Optimization of convective drying assisted by ultrasound for Mango Tommy (Mangifera indica L.)

Abstract

Convective drying is a conventional method to prolong the shelf‐life of foods that could negatively affect the product quality due to the long exposure time to high temperature. Ultrasound (US) has been used for reducing the drying time while maintaining the product quality. In this study a Box‐Behnken design of Response Surface Methodology (RSM) was used to evaluate the effects of US time‐frequency (t), US power level (Pot), and hot air temperature (T) on the drying process time (DPT), apparent density (AD), and color difference (ΔE) of the dried mango slices (10.0 ± 1.0% wet basis). Fisher's statistical testing was performed for the analysis of variance (ANOVA) for quadratic regression equations. The optimization goals were to minimize the responses. Modeled optimized conditions were 52–55 °C, 45–60 W, and 3 min/30 min for T, Pot, and t, respectively. Energy consumption and carbon footprint were also estimated during the validation of the optimal drying conditions. Practical applications This research explored the use of response surface methodology polynomial models fitted to the experimental data of US assisted drying assays to find the best values of air temperature, time‐frequency, and power of sonication for minimization of the drying process time (DPT) apparent density, and color difference of mango slices. The results specified ranges for the input‐variables where lower DPT and properly dried mango quality parameters co‐exist with important reductions in operational costs and carbon foot‐print compared with those estimated for conventional dehydration process. These findings are of interest toward the development of greener and more sustainable food drying processes.

The effect of ultrasound pre‐treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network

“…A similar result was obtained through a study on a type of almond in which change in the product color increased by the increase in temperature and ultrasonic duration (Safary & Chayjan, 2016). Similar results have been obtained for mango tommy (Mendez-Calderon et al, 2017) and green pepper (Szadzi nska et al, 2017). With regard to the importance of quality indexes (color and shrinkage) in this study, it became clear that the minimum color change (ΔE = 9.14) and shrinkage (7.1%) occurred at the temperature of 40 C and control sample (0 min) application.…”

“…A number of researchers have studied about different dryers for agricultural product drying with convection dryer and ultrasound pre‐treatment including of paddy thyme (Jafari & Zare, ; Rodriguez, Melo, Mulet, & Bon, ), apple (Kowalski, Mierzwa, & Stasiak, ), mango tommy (Mendez‐Calderon, Ocampo‐Castano, & Orrego, ), and green pepper (Szadzińska, Łechtańska, Kowalski, & Stasiak, ) and shelled corn (Abdoli, Zare, Jafari, & Chen, ). In Iran, the product is more dried in a traditional way that has health problems.…”

The effect of microwave and convective dryer with ultrasound pre‐treatment on drying and quality properties of walnut kernel

“…In other words, higher temperature led to larger mass transfer and resulted in lower drying time and reduction in specific energy consumption (Filippin, Filho, Fadel, & Mauro, ). The values of SEC are in agreement with the documented values of 1.197–1.357 kWh for oven drying, 1.107–1.500 kWh for vacuum drying, 1.731–1.961 kWh for US‐vacuum, and 1.571–1.665 kWh for the control applied for green beans (Tekin, Başlar, Karasu, & Kilic, ), 0.17 kWh for CON drying assisted by US of mango Tommy (Mendez‐Calderon, Ocampo‐Castano, & Orrego, ), 20.03 to 56.15 MJ/kg for air‐borne US on fluidized bed drying at different frequencies (20 and 30 kHz) and air temperature (40 to 60°C) of corn kernels (Abdoli et al, ).…”

Optimization of ultrasound‐assisted extraction of functional polysaccharides from common mullein (Verbascum thapsus L.) flowers

“…Meanwhile, use of an optimization procedure such as response surface methodology (RSM) can be helpful to attain high values in the yield of extracted polysaccharides and other natural compounds based on the mathematical models (Gharibzahedi, Razavi, & Mousavi, 2015a). This statistical model-based methodology not only again decreases the required time and cost to perform experimental experiments, but also determines a calculated relationship between one or more studied responses (Mendez-Calder, Ocampo-Casta, & Orrego, 2017).…”