Development and Validation of an IoF-Based Sensing Architecture for Microclimate Monitoring: Quantifying Spatial ET₀...

This study presents and validates a modular Internet of Farming (IoF) sensing architecture designed for high-fidelity microclimate monitoring to address the spatial biases in reference evapotranspiration (ET₀) estimation for precision viticulture. Deployed in a Mediterranean vineyard in Antalya, Türkiye, the system demonstrated high operational robustness with a 98.6% data completion rate over an annual cycle. Comparative analysis between field-level IoF data and regional meteorological station (TSMS) records revealed a systematic overestimation of ET₀ by regional networks (MBE = -0.695 mm/day, MAPE = 10.56%). Sensitivity analysis identified discrepancies in wind speed (36.6%), net radiation (31%), and relative humidity (30%) as the primary physical drivers of this spatial bias, with air temperature serving as a seasonal index for their integrated intensification rather than as a direct dominant contributor (~2.4%). Results indicate that reliance on regional data would lead to an irrigation surplus of approximately 97.5 mm (11.4%) during the growing season. The findings underscore the critical role of localized sensing layers in resolving microclimatic heterogeneities that regional grids fail to capture within the specific site and year examined. While these results motivate further investigation into IoF-based architectures as a potentially transferable framework for ET₀ bias correction, broader generalisation to other crops, climate regimes, and management systems remains a promising avenue for future multi-site, multi-year validation rather than an established conclusion of the present study.