A 3D MRI-based Numerical Model Dedicated to Industrial Thawing of Large Tuna Fishes

Abstract

ABSTRACT Industrial thawing of raw tuna fishes for the canning industry is of great importance in the global economy. Due to the heat transfer limitations within large sample pieces, these processes need to be improved to reduce fluid and energy consumption. In this work, the water immersion thawing process of yellowfin tuna was studied from both experimental and numerical approaches. First, the heat transfer model is validated with precooked tuna samples undergoing forced-air convection thawing. Then, the water immersion thawing process of yellowfin was studied with temperature measurements performed under an industrial environment. The numerical model considers the real geometry of the yellowfin using magnetic resonance imaging (MRI) integrated into a 3D finite element model. Overall, good agreement was found between experimental and predicted temperatures by considering a uniform convective heat transfer coefficient. A simplified 2D model can accurately predict the thawing time, but a 3D model is needed to predict the spatiotemporal temperature distribution in the product. The results have also shown the strong influence of the ambient temperature on the thawing time. This original approach considering the real fish geometry could now be used with different sized-tuna and various thawing kinetics to reach optimal processing conditions while improving product quality.