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dc.contributor.authorMéndez, Valeriano
dc.contributor.authorPérez-Romero, Antonio
dc.contributor.authorSola Guirado, Rafael Rubén
dc.contributor.authorMiranda Fuentes, Antonio
dc.contributor.authorManzano Agugliaro, Francisco
dc.contributor.authorZapata-Sierra, Antonio
dc.contributor.authorRodríguez Lizana, Antonio
dc.date.accessioned2019-12-16T10:26:12Z
dc.date.available2019-12-16T10:26:12Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10396/19217
dc.description.abstractThe 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.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.sourceAgronomy 9(12), 885 (2019)es_ES
dc.subjectOrange treees_ES
dc.subjectFruit recognitiones_ES
dc.subjectK-meanses_ES
dc.subjectLiDARes_ES
dc.subjectHDSes_ES
dc.subjectGNSSes_ES
dc.subjectYield estimationes_ES
dc.subjectIn-fieldes_ES
dc.titleIn-Field Estimation of Orange Number and Size by 3D Laser Scanninges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3390/agronomy9120885es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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