Predictive modeling of apple slice drying: Integrating temperature, thickness, and shrinkage dynamics.

Area of Science:

• Food Science
• Agricultural Engineering
• Process Optimization

Background:

• Dehydration is crucial for preserving fruits like apples.
• Understanding the impact of process parameters on drying kinetics and quality is essential for efficient food processing.

Purpose of the Study:

• To investigate the influence of drying temperature and slice thickness on Golden Delicious apple slices.
• To analyze drying kinetics, shrinkage, moisture diffusivity, and color changes.
• To develop predictive models for shrinkage and moisture diffusivity.

Main Methods:

• Controlled cabinet drying experiments at 50°C, 60°C, and 70°C with slice thicknesses of 2, 4, and 6 mm.
• Statistical analysis (ANOVA) to determine factor significance.
• Multivariate regression and Finite Element Modeling (FEM) for prediction and validation.

Main Results:

• Drying time significantly decreased with increased temperature and reduced slice thickness, with thickness being more influential.
• Shrinkage decreased, while effective moisture diffusivity increased under optimized conditions.
• The combination of 70°C and 4 mm slice thickness yielded the lowest total color change (ΔE).

Conclusions:

• Drying temperature and slice thickness are critical parameters affecting apple dehydration and quality.
• Predictive models accurately described shrinkage and moisture diffusivity.
• Optimal drying conditions (70°C, 4 mm) minimize color degradation, offering practical insights for energy-efficient apple processing.