Remote and proximal sensing techniques to support precision irrigation in the olive orchard

Water availability is the main limiting factor for orchards in the Mediterranean region. Although olive trees (Olea europaea L.) are drought tolerant, many studies showed the beneficial effects of irrigation on vegetative growth, yield components, and oil quality. We assessed the potential use of remote and proximal sensing techniques in supporting the precision irrigation of olive orchards. Experiments were carried out in two high density olive orchards in Tuscany where three irrigation regimes (full irrigation, deficit irrigation and rainfed conditions) were applied. An unmanned aerial vehicle equipped with VIS-NIR-TIR cameras (visible, near infrared and thermal infrared) was used to measure the canopy normalized difference vegetation index (NDVI) and the crop water stress index (CWSI), whereas two different proximal soil sensors were used to map the soil spatial variability. In experiment 1 UAV imagery allowed to properly monitor tree growth (canopy volume) and water status (CWSI). A significant relationship (R²=0.70) between SWP and CWSI was measured. In experiment 2 we identified two clusters of trees, based on NDVI and ECa measurements, showing differences in fruit yield and annual trunk cross sectional area (TCSA) increment. The two clusters showed significant differences in fruit yield and annual TCSA increment. In conclusion, our results showed that: i) UAV VIS-TIR images can be efficiently used to monitor the canopy growth and tree water status in the olive orchard; ii) remote and proximal sensing technologies allowed to determine that the effect of different irrigation regimes on tree performance depended on the location within the orchard (Clusters 1 and 2).