A Comprehensive Review of Mathematical Modeling for Drying Processes of Fruits and Vegetables.

Drying fruits and vegetables is a procedure of food preservation with simultaneous heat, mass, and momentum transfer, which increases the shelf life of the food product. The aim of this review was to provide an overview of the researches on mathematical modeling for drying of fruits and vegetables with the special emphasis on the computational approach. Various heat-mass transport models, their applications, and modern drying technologies to the food industry have been reported in this study. Computational fluid dynamics, a new approach for solving heat and mass transfer problems, increases the accuracy of the predicted values. To investigate the parameters of drying needs a significant amount of time as well as costly laboratory and experimental efforts. Therefore, computational modeling could be an effective alternative to experimental approaches. This review will be beneficial for future studies in drying processes, especially for modeling, analysis, design, and optimization of food science and food engineering.

Optimization of Drying Parameters for Total Phenolic Content of Papaya Using Response Surface Methodology.

An optimum condition of the drying process can minimize nutrient losses and maximize the shelf life of food products. Thus, this study is aimed at developing an optimized system for the process conditions to determine the total phenolic content (TPC) of oven-dried papaya slices. The response surface method and central composite design were used to design the experiment, and it was found that the drying conditions had a significant impact on the total phenolic content of papaya slices. TPC was determined in relation to their interactions with the independent variables that include time, temperature, sample thickness, and stage of ripeness. The optimum drying conditions are those with the maximum content of TPC. In order to fit the experimental data, a quadratic polynomial model is created for the output variable, and an analysis of variance is carried out to determine whether or not the model is compatible to determine the optimal drying conditions. Time (10 h), temperature (62.02°C), thickness (9.75 mm) and stages (ripe) were found to be the optimal drying conditions. It was found that temperature had more effect on the amount of TPC than other factors. The numerical findings showed a good agreement with experimental data, with R 2 = 0.9237. It is hoped that the findings will make a contribution to the process of drying food.