Development of a TGC-based growth model for the olive flounder, Paralichthys olivaceus, and its application in developing a fish growth simulator architecture

Temperature is one of the main factors affecting fish growth. Many studies have proposed a fish growth model considering the effect of temperature. Among these models, the TGC (thermal growth coefficient) model which digitized the influence of temperature on fish growth is the most notable. The original TGC model was made in the form of applying 1/3 as an exponent, but subsequent studies have shown that it is necessary to apply different exponent value or other constant depending on the dynamics of growth. In this study, the original TGC model using 1/3 as an exponent and the new model using 2/3 as an exponent were compared for olive flounder (Paralichthys olivaceus). The seasonal temperature function under the conditions of the flow-through system was applied and the transition point of change in the growth dynamics was obtained by comparing the instantaneous growth rate of the two TGC models. Around 541 g of the transition point was obtained, and a combined TGC model was presented that integrated the two models. However, the growth prediction model based on these statistical techniques does not reflect real-time changes in each parameter and requires academic knowledge, making it difficult to use in the actual field. Recently, as the smart aquaculture industry incorporating ICT (information and communication technologies) has grown rapidly, many solutions such as fish growth prediction simulators using statistical growth models have been developed. Therefore, in this study, input and output variables were classified and software architectures were presented so that the statistical form of fish growth model using TGC derived above could be applied when developing a fish growth prediction simulator. Deriving these growth models and interpreting them into languages in the field of ICT will enhance the field applicability of academic research results as a part of smart aquaculture technology.