INTEGRATING FIELD EXPERIMENTS AND SENSING TECHNOLOGIES TO IMPROVE CROPS IRRIGATION MANAGEMENT

The sustainable management of water resources is one of the main challenges for agriculture in the current context of increasing pressure due to climate change, global population growth, and competition among agricultural, civil, and industrial uses. Soybean (Glycine max L.) plays a strategic role worldwide for human and animal nutrition as well as for the energy sector, but its productivity is strongly affected by water availability. In this framework, the adoption of efficient irrigation strategies, such as Regulated Deficit Irrigation (RDI), represents a promising practice to enhance water productivity while reducing irrigation volumes. At the same time, the rapid development of remote sensing technologies and proximal sensors is opening new perspectives for monitoring crop and soil water status, enabling optimization of irrigation volumes at both field and plant scale. The integration of satellite data, intermediate platforms (such as tethered balloons), in-situ sensors, and agricultural robotics constitutes an innovative and multidisciplinary approach to irrigation management. This PhD thesis gathers and integrates several studies conducted in Italy and the United States, addressing the issue of sustainable water management through: (i) a systematic review of the literature on deficit irrigation in soybean; (ii) field experiments in Italy to assess the effects of RDI on soybean yield and quality; (iii) applications of satellite and airborne remote sensing techniques to monitor crop responses; and (iv) the development and validation of innovative robotic and electromagnetic induction approaches for soil moisture estimation in micro-irrigated orchards.