Olive has a notable importance in countries of Mediterranean basin and its profitability depends on several factors such as actual yield, production cost or product price. Actual “on year” Yield (AY) is production (kg tree⁻¹) in “on years”, and this research attempts to relate it with geometrical parameters of the tree canopy. Regression equation to forecast AY based on manual canopy volume was determined based on data acquired from different orchard categories and cultivars during different harvesting seasons in southern Spain. Orthoimages were acquired with unmanned aerial systems (UAS) imagery calculating individual crown for relating to canopy volume and AY. Yield levels did not vary between orchard categories; however, it did between irrigated orchards (7000–17,000 kg ha⁻¹) and rainfed ones (4000–7000 kg ha⁻¹). After that, manual canopy volume was related with the individual crown area of trees that were calculated by orthoimages acquired with UAS imagery. Finally, AY was forecasted using both manual canopy volume and individual tree crown area as main factors for olive productivity. AY forecast only by using individual crown area made it possible to get a simple and cheap forecast tool for a wide range of olive orchards. Finally, the acquired information was introduced in a thematic map describing spatial AY variability obtained from orthoimage analysis that may be a powerful tool for farmers, insurance systems, market forecasts or to detect agronomical problems.

The estimation of fruit load of an orchard prior to harvest is useful for planning harvest logistics and trading decisions. The manual fruit counting and the determination of the harvesting capacity of the field results are expensive and time-consuming. The automatic counting of fruits and their geometry characterization with 3D LiDAR models can be an interesting alternative. Field research has been conducted in the province of Cordoba (Southern Spain) on 24 ‘Salustiana’ variety orange trees—Citrus sinensis (L.) Osbeck—(12 were pruned and 12 unpruned). Harvest size and the number of each fruit were registered. Likewise, the unitary weight of the fruits and their diameter were determined (N = 160). The orange trees were also modelled with 3D LiDAR with colour capture for their subsequent segmentation and fruit detection by using a K-means algorithm. In the case of pruned trees, a significant regression was obtained between the real and modelled fruit number (R² = 0.63, p = 0.01). The opposite case occurred in the unpruned ones (p = 0.18) due to a leaf occlusion problem. The mean diameters proportioned by the algorithm (72.15 ± 22.62 mm) did not present significant differences (p = 0.35) with the ones measured on fruits (72.68 ± 5.728 mm). Even though the use of 3D LiDAR scans is time-consuming, the harvest size estimation obtained in this research is very accurate.

The fruit harvesting is a key factor involving both product quality and profitability. Particularly, mechanical harvesting of traditional oil olive orchards is hint by tree training system for manual harvesting, tree size and several and slanted trunks which makes difficult trunk shaker work. Therefore, canopy shaker technology could be a feasible alternative to develop an integral harvester able to work on irregular canopies. The aim of this research was to determine vibration parameters applied to the olive tree for efficient mechanical harvesting by canopy shaker measuring fruit removal efficiency and debris. In this work, a continuous lateral canopy shaker harvester has been developed and tested on large olive trees in order to analyse the operating harvester parameters and tree properties to improve mutual adaptation. Vibration amplitude and frequency, rod density and ground speed were assessed. Vibration amplitude and frequency beside ground speed were decisive factors on fruit removal efficiency. Increasing rod density has not influenced on removal efficiency although it increased significantly debris. Promising results has been reached with 77.3% of removal efficiency, applying a 28 s shaking duration, 0.17 m amplitude vibration and 12 rod drum. This result was obtained reporting 0.26 s of accumulative shaking time over 200 m/s2 resultant acceleration. The canopy shaker mechanism enabled more than 65% of detached fruits to fall vertically, facilitating catch fruit. In order to improve removal efficiency it is advisable to adapt trees, set high amplitude in the shaker mechanism, and enhance the contact time between rods and tree.