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

Lugert, Vincent, Tetens, Jens, Thaller, Georg, Schulz, Carsten and Krieter, Joachim (2015) Finding suitable growth models for turbot (Scophthalmus maximusL.) in aquaculture 1 (length application). Aquaculture Research, 48 (1). pp. 24-36. DOI 10.1111/are.12857.

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Supplementary data:

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.

Document Type: Article
Research affiliation: Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Kiel University
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1111/are.12857
ISSN: 1355-557X
Date Deposited: 21 Dec 2017 12:26
Last Modified: 26 Apr 2019 11:06
URI: http://oceanrep.geomar.de/id/eprint/41094

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