نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Water scarcity is one of the most critical challenges facing agriculture in arid and semi-arid regions. This study designed and implemented a fuzzy logic-based smart irrigation system to accurately predict the water requirements of Indian ginseng (Ashwagandha). Fuzzy logic was selected due to its exceptional ability to handle uncertainty and model complex, nonlinear relationships among input variables, making it an ideal approach for irrigation optimization. Field experiments were conducted on a 400 m² plot in Saravan (Sistan and Baluchestan Province, Iran) during the 2025 growing season. Utilizing five environmental inputs (soil moisture, air temperature, relative humidity, wind speed, and plant age) and 243 Mamdani-type fuzzy rules, the system achieved a **41.9% reduction in water consumption** (from 336 to 195 L per season), a **16.3% increase in yield** (from 46 to 53.5 kg), and a **98.2% prediction accuracy** (R² = 0.982). Compared to traditional irrigation practices, the proposed system improved water use efficiency by **71.4%**.
کلیدواژهها English
