Assessing the Dynamic Rheology at Various Frequencies of Surimi Paste as Affected by Heating Rates and Moisture Contents

Insight into the Effect of Ice Addition on the Gel Properties of Nemipterus virgatus Surimi Gel Combined with Water Migration

The effect of the amount of ice added (20–60%) on the gel properties and water migration of Nemipterus virgatus surimi gel obtained with two-stage heat treatment was studied. The gel strength and water-holding capability (WHC) of the surimi gel with 30% ice added were significantly higher than those of other treatment groups (p < 0.05). The addition of 30% ice was conducive to the increase of protein β-sheet proportion during heat treatment, exposing more reactive sulfhydryl groups. These promoted the combination of protein-protein through disulfide bonds and hydrophobic-hydrophobic interactions, forming an ordered three-dimensional gel network structure. Meanwhile, the increase in hydrogen bonds promoted the protein-water interaction. Low-field nuclear magnetic resonance analysis showed that more bound water was locked in the gel system, reducing the migration of immobile water to free water and finally showing better gel properties. When the amount of ice added was insufficient (20%), the gel structure lacked the support of immobile water, resulting in deterioration of gel strength. However, excessive addition of ice (>30%) was not conducive to the combination of protein-protein and protein-water, forming a large and rough gel structure, resulting in the migration of immobile water to free water and ultimately exhibited weak gel properties.

Application of multi-element viscoelastic models to freshness evaluation of beef based on the viscoelasticity principle

The aims of this work were to develop multi-element viscoelastic models for beef and apply them to detect total volatile basic nitrogen (TVB-N) content for freshness evaluation. The deformation data were collected by a viscoelasticity detection system that employed the airflow and laser technique. Then, TVB-N contents were measured to determine the freshness of samples during storage. A universal global optimization (UGO) algorithm was applied to fit the deformation data. Various multi-element viscoelastic models including the Burgers, six-element and eight-element models were built using the obtained fitting parameters, and different viscoelastic parameters representing the degree of beef spoilage were obtained. All the viscoelastic parameters of each multi-element model and parameter combinations of the selected six-element model were employed to build mathematical models for predicting TVB-N content by support vector machine regression (SVR). In comparison, the six-element model with all the viscoelastic parameters performed the best and was determined to predict TVB-N content with correlation coefficient in the prediction set (R_P ) of 0.891 and root mean squared error in the prediction set (RMSEP) of 1.467 mg/100 g. Based on the results of parameter combinations, combination (E₂ , E₃ , E₁ , η₁ , η₂ ) from the six-element model performed the best, which was comparatively inferior to all the viscoelastic parameters of the six-element model. Results demonstrated that it was possible to predict TVB-N content for freshness evaluation by applying method of developing multi-element model based on the viscoelasticity with chemometrics.