Abstract

The aim of this study is to determine the kinetics and quality properties of pistachios under different microwave powers (270, 450, and 630 W) and ultrasound (US) pretreatment at 0, 10, 20, 40, and 60 min. It is also aimed at comparing the estimations of the moisture ratio of pistachio by mathematical modeling, artificial neural networks (ANNs), and adaptive neuro-fuzzy inference system (ANFIS) methods. The minimum and maximum values of effective moisture diffusivity () were 1.43 × 10–8 and 4.30 × 10–8 m2/s, respectively. Specific energy consumption () of the samples was varied between 58.097 and 122.21 kWh/kg. The lowest value of shrinkage (13.1%) and color change (19.97) were reported in a microwave power of 270 W and duration of US 0 min. The results showed that considering ( = .9997) and Mean Square Error ( = 0.0004), the ANFIS model had a better performance in predicting the moisture ratio of pistachios compared to the mathematical models and ANNs. Practical applications Drying is defined as the process of removing moisture through the simultaneous transfer of heat and mass. Heat transfer from the surrounding environment to the foodstuff leads to the evaporation of the surface moisture. Moisture can also be transferred from inside the product to its surface and then evaporate there. The use of US waves has been suggested in combination drying methods especially in situations where preserving the appearance and nutritional value of the food are the main priority. The effective moisture diffusion coefficient is one of the important parameters in modeling, designing, and optimizing the drying process. Color is an important indicator of the quality of the food and represents the chemical, biochemical, and microbiological characteristics of the product. During the drying process, due to the evaporation of moisture from the foodstuff, the phenomenon of shrinkage occurs and this also affects the physical properties of the solids and the appearance of the final product.

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