Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (V_E) and Tree Silhouette Volume method (V_TS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R² = 0.783, 0.843 and 0.824 for VCPA, V_E and V_TS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.

Pneumatic sprayers are widely used in vineyards due to their very fine droplet size, which makes the drift risk to become an important problem to be considered. The aim of this study was to assess the effect of the spout diameter at the release point on the spray droplet size and uniformity achieved for different liquid flow rates (LFR) and air flow rates (AFR). A test bench was developed to simulate a real pneumatic sprayer under laboratory conditions, and it was empirically adjusted to match the air pressure conditions as closely as possible to real working conditions. Two positions of insertion of the liquid hose, the conventional position (CP) and an alternative position (AP), were tested for three LFRs, 1.00, 1.64, and 2.67Lmin-1, and four AFRs, 0.280, 0.312, 0.345, and 0.376m3s-1. The air speed decrease between the two insertion points of the liquid hose was measured. A Malvern SprayTec® instrument was used to measure the droplet size, and the D50, D10, and D90 parameter values were obtained. The relative SPAN factor (RSF) was also calculated. A model to predict variations in D50 was fitted using the aforementioned parameters. The results show that variations in the diameter of the spout significantly change the droplet size, producing a mean increase of 59.45% in D50 and similar increases in D10 and D90. The model developed to predict variations in D50 has a very high degree of accuracy (R2=0.945). The relative decrease in the air speed along the spout did not present significant differences for the different airflow rates tested. The results of the study show that the droplet size produced in pneumatic spraying can be modified easily by varying the air spout dimensions. This should be taken into account by manufacturers from a design point of view.

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.