Optimization of pulsed ultrasonic‐assisted extraction of punicalagin from pomegranate ( Punica granatum ) peel: A comparison between response surface methodology and artificial neural network‐multiobjective genetic algorithm

Abstract

The present study focuses on the valorization of pomegranate peel waste by extracting bioactive compounds (mainly punicalagin) through pulsed ultrasonic‐assisted extraction. Response surface methodology (RSM) and artificial neural network coupled with multiobjective genetic algorithm (ANN‐MOGA) were used to determine the optimum extraction condition, namely, solvent volume, amplitude, time, and duty cycle. The responses for the optimization process include punicalagin content, ellagic acid, antioxidant activity, total phenolic content (TPC), total flavonoid content, and anthocyanin content. By applying ANN‐MOGA it was found that at optimum condition of 35 ml of solvent, 35% amplitude, 23 min and 100% duty cycle, punicalagin, ellagic acid, antioxidant activity, and TPC was 6.63%, 18.59%, 52%, and 4.23% higher than RSM predicted values, respectively. Thus, the study proves that ANN‐MOGA is an effective tool in predicting maximum punicalagin production from pomegranate peel. The optimization showed a close match between predicted and experimental data. Practical applications Pomegranate peel is a source of bioactive components. With the increase in demand for “clean label” products worldwide, valorization of pomegranate peel could be a potent alternative. This study investigates the ultrasonic‐assisted extraction of major bioactive components from pomegranate peel in order to aid scaling up of the process. Also, the comparison between mathematical tools can give an insight into higher yielding process parameters.

Effects of process parameters on the extraction of total anthocyanins from purple sweet potatoes by ultrasound with wide frequency and its kinetics study

“…Nonetheless, the main drawbacks of those extraction processes are of large amount of solvents, longer time of treatment, higher consumption of energy, and lower extraction efficiency (Tiwari, 2015). As a consequence, in order to overcome these shortcomings associated with conventional extraction methods, various new techniques, such as ultrasound‐assisted extraction (Dranca & Oroian, 2019; Xue, Tan, Li, Cai, & Tang, 2021), microwave‐assisted extraction (González de Peredo et al, 2018), supercritical carbon dioxide extraction (Paes et al, 2014), and other novel extraction approaches (Budiene et al, 2021; Rakshit & Srivastav, 2021; Tzanova et al, 2020; Xue, Tan, Li, Tang, & Cai, 2021), have been developed for the extraction of anthocyanins from various plant materials.…”

Response surface methodology as a tool to optimize the extraction of bioactive compounds from plant sources

“…The ANN approach also demonstrated superiority in the optimization step with higher recovery and less variation range between optimized and validated values. Several other studies have also demonstrated improved predictive accuracy of RSM in combination approach for optimization of the extraction of bioactive compounds 48,51,61,66‐68 …”

“…Several other studies have also demonstrated improved predictive accuracy of RSM in combination approach for optimization of the extraction of bioactive compounds. 48,51,61,[66][67][68]…”

Modelling and Multi-Objective Optimization of Continuous Indirect Electro-Oxidation Process for RTB21 Dye Wastewater Using ANN-GA Approach

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