SciELO journals
Browse
1/1
3 files

Optimal feeding frequency for Heros severus (Heckel, 1840), an Amazon ornamental fish

dataset
posted on 2019-08-07, 02:47 authored by Daércio José de Macedo Ribeiro Paixão, Marcos Ferreira Brabo, Lourdes Marília Oliveira Soares, Daniel Abreu Vasconcelos Campelo, Galileu Crovatto Veras

ABSTRACT The influence of feeding frequency on growth performance, batch uniformity, and survival rate of severum (Heros severus) larvae and juveniles was investigated in two experiments. In the first, 200 five-day-old severum larvae with 3.20±0.31 mg and 6.20±0.39 mm were randomly distributed into 20 aquaria (1 L) and fed 500 Artemia nauplii larvae−1 day−1 for 15 days. In the second, 120 severum juveniles, 178.19±33.59 mg and 1.82±0.09 cm, were randomly distributed into 15 aquaria (300 L) and hand-fed a commercial diet (400.0 g kg−1 crude protein and 21.2 kJ g−1 gross energy) until apparent satiety for 30 days. For both experiments, feeding frequencies of one, two, three, four, and five meals day−1 were evaluated. We used four replicates for the first experiment and three for the second. At the end of both experiments, survival rate and batch uniformity were unaffected by the feeding frequency. Severum larvae fed three, four, and five meals day−1 showed higher final weight, weight gain, and specific growth rate, but only the larvae fed five meals day−1 showed higher final length and length gain than those fed once and twice day−1. Severum juveniles fed two, four, and five meals day−1 showed higher final weight, weight gain, and specific growth rate. Growth performance parameters of final length and length gain were not affected by feeding frequencies. Thus, we recommend that the optimal feeding frequency for severum larvae fed Artemia nauplii is three meals day−1 and for juvenile severum fed a commercial diet, the optimal frequency is two meals day−1.

History

Usage metrics

    Revista Brasileira de Zootecnia

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC