Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size

Computer vision systems are powerful tools to automate inspection tasks in agriculture. Typical target applications of such systems include grading, quality estimation, yield prediction and monitoring, among others. The capabilities of an artificial vision system go beyond the limited human capacity...

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Authors: Tardaguila, J. [0000-0002-6639-8723], Diago, M.P. [0000-0003-4049-0879], Millan, B. [0000-0001-9313-5104], Blasco, J., Cubero, S. [0000-0002-9346-3236], Aleixos, N. [0000-0001-6051-3375]
Format: article
Status:Published version
Publication Date:2013
Country:España
Institution:Universidad de La Rioja (UR)
Repository:RIUR. Repositorio Institucional de la Universidad de La Rioja
OAI Identifier:oai:portal.dialnet.es:doc/5bbc69b1b750603269e81fd4
Online Access:https://investigacion.unirioja.es/documentos/5bbc69b1b750603269e81fd4
Access Level:Open access
Keyword:Automation
Grapevine
Image analysis
Machine vision
Vineyard
id ES_d78b57072064eb25f6bd8c7a39a7546e
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spelling Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry sizeTardaguila, J. [0000-0002-6639-8723]Diago, M.P. [0000-0003-4049-0879]Millan, B. [0000-0001-9313-5104]Blasco, J.Cubero, S. [0000-0002-9346-3236]Aleixos, N. [0000-0001-6051-3375]AutomationGrapevineImage analysisMachine visionVineyardComputer vision systems are powerful tools to automate inspection tasks in agriculture. Typical target applications of such systems include grading, quality estimation, yield prediction and monitoring, among others. The capabilities of an artificial vision system go beyond the limited human capacity to evaluate long-term processes objectively and provide valuable data to take decisions that will have great influence in later operations. This work explores the application of machine vision techniques in viticulture from several approaches. The first approach is aimed at working outdoors, developing in-field systems capable of assessing the canopy features of the vineyard (Vitis vinifera L.) by taking digital images and applying computer vision systems. The second approach is aimed at analysing cluster morphology using image analysis. Berry number per cluster and cluster weight were estimated using several algorithms of image processing. Lately, machine vision has been used as a tool to automate the measurement of berry size and weight under laboratory conditions. Manual measurement of the canopy features and yield components are tedious and subjective tasks that can be time-consuming and labour demanding. In this regard, by means of computer vision techniques, a large set of samples can be automatically measured, saving time and providing more objective and precise information.2013info:eu-repo/semantics/articleSubtype: Articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://investigacion.unirioja.es/documentos/5bbc69b1b750603269e81fd4reponame:RIUR. Repositorio Institucional de la Universidad de La Riojainstname:Universidad de La Rioja (UR)Inglésinfo:eu-repo/semantics/altIdentifier/wos/WOS:000323817800007info:eu-repo/semantics/altIdentifier/pissn/0567-7572Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size, 2013, vol. 978, pág. 77-84info:eu-repo/semantics/openAccessoai:portal.dialnet.es:doc/5bbc69b1b750603269e81fd42026-06-14T12:47:17Z
dc.title.none.fl_str_mv Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
title Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
spellingShingle Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
Tardaguila, J. [0000-0002-6639-8723]
Automation
Grapevine
Image analysis
Machine vision
Vineyard
title_short Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
title_full Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
title_fullStr Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
title_full_unstemmed Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
title_sort Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size
dc.creator.none.fl_str_mv Tardaguila, J. [0000-0002-6639-8723]
Diago, M.P. [0000-0003-4049-0879]
Millan, B. [0000-0001-9313-5104]
Blasco, J.
Cubero, S. [0000-0002-9346-3236]
Aleixos, N. [0000-0001-6051-3375]
author Tardaguila, J. [0000-0002-6639-8723]
author_facet Tardaguila, J. [0000-0002-6639-8723]
Diago, M.P. [0000-0003-4049-0879]
Millan, B. [0000-0001-9313-5104]
Blasco, J.
Cubero, S. [0000-0002-9346-3236]
Aleixos, N. [0000-0001-6051-3375]
author_role author
author2 Diago, M.P. [0000-0003-4049-0879]
Millan, B. [0000-0001-9313-5104]
Blasco, J.
Cubero, S. [0000-0002-9346-3236]
Aleixos, N. [0000-0001-6051-3375]
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Automation
Grapevine
Image analysis
Machine vision
Vineyard
topic Automation
Grapevine
Image analysis
Machine vision
Vineyard
description Computer vision systems are powerful tools to automate inspection tasks in agriculture. Typical target applications of such systems include grading, quality estimation, yield prediction and monitoring, among others. The capabilities of an artificial vision system go beyond the limited human capacity to evaluate long-term processes objectively and provide valuable data to take decisions that will have great influence in later operations. This work explores the application of machine vision techniques in viticulture from several approaches. The first approach is aimed at working outdoors, developing in-field systems capable of assessing the canopy features of the vineyard (Vitis vinifera L.) by taking digital images and applying computer vision systems. The second approach is aimed at analysing cluster morphology using image analysis. Berry number per cluster and cluster weight were estimated using several algorithms of image processing. Lately, machine vision has been used as a tool to automate the measurement of berry size and weight under laboratory conditions. Manual measurement of the canopy features and yield components are tedious and subjective tasks that can be time-consuming and labour demanding. In this regard, by means of computer vision techniques, a large set of samples can be automatically measured, saving time and providing more objective and precise information.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
Subtype: Article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://investigacion.unirioja.es/documentos/5bbc69b1b750603269e81fd4
url https://investigacion.unirioja.es/documentos/5bbc69b1b750603269e81fd4
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/wos/WOS:000323817800007
info:eu-repo/semantics/altIdentifier/pissn/0567-7572
Applications of computer vision techniques in viticulture to assess canopy features, cluster morphology and berry size, 2013, vol. 978, pág. 77-84
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:RIUR. Repositorio Institucional de la Universidad de La Rioja
instname:Universidad de La Rioja (UR)
instname_str Universidad de La Rioja (UR)
reponame_str RIUR. Repositorio Institucional de la Universidad de La Rioja
collection RIUR. Repositorio Institucional de la Universidad de La Rioja
repository.name.fl_str_mv
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