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Response surface optimization and artificial neural network modeling of microwave assisted natural dye extraction from pomegranate rind
Authors:Keka Sinha  Papita Das Saha  Siddhartha Datta
Institution:1. Department of Biotechnology, National Institute of Technology Durgapur, Durgapur, West Bengal, India;2. Chemical Engineering Department, Jadavpur University, Kolkata, India;1. Research Unity of Applied Chemistry and Environment, Faculty of Sciences of Monastir, University of Monastir, Tunisia;2. Textile Engineering Laboratory, University of Monastir, Tunisia;3. National Engineering School of Monastir, University of Monastir, Tunisia;4. Al Imam Mohammad Ibn Saud Islamic University (IMSIU), College of Sciences, Department of Chemistry, 11623 Riyadh, Saudi Arabia;1. Assistant Professor, Department of Textiles and Apparel Design, Bharathiar University, Coimbatore, India;2. Professor, Department of Textiles and Apparel Design, Bharathiar University, Coimbatore, India;3. Textile Chemistry Division, The South India Textile Research Association, Coimbatore, India;1. Department of Chemistry, YMD College, Maharshi Dayanand University, Haryana 122107, India;2. Department of Chemistry, Jamia Millia Islamia (A Central University), New Delhi 110025, India
Abstract: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.
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