Ecofriendly process optimization of natural dye extraction from clove (Syzygium aromaticum L.) using response surface methodology and artificial neural network modeling

Abstract

Process optimization through statistical and machine learning techniques has been used as the recent growing interest for the researchers. Current study has been undertaken to optimize the dyeing behavior of clove (Syzygium aromaticum L.) for cotton under microwave treatment. Response surface methodology and artificial neural network modeling with simplest structure was performed to observe the significance of selected color parameters. The results reveal that if extract and fabric is simulated for optimal MW time then high yield is obtained. For shade development, dyeing of irradiated cotton at 70 °C for 50 min with irradiated extract of 7 pH, using 3 g/100 mL salt has given color fast shades. ISO standard reveal that using selected dyeing conditions with carefully chosen chemical and bio-mordants has possessed good to excellent ratings. Microwave treatment should be used to get effective yield of colorant from clove for cotton dyeing. Additionally the utilization of ecofriendly mordants to make dyeing process greener should be included. It is recommended that artificial neural network model has better predicative capacity for process optimization as compared to response surface methodology.