Evaluation of fish density influence on the growth of the spotted rose snapper reared in floating net cages using growth models and non-parametric tests

In commercial fish farming, growth performance is the most influential factor in economic profitability; so, biomass optimization has become a growing concern. We analyzed the influence of 3 harvest densities (15, 20, and 22 kg·m–3) on the growth of spotted rose snappers reared in floating net cages during a production cycle. To assess the impact of stocking density on growth performance, we used 2 indicators: final total length-at-age (12 months) and the growth rate estimated from growth models (von Bertalanffy, logistic, and Gompertz). For the first indicator, we tested for normality. We did the Kruskal–Wallis and the post hoc Kruskal–Wallis tests to compare the mean total final length from each density. Accordingly, the means of densities D15 and D20 were the same (P value = 0.22). For the second indicator, we fitted the models with the subroutine optim of the R statistical package using the L-BFGS-B algorithm. Model selection was made with the Akaike and the Bayesian information criteria. Both criteria suggested that the logistic model fitted the data best. With the best model (logistic), we did 1,000 bootstrap simulations for each density scenario to determine the distribution of the maximum likelihood estimation for the instantaneous growth rate. Because the estimates were normally distributed, we used ANOVA to test the equality of the instantaneous growth. The Tukey HSD test suggested that all means were statistically different from each other. The fastest growth rate (K = 0.275) corresponded to the cage with a density of 20 kg·m–3. These findings demonstrate that the logistic model can predict the growth of spotted rose snappers under culture conditions using floating net cages. These results strengthen the productive potential and economic profitability of snapper aquaculture using floating cage and may help the start of commercial scale aquaculture.