Limit growth of ice crystals under different temperature oscillations levels in nile Tilapia

Effect of sodium alginate ice glazing on the quality of the freeze-thawed fish balls

The effect of 1.0 % (w/v) sodium alginate (SA) glazing on surface frost formation and the quality of frozen fish balls in repeated freeze-thaw (F-T) cycles was studied. The optimal glazing property of 1.0 % SA solution was manifested by high transmittance, excellent water resistance, and high ice glazing rate. After seven F-T cycles, compared with the control, the ice production, thawing loss, and total volatile base nitrogen (TVB-N) value of samples with 1.0 % ice glazing decreased by 28.30 %, 21.02 %, and 27.35 %, while the chewiness and whiteness were increased by 15.02 % and 10.40 %, respectively. Moreover, compared to the control, the microstructure of fish balls glazed with 1.0 % SA was smoother and more uniform, and the ice crystal diameter was smaller. Therefore, 1.0 % SA glazing effectively inhibits the formation of ice crystals, reducing water migration and loss while minimizing damage to the meat structure, thus enhancing the quality of meat products.

Inhibition of Chitosan Ice Coating on the Quality Deterioration of Quick-Frozen Fish Balls during Repeated Freeze-Thaw Cycles

Chitosan ice coating's properties and its inhibitory effect on the quality deterioration of quick-frozen fish balls during repeated freeze-thaw cycles were investigated. When the chitosan (CH) coating concentration increased, the viscosity and ice coating rate increased, while water vapor permeability (WVP), water solubility, and transmittance decreased, and 1.5% CH was regarded as the excellent coating to apply to freeze-thaw quick-frozen fish balls. As the freeze-thaw cycles increased, the frost production, total volatile base nitrogen (TVB-N) values, and free water content of all of the samples increased significantly (p < 0.05), and the whiteness values, textural properties, and water-holding capacity (WHC) decreased. Freeze-thaw cycles expanded the aperture between the muscle fibers and the occurrence of crystallization and recrystallization between cells increased, damaging the original intact tissue structure, which were confirmed by SEM and optical microscopy. Compared with the untreated ones, the frost production, free water, and TVB-N of the samples with 1.5% CH decreased during 1, 3, 5, and 7 cycles, and were reduced by 23.80%, 32.21%, 30.33%, and 52.10% by the 7th cycle. The WHC and texture properties showed an increasing trend during the freeze-thaw cycles. Therefore, the chitosan ice coating effectively inhibited the quality deterioration by reducing water loss, the occurrence of ice crystallization and recrystallization, and the pores of the samples.

A feasibility study on nondestructive classification of frozen Atlantic salmon (Salmo salar) fillets based on temperature history at the logistics using NIR spectroscopy

Temperature fluctuation commonly occurs in the cold chain leading to complete or partial thawing and refreezing of frozen products resulting in a multifrozen product. Such oscillation of temperature could cause significant quality reduction compared to single frozen products. This study was designed to differentiate frozen Atlantic salmon fillets based on the level of temperature fluctuation. Near-infrared spectroscopy (NIRS) coupled with chemometrics was used to classify the frozen fillets stored at no fluctuation (NF), low fluctuation (LF), high fluctuation (HF), and very high fluctuation (VF) temperature. Using spectral profiles obtained at both frozen and thawed states, fillets were classified based on the level of temperature fluctuation by partial least squares discriminant analysis (PLS-DA). The thawed samples showed better classification accuracy (71%) than frozen samples (66%) in a four-class model. Considering the small variation within the first two (NF, LF) and the last two (HF, VF) groups, a two-class classification model was developed using thawed samples, and the obtained model correctly classified the two groups ([NF, LF] and [HF, VF]) with 100 % classification accuracy. Protein- and water-related changes were found important to distinguish the fillets. Based on these findings, the four-class prediction model is found insufficient to be used for nondestructive determination of temperature history of frozen fillets. However, the two-class prediction model with further external validation can be applied to determine the level of temperature fluctuation particularly using fillets scanned at thawed state. PRACTICAL APPLICATION: NIR spectroscopy can be used to evaluate the degree of temperature fluctuation and thus related quality loss throughout the logistics of frozen Atlantic salmon fillets. Researchers, food control authorities, and the retail industry could be the primary beneficiaries of this research output.