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Finding suitable growth models for turbot ( Scophthalmus maximus L.) in aquaculture 1 (length application)
Author(s) -
Lugert Vincent,
Tetens Jens,
Thaller Georg,
Schulz Carsten,
Krieter Joachim
Publication year - 2017
Publication title -
aquaculture research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.646
H-Index - 89
eISSN - 1365-2109
pISSN - 1355-557X
DOI - 10.1111/are.12857
Subject(s) - scophthalmus , turbot , sigmoid function , akaike information criterion , biology , growth curve (statistics) , statistics , parametric statistics , parametric model , mathematics , gompertz function , growth model , growth function , inflection point , function (biology) , biological system , fishery , fish <actinopterygii> , computer science , geometry , artificial intelligence , mathematical economics , evolutionary biology , artificial neural network
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.