인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background This ethnobotanical study in Dunyapur, District Lodhran, Pakistan, focuses on traditional medicinal knowledge, exploring 41 plants across 28 families. The research involves 496 informants from diverse backgrounds, including farmers, herbalists, housewives, teachers, and shopkeepers. The prevalence of herbs (68%) aligns with their accessibility and rapid regrowth, shaping the local medicinal landscape. The study investigates socio-demographic features, emphasizing the importance of considering the community's diverse perspectives. Methods The research employs quantitative ethnobotanical data analysis, introducing various indices like PPV, FUV, FIV, RFC, UV, and RI. The analysis of plant growth habits underscores the dominance of herbs, and the method of preparation evaluation identifies decoction as the most common (23%). Leaves (27%) are the most utilized plant part, and Resedaceae stands out with the highest FUV (0.38). FIV highlights the ecological and cultural significance of Poaceae, Boraginaceae, Fabaceae, and Solanaceae. Results The RFC values range from 0.016 to 0.032, with Cucumis melo having the highest value (0.032), indicating its frequent citation and cultural significance. The study reveals specific plants like Melia azedarach, Peganum harmala and Salvadora oleoides with high PR values for skin issues, reflecting their widespread acceptance and effectiveness. Oligomeris linifolia emerges with the highest UV (0.38), emphasizing its greater significance in local traditional practices. Leptadenia pyrotechnica records the highest RI (9.85), underlining its exceptional importance in the community's traditional pharmacopeia. Conclusion The findings offer a holistic understanding of ethnobotanical knowledge in Dunyapur, emphasizing the role of local contexts and ecological factors in shaping traditional plant uses. The study contributes valuable insights into the diverse practices within the community, laying the foundation for sustainable integration of traditional knowledge into broader healthcare frameworks.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.