Water is the main limiting factor in agricultural production as well as a scarce resource that needs to be optimized. The measurement of soil water with sensors is an efficient way for optimal irrigation management. However, commercial sensors are still too expensive for most farmers. This paper presents the design, development and calibration of a new capacitive low-cost soil moisture sensor that incorporates SDI-12 communication, allowing one to select the calibration equation for different soils. The sensor was calibrated in three different soils and its variability and accuracy were evaluated. Lower but cost-compensated accuracy was observed in comparing it with commercial sensors. Field tests have demonstrated the temperature influence on the sensor and its capability to efficiently detect irrigation and rainfall events.

The reproductive response of fifteen year old sweet cherry trees (Prunus avium L.) combination ‘Prime Giant’/SL64 under Mediterranean climate to deficit irrigation was studied in a commercial orchard in south-eastern Spain for four seasons. Three irrigation treatments were assayed: (i) control treatment, irrigated without restrictions at 110% of seasonal crop evapotranspiration; (ii) sustained deficit irrigation treatment, irrigated at 85% ET_c during pre-harvest and post-harvest periods, and at 100% ET_c during floral differentiation, and (iii) regulated deficit irrigation treatment, irrigated at 100% ET_c during pre-harvest and floral differentiation and at 55% ET_c during post-harvest. The duration and intensity of the phenological phases of sweet cherry trees, including cold accumulation, flowering, fruit set or fruit and vegetative growth, were assessed to ascertain whether the different irrigation strategies imposed affect the trees’ reproductive response (fruit yield, fruit size, leaf area, fruit physiological disturbances, and starch and soluble carbohydrates stock) in the same season or have a negative effect in the next season. Deficit irrigation did not advance, enhance or penalize flowering, fruit set or fruit growth. Neither did it diminish carbohydrate concentration in roots or cause an increase in the number of double fruits, which was more linked to high temperatures after harvest. However, deficit irrigation decreased vegetative growth and consequently the leaf area/fruit ratio, which, when it fell below 180 cm² fruit⁻¹, affected cherry size.

Infrared thermography has been introduced as an affordable tool for plant water status monitoring, especially in regions where water availability is the main limiting factor in agricultural production. This paper outlines the potential applications of low-cost thermal imaging devices to evaluate the water status of young and mature sweet cherry trees (Prunus avium L.) submitted to water stress. Two treatments per plot were assayed: (i) a control treatment irrigated to ensure non-limiting soil water conditions; and (ii) a water-stress treatment. The seasonal evolution of the temperature of the canopy (Tc) and the difference between Tc and air temperature (ΔT) were compared and three thermal indices were calculated: crop water stress index (CWSI), degrees above control treatment (DAC) and degrees above non-water-stressed baseline (DANS). Midday stem water potential (Ψstem) was used as the reference indicator of water stress and linear relationships of Tc, ΔT, CWSI, DAC and DANS with Ψstem were discussed in order to assess their sensitivity to quantify water stress. CWSI and DANS exhibited strong relationships with Ψstem and two regression lines to young and mature trees were found. The promising results obtained highlight that using low-cost infrared thermal devices can be used to determine the plant water status in sweet cherry trees.

The present work aims to assess the usefulness of five vegetation indices (VI) derived from multispectral UAS imagery to capture the effects of deficit irrigation on the canopy structure of sweet cherry trees (Prunus avium L.) in southeastern Spain. Three irrigation treatments were assayed, a control treatment and two regulated deficit irrigation treatments. Four airborne flights were carried out during two consecutive seasons; to compare the results of the remote sensing VI, the conventional and continuous water status indicators commonly used to manage sweet cherry tree irrigation were measured, including midday stem water potential (Ψ_s) and maximum daily shrinkage (MDS). Simple regression between individual VIs and Ψ_s or MDS found stronger relationships in postharvest than in preharvest. Thus, the normalized difference vegetation index (NDVI), resulted in the strongest relationship with Ψ_s (r² = 0.67) and MDS (r² = 0.45), followed by the normalized difference red edge (NDRE). The sensitivity analysis identified the optimal soil adjusted vegetation index (OSAVI) as the VI with the highest coefficient of variation in postharvest and the difference vegetation index (DVI) in preharvest. A new index is proposed, the transformed red range vegetation index (TRRVI), which was the only VI able to statistically identify a slight water deficit applied in preharvest. The combination of the VIs studied was used in two machine learning models, decision tree and artificial neural networks, to estimate the extra labor needed for harvesting and the sweet cherry yield.