Assessment of cluster yield components by image analysis

Diago, Maria P.; Tardáguila, Javier; Aleixos, Nuria; Millán Prior, Borja; Prats-Montalbán, J. M.; Cubero, Sergio; Blasco, José; CSIC - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)

Assessment of cluster yield components by image analysis

[Background] Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way.

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Bibliographic Details
Main Authors:	Diago, Maria P., Tardáguila, Javier, Aleixos, Nuria, Millán Prior, Borja, Prats-Montalbán, J. M., Cubero, Sergio, Blasco, José
Other Authors:	CSIC - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)
Format:	artículo biblioteca
Published:	John Wiley & Sons 2015-04
Subjects:	Berry number per cluster, LIP–Canny, Hough Transform, Berry weight, Cluster weight, Vitis vinifera L,
Online Access:	http://hdl.handle.net/10261/144428 http://dx.doi.org/10.13039/100007652 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100003329
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spelling	dig-icvv-es-10261-1444282017-03-08T08:50:27Z Assessment of cluster yield components by image analysis Diago, Maria P. Tardáguila, Javier Aleixos, Nuria Millán Prior, Borja Prats-Montalbán, J. M. Cubero, Sergio Blasco, José CSIC - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) European Commission Ministerio de Economía y Competitividad (España) Universidad Politécnica de Valencia Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L [Background] Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. [Results] Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R2 between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. [Conclusion] The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry This work has been partially funded by INIA through research projects RTA2012-00062-C04-01 and RTA2012-00062-C04-03 with the support of European FEDER funds. The authors wish also to thank the MINECO which provided support for this research work through project AGL2011-23673 and also the UPV project UPV-SP10120276. Peer Reviewed 2017-02-21T12:38:18Z 2017-02-21T12:38:18Z 2015-04 2017-02-21T12:38:19Z artículo http://purl.org/coar/resource_type/c_6501 issn: 1097-0010 e-issn: 0022-5142 Journal of the Science of Food and Agriculture 95(6): 1274-1282 (2015) http://hdl.handle.net/10261/144428 10.1002/jsfa.6819 http://dx.doi.org/10.13039/100007652 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100003329 http://doi.org/10.1002/jsfa.6819 Sí none John Wiley & Sons
institution	ICVV ES
collection	DSpace
country	España
countrycode	ES
component	Bibliográfico
access	En linea
databasecode	dig-icvv-es
tag	biblioteca
region	Europa del Sur
libraryname	Biblioteca del ICVV España
topic	Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L
spellingShingle	Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L Diago, Maria P. Tardáguila, Javier Aleixos, Nuria Millán Prior, Borja Prats-Montalbán, J. M. Cubero, Sergio Blasco, José Assessment of cluster yield components by image analysis
description	[Background] Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way.
author2	CSIC - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)
author_facet	CSIC - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Diago, Maria P. Tardáguila, Javier Aleixos, Nuria Millán Prior, Borja Prats-Montalbán, J. M. Cubero, Sergio Blasco, José
format	artículo
topic_facet	Berry number per cluster LIP–Canny Hough Transform Berry weight Cluster weight Vitis vinifera L
author	Diago, Maria P. Tardáguila, Javier Aleixos, Nuria Millán Prior, Borja Prats-Montalbán, J. M. Cubero, Sergio Blasco, José
author_sort	Diago, Maria P.
title	Assessment of cluster yield components by image analysis
title_short	Assessment of cluster yield components by image analysis
title_full	Assessment of cluster yield components by image analysis
title_fullStr	Assessment of cluster yield components by image analysis
title_full_unstemmed	Assessment of cluster yield components by image analysis
title_sort	assessment of cluster yield components by image analysis
publisher	John Wiley & Sons
publishDate	2015-04
url	http://hdl.handle.net/10261/144428 http://dx.doi.org/10.13039/100007652 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100003329
work_keys_str_mv	AT diagomariap assessmentofclusteryieldcomponentsbyimageanalysis AT tardaguilajavier assessmentofclusteryieldcomponentsbyimageanalysis AT aleixosnuria assessmentofclusteryieldcomponentsbyimageanalysis AT millanpriorborja assessmentofclusteryieldcomponentsbyimageanalysis AT pratsmontalbanjm assessmentofclusteryieldcomponentsbyimageanalysis AT cuberosergio assessmentofclusteryieldcomponentsbyimageanalysis AT blascojose assessmentofclusteryieldcomponentsbyimageanalysis
_version_	1777670870766977024

Assessment of cluster yield components by image analysis

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