Login / Signup

Growth curve of Nile tilapia from different families of the AquaAmérica variety.

J C CarvalhoRuy A C CorrÊa FilhoCarlos Antonio Lopes de OliveiraRicardo Pereira RibeiroGuilherme N SeraphimA L N SilvaG N Kinjo JuniorL M LaiceLetícia Emiliani FantiniNelson Mauricio Lopera-BarreroJayme Aparecido Povh
Published in: Brazilian journal of biology = Revista brasleira de biologia (2021)
Selection can affect growth, changing performance and asymptotic values. However, there is little information about the growth of families in fish breeding programs. The aim of this study was to evaluate the performance and growth of families of Nile tilapia AquaAmérica. Twenty AquaAmérica families cultivated in a net cage (13.5 m3) for 181 days were evaluated. The nonlinear Gompertz regression model was fitted to the data by the weighted least squares method, taking the inverse of the variance of weight in different families and at different ages as the weighting variable. The model was adjusted to describe the growth in weight and morphometric characteristics. Two families showed highest (P<0.05) weights at both 133 days (family AA10: 743.2 g; family AA16: 741.2 g) and 181 days (family AA10: 1,422.1 g; family AA16: 1,393.4 g) of the experiment. In both experimental periods, the males showed a heavier weight, with the greatest contrast between the sexes occurring at 181 days. The analysis of the three most contrasting families (AA1, AA9 and AA14) showed that the asymptotic value for weight was higher (P<0.05) in family AA9 (3,926.3 g) than in family AA14 (3,251.6 g), but specific growth rate and age at the inflection point did not differ significantly between families. In conclusion, two of the 20 families were superior; males exhibited a greater growth, mainly in the period of 181 days; and the growth curve differed between the families, especially for asymptotic weight.
Keyphrases
  • body mass index
  • physical activity
  • weight loss
  • magnetic resonance
  • healthcare
  • magnetic resonance imaging
  • contrast enhanced
  • artificial intelligence
  • electronic health record