Kinetic and artificial neural network modeling of dried black beauty eggplant (Solanum melongenaL.) slices during rehydration

Abstract

AbstractThis paper targeted to investigate rehydration characteristics of dehydrated black beauty eggplant (which was dried under sun, by hot air, microwave, and infrared) at 25, 50, and 75°C, and to analyze rehydration ratio (RR) by artificial neural network (ANN) approach. RRs of both microwave‐processed specimens (between 5.66 and 7.91) and sun‐dried ones (between 5.38 and 6.37) were always greater than the others, at all rehydration temperatures. Rehydration temperature had an enhancing effect on RRs, and the image that closely resembled the fresh sample was captured in the microwave‐dried rehydrated samples. Nearly 180–240 min was adequate for rehydration of all slices. Zeroth‐ and first‐order kinetic models, Peleg, Peppas, and two‐term exponential decay models, as well as a new rational model were tested to describe rehydration kinetics. Two‐term equation was almost superior with high R2 (between 0.9734 and 0.9994) and the lowest root mean square error (RMSE) and χ2. Novel recommended mathematical expression was also successful (R2: 0.9679–0.9989, χ2: 0.0051–0.0975, RMSE: 0.0191–0.0866). Regarding relationship between actual and predicted RRs and performance indices of ANN equation, overall R and R2 were recorded as follows: 0.9975–0.9950 (sun‐dried) > 0.99642–0.9929 (hot air‐dried) > 0.9955–0.9911 (infrared‐dried) > 0.9907–0.9815 (microwave‐dried), respectively. The proposed ANN model and novel mathematical formula not only offer a considerable potential in predicting rehydration patterns and developing rehydration protocols in food production sector, but also contribute to save energy by completely understanding the process and optimizing conditions.Practical applicationsThe eggplant is a cherished vegetable often dried, providing a velvety texture and rich taste in Anatolian recipes. In Anatolia, colorful vegetables are strung together on strings, adorning traditional houses, and serving as a testament to the region's deep‐rooted cultural heritage. The Turkic people in Central Asia demonstrated remarkable skill in preserving plants by carefully drying leaves, stems, or roots. The process of rehydration entails the addition of water to dehydrated eggplant slices in order to restore their initial dimensions and attributes for being consumed. This investigation integrates the utilization of ANNs to simulate the rehydration procedures of eggplant. This simulation can be employed for the purpose of quality control and standardization within the food sector. Hence, food manufacturers can anticipate the rehydration characteristics of their products across various production batches and conditions, thereby guaranteeing adherence to quality benchmarks.