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The increasing environmental concerns of synthetic dyes have led to a renewed interest in natural dyes derived from plant sources. This study investigates the potential of weed flower petals, often considered waste flora, as a sustainable source of natural dyes for cotton fabric. Three different extraction methods were employed: Alkaline extraction (using dilute base to enhance pigment release), chloroform extraction (to isolate non-polar pigments), and aqueous extraction (using water as a solvent for eco-friendly processing). Each method yielded distinct pigment profiles, highlighting the influence of solvent polarity and extraction conditions on dye yield and quality. The extracted dyes were used to treat pre-mordanted cotton fabric using chemical mordants to improve dye fixation, color intensity, and wash fastness. The dyed samples were then analyzed using UV-Visible spectroscopy to characterize the pigment compounds present in each extract and to assess the optical absorbance across visible wavelengths. The results revealed notable differences in pigment concentration and stability among the three extraction methods, with acid and chloroform extractions showing higher pigment intensities compared to aqueous extraction. This research demonstrates the viability of utilizing weed flower petals as an eco-conscious dye source and emphasizes the role of extraction technique and mordant treatment in optimizing natural dye applications for textiles. The findings contribute to the field of sustainable textile development by promoting the use of locally available, biodegradable dye sources and green processing methods.
"From Weeds to Wearables: Exploring Sustainable Textile Dyeing through Wildflower Pigments", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.a613-a621, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506071.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator