Osmotic Treatment of Fish in Two Different Solutions-Artificial Neural Network Model

Abstract

© 2015 Wiley Periodicals, Inc. Osmotic treatment of fish (Carassius gibelio) was studied in two osmotic solutions (ternary aqueous solution - S1 and sugar beet molasses - S2) at three temperatures (20, 35 and 50C) and atmospheric pressure. The aim was to examine the influence of type and concentration of used hypertonic agent, temperature and immersion time on the water loss, solid gain, dry mater content, water activity and minerals content (Na, K, Ca and Mg). During experiments, the maximum mineral content has been obtained using S2 solution, concentrated to 80%, at 50C after 5h of osmotic treatment, at which maximum water loss has been obtained. Artificial neural networks (ANN) have been developed for mathematical modeling of observed responses, and afterwards they were compared with experimental results and empirical linear multivariate regression models. ANN models performed high prediction accuracy (0.975-0.993) and can be considered as precise and very useful for outputs production.