The growing scarcity and competition for water resources requires the urgent implementation of measures to ensure their rational use. Farmers need affordable irrigation tools that allow them to take advantage of scientific know-how to improve water use efficiency in their common irrigation practices. The aim of this study is to test under field conditions, and adjust where required, an automated irrigation system that allows the establishment of regulated deficit irrigation (RDI) strategies in a stone fruit orchard. For this, an automated device with an algorithm which combines water-balance-based irrigation scheduling with a feedback adjustment mechanism using 15 capacitive sensors for continuous soil moisture measurement was used. The tests were carried out in 2016 and 2017 in Vegas Bajas del Guadiana (Extremadura, Spain) on an experimental plot of ‘Red Beaut’, an early-maturing Japanese plum cultivar. Three irrigation treatments were established: control, RDI and automatic. The control treatment was scheduled to cover crop water needs, a postharvest deficit irrigation (40% crop evapotranspiration (ETc)) strategy was applied in the RDI treatment, while the Automatic treatment simulated the RDI but without human intervention. After two years of testing, the automated system was able to “simulate” the irrigation scheduling programmed by a human expert without the need for human intervention.

Canopy light interception (LI) is a determining factor for crop growth and yield. Crop yield depends on a canopy's capacity to intercept incident solar radiation, which in turn depends on the available leaf area, its structure, and its efficiency in converting the energy captured by the plant into biomass. Digital images offer a series of advantages over other methods of LI estimation, including the possibility to directly process images by computer for which free software is available. The objectives of this work were to develop a simple, economical method for determining LI in low-lying crops such as processing tomato using digital images obtained with a standard, commercial camera and free software and to evaluate the influence of different types of soil coverage (bare soil and plastic mulch) on LI. Photographs of the selected areas were taken using a digital camera at a distance of 160 cm above the center of each area. The resulting digital images were then analyzed with the free software GIMP 2.2 and IMAGE J. Three methods [area (SA), contour (SC). and reclassification (SR)] were used to quantify the percentage of groundcover (PGC). They were applied to the same images and compared with LI as measured with a line quantum sensor at solar noon. There was a close relationship between LI and estimated PGC with all three methods and for different soil cover regimes. In all cases, there was a linear adjustment with a significant correlation coefficient ( P < 0.01) and an r ² of greater than 0.88. The adjustment with RI was narrowest when the SR method was used to estimate PGC ( r ² = 0.93) followed by SC ( r ² = 0.92) and SA ( r ² = 0.88). Measurements of LI based on digital images offered practical advantages with respect to the use of photosynthetically active radiation bars because the latter must be used at solar noon. In contrast, measurements obtained with a digital camera can be taken at any time of day and bright sunshine is not necessary. Different correlations were obtained for bare soil and plastic mulch conditions, so it was necessary to use a different equation to estimate LI under each condition.