Remote and Proximal Sensing Techniques for Site-Specific Irrigation Management in the Olive Orchard

Abstract

The aim of this study was to evaluate the potential use of remote and proximal sensing techniques to identify homogeneous zones in a high density irrigated olive (Olea europaea L.) orchard subjected to three irrigation regimes (full irrigation, deficit irrigation and rainfed conditions). An unmanned aerial vehicle equipped with a multispectral camera was used to measure the canopy NDVI and two different proximal soil sensors to map soil spatial variability at high resolution. We identified two clusters of trees showing differences in fruit yield (17.259 and 14.003 kg per tree in Cluster 1 and 2, respectively) and annual TCSA increment (0.26 and 0.24 dm2, respectively). The higher tree productivity measured in Cluster 1 also resulted in a higher water use efficiency for fruit (WUEf of 0.90 g dry weight L−1 H2O) and oil (WUEo of 0.32 g oil L−1 H2O) compared to Cluster 2 (0.67 and 0.27 for WUEf and WUEo, respectively). Remote and proximal sensing technologies allowed to determine that: (i) the effect of different irrigation regimes on tree performance and WUE depended on the location within the orchard; (ii) tree vigour played a major role in determining the final fruit yield under optimal soil water availability, whereas soil features prevailed under rainfed conditions.

Relationship between Height and Exposure in Multispectral Vegetation Index Response and Product Characteristics in a Traditional Olive Orchard

“…In the second case, ToW, cultivar PT obtained a negative trend. On the other hand, SC showed a positive trend, confirming the results of previous studies [ 48 , 49 ]. The results show that the effect of cultivar must be considered in the use and study of VIs in olive grove management.…”

Advancements in Remote Sensing Imagery Applications for Precision Management in Olive Growing: A Systematic Review

“…In regard to the use of UAV platforms, Jorge et al [152] used an MSP sensor to detect irrigation variations, finding strong correlations between NDVI and Green Normalized Difference Vegetation Index (GNDVI) [236]. Caruso et al [143] assessed irrigation effects using both RGB and MSP sensors, highlighting significant water savings with minimal yield impact under deficit irrigation (DI). Santos-Rufo et al [168] compared subsurface drip irrigation and surface drip irrigation impacts using RGB and HSP sensors coupled to UAVs.…”

Continuous Plant-Based and Remote Sensing for Determination of Fruit Tree Water Status

“…The authors showed that the NDVI and photochemical reflectance index (PRI; a further VI calculated in the VIS region) were the indices that best correlated with the Ψ stem (R 2 = 0.61 and 0.65, respectively), whereas, for analyzing within single species, peach and 'Garrigue' almond were found to be the most suitable species for the prediction of both the Ψ stem and g s from NDVI data (R 2 = 0.72 and 0.74 for Ψ stem and R 2 = 0.75 and 0.71 for g s , respectively). In olive, Caruso et al [265] demonstrated that the NDVI can be a reliable indicator of tree water stress. In grapevine, several works confirm that the NDVI can be a good indicator of PWS [266][267][268][269].…”

“…To date, there is not a large number of studies combining remote and proximal sensing. Caruso et al evaluated the combined use of multispectral data from UAVs with data from soil electrical conductivity sensors in order to identify homogeneous zone in a high-density irrigated olive orchard [265]. The authors found that the impact of various irrigation strategies on tree performance and water use efficiency (WUE) is location-dependent within the orchard, and tree vigor emerges as a primary factor influencing the ultimate fruit yield when the soil water availability is optimal.…”