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dc.contributor.authorMiranda, Juan Carlos
dc.contributor.authorArnó, Jaume
dc.contributor.authorGené-Mola, Jordi
dc.contributor.authorFountas, Spyros
dc.contributor.authorGregorio, Eduard
dc.contributor.otherProducció Vegetalca
dc.date.accessioned2023-10-25T15:54:09Z
dc.date.available2023-10-25T15:54:09Z
dc.date.issued2023-10-06
dc.identifier.citationMiranda, Juan Carlos, Jaume Arnó, Jordi Gené-Mola, Spyros Fountas, and Eduard Gregorio. 2023. “AKFruitYield: Modular Benchmarking and Video Analysis Software for Azure Kinect Cameras for Fruit Size and Fruit Yield Estimation in Apple Orchards.” SoftwareX 24 (December): 101548. doi:10.1016/j.softx.2023.101548.ca
dc.identifier.isbn2352-7110ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/2463
dc.description.abstractAKFruitYield is a modular software that allows orchard data from RGB-D Azure Kinect cameras to be processed for fruit size and fruit yield estimation. Specifically, two modules have been developed: i) AK_SW_BENCHMARKER that makes it possible to apply different sizing algorithms and allometric yield prediction models to manually labelled color and depth tree images; and ii) AK_VIDEO_ANALYSER that analyses videos on which to automatically detect apples, estimate their size and predict yield at the plot or per hectare scale using the appropriate algorithms. Both modules have easy-to-use graphical interfaces and provide reports that can subsequently be used by other analysis tools.ca
dc.description.sponsorshipThis work was partly funded by the Department of Research and Universities of the Generalitat de Catalunya (grants 2017 SGR 646) and by the Spanish Ministry of Science and Innovation/AEI/10.13039/501100011033/ERDF (grant RTI2018–094222-B-I00 [PAgFRUIT project] and PID2021–126648OB-I00 [PAgPROTECT project]). The Secretariat of Universities and Research of the Department of Business and Knowledge of the Generalitat de Catalunya and European Social Fund (ESF) are also thanked for financing Juan Carlos Miranda's pre-doctoral fellowship (2020 FI_B 00586). The work of Jordi Gené-Mola was supported by the Spanish Ministry of Universities through a Margarita Salas postdoctoral grant funded by the European Union - NextGenerationEU. The authors would also like to thank the Institut de Recerca i Tecnologia Agroalimentàries (IRTA) for allowing the use of their experimental fields, and in particular Dr. Luís Asín and Dr. Jaume Lordán who have contributed to the success of this work.ca
dc.format.extent7ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofSoftwareXca
dc.rightsAttribution 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleAKFruitYield: Modular benchmarking and video analysis software for Azure Kinect cameras for fruit size and fruit yield estimation in apple orchardsca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/publishedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.relation.projectIDMICIU/Programa Estatal de I+D+I orientada a los retos de la sociedad/RTI2018-094222-B-100/ES/Tecnologías de agricultura de precisión para optimizar el manejo de dosel foliar y la protección fitosanitaria sostenible en plantaciones de frutales/PAgFRUITca
dc.relation.projectIDMICINN/Programa Estatal para impulsar la investigación científico-técnica y su transferencia/PID2021-126648OB-100/ES/Protección de cultivos de precisión para conseguir objetivos del Pacto Verde Europeo en uso eficiente y reducción de fitosanitarios mediate Agricultura de Precisión/PAgPROTECTca
dc.subject.udc62ca
dc.subject.udc633ca
dc.identifier.doihttps://doi.org/10.1016/j.softx.2023.101548ca
dc.contributor.groupÚs Eficient de l'Aigua en Agriculturaca


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