Optimization and Evaluation of Drying Kinetics and Quality Attributes of Persimmon Using Infrared Dryer: Influence of Operational Parameters

The impact of infrared drying parameters on drying time and the qualitative characteristics of the persimmon was thoroughly investigated by varying sample thickness (۳, ۵, and ۷ mm), air velocity (۰.۵, ۱.۲۵, and ۲ m/s), and infrared power levels (۱۰۰۰, ۱۵۰۰, and ۲۰۰۰ W). The study utilized the Box-Behnken design of response surface methodology to conduct drying tests that elucidate the relationships between input and output variables. The primary objective was to enhance the drying process while preserving quality in persimmons, which are particularly susceptible to thermal degradation during conventional drying methods. The effects of various drying conditions were assessed regarding drying time, total phenolic content, antioxidant activity ( ), potassium and phosphorus contents, and color parameters ( ). Results indicated that increasing infrared power and reducing sample thickness significantly decreased drying time while improving the retention of total phenolic content, antioxidant activity, and mineral contents. Specifically, total phenolic content and antioxidant activities were best preserved at high infrared power and low sample thickness, while potassium content increased and phosphorus content exhibited more complex behavior.  values achieved the most favorable results with higher infrared power, moderate air velocity, and reduced sample thickness. Furthermore, all responses demonstrated a strong quadratic model, supported by high values. The optimal drying parameters identified were a sample thickness of ۷ mm, an air velocity of ۱.۲۹ m/s, and an infrared power level of ۲۰۰۰ W. This study offers valuable insights for optimizing infrared drying of persimmons, contributing to advancements in food processing technologies and presenting practical applications for industrial-scale operations.

کلیدواژه ها:

Infrared dryer ، Drying kinetics ، Persimmon ، Response surface methodology ، Optimization