In-Field Estimation of Orange Number and Size by 3D Laser Scanning

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

Weak genetic differentiation but strong climate-induced selective pressure toward the rear edge of mountain pine in north-eastern Spain

Local differentiation at distribution limits may influence species' adaptive capacity to environmental changes. However, drivers, such gene flow and local selection, are still poorly understood. We focus on the role played by range limits in mountain forests to test the hypothesis that relict tree populations are subjected to genetic differentiation and local adaptation. Two alpine treelines of mountain pine (Pinus uncinata Ram. ex DC) were investigated in the Spanish Pyrenees. Further, an isolated relict population forming the species' southernmost distribution limit in north-eastern Spain was also investigated. Using genotyping by sequencing, a genetic matrix conformed by single nucleotide polymorphisms (SNPs) was obtained. This matrix was used to perform genotype-environment and genotype-phenotype associations, as well as to model risk of non-adaptedness. Increasing climate seasonality appears as an essential element in the interpretation of SNPs subjected to selective pressures. Genetic differentiations were overall weak. The differences in leaf mass area and radial growth rate, as well as the identification of several SNPs subjected to selective pressures, exceeded neutral predictions of differentiation among populations. Despite genetic drift might prevail in the isolated population, the Fst values (0.060 and 0.066) showed a moderate genetic drift and Nm values (3.939 and 3.555) indicate the presence of gene flow between the relict population and both treelines. Nonetheless, the SNPs subjected to selection pressures provide evidences of possible selection in treeline ecotones. Persistence in range boundaries seems to involve several selective pressures in species' traits, which were significantly related to enhanced drought seasonality at the limit of P. uncinata distribution range. We conclude that gene flow is unlikely to constrain adaptation in the P. uncinata rear edge, although this species shows vulnerability to future climate change scenarios involving warmer and drier conditions

SIMLIDAR Simulation of LiDAR performance in artificially simulate orchards

SIMLIDAR is an application developed in Cþþ that generates an artificial orchard using a Lindenmayer system. The application simulates the lateral interaction between the artificial orchard and a laser scanner or LIDAR (Light Detection and Ranging). To best highlight the unique qualities of the LIDAR simulation, this work focuses on apple trees without leaves, i.e. the woody structure. The objective is to simulate a terrestrial laser sensor (LIDAR) when applied to different artificially created orchards and compare the simulated characteristics of trees with the parameters obtained with the LIDAR. The scanner is mounted on a virtual tractor and measures the distance between the origin of the laser beam and the nearby plant object. This measurement is taken with an angular scan in a plane which is perpendicular to the route of the virtual tractor. SIMLIDAR determines the distance measured in a bi-dimensional matrix N M, where N is the number of angular scans and M is the number of steps in the tractor route. In order to test the data and performance of SIMLIDAR, the simulation has been applied to 42 different artificial orchards. After previously defining and calculating two vegetative parameters (wood area and wood projected area) of the simulated trees, a good correlation (R2 ¼ 0.70e0.80) was found between these characteristics and the wood area detected (impacted) by the laser beam. The designed software can be valuable in horticulture for estimating biomass and optimising the pesticide treatments that are performed in winter

Corrosión en una planta de alquilación que utiliza como catalizador ácido fluorhídrico.

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