Smart Monitoring, Sap-Flow, Stem-Psychrometer And Soil-Moisture Measurements Tools For Precision Irrigation And Water Saving Of Date Palm

Wireless real-time monitoring with sensor technologies is an important component of intelligent systems for precise and sustainable crop water management. However, this approach has never been investigated on date palm trees in arid environments using standard Aflaj and bubbler irrigation systems. The goal of this study was to perform smart monitoring of temperature (T), solar radiation (Rs), relative humidity (RH) and wind speed (U), as well as sap flow (SF) rates and stem water potential (SWP) in addition to soil volumetric water contents (VWC). The findings revealed that climatic variables had greatest impact on SF rates with the following order: air temperature > solar radiation > vapor pressure deficit > wind speed. Plant water stress under the Aflaj system reached up to -5.8 MPa while bubbler system kept water stress at its optimal level at an SWP of -1 MPa. Moreover, the crop evapotranspiration (ETc) using a modified Penman-Monteith (PM) model found with 49 and 31% higher in both summer and winter seasons when compared to SF rates. Additionally, a regression model was developed to simulate SF using combined factors of Rs and T, with R^{2<\Sup> = 0.94 for Aflaj and 0.93 for bubbler systems. When the modern/bubbler system combined with the soil-plant-atmosphere continuum tools and real-time monitoring-based irrigation was used, the optimum reductions of irrigation water use over the Aflaj system has reached 92 and 91% during summer and winter seasons, respectively. Moreover, the financial analysis showed that modern/bubbler irrigation system produced more crop yield and farm revenue. Hence, this study revealed that advance technology, instrumentation and monitoring systems have ability to explore a significant potential for measuring the combined plant factors such as plant vigor, production efficiency, nutrient-water uptake volume and timing. These systems also have the ability to track tree responses for changes in weather, water status, moisture levels, soil conditions, and water stress.}