Response surface optimization and artificial neural network modeling of microwave assisted natural dye extraction from pomegranate rind

The extracted dye from brown dry rind of the pomegranate has been used as natural colorant for textiles from ancient times. In this study, microwave assisted extraction (MAE) has been used for extraction for dye from dried pomegranate rind. The effect of three independent parameters namely extraction time (25–90 s), pH of solution (3.5–8) and amount of pomegranate rind (0.5–1.5 g) was considered. Response surface methodology (RSM) is applied to optimize the effects of processing parameters of extraction on the yield of dye and a computer-stimulated artificial neural network (ANN) model is developed to get a good correlation between the input variables responsible for extraction and the output parameter (concentration of dye) of extraction from pomegranate rind. Considering the yield of dye extraction and the feasibility of the experiment, the optimum conditions of dye extraction are extraction time 90 s, pH 3.5, amount of sample 1.48. Application of microwave irradiation method proved to be a rapid and improved technique for dye extraction and significantly reduced the extraction time. The optimization procedure shows a close interaction between the experimental and simulated values for dye extraction.

► The advantages of natural dye are cost effective, renewable, and non-carcinogenic in nature and have no allergic reaction on skin.
► Pomegranate has been used to extract the color and the colorant is extracted at different elevated times, and the extraction time is analyzed using RSM and ANN methods.
► The ANN simulation process shows satisfactory agreement with the experimental results.
► The % error of experimental and simulation results are very low.