Delineating Management Zones Using Principal Component Analysis–Fuzzy Clustering for Variable-Rate Irrigation: Effects on Sweet Cherry Yield and Quality
摘要
The increasing frequency of climate extremes and water scarcity in the Mediterranean basin necessitate a transition from conventional uniform irrigation toward precision water management, particularly for high-value crops like sweet cherry (Prunus avium L.). This study evaluates the effectiveness of satellite-based variable-rate irrigation (VRI) in improving water productivity while maintaining fruit quality in a commercial orchard in the Gediz Basin, Türkiye. Management zones were first delineated using archival PlanetScope normalized difference vegetation index (NDVI) imagery (2020–2022) through principal component analysis and Fuzzy c‑means clustering. These predefined zones then served as the basis for the VRI trials conducted during the 2023 and 2024 growing seasons. Zone-specific irrigation schedules were implemented and compared with conventional uniform irrigation based on local farmers’ practices. Results demonstrated that the VRI approach successfully captured within-orchard spatial heterogeneity, enabling precise water allocation. Compared to the control, VRI achieved substantial irrigation water savings of 35–49% in 2023 and 25–36% in 2024. Water productivity index values were consistently higher under VRI, reaching 1.38 kg m−3 compared to 0.70 kg m−3 in the control during 2023. Despite severe heat stress and generalized yield reduction in 2024, VRI maintained superior efficiency (0.26 kg m−3) relative to uniform irrigation (0.16 kg m−3). Statistical analysis of fruit quality attributes, including size, weight, and firmness, indicated no significant differences (p > 0.05), demonstrating that substantial water savings were achieved without compromising fruit quality. These findings highlight high-resolution remote sensing integration as a resilient strategy for sustainable sweet cherry production under semi-arid conditions.