Microencapsulation of Dragon Fruit Peel Extract by Freeze-Drying Using Hydrocolloids: Optimization by Hybrid Artificial Neural Network and Genetic Algorithm

Abstract

The freeze drying encapsulation process was used to encapsulate dragon fruit peel extract with three distinct wall materials: maltodextrin, gum arabica, and gelatin. The process was modeled using a feed forward back propagation arti cial neural network with four, eleven, and four neurons in the input, hidden, and output layers. Three of the four input neurons were concentrations of wall material (g), while the fourth was ultrasonication power. The four output neurons were encapsulation e ciency, antioxidant activity, hygroscopicity, and solubility of freeze-dried encapsulation powder. The procedure was optimized using hybrid arti cial neural network (ANN) and genetic algorithm (GA) approach. The optimal wall material composition for encapsulation obtained by the integrated ANN and GA was 4.461 g maltodextrin, 3.863 g gum arabic, and 3.198 g gelatin. The optimal ultrasonication power for achieving a homogenous mixture was determined to be 123 W. At the optimal condition, the predicted values for the responses encapsulation e ciency, antioxidant activity, hygroscopicity, and solubility were found to be 88.143%, 81.702%, 6.924 g/100g, and 32.841%, respectively. Under optimal conditions, the relative deviation between the predicted model and experimental outcomes was less than 2.077%. The thermal stability of the encapsulated powder followed the rst order kinetic modeling. The results showed that the sample treated at pH of 7 was more thermally stable at 80°C than the sample treated at pH of 3.6. The half-life time was found to be 140 min and 103 min for the sample treated at pH of 7 and 3.6, respectively.

Effect of ultrasound pretreatment and microwave vacuum drying in the production of dried poniol fruit

“…The antioxidant activity of microwave vacuum dried poniol fruit was evaluated by DPPH radical‐scavenging method (Bhagya Raj, 2022). Briefly, 100 μL of extract was mixed with 2.9 mL of DPPH radical solution (10 −4 M).…”

Characterization and storage stability of microencapsulated black jamun (Syzygium cumini) pulp extract via freeze drying

“…The wall material and jamun pulp extract were mixed in a ratio of 1:4 (w/w) for 5 min at 25 C using a magnetic stirrer (Tarson). The solution was subjected to sonication at 100 W for 5 min at 30 C using an ultrasonicator with a probe (U500, Takashi, Japan) to ensure particle uniformity (Raj & Dash, 2022). The prepared homogenized mixture of wall material and the extract were subjected to freeze drying using a freeze drier (Lyolab Freeze Lab, Lyophilization Systems Inc., USA), grounded to fine powder, and screened using a 300-mesh filter.…”

Ultrasound-assisted extraction of phytochemicals from green coconut shell: Optimization by integrated artificial neural network and particle swarm technique

“…This makes the prediction more robust and accurate for the prediction of responses by the optimization algorithm. Many researchers have implemented, ANN and RSM based integrated approaches for the modeling and optimization of various extraction conditions of biological materials [ [15] , [16] , [17] , [18] ]. Based on this the objective of this study is to maximize the extraction of antioxidants and antimicrobial activities from green coconut shells and study the impacts of the extraction process parameters (methanol, ultrasonication temperature, time, and the ratio of solvent-solid) by applying an integrated approach of artificial neural network (ANN) and particle swarm optimization (PSO).…”