Utilization of agro-waste-derived cellulose for eco-friendly hydrogel production in irrigation management
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Swetha Satheesh
and
Thenesh Kumar Saghadevan
Abstract
Water scarcity and irregular rainfall pose significant challenges to irrigation, especially for small-scale farmers. This study presents the development of an eco-friendly, cellulose-based hydrogel using agricultural waste such as sugarcane bagasse and pea peels aimed at improving soil moisture retention. Cellulose was extracted via alkali treatment, aligning with principles of waste valorization and the circular economy. The hydrogel was synthesized using carboxymethyl cellulose sodium (CMCNa) and xanthan gum with citric acid as a biodegradable crosslinker. Cellulose nanocrystals (CNC’s), obtained through acid hydrolysis, were incorporated to enhance structural integrity. The hydrogel was characterized through Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), thermogravimetric analysis (TGA), and energy-dispersive spectroscopy (EDS). It demonstrated excellent swelling capacity, sustained moisture retention, and biodegradability. Soil amended with the hydrogel retained 67 % of moisture after 15 days compared to 50 % in control soil and supported enhanced plant growth (26.9 cm of height vs. 20.7 cm in control). Biodegradability tests indicated 20 % degradation within 2 weeks. These results show that the hydrogel offers a cost-effective and sustainable approach to irrigation management, with strong potential for application in drought-prone agricultural areas.
Acknowledgments
The authors would like to thank the Department of Chemical Engineering, St. Peter’s College of Engineering and Technology, Avadi, for providing the necessary support and facilities for this project.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: SS: conceptualization, experimentation, data analysis, and manuscript drafting. TK: supervision, project guidance and manuscript review. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: The authors used Grammarly and ChatGPT to improve the language and flow of the manuscript. These tools were not used to generate content or conduct analysis.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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