Microwave vacuum drying of lotus (Nelumbo nucifera Gaertn.) seeds: Effects of ultrasonic pretreatment on color, antioxidant activity, and rehydration capacity
“…Thus, more extracts are rapidly released from plant cells. But when ultrasound power is too low or too high, the cavitation intensity is very weak or will not even occur [62] , [63] . Fig.…”
“…Thus, more extracts are rapidly released from plant cells. But when ultrasound power is too low or too high, the cavitation intensity is very weak or will not even occur [62] , [63] . Fig.…”
“…The color changes may be caused by cavitation that is known to accelerate chemical reactions (Tiwari et al, 2010). These changes were caused by oxidation reactions in carotenoids that were promoted by the interaction with free radicals formed during sonication (Zhao et al, 2021). These results accord with those reported by Erdem et al (2018) and Bromberger Soquetta et al (2018).…”
Peach, which is one of the most critical garden products in Iran has a lot of postharvest lesions. In this sense, processing the product would result in reducing the postharvest lesions. Recently, ultrasound waves have been widely applied as a new pretreatment method in drying food. Herein, we aim at investigating the effect of high power ultrasound pretreatment on the drying kinetics of peach slices. The effective moisture penetration coefficient, color changes and elastic modulus were investigated. The drying process was modeled using mathematical equations. The results showed that the ultrasound use as a pretreatment before drying reduces the drying time by up to 40%. The ultrasound treatment effect and the duration of their application on the color changes of the samples are not significant, and the reason for the color change is due to maillard reactions. The results of the effect of ultrasound pretreatment on the elastic modulus due to loading in the compression test showed that the application of pretreatment on the deformation of the samples is significant and reduced the modulus of elasticity by about 46%. The midilli model in different pretreatments, as compared to other models, had the best fitting with the experimental data. Moreover, the amount of effective diffusivity coefficient in the dried samples of peach slices, in different pretreatments, varies from 1.345 × 10−9 to 5.370 × 10−10 m2 s−1. In addition, it is worth mentioning that ultrasound pretreatment can be regarded as a promising approach. As far as food and agricultural products have typical structure and composition, ultrasound pretreatment application requires more through research.
Practical Applications
As compared to the untreated peach slices, a significant enhancement was witnessed in the ultrasound (US)‐treated slices. Herein, a new method is proposed, which results in producing slices with an improved quality. Generally, peach‐slice processing has been applied to get high‐quality products.
“…The rehydration capacity is a quality index for evaluating the microstructural changes in plant tissues during drying and other treatments [ 39 ]. The influence of blanching time on the RC of dried blueberries is shown in the green columns in Figure 7 .…”
This study aimed to optimize the postharvest blanching and drying process of blueberries using high-humidity air impingement (HHAIB) and hot-air-assisted infrared (HAIR) heating. A novel pilot-scale hot-air-assisted carbon-fiber infrared (IR) blanching/drying system was developed. Fresh blueberries with an average diameter of 10~15 mm were first blanched with high-humidity air at 110 °C and 12 m/s velocity for different durations (30, 60, 90, and 120 s); subsequently, the preblanched blueberries were dried at different IR heating temperatures (50, 60, 70, 80, and 90 °C) and air velocities (0.01, 0.5, 1.5, and 2.5 m/s), following a factorial design. The drying time (DT), specific energy consumption (SEC), ascorbic acid content (VC), and rehydration capacity (RC) were determined as response variables. A three-layer feed-forward artificial neural network (ANN) model with a backpropagation algorithm was constructed to simulate the influence of blanching time, IR heating temperature, and air velocity on the four response variables by training on the experimental data. Objective functions for DT, SEC, VC, and RC that were developed by the ANN model were used for the simultaneous minimization of DT and SEC and maximization of VC and RC using a nondominated sorting genetic algorithm (NSGA II) to find the Pareto-optimal solutions. The optimal conditions were found to be 93 s of blanching, 89 °C IR heating, and a 1.2 m/s air velocity, which resulted in a drying time of 366.7 min, an SEC of 1.43 MJ/kg, a VC of 4.19 mg/100g, and an RC of 3.35. The predicted values from the ANN model agreed well with the experimental data under optimized conditions, with a low relative deviation value of 1.43–3.08%. The findings from this study provide guidance to improve the processing efficiency, product quality, and sustainability of blueberry postharvest processes. The ANN-assisted optimization approach developed in this study also sets a foundation for the smart control of processing systems of blueberries and similar commodities.
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