OPTIMIZATION OF INFRARED-CONVECTIVE DRYING MODES FOR APPLES CONSIDERING MOISTURE REMOVAL KINETICS, ENERGY CONSUMPTION, AND VITAMIN «C» PRESERVATION
DOI:
https://doi.org/10.15421/jchemtech.v34i1.346706Keywords:
infrared drying, apples, moisture removal kinetics and mass transfer parameters, vitamin C degradation kineticAbstract
The object of the study is the process of infrared –convective drying of medium-ripeness «Golden Delicious» apples. The relevant problem was to determine the optimal drying modes that ensure efficient moisture removal with minimal energy consumption while preserving bioactive components, particularly vitamin C. The experiment used slices 3.5 mm thick; drying was carried out at temperatures of 50, 60, and 70 °C and an air velocity of 3 m/s, achieving a final moisture content of 10 %. The mass of removed water, specific energy consumption (SEC = 71.78–110.35 kWh/kg water), average system power (2.78 kW), and the characteristic internal diffusion time (τ≈51 min) were determined. The kinetics of vitamin C degradation was modeled as a first-order process: losses amounted to 20 % at 50 °C, 30 % at 60 °C, and 40 % at 70 °C, which allowed calculating the degradation rate constants kvitC. Statistical analysis showed a high correlation between temperature and drying parameters (r≈0.995–0.998), and the constructed regression and exponential models adequately describe the experimental data (R²≈0.998). The obtained results are explained by intensified mass and heat-mass transfer at higher temperatures and the corresponding acceleration of thermolabile component degradation. A distinctive feature of the study is its comprehensive approach, simultaneously accounting for drying kinetics, process energetics, and changes in the biochemical composition of the product, enabling optimization of the mode to obtain high-quality dried fruit. The practical application of the results covers industrial and laboratory infrared drying of apples and similar fruits, where balancing drying rate and vitamin preservation is required, and the developed models allow predicting the energy and quality characteristics of the product.
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