Artificial neural network and kinetic modeling of capers during dehydration and rehydration processes

Abstract

AbstractThis study aimed to investigate the drying kinetics of capers at different temperatures and to examine the morphological changes of capers during the drying and rehydration processes. Computer‐aided image processing and Artificial Neural Network models (ANN) were used to analyze the shrinkage and moisture ratio of capers (drying) and the expansion of capers (rehydration). Lewis, Page, Fick's law, and logarithmic models were investigated to describe the conventional drying kinetics of capers at 50, 60, and 70°C; the logarithmic model was shown to be the best describing model (r2: 0.9996, 0.9996 and 0.9981, respectively). Effective diffusivities varied between 1.91 × 10−10 and 2.62 × 10−10 m2/s for the temperature range. The activation energy was 14.572 kJ/mol. Image processing revealed that diameter reduction rates were 1 × 10−4 mm/s for 50 and 70°C and 7 × 10−5 mm/s for 60°C. ANN was applied using multilayer perceptron models with three layers (input: ANN1, hidden: ANN2, and output: ANN3) which were sufficiently valid for predicting the experimental parameters (r2: 0.9992, 0.9915, and 0.8484, respectively). All morphological properties were reduced with drying, and shrinkage of capers was increased proportionally with the moisture content. The Global Sensitivity Analysis recognized treatment time as the most influential parameter affecting the moisture ratio and the caper diameter changes.Practical applicationsOne of the major problems for humans has been to improve food preservation techniques for long‐term storage. The major scope of industry is the drying of fruits and/or vegetables to produce dried foods with high quality and a long shelf life. To the best of our knowledge, drying of capers regarding the drying kinetics, modeling and quality changes has not been published to date. In this study, goal was to better understand drying kinetics and geometric changes that occur to capers during the dehydration and rehydration processes at various drying temperatures. Quantitative information regarding geometrical changes to capers was supplied by the image processing of the acquired pictures, which enabled rapid monitoring of physical changes during dehydration and rehydration. The remarked kinetic model, ANN model, and Quantitative information regarding geometrical changes are valuable information for researchers studying on drying of food and large‐scale dryer designers.