Developing a new tool based on a quantile regression mixed-TGC model for optimizing gilthead sea bream (Sparus aurata L) farm management

Abstract

[EN] In this work, a seasonal quantile regression growth model for the gilthead sea bream (Sparus aurata L) based on an aggregation of the quantile TGC models with exponent 1/3 and 2/3, named the Quantile TGC-Mixed Model, is presented. This model generalizes the proposal of Mayer, Estruch and Jover (Aquaculture, 358-359, 2012, 6) in the sense that the new model is able to describe the evolution of weight distribution throughout an entire production cycle, which could be a powerful tool for fish farm management. The information provided by the model simulations enables us to estimate total fish production and final fish size distribution and helps to design and simulate production and sales plan strategies considering the market price of different fish sizes, in order to increase economic profits. The most interesting alternative in the studied case results in sending all production when 0.25 quantile fish reach 600g, although on each fish farm it would be necessary to evaluate optimum strategy depending on its own quantile regression model, the production cost and the market price.