate genetic parameters and conduct association studies between traits of agro-industrial interest in 24 accessions of vegetable sponge (Luffa cylindrica L.) from seven Brazilian states in order to identify potentially promising genotypes to be introduced in crop breeding programs. The assessment covered nine traits related to the yield and quality of fruits and fibers of economic importance for the species. The presence of genetic variability and high mean heritability (0.70 - 0.99) are indicative of possible significant gains by applying phenotypic selection for traits of interest. A genetic gain of 42.79% was obtained for fiber production after selecting eight superior genotypes. The highest estimated correlations (r > 0.73) were between the traits related to fruit circumference and fiber thickness. Dry fiber weight and the number of fruits showed strong direct effects on fiber yield, but there were some undesirable indirect effects. Use of the selection index produced simultaneous gains in negatively correlated traits, offering a promising outlook for the development of vegetable sponge cultivars for use in agro-industry.

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Published

2018-06-30

How to Cite

Ariel Dotto Blind, Mágno Sávio Ferreira Valente, Maria Teresa Gomes Lopes, & Marcos Deon Vilela de Resende. (2018). Estimates of genetic parameters, path analysis and selection on vegetable sponge for agronomic traits. Brazilian Journal of Agricultural Sciences, 13(2), 1-8. https://doi.org/10.5039/agraria.v13i2a5522

Issue

Section

Agronomy