Artificial neural network modelling approach of drying kinetics evolution for hot air oven, microwave, microwave convective and freeze dried pineapple

Abstract

This study presents the dehydration characteristics of the drying of the pineapple slice. Hot air oven (60 °C), microwave (100 W), microwave convective (600 W, 40 °C) and freeze drying (0.1 mbar, − 40 °C) of pineapple slice through artificial neural network (ANN) modeling approach (Backpropagation algorithm for feed-forward network). Considering the sample thickness of 0.15 cm, effective moisture diffusivity is calculated. To study the reconstitution property of the product, the rehydration ratio is considered at 20 °C, 40 °C, 60 °C and 80 °C. The microwave convective drying (96 min) is the fastest while the freeze drying is slowest (20 h). The coefficient of correlation through the ANN model for hot air oven, microwave, microwave convective and freeze dried sample are 0.99936, 0.9994, 0.99948, and 0.99926 respectively. In terms of rehydration ratio, freeze drying (5.49) is found best followed by microwave (4.62), hot air (4.50), and microwave convective drying (2.00). At 80 °C the coefficient of rehydration value attains the maximum of 0.969 for freeze dried sample, whereas the minimum value of 0.369 is observed at 20 °C for the microwave-convective dried sample. From the observations obtain it may be stated that the ANN model predicts the dehydration kinetics adequately for the entire drying process. Freeze dried product appears to be the best in terms of reconstitution properties.