Investigating the potential use of natural dye extracted from Artocarpus heterophyllus sawdust waste in cotton fabric dyeing: A sustainable approach

Purpose The improper disposal of waste materials negatively impacts the environment by causing pollution and creating health hazards for humans. This study aims to offer a hopeful solution and focuses on extracting and characterizing a novel natural dye from sawdust waste of Artocarpus heterophyllus and investigating its potential use in cotton fabric dyeing. Design/methodology/approach The natural dye was obtained from Artocarpus heterophyllus sawdust waste through an aqueous extraction method. The characterization of dye extraction involved various analytical methods, including pH, gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible (UV-vis) and cyclic voltammetry (CV) measurements. The dyeing rate and percentage of dyeing at equilibrium of cotton fabric with the aqueous extract were evaluated at 70 °C, 80 °C and 90 °C. Colour properties of the dyed fabric samples were assessed using colourfastness, colour intensity and colour coordinates. The environmental impact of residual dye solutions was assessed using biochemical oxygen demand, chemical oxygen demand and biodegradability index. Findings The yellow aqueous dye extract (pH 5.86) contained 20 active compounds identified by GC-MS. FTIR and UV-vis analyses confirmed functional groups responsible for the yellow colouration. CV measurements discovered the extract’s electrochemical properties. Dyeing experiments showed that the dyeing rate and equilibrium uptake were influenced by the dyeing process. Mordanting processes significantly influenced dye uptake, colourfastness and wastewater characteristics, with pre-mordanting resulting in better biodegradability. Originality/value This study presents a sustainable use of Artocarpus heterophyllus sawdust waste as a natural dye, indicating its effectiveness for eco-friendly textile colouration through comprehensive characterization and performance analysis.