Prediction of Cut Surface Angle of the Frozen Fish by Bending

Abstract

We have proposed a new cutting method (cryo-cutting method) in which a frozen fish is cut by applying the 3-point bending force, instead of a band saw in the conventional cutting method using. We have already reported that the cutting destruction of fish meat occurred in two typical destruction modes of "the destruction across the muscle fiber" and "the destruction along the muscle fiber" when frozen fish are cut by the new method. The frequency of these two destruction modes was dependent on muscle fiber orientation angle (θ_f). In order to obtain the accurate cut section of frozen fish, it is necessary that only "the destruction across the muscle fiber" would be developed. In this paper, we tried to predict the range of muscle fiber orientation angle for yielding only "the destruction across the muscle fiber", based on the assumption the fish muscular tissue is the unidirectional composite material strengthened with the muscle fiber. By modifying the fracture theory of the unidirectional composite material strengthened in the fiber, we proposed a prediction equation for the destruction mode in 3-point bending fracture. Using the equation and the bending fracture stress of test pieces at θ_f=0° and 90° (S₀ and S₉₀), we estimated the range of muscle fiber orientation angle only for "the destruction across the muscle fiber" in order to prove the effectiveness of the equation, three-point bending test of frozen tuna muscle was carried out at -70, -100 and -130°C and the generation frequency of each destruction mode was measured. The following results were obtained. (1) At all the temperatures tested, only "the destruction across the muscle fiber" was generated muscle fiber orientation between θ_f=0° and 20°. (2) The frequency of each destruction mode measured in the experiments agreed with the predicted at all the temperature tested, when the mean value of bending fracture stress (S)±double of the standard deviation (σ), S_0(mean)±2σ₀ and S_90(mean)±2σ₉₀, were used for the prediction calculation.