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Pilot study evaluates a fuzzy logic irrigation controller in vineyards, showing reduced water use and improved grape quality indicators.
Water scarcity in arid and semi-arid regions calls for irrigation strategies that adapt to real-time field conditions. This pilot study presents a low-cost fuzzy logic–based irrigation controller for vineyards in Malekan County (East Azerbaijan, Iran). The controller uses three environmental inputs (soil moisture, air temperature, and a solar-radiation index derived from light intensity (LDR)) and applies a rule-based fuzzy inference system to determine irrigation duration (with pump activation derived from the duration). A rainfall-gating rule is also used to prevent unnecessary irrigation during rainfall events. The system was implemented on an Arduino Uno using off-the-shelf sensors and evaluated through MATLAB surface analysis and a field pilot conducted from March to August 2024. In addition, an adjacent-plot pilot comparison against conventional irrigation was performed to examine seasonal water use and plot-level grape performance indicators (cluster weight, °Brix, acidity, and rotten cluster rate). The proposed controller was associated with a 34.6% reduction in irrigation water use (520 → 340 m 3 /ha) and descriptive improvements in cluster weight, °Brix, and rotten cluster incidence. These pilot results demonstrate the technical feasibility and operational reliability of the fuzzy logic–based controller under real-world semi-arid vineyard conditions, alongside promising descriptive improvements in water-use efficiency and key grape performance indicators. However, as this was a single-season, unreplicated adjacent-plot pilot study, the observed differences in yield and quality parameters should be interpreted as exploratory. Larger-scale, multi-season field trials are therefore required to statistically validate these preliminary findings and confirm their generalizability.
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Shayesteh Tabatabaei (2026) studied this question.
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