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Application of 2D and 3D image technologies to characterize morphological attributes of grapevine clusters

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Application of 2D and 3D image technologies to characterize morphological attributes of grapevine clusters

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dc.contributor.author Tello, Javier es_ES
dc.contributor.author Cubero, Sergio es_ES
dc.contributor.author BLASCO IVARS, JOSE es_ES
dc.contributor.author Tardaguila, Javier es_ES
dc.contributor.author Aleixos Borrás, María Nuria es_ES
dc.contributor.author Ibanez, Javier es_ES
dc.date.accessioned 2020-09-24T12:29:03Z
dc.date.available 2020-09-24T12:29:03Z
dc.date.issued 2016-10 es_ES
dc.identifier.issn 0022-5142 es_ES
dc.identifier.uri http://hdl.handle.net/10251/150640
dc.description.abstract [EN] BACKGROUND: Grapevine cluster morphology influences the quality and commercial value of wine and table grapes. It is routinely evaluated by subjective and inaccurate methods that do not meet the requirements set by the food industry. Novel two-dimensional (2D) and three-dimensional (3D) machine vision technologies emerge as promising tools for its automatic and fast evaluation. RESULTS: The automatic evaluation of cluster length, width and elongation was successfully achieved by the analysis of 2D images, significant and strong correlations with the manual methods being found (r = 0.959, 0.861 and 0.852, respectively). The classification of clusters according to their shape can be achieved by evaluating their conicity in different sections of the cluster. The geometric reconstruction of the morphological volume of the cluster from 2D features worked better than the direct 3D laser scanning system, showing a high correlation (r = 0.956) with the manual approach (water displacement method). In addition, we constructed and validated a simple linear regression model for cluster compactness estimation. It showed a high predictive capacity for both the training and validation subsets of clusters (R2 = 84.5 and 71.1%, respectively). CONCLUSION: The methodologies proposed in this work provide continuous and accurate data for the fast and objective characterisation of cluster morphology. © 2016 Society of Chemical Industry es_ES
dc.description.sponsorship We acknowledge R. Aguirrezabal, B. Larreina and M.I. Montemayor for their technical assistance. This work was supported by the Spanish Ministerio de Economia y Competitividad (MINECO) through project AGL2010-15694 and the Instituto Nacional de Investigation y Tecnologia Agraria y Alimentaria (INIA) through projects RTA2012-00062-004-01 and RTA2012-00062-004-03 with the support of European FEDER funds. Javier Tello acknowledges the MINECO for his predoctoral fellowship (BES-2011-047041) es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Journal of the Science of Food and Agriculture es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Vitis vinifera L es_ES
dc.subject Cluster size es_ES
dc.subject Cluster compactness es_ES
dc.subject Cluster shape es_ES
dc.subject Machine vision es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Application of 2D and 3D image technologies to characterize morphological attributes of grapevine clusters es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/jsfa.7675 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//AGL2010-15694/ES/ESTUDIO GENETICO Y MORFOLOGICO DE LA COMPACIDAD DEL RACIMO DE VID MEDIANTE LA CARACTERIZACION FENOTIPICA Y EL ANALISIS GENOMICO DE LA VARIACION NATURAL/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//BES-2011-047041/ES/BES-2011-047041/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//RTA2012-00062-C04-03/ES/Nuevas técnicas de inspección basadas en visión por computador multiespectral para la estimación de propiedades y determinación automática de la calidad y sanidad de la producción agroalimentaria en líneas de inspección y manipulación (VIS-DACSA)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Mecanización y Tecnología Agraria - Departament de Mecanització i Tecnologia Agrària es_ES
dc.description.bibliographicCitation Tello, J.; Cubero, S.; Blasco Ivars, J.; Tardaguila, J.; Aleixos Borrás, MN.; Ibanez, J. (2016). Application of 2D and 3D image technologies to characterize morphological attributes of grapevine clusters. Journal of the Science of Food and Agriculture. 96:4575-4583. https://doi.org/10.1002/jsfa.7675 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/jsfa.7675 es_ES
dc.description.upvformatpinicio 4575 es_ES
dc.description.upvformatpfin 4583 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 96 es_ES
dc.identifier.pmid 26910811 es_ES
dc.relation.pasarela S\303233 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación
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