Prediction of Peroxidase Inactivation During Broccoli Blanching

Area of Science:

• Food Science and Technology
• Biochemical Engineering
• Thermal Processing

Background:

• Peroxidase inactivation is crucial for maintaining vegetable quality during blanching.
• Accurate prediction of enzyme inactivation requires integrating kinetic parameters with temperature profiles.
• Finite Element Method (FEM) offers a powerful tool for simulating complex thermal processes.

Purpose of the Study:

• To integrate decimal reduction time (D_T) and thermal resistance parameter (z) with 3D FEM-predicted temperature histories for predicting peroxidase inactivation in broccoli.
• To validate the predictive model using experimental data from broccoli blanching.
• To assess the impact of temperature-dependent thermophysical properties on inactivation predictions.

Main Methods:

• Determined D_T and z-parameter for peroxidase inactivation across various temperatures.
• Utilized 3D FEM to predict temperature histories (FEMTH) within broccoli cylinders and florets.
• Compared FEMTH and experimental temperature histories (ETH) for predicting residual peroxidase activity (a_res).

Main Results:

• D_T values ranged from 57.0 min at 50°C to 2.00 min at 70°C; z-parameter was 13.9°C.
• No significant differences in a_res were observed between ETH and FEMTH.
• The integrated model accurately predicted peroxidase inactivation under blanching conditions (80°C for 2 min).

Conclusions:

• Integration of thermokinetic parameters with FEM-predicted temperatures provides a reliable method for predicting peroxidase inactivation.
• The study underscores the importance of using vegetable-specific enzyme data for accurate modeling.
• Optimized thermal treatments based on these findings can enhance nutritional and sensory attributes of blanched vegetables.