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@article{199473,
        author = {Srinithi S and Aswanth K},
        title = {COMPARATIVE STUDY OF NATURAL PLANT EXTRACTS FOR THE EXTRACTION OF ALCOHOL BIOMARKERS (ETHYL GLUCURONIDE) FROM HUMAN NAIL SAMPLES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12918-12921},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199473},
        abstract = {The detection of alcohol consumption through biological matrices has gained increasing importance in forensic and clinical toxicology. Ethyl glucuronide (EtG), a direct metabolite of ethanol, serves as a reliable biomarker for alcohol intake due to its longer detection window compared to ethanol itself. Human nails have emerged as a promising alternative matrix for EtG analysis because of their stability, resistance to external contamination, and extended detection period. Traditional extraction methods rely heavily on synthetic chemicals, which can be costly and environmentally hazardous. This study explores the efficacy of natural plant extracts as alternative solvents for the extraction of EtG from human nail samples. Various plant-based extracts, including citrus, aloe vera, and green tea, were evaluated for their extraction efficiency, cost-effectiveness, and environmental sustainability. Comparative analysis revealed that certain plant extracts demonstrated comparable performance to conventional solvents while offering advantages such as reduced toxicity and biodegradability. The findings suggest that natural plant-based extraction methods could serve as a sustainable and economical approach in forensic toxicology. This research contributes to the growing interest in green chemistry applications in analytical science and opens avenues for further innovation in biomarker detection techniques.},
        keywords = {Ethyl Glucuronide (EtG) , Human Nail Analysis , Natural Plant Extracts . Forensic Toxicology},
        month = {April},
        }