Finding suitable growth models for turbot (Scophthalmus maximusL.) in aquaculture 1 (length application)

Abstract

Growth data of two different commercial turbot (Scophthalmus maximus) strains reared in recirculating aquaculture systems were analysed with the aim to determine the most suitable model for turbot. To assess the model performance three different criteria were used: (1) The mean percentage deviation between the estimated length and actual length; (2) the residual standard error with corresponding degrees of freedom and (3) the Akaike information criterion. The analyses were carried out for each strain separately, for sexes within strains and for a pooled data set containing both strains and sexes. We tested a pre-selection of six models, containing three to four parameters. Models were of monomolecular shape or sigmoid shape with a flexible point of inflection including the special case of monomolecular shape in defined cases of their parameters. The 4-parametric Schnute model achieved best fit in 62% of all cases and criteria tested, followed by the also 4-parametric generalized Michaelis-Menten equation in 48% and the 4-parametric Janoschek model (38%). The von Bertalanffy growth function achieved only 29%, Brody 24% and a new flexible function 19% best fit. In a 1-1000 day growth-simulation sigmoid shaped curves were produced by the Schnute model in 71% of cases. The Janoschek and the Michaelis-Menten model each produced sigmoid curves in 57% of all cases. This indicates that a flexible 4-parametric function reflects the growth curve of turbot the best and that this curve is rather sigmoid than monomolecular shaped.

Evaluating the most suitable nonlinear growth model for turbot (Scophthalmus maximus) in aquaculture 2 (weight application): Multi‐criteria model selection and growth prediction

“…This is also reflected in our own data, indicating the need for further efforts in trait-specific breeding programs (e.g. Several different functions have been proposed and challenged against each other (Baer et al, 2010;Krüger, 1973;Lugert, Tetens, Thaller, Schulz, & Krieter, 2017;Richards, 1959;Schnute, 1981;Wang & Ma, 2016). Accordingly, there is a demand for precise prediction of harvest size and corresponding production time by farmers.…”

“…As a response to this demand, growth models are increasingly used in various aquaculture species (Dumas et al, 2010). Several different functions have been proposed and challenged against each other (Baer et al, 2010;Krüger, 1973;Lugert, Tetens, Thaller, Schulz, & Krieter, 2017;Richards, 1959;Schnute, 1981;Wang & Ma, 2016). Most of these functions comprise three regression parameters, whereas 4-parametric functions became more frequently used in recent years (Baer et al, 2010;Lugert et al, 2017;López et al, 2000;Schnute, 1981;Wang & Ma, 2016).…”

“…homogeneity). Most of these functions comprise three regression parameters, whereas 4-parametric functions became more frequently used in recent years (Baer et al, 2010;Lugert et al, 2017;López et al, 2000;Schnute, 1981;Wang & Ma, 2016). As a response to this demand, growth models are increasingly used in various aquaculture species (Dumas et al, 2010).…”

Modeling the weight gain of freshwater-reared rainbow trout ( Oncorhynchus mykiss ) during the grow-out phase

“…In this study, all models met convergence in all tested cases using the Marquardt algorithm. This algorithm is described as more robust than others offered in statistical software (Elzhov et al, 2013;Lugert et al, 2017). This is especially important, as non-convergence situations of models for aquaculture data are described by several authors (Costa et al, 2009;Mansano et al, 2012;Allaman et al, 2013;Sousa Júnior et al, 2014).…”

“…Predominantly, non-linear equations are used to model population and/or individual growth of fish in their natural environment. However, research on modeling the growth of fish in aquaculture has proven great suitability and has presented relevant contributions within the last years (Santos et al, 2013;Lugert et al, 2017;Powel et al, 2019).…”